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Light scattering properties vary across different regions of the adult mouse brain

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Title:
Light scattering properties vary across different regions of the adult mouse brain
Creator:
Al-Juborri, Saif I. ( author )
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Denver, CO
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University of Colorado Denver
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English
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Light -- Scattering ( lcsh )
Optogenetics ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Recently developed optogenetic tools provide powerful approaches to optically excite or inhibit neural activity. In a typical in-vivo experiment, light is delivered to deep nuclei via an implanted optical fiber. Light intensity attenuates with increasing distance from the fiber tip, determining the volume of tissue in which optogenetic proteins can successfully be activated. However, whether and how this volume of effective light intensity varies as a function of brain region or wavelength has not been systematically studied. The goal of this study was to measure and compare how light scatters in different areas of the mouse brain. We delivered different wavelengths of light via optical fibers to acute slices of mouse brainstem, midbrain and forebrain tissue. We measured light intensity as a function of distance from the fiber tip, and used the data to model the spread of light in specific regions of the mouse brain. We found substantial differences in effective attenuation coefficients among different brain areas, which lead to substantial differences in light intensity demands for optogenetic experiments. The use of light of different wavelengths additionally changes how light illuminates a given brain area. We created a brain atlas of effective attenuation coefficients of the adult mouse brain, and integrated our data into an application that can be used to estimate light scattering as well as required light intensity for optogenetic manipulation within a given volume of tissue.
Thesis:
Thesis (M.S.)--University of Colorado Denver. Electrical engineering
Bibliography:
Includes bibliographic references.
General Note:
Department of Electrical Engineering
Statement of Responsibility:
by Saif I. Al-Juboori.

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Full Text
LIGHT SCATTERING PROPERTIES VARY ACROSS DIFFERENT REGIONS OF
THE ADULT MOUSE BRAIN
by
SAIF I. AL-JUBOORI
B.S., Nahrain University, 2008
A thesis submitted to the
Faculty of the Graduate School of the
University of Colorado in partial fulfillment
of the requirements for the degree of
Master of Science
Electrical Engineering
2013


This thesis for the Master of Science degree by
Saif I. Al-Juboori
has been approved for the
Electrical Engineering Program
by
Tim Lei, Chair
Achim Klug
Yiming Deng


Al-Juboori, Saif, I. (M.S., Electrical Engineering)
Light Scattering Properties Vary across Different Regions of the Adult Mouse Brain
Thesis directed by Assistant Professor Tim Lei.
ABSTRACT
Recently developed optogenetic tools provide powerful approaches to optically
excite or inhibit neural activity. In a typical in-vivo experiment, light is delivered to deep
nuclei via an implanted optical fiber. Light intensity attenuates with increasing distance
from the fiber tip, determining the volume of tissue in which optogenetic proteins can
successfully be activated. However, whether and how this volume of effective light
intensity varies as a function of brain region or wavelength has not been systematically
studied.
The goal of this study was to measure and compare how light scatters in different
areas of the mouse brain. We delivered different wavelengths of light via optical fibers to
acute slices of mouse brainstem, midbrain and forebrain tissue. We measured light
intensity as a function of distance from the fiber tip, and used the data to model the
spread of light in specific regions of the mouse brain. We found substantial differences in
effective attenuation coefficients among different brain areas, which lead to substantial
differences in light intensity demands for optogenetic experiments. The use of light of
different wavelengths additionally changes how light illuminates a given brain area. We
created a brain atlas of effective attenuation coefficients of the adult mouse brain, and
integrated our data into an application that can be used to estimate light scattering as well
as required light intensity for optogenetic manipulation within a given volume of tissue.
m


The form and content of this abstract are approved. I recommend its publication.
Approved: Dr. Tim Lei
IV


DEDICATION
I dedicate this work to those beloved ones whom I have lost and I still
remember; to those who are suffering, not only every single day, but every single
moment hoping that there will be a day in which researchers, like us, will come up with
treatment for their illnesses to mitigate their suffering and alleviate their pain; to those
whom I have promised that I am going to do my best in participating in whatever is going
to be available for me to pave the way for breakthroughs that will lead to a better life with
less pain and more pleasure for them and their dearest ones; to those whom I gave my
words to that I will never let them down; to people whom I am always looking forward to
putting a smile on their faces.
v


ACKNOWLEDGMENTS
I acknowledge my fellowship from the Higher Committee for Education
Development in Iraq (HCED).
I would like to thank my consultant, advisor, and mentor, Dr. Tim Lei for all his
encouragement, support, consultation, and advising that he has bestowed upon me
throughout my graduate studies. Without his help, I would not have been able to spend
my time, day by day, in a scientific and intellectual milieu which has been giving me the
chance to learn from, study, meet, and collaborate with incredible researchers and
students who have had a great influence on me. I am honored to work under his
supervision.
Here, I would also like to thank Dr. Achim Klug, Dr. Gidon Felsen, Dr. Anna
Dondzillo, and Dr. Elizabeth Stubblefield for their collaboration in this work. I am
indeed grateful for having this wonderful opportunity collaborating with all of them. It
has been such an enriching experience being around people of knowledge like them.
vi


TABLE OF CONTENTS
CHAPTER
I. INTRODUCTION............................................................1
Optogenetics Era.....................................................1
Neuroscience-Optogenetics Experimental Insights......................3
Main Goals of This Study.............................................4
Ethics Statement.....................................................5
Animal Subjects......................................................5
Thesis Orientation...................................................5
II. EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED BRAIN
AREAS, EXPERIMENTAL PROCEDURE, AND LIGHT PROFILE AND
TISSUE DAMAGE CONTROL EXPERIMENTS....................................7
Experimental Setup...................................................7
Optical Fiber Assembly............................................8
Linearity Tests..................................................11
The Importance of These Linearity Tests......................11
LEDs Power Intensity Linearity Tests.........................11
CCD Camera Linearity Tests....................................16
Sample Preparation..................................................19
Targeted Brain Areas................................................20
Experimental Procedure..............................................21
Manually-Controlled Method.......................................21
Pico-Motor-Controlled Fiber Punch-Through Method.................23
Light Profile and Tissue Damage Control Experiments.................29
vii


III. DATA ANALYSES, THE MODIFIED BEER-LAMBERT LAW, BRAIN ATLAS
ESTABLISHMENT, AND RESULTS.........................................32
Data Analyses......................................................32
The Modified Beer-Lambert Law and the Effective Attenuation Coefficients for
Highly Scattering Neural Targets...................................38
The Brain Atlas, and a Technique of Mapping the Effective Attenuation
Coefficients across the Entire Brain...............................41
The Effective Excitation Distance for Optogenetic Proteins.........42
Integration of All Relevant Data in a Computer Program.............42
Results............................................................43
Light Intensity Decreases Exponentially in Brain Tissue.........44
Light Scattering Properties Vary across Different Brain Regions.45
Light Scattering Varies with Wavelength.........................49
Light Scattering Brain Atlas....................................53
Applying the Data to Experimental Design........................56
IV. DISCUSSION AM) MAIN FINDINGS.........................................61
Discussion.........................................................61
Main Findings......................................................62
V. IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES, AND FUTURE
PLANS..............................................................64
Improvements.......................................................64
Comparison with Previous Studies...................................65
Future Plans.......................................................68
Application of the Findings to Future Experiments...............68
Research Proposal for Determining Diffusivity Constants for Individual Brain
Areas...........................................................69
viii


REFERENCES
74
IX


LIST OF TABLES
Table
III. 1 Brain areas that were measured with three different wavelengths, and sample size
(the unit of the effective attenuation coefficient is 1/mm) [12].....................47
V.l Midori-Ishi Cyan and mRFPl properties [21].......................................71
x


LIST OF FIGURES
Figure
11.1 The experiments desk showing the experimental setup equipment.....................7
11.2 A 100 jjm core, coupled to a 518 nm green LED and driven by a 100 mA current
source, optical fiber output profile....................................................9
11.3 A 100 jjm core, coupled to a 518 nm green LED and driven by a 100 mA current
source, optical fiber output profile after traversing a 100 iim sample thickness......9
11.4 A 100 [im core, coupled to a 518 nm green LED and driven by a 100 mA current
source, optical fiber output profile after traversing a 200 iim sample thickness......10
11.5 A 500 jjm core, coupled to a 453 nm blue LED and driven by a 100 mA current
source, optical fiber output profile after traversing a 100 iim sample thickness at 10 ms
exposure time..........................................................................10
11.6 A 500 jjm core, coupled to a 453 nm blue LED and driven by a 100 mA current
source, optical fiber output profile after traversing a 100 iim sample thickness at 20 ms
exposure time..........................................................................11
II. 7 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 518 nm green (LED), when the room light is turned off.....................12
II. 8 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 518 nm green (LED), under normal rooms illumination......................13
II. 9 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 528 nm green (LED), when the room light is turned off.....................13
II. 10 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 528 nm green (LED), under normal rooms illumination......................14
II. 11 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 453 nm blue (LED), when the room light is turned off......................14
II. 12 The data fitting line for the output power density of the 100 pm core optical fiber,
coupled to a 453 nm blue (LED), under normal rooms illumination.......................15
II. 13 The data fitting line for the output power density of the 500 pm core optical fiber,
coupled to a 453 nm blue (LED), when the room light is turned off......................15
II. 14 The data fitting line for the output power density of the 500 pm core optical fiber,
coupled to a 453 nm blue (LED), under normal rooms illumination.......................16
xi


II. 15 Linearity test for the CCD camera at (100, 100) pixels location of (1040 x 1392)
pixel image............................................................................17
II. 16 Linearity test for the CCD camera at (100, 1292) pixels location of (1040 x 1392)
pixel image........................................................................17
II. 17 Linearity test for the CCD camera at (520, 696) pixels location of (1040 x 1392)
pixel image........................................................................18
II. 18 Linearity test for the CCD camera at (940, 100) pixels location of (1040 x 1392)
pixel image........................................................................18
II. 19 Linearity test for the CCD camera at (940, 1292) pixels location of (1040 x 1392)
pixel image........................................................................19
11.20 Light arbitrary digital intensity as a function of tissues thickness for a PPT region.
This is a one single set of measurements...........................................22
11.21 Basic experimental setup of the punch-through method. On an inverted microscope,
an optical fiber was placed on a section of brain tissue such that light from the fiber
would pass through the tissue and subsequently be imaged by an objective attached to a
CCD camera [12].......................................................................24
11.22 A snap shot for the controlling program front panel expressing the adjustable
significant parameters and other details..............................................26
11.23 An example of an original image captured by the CCD camera, showing light
emitted from an optical fiber after it passed though a section of brain tissue [12]...27
11.24 Optical transmittance as a function of tissue thickness. As the optical fiber was
advanced through the section of brain tissue and repeated images such as the one in
figure 11.23 were taken, the decrease in optical transmittance as a function of tissue
thickness could be evaluated. The single measurements (+ symbols) represent
transmittance of blue light (453 nm) through a section of PPT at various thicknesses,
while the solid line represents an exponential fit [12]...............................28
11.25 (Left) it is an overlapped picture of two images that are taken for a PPT region, in
300 pm of thickness and 1300 pm from the midline of depth slide. The background
image (which is in black and white colors) shows the PPT area, while the blue one is, the
output optical power intensity profile for the 100 pm core optical fiber connected to a 453
nm blue LED, driven by a 28 mA current source. This picture is evidence that the blue
LED light is not sufficient to cover the whole PPT region. These two images are taken on
an integration time of 100 ms. (Right) it is an overlapped picture of two images that are
taken for a PPT region, in 300 pm of thickness and 1300 pm from the midline of depth
slide. The background image (which is in black and white colors) shows the PPT area,
while the green one is, the output optical power intensity profile for the 100 pm core
optical fiber connected to a 518 nm green LED, driven by a 100 mA current source. This
xii


picture is evidence that the green LED light is not sufficient to cover the whole PPT
region. These two images are taken on an integration time of 100 ms...............29
II. 26 (Top left) a 300 pm of thickness and a 1500 pm from the midline of depth slides
image, showing the actual image that is taken from the CCD camera, of the CA3
Hippocampus region under white light illumination and before the laser damage. This
image is taken on an integration time of 100 ms. (Top right) a 300 pm of thickness and a
1500 pm from the midline of depth slides image, showing the false color of the CA3
Hippocampus region under white light illumination and before the laser damage. This
image is taken on an integration time of 100 ms. (Bottom left) a 300 pm of thickness and
a 1500 pm from the midline of depth slides image, showing the actual image, that is
taken from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5 mW
laser source illumination, being applied for 3 minutes of time. The image shows a real
tissue damage which is caused by the laser source under these circumstances. This image
is taken on an integration time of 100 ms. (Bottom right) A 300 pm of thickness and a
1500 pm from the midline of depth slides image, showing the false color of the CA3
Hippocampus region under 405 nm and 3.5 mW laser source illumination, being applied
for 3 minutes of time. The image shows a real tissue damage which is caused by the laser
source under these circumstances. This image is taken on an integration time of 100 ms30
III. 1 A snap shot for the viewer program front panel screen that is used for retrieving the
intensities from the images and plotting them as a function of tissue thickness according
to the specific cursor location....................................................33
ID.2 A cerebellum one raw data and fitting curve. Note the offset in the fit. This issue
will be addressed below............................................................35
ID. 3 A comparison between PPT one and PPT two. Note the offset in the fit. This issue
will be addressed below............................................................36
IE. 4 A comparison between CA3 one and CA3 two. Note the offset in the fit. This issue
will be addressed below............................................................36
111.5 A comparison between PPT one and PPT two after taking the offset factor Yo into
account which demonstrates its significant impact on the reanalyzed and refitted the data
37
111.6 A comparison between CA3 one and CA3 two after taking the offset factor Yo into
account which demonstrates its significant impact on the reanalyzed and refitted the data
38
ID. 7 Optical transmittance through different types of brain tissue. Measurements using
the fiber punch-through technique were taken in eight different brain areas with blue (453
nm) light. In each case, optical transmittance decreased exponentially with tissue
thickness; however, the exponential decreases observed varied greatly with the type of
tissue. Single measurements are represented by the respective symbols while the solid
lines represent exponential fits of the data........................................45


III.8 Effective attenuation coefficients with SEMs for the eight brain areas: VNTB 19.96
+/- 0.26 (1/mm); CA3 19.12 +/- 0.84 (1/mm); MNTB 18.16 +/- 0.69 (1/mm); LSO 17.92
+/- 0.80 (1/mm); PPT 15.26 +/- 0.78 (1/mm); OB 14.88 +/- 0.74 (1/mm); SC 13.91 +/-
0.83 (1/mm); Cerebellum 9.76 +/- 0.78 (1/mm)................................46
III.9 Optical power values that would need to be fed into a 100 pm diameter optical fiber
when 300 pm of tissue needs to be illuminated at intensities typically used for
Channelrhodopsin activation.................................................48
III. 10 Same as figure III. 11 except that in this example the illumination was calculated to
hypothetically activate Channelrhodopsin over a distance of 600 pm from the fiber tip. 49
III. 1 lEffects of wavelength on optical transmittance. Optical transmittance in the MNTB
as a function of tissue thickness and optical wavelengths. The three colorcoded data sets
represent corresponding measurements with light of three different optical wavelengths
(blue (453 nm), green (528 nm), and red (940 nm)). Longer-wavelength light penetrates
tissue deeper, resulting in a higher transmittance at any given tissue thickness [12].50
III. 12 Optical transmittance in the VNTB as a function of tissue thickness and optical
wavelengths. The three colorcoded data sets represent corresponding measurements with
light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940
nm)). Longer-wavelength light penetrates tissue deeper, resulting in a higher
transmittance at any given tissue thickness...........................................51
III. 13 Effects of light wavelength on transmittance in two brain areas (MNTB and
VNTB). The effective attenuation coefficient decreases with wavelength for the three
wavelengths tested. MNTB measurements are represented by round symbols while
VNTB measurements are represented by square symbols. Measurements in the three
different colors are indicated by the color-code of the symbols [12]...................52
III. 14 MNTB and VNTB proposed fitting curves for the effective attenuation coefficients
as a function of wavelengths...........................................................52
III. 15 Relating fiber punch-though measurements to brain atlas measurements. An image
of a 300 pm coronal section of mouse brain stem, taken on a calibrated virtual
microscopy system with monochromatic light. Areas with higher optical transmittance
appear brighter on the image, while areas with lower transmittance appear darker.
MNTB, VNTB, and LSO are outlined in red, orange, and yellow, respectively [12]..54
III. 16 Correlation in digital irradiance for brain areas tested with both the fiber punch-
through and the virtual microscopy method. Digital irradiance was measured in six brain
areas (MNTB (red), VNTB (orange), LSO (yellow), PPT (green), SC (light blue), and
cerebellum (dark blue) with both the fiber punch through and the virtual microscopy
technique. Results were normalized and plotted against each other. Each colored symbols
represents the measurements from one brain area with two methods, the solid line
indicates complete overlap between the measurements. The bars attached to each data
point represent the standard error [12].........................................55
xiv


III. 19 The desired input parameters control panel
57
III.20 The attainable penetration depth as a function of optical power at the fiber tip for
the desired entered input parameters............................................58
ID.21 A sample image from the brain atlas where the investigator can select the area of
interest precisely such that its optical properties are designated, and the corresponding
penetration depth and optical power at the fiber tip are calculated, accordingly.59
III.22 A screenshot for the user manual that is available in the computer program also, in
which the user can be taken through details about how to use this application to its full
extent..........................................................................60
V. 1 A comparison between our exponential fit and Kubelka-Munk fit for a PPT raw data
showing that it is best fitted with a single exponential curve..................66
V.2 A comparison between our exponential fit and Kubelka-Munk fit for an MNTB total
intensity measurements of the raw data averaged over the entire detectors area showing
that it is best fitted with a single exponential curve..........................67
V.3 MiCy excitation and emission spectra [22]...................................71
V.4 mRFPl absorption (solid line), excitation (dotted line), and emission (dashed line)
spectra [23]....................................................................72
V.5 ChR2 and NpHR activation spectra [4].......................................72
xv


CHAPTER I
INTRODUCTION
Optogenetics Era
Deep brain stimulation (DBS) technology is one of the most effective
technologies that have been used as a treatment and a cure for a wide spectrum of
psychiatric disorders and diseases. The key function of this technology is making various
kinds of stimulation to specific defective areas that are responsible for certain brains
functions by either activate or deactivate them to compensate for the malfunction that is
happening in them. The conventional approach to this technology is by doing the stimuli
electrically by inserting metal electrodes in those areas and implementing that required
current intensity to achieve the pre-decided aim. However, as one can see, there are some
downsides to this method though. Cells damage, corrosions, tumors.. .etc., are
predisposed by this invasive method [1], It might also have a severe effect on the
surrounding and the intact cells. In addition, metal electrodes can not specifically target a
certain cell type in the neural target, making the treatment much less specific and could
lead to adverse treatment outcomes. Moreover, it is not possible to specifically control
stimulation or suppression of the neural signals in the brain. Nonetheless, DBS using
metal electrodes is the current state-of-the-art method of deep brain stimulation. After
discovering some photosensitive materials especially photosensitive proteins that could
be latched on cells and cells membranes, the idea of using light to do the same required
stimuli, but this time optically, came out to the surface as a safer and noninvasive
breakthrough to deal with these conditions and diseases [2], In this method, the light is
1


shining specific areas which have already those photosensitive proteins, and some parts
of the neural networks start to fire or suppress that firing and control some brain
functions to deliver the desired treatment. This is what is called optogenetic technique,
in brief! [2] And nowadays, it is considered as one of the recent cutting edge technologies
in this field. And from this point forward, manipulating neural function with light is
becoming an increasingly important technique. This is particularly important for this
recently emerging field of optogenetics, which provides powerful tools to either activate
or suppress neural activity with light at a relatively fast time scale (sub-millisecond) (e.g.
[3]-[5]). Controlling neuronal firing with light has opened up not only a number of
exciting new avenues to study neural circuits, but also treatment options of a number of
medical conditions such as Parkinsons disease or certain forms of blindness [6]-[8],
As it has been known for the conventional approach that the amount of charge
intensity will specify the demanded treatment as the brain areas have different electrical
properties, the amount of light (or the light intensity) required to serve the same purpose
should be pre-specified as well, as those brain areas may show different optical
properties. Having said that, the first question that have been asked is; how much optical
power intensity that is required to deliver light to a specific neural target with a specific
optical penetration depth to get the stimulation, activation or deactivation, and the neural
responses desired will be. After determining this amount of the power intensity required
to do the process, the second question is, what is the initial optical power intensity that
the physician should start with at the outer boundary of the neural target- as it is not
preferable to punch through it, yet instead, shining light directly on top of it.
2


The latter question requires the knowledge of the optical properties for those areas
under study or investigation, because it is related to the light transmission, absorption,
and the scattering phenomena that are happening within the targeted area. Therefore, the
idea of having a three-dimensional (3D) light scattering model has become a necessity in
order to give a comprehensive expectation of how light behaves inside different brain
areas. Yet, it has been required to collect the constructing optical parameters of this light
scattering model. Thus, the scientific journey has started by conducting this study to
achieve this goal by extracting the effective attenuation coefficient (/it) which is one of
the main optical parameters that this model will be composed of.
Neuroscience-Optogenetics Experimental Insights
For experiments using cell cultures or brain slices, the precise and reliable
delivery of light to the neurons to be manipulated is relatively simple and is typically
achieved by attaching a suitable light source to a microscope, and subsequently
delivering light stimuli with the desired parameters directly to the neural tissue. For in-
vivo experiments, however, light delivery to deep brain areas is much more challenging.
Typically, investigators use stereotaxic methods to place an optical fiber just above the
brain neural target to be illuminated, such that light emitting from the fiber effectively
illuminates the tissue below the fiber tip [9],
Depending on the optical properties of the specific tissue, light emitted from the
fiber tip propagates deeper or less deep through the tissue, with neurons more distant
from the fiber tip receiving higher or lower light intensities. All light sensitive molecules
(such as the various opsins typically used in optogenetic experiments, but also caged
compounds and fluorescent dyes) have a threshold of activation, (for the purpose of this
3


publication defined in practical terms as the minimum light intensity required to
effectively trigger or inhibit the desired neural action potential). Therefore, light sensitive
molecules can only be activated at a certain maximum distance from the light source, and
this distance depends on both the optical properties of the tissue and the activation
threshold of the molecule used in the experiment. Most studies involving delivery of light
to deep brain areas assume, for simplicity, that all brain tissue scatters light in the same
way, i.e. different brain areas behave similarly if not identically as far as light
propagation in the tissue is concerned [1], [10], [11], However, some brain areas consist
primarily of cell bodies while others consist primarily of neural fibers, and some brain
areas with significant myelination appear darker while others appear lighter when
observed under a microscope with transmitted light, suggesting differences in optical
properties between different brain areas.
Main Goals of This Study
The primary goal of this study was to test the hypothesis that different brain areas
scatter and propagate light to different degrees. If correct, specific knowledge about the
brain area to be manipulated would be required for the appropriate design of
experimental manipulations. A secondary goal of the study was to create an easy to use
computer program to estimate light scattering values for different areas of the mouse
brain that could be used as a reference in future experiments.
Our experimental approach was to use sections of fresh brain tissue in
combination with light emitting optical fibers that were advanced through the tissue to
precisely measure light scattering properties. The results presented here are supplemented
with a light scattering mouse brain atlas programmed as an iPhone application. These
4


tools are intended to aid an investigator in determining the required light intensity to be
delivered for successful optogenetic manipulation.
Ethics Statement
All animal procedures were approved by the Institutional Animal Care and Use
Committee (IACUC) of the University of Colorado Medical Campus (Permit number B-
88412(05)1D. Furthermore, all applicable laws and regulations, as well the PHS Policy
were strictly followed.
Animal Subjects
34 male and female C57BL/6J mice were used in these experiments. All animal
procedures were approved by the University of Colorado Institutional Animal Care and
Use Committee, and were conducted in accordance with National Institutes of Health
standards on humane treatment of laboratory animals.
Thesis Orientation
In the following chapters, the experimental setup, sample preparation, targeted
brain areas, and experimental procedure needed to measure effective attenuation
coefficients will be presented (Chapter II). The results of these sets of experiments and
the brain atlas establishment will be shown, as well, in both graphical and numerical
presentations in Chapter III. These results will also be discussed, summarizing the main
findings of this study, in Chapter IV, and some impairment will be illustrated in one of
these sections. Finally, solutions for those difficulties that have worked out so far,
improvements that have been come up with, some other suggestions, comparison with
previous studies, and future plans (research proposal for gathering more parameters to
5


perfect a three-dimensional (3D) light scattering model of the mouse brain) will also be
available to the researcher in Chapter V.
6


CHAPTER II
EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED
BRAIN AREAS, EXPERIMENTAL PROCEDURE, AND LIGHT
PROFILE AND TISSUE DAMAGE CONTROL EXPERIMENTS
Experimental Setup
The experimental setup is mainly composed of the following devices: an inverted
microscope (Nikon Diaphot 200, Nikon Corp., Japan) with a monochromatic 12bit
Charged-Coupled Device (CCD) camera (Mightex CCE-B013-U) attached to it, a current
derive source- a Mightex LED power supply (SLB-1200-1)- which derives the optical
fibers, a computer, a CCD video camera and a monitor. The latter two components have
been added afterward to adjust the fiber tip precisely on top of the sample before starting
running the experiment. The investigational bench is pictured in figure II. 1.
!
Figure II.l The experiments desk showing the experimental setup equipment
7


Optical Fiber Assembly
Three different optical fiber assemblies were used for the measurements. All three
assemblies consisted of 100 pm core diameter optical fibers (UM22-100, Thorlabs,
Newton, NJ)) attached to 453 nm (blue), 528 nm (green), and 940 nm (near infra-red)
LEDs, respectively. All LEDs were purchased from Digikey (Thief River Falls, MN).
The optical fiber was lined up with its respective LED using two precision manipulators.
The alignment was carefully done to obtain maximum optical throughput but avoiding
crashing the fiber tip into the LED. UV optical epoxy was used to set the optical fiber in
place and to secure the alignment between the LED and the optical fiber. In each case, the
LED-optical fiber assemblies were powered by the Mightex LED power supply, allowing
the optical power output to be adjusted by changing the electrical current running through
the LEDs. Each and every experiment, the fiber optics should be examined not only to
make sure that the output optical power intensity is steady but also the fiber tips are still
intact and having a uniform light profile. Figure II.2 shows the optical fiber output light
profile, whereas figure II.3 and figure II.4 illustrate how this light profile would be after
traveling through 100 pm and 200 pm tissue thickness for the same exposure time (2500
ms). Another example when the exposure time has changed for the same tissue thickness
is presented in figure II.5 and figure II.6.
8


tOO micrometer core, optical fiber output profile, coupled to 518
i, green (LED) driven by a 100 mA current source, at exposure time equals to 500 ms
4500
4000
Figure II.2 A 100 [im core, coupled to a 518 nm green LED and driven by a 100 mA
current source, optical fiber output profile
The light profile of 100 micrometer core, optical fiber, coupled to 518 nm, green (LED) driven by a 100 mA current source, at exposure time equals to 2500 ms, through 100 micrometer sample thickness
4500--.
4000- ...
Figure II.3 A 100 [im core, coupled to a 518 nm green LED and driven by a 100 mA
current source, optical fiber output profile after traversing a 100 [im sample
thickness
9


The light profile of TOO micrometer core, optical fiber, coupled to 518 nm, green (LED) driven by a 100 mA current source, at exposure time equals to 2500 ms, through 200 micrometer sample thickness
Figure II.4 A 100 [im core, coupled to a 518 nm green LED and driven by a 100 mA
current source, optical fiber output profile after traversing a 200 [im sample
thickness
The light profile of 500 micrometer core, optical fiber, coupled to 453 nm. blue (LED) driven by a 100 mA current source, at exposure lime equals to 10 ms. through 100 micrometer sample thickness
Figure II.5 A 500 [im core, coupled to a 453 nm blue LED and driven by a 100 mA
current source, optical fiber output profile after traversing a 100 [im sample
thickness at 10 ms exposure time
10


The light profile of 5DO micrometer core, optical fiber, coupled to 453 nm. blue (LEO) driven by a 100 mA current source, at exposure time equals to 20 ms. through 100 micrometer sample thickness
£
b
4500
4000
3500
3000
2500
2000
1500
tcno
500
0
1200
1040 (pixel)
1392 (pixel)
Figure II.6 A 500 [im core, coupled to a 453 nm blue LED and driven by a 100 mA
current source, optical fiber output profile after traversing a 100 [im sample
thickness at 20 ms exposure time
Linearity Tests
The Importance of These Linearity Tests
Now that these first sets of graphs had been collected and made as empirical
references for the next following sets of experiments that have been launched after. And
that has given the flexibility required to modify and adjust some experimental parameters
without changing the setup or the procedure entirely. In addition to that, comparable
ways of presenting the analyzed data and the results have been allowed by the aid of
those graphs.
LEDs Power Intensity Linearity Tests
Four different types of optical fibers coupled to four different LEDs having
different wavelengths had been tested to incorporate within this experiment; those fibers
11


are: green 518 (nm), 100 (gin) core diameter, green 528 (nm), 100 (gm) core diameter,
blue 453 (nm), 100 (gm) core diameter, blue 453 (nm), 500 (gm) core diameter. The
power intensity graph as a function of current intensity had been measured for those four
optical fibers and drawn as they can be seen in the following figures. The CCD camera
sensitivity for LEDs power intensity linearity responses under normal rooms
illumination versus when the room light is turned off had been tested taking into account
the different LEDs wavelengths and different optical fibers core diameters. The results
show very reliable linearity responses for the camera.
Figure II.7 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 518 nm green (LED), when the room light is turned off
12


Figure II.8 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 518 nm green (LED), under normal rooms
illumination
Figure II.9 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 528 nm green (LED), when the room light is turned off
13


Figure 11.10 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 528 nm green (LED), under normal rooms
illumination
Figure 11.11 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 453 nm blue (LED), when the room light is turned off
14


Figure 11.12 The data fitting line for the output power density of the 100 pm core
optical fiber, coupled to a 453 nm blue (LED), under normal rooms illumination
Figure 11.13 The data fitting line for the output power density of the 500 pm core
optical fiber, coupled to a 453 nm blue (LED), when the room light is turned off
15


Figure 11.14 The data fitting line for the output power density of the 500 pm core
optical fiber, coupled to a 453 nm blue (LED), under normal rooms illumination
CCD Camera Linearity Tests
The CCD camera linearly tests had also been experimented as a function of
various exposure times and these graphs can be shown in the following figures. Five
different pixel locations had been taken into consideration which are (100, 100), (100,
1292), (520, 696), (940, 100), and (940, 1292) of (1040 x 1392) pixels image to show the
consistency and robustness of the linearity responses across the entire detection area.
16


Figure 11.15 Linearity test for the CCD camera at (100,100) pixels location of (1040
x 1392) pixel image
Figure 11.16 Linearity test for the CCD camera at (100,1292) pixels location of
(1040 x 1392) pixel image
17


Figure 11.17 Linearity test for the CCD camera at (520, 696) pixels location of (1040
x 1392) pixel image
Figure 11.18 Linearity test for the CCD camera at (940,100) pixels location of (1040
x 1392) pixel image
18


Figure 11.19 Linearity test for the CCD camera at (940,1292) pixels location of
(1040 x 1392) pixel image
Sample Preparation
Another significant and vital part before initiating these experiments is the case
study sample preparation. This operation has had a lot of impacts on the results, on the
whole, and during the course of action through conducting these experiments. This
process is started by getting the animal down, decapitated, after being briefly anesthetized
via isoflurane inhalation (IsoFlo, Abbott Laboratories, USA). All animals that are
allocated for those sets of experiments were six to eight weeks old mice from which
coronal and sagittal brain slices were prepared. Then the brain is being taken out of the
skull through a neat procedure and was dissected out under ice-cold dissection Ringer
containing either (in mM): Ringer 1: 125 NaCl, 2.5 KC1, 1 MgCh, 0.1 CaCh, 25 glucose,
1.25 NaH2P04, 25 NaHCCb, 0.4 ascorbic acid, 3 myo-inositol, and 2 pyruvic acid; or
Ringer 2: 200 sucrose, 1.25 NafUPCK 26 NaHCOs, 10 glucose, 3.5 KC1, 7 MgCl, 1.5
ascorbic acid (all chemicals from Sigma). After that, its adhered and sliced using the
19


slicing machine to different slices thicknesses (mainly 600 pm). Those slices were cut
with a vibratome (VT1000S, Leica), transferred to an incubation chamber containing
extracellular solution (ECS) [ECS; containing (in mM) 125 NaCl, 2.5 KC1, 1 MgCh, 2
CaCh, 25 glucose, 1.25 NaEEPCN, 25 NaHCCb, 0.4 ascorbic acid, 3 myo-inositol, and 2
pyruvic acid, all chemicals from Sigma] and bubbled with 5% C02-95% O2. Slices were
incubated in ECS for 15 30 minutes at 37C and then cooled down to room temperature.
All measurements were obtained within 2-3 h of slicing.
Targeted Brain Areas
The brain areas that have been dealt with throughout this study are: Medial
Nucleus of the Trapezoid Body (MNTB), Ventral Nucleus of the Trapezoid Body
(VNTB), Lateral Superior Olive (LSO), Pedunculopontine Tegmental nucleus (PPT),
Superior Colliculus (SC), Cornu Ammonis 3 of hippocampus (CA3), the cerebellar
cortex molecular layer, Olfactory Bulb (OB). The brain regions were chosen because
previous knowledge suggested that they would represent a wide range of scattering
coefficients, but also to perform control experiments for future optogenetics
manipulations.
And since in these experiments, the thicknesses of the samples play a significant
role in determining how the results would look like, this issue has been always borne in
mind and taken into account by having those brain areas completely confined within the
sample thickness, by making its surface as a flat as it could be, and by immersing it in the
ECS while doing the slicing process and when the measurements are being taken.
Moreover, sometimes it's also being bubbled throughout the experiment to keep it
oxygenated. The truth of the matter behind these strict sample preparations is the
20


tendency to mimic almost the same "in vivo" environment and maintain the metabolism
of the sample as long as possible. This study has shown how this aspect has an absolute
relevance with how those biological tissues respond optically (more details will be
presented in the discussion section).
Experimental Procedure
Manually-Controlled Method
After the sample is prepared with a certain thickness, it is transferred to a small
chamber that is transparent from the bottom to make it more convenient for using with
the inverted microscope. That chamber will have been already cleaned using special lens
papers. The sample will be floating inside the preserving fluid (that is bubbled sometimes
to keep it oxygenated and healthy, as it is mentioned before). And for that reason, it is
required to add a piece of metal with strings as a mass to keep it from that random
movement. However, the latter has undesirable effects on the sample as well; these
effects will be elucidated in the discussion section. The earlier stages of these sets of
experiments had been done manually without having a pico-motor and the CCD video
camera and the monitor, by trying to land the fiber tip on the top of the sample and get it
to be centered on the targeted area without forgetting having the sample being in focus by
moving the stage up and down, and take an image that represents arbitrary digital
intensities for the original optical power intensities after passing through that specific
thickness. Then, that sample will be replaced by another one with another thickness and
the same procedure is being repeated. The current intensity that is corresponding to the
aimed optical power intensity is set up based on the optical power intensities curves for
21


each individual optical fiber. Rooms lights will be turned off to avoid any other
illumination sources. The main goal for those types of experiments was to construct a
curve for the arbitrary digital intensities or the optical power intensities as a function of
sample thickness. Each point accounts for the maximum intensity accompanied with the
fact that this fiber optic output profile is Gaussian (Some results belongs to this approach
can be seen in figure 11.20).
Figure 11.20 Light arbitrary digital intensity as a function of tissues thickness for a
PPT region. This is a one single set of measurements
As it stated earlier, the first sets of experiments had been performed without
having the pico-motor which is implemented later in order to make punching through the
brains samples possible with higher accuracy (see next section). Before that, all the
punching trials had been done manually which had been considered to be a vague process
since there are no enough clues to determine how far the fiber tip inside the sample goes.
22


Pico-Motor-Controlled Fiber Punch-Through Method
The other approach that has been launched after that pico-motor and the CCD
video camera had been installed to the system is the punching through approach or fiber
punch-through method. In this approach, instead of having several samples with
different thicknesses in order to construct that formerly mentioned graph, there will be
only one sample with the thickness that contained the whole area under investigation
from the top to the bottom, and now the fiber tip can punch through driven by that pico-
motor through precisely determined step sizes to trace the total moving distance after
making sure that the fiber tip is properly landed on the top of the sample surface.
After the incubation period, a slice was placed into a measurement chamber and
continuously superfused with bubbled extracellular solution for the duration of the
experiment. The measurement chamber was then positioned on the inverted microscope
in which the standard transmitted light source was replaced by an assembly consisting of
a three-axis manual micromanipulator (Narishige model MM-3), a calibrated piezo
driven one axis micromanipulator (Model 8302 Picomotor Actuator, Newport, Irvine,
CA), and a custom made optical fiber holder to hold one of the three fiber/LED
assemblies in place. The output end of the optical fiber was placed directly onto the
surface of the brain slice under the guidance of the CCD video camera using macro
optics, such that the emitted light was facing the brain section and the microscopes
objective (EF lOx, N.A. 0.25, Leitz Wetzlar, Germany). The light was then captured by
the monochromatic 12bit camera attached to the microscope via the camera port (see
figure 11.21 for a sketch of the setup).
23


Light
source
Optical fiber
Glass slide
Section
600|jm thick
Objective xIO
N.A. 0.25
Monochrome
12 bit camera
Figure 11.21 Basic experimental setup of the punch-through method. On an inverted
microscope, an optical fiber was placed on a section of brain tissue such that
light from the fiber would pass through the tissue and subsequently be imaged
by an objective attached to a CCD camera [12]
Exposure time and the irradiance of the optical fiber (Ia) were adjusted to
optimally utilize the Mightex camera dynamic range throughout the entire data set.
Subsequently, the fiber was lowered into the slice in 5 pm steps using the precision piezo
micromanipulator, starting from the surface of the section and ending at a depth of 500
pm. At every step, the camera will be taking a number of images and get them to be
averaged by a number, which can be manipulated from the controlling program front
panel. Instantaneously, a graph will be drawn for arbitrary digital intensities as a function
of sample thickness after allocating the cursor in the right position. Consequently, the
images taken will be stored in a chosen folder to pave the way for more data analysis to
be accomplished upon them succeedingly.
24


Computer software, Lab VIEW 2009 Service Pack 1 (National Instruments,
Austin, TX), has been installed on the computer, and a computer program was written in
this software to control the pico-motor and get it to move up and down in very precise
step sizes, and to control the Mightex camera. Other very important parameters can be
changed or adjusted through the program panel; for example, the CCD camera exposure
time, total moving distance, the number of pictures that are going to be taken and
averaged for each individual step size measurement. It is also allowed to change the
cursor position to another pixel location rather than the central one to read the digital
intensities from those pixels locations (a snap shot for the controlling program front panel
screen can be seen in figure 11.22).
25


E Tissue Light Scattering Control Program.vi Front Panel B0S1
Fjle Edit View project Operate Tools Window Help |0|#j [ll|| 13pt Application Font | So' ll^klliSH |0| ffiS
iiaSvHaSSpi
iMippniMl
5odb -f
Intensity at Cursor
0
j C:\Docunentsand5ettings\Lefca2_3i
i Desktop\testitest
Wait Time for Motor (ms)
:Jt........'
Main Application Instancel <
Cursors: 1X ] V \ 2 j 1 1 1 1 J
H Cursor 0 742 585 2214 1 zl
u ir
j Start 1 to TissueLightScatterin... E Tissue Light Scatterin... Lab VIEW
Figure 11.22 A snap shot for the controlling program front panel expressing the
adjustable significant parameters and other details
Images taken at different steps were stored for further data analysis. An example
of such an image is shown in figure 11.23.
26


Figure 11.23 An example of an original image captured by the CCD camera,
showing light emitted from an optical fiber after it passed though a section of
brain tissue [12]
The data was extracted from images by locating the pixel representing the fiber
center, and collecting that pixel 12 bit gray scale value for the digitized optical irradiance
/(z). This process was repeated for each image, /(z) was normalized to I0 to obtain the
optical transmittance T(z) = I (z) //0, which was then fitted by a single exponential
function (Figure 11.24) according to the modified Beer-1 ambert law (see Chapter III) to
extract the effective attenuation coefficient p^of the measured neural target.
27


1.0
CD
o
c
03
E
(/)
c
05
0.8
0.6
0.4
J 0.2
CL
O
0.0
0
100 200
Tissue Thickness (|jm)
300
Figure 11.24 Optical transmittance as a function of tissue thickness. As the optical
fiber was advanced through the section of brain tissue and repeated images such
as the one in figure 11.23 were taken, the decrease in optical transmittance as a
function of tissue thickness could be evaluated. The single measurements (+
symbols) represent transmittance of blue light (453 nm) through a section of
PPT at various thicknesses, while the solid line represents an exponential fit [12]
Eventually, the output optical power intensity and the light profile will be tested
again to be certain that the fiber tip has not been defected and the light profile is not
distorted throughout the experiment.
Control experiments determined that the forces applied on the tissue by the
advancing glass fiber are comparable to those created by an advancing sharp
microelectrode (< 200 pN, data not shown). We thus concluded that lowering the fiber
into the tissue caused the fiber tip to slice through, rather than squish the tissue together,
such that measurements at many different tissue thicknesses could be taken reliably from
the same tissue section at precisely controlled depths (referred to as fiber punch-through
method).
28


Light Profile and Tissue Damage Control Experiments
Incidentally, and as it is referred to the idea of whether the light profile is enough
to cover the targeted areas or not, it is convenient to show the results regarding this part
of the study as shown in figure 11.25.
Figure 11.25 (Left) it is an overlapped picture of two images that are taken for a PPT
region, in 300 pm of thickness and 1300 pm from the midline of depth slide. The
background image (which is in black and white colors) shows the PPT area,
while the blue one is, the output optical power intensity profile for the 100 pm
core optical fiber connected to a 453 nm blue LED, driven by a 28 mA current
source. This picture is evidence that the blue LED light is not sufficient to cover
the whole PPT region. These two images are taken on an integration time of 100
ms. (Right) it is an overlapped picture of two images that are taken for a PPT
region, in 300 pm of thickness and 1300 pm from the midline of depth slide. The
background image (which is in black and white colors) shows the PPT area,
while the green one is, the output optical power intensity profile for the 100 pm
core optical fiber connected to a 518 nm green LED, driven by a 100 mA current
source. This picture is evidence that the green LED light is not sufficient to cover
the whole PPT region. These two images are taken on an integration time of 100
ms
Another potential trial which has emerged from the eagerness of showing how the
laser light intensity could expose a thermal damage in the targeted area had been
performed and its results are nicely presented in figure 11.26.
29


100
Figure 11.26 (Top left) a 300 pm of thickness and a 1500 pm from the midline of
depth slides image, showing the actual image that is taken from the CCD
camera, of the CA3 Hippocampus region under white light illumination and
before the laser damage. This image is taken on an integration time of 100 ms.
(Top right) a 300 pm of thickness and a 1500 pm from the midline of depth
slides image, showing the false color of the CA3 Hippocampus region under
white light illumination and before the laser damage. This image is taken on an
integration time of 100 ms. (Bottom left) a 300 pm of thickness and a 1500 pm
from the midline of depth slides image, showing the actual image, that is taken
from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5
mW laser source illumination, being applied for 3 minutes of time. The image
shows a real tissue damage which is caused by the laser source under these
circumstances. This image is taken on an integration time of 100 ms. (Bottom
right) A 300 pm of thickness and a 1500 pm from the midline of depth slides
image, showing the false color of the CA3 Hippocampus region under 405 nm
and 3.5 mW laser source illumination, being applied for 3 minutes of time. The
image shows a real tissue damage which is caused by the laser source under
these circumstances. This image is taken on an integration time of 100 ms
30


Now that, tissue damage was checked. Therefore, it was concluded that it needs to
illuminate the section with much higher light intensities and exposure times to cause
damage than what has been used during this study measurements.
31


CHAPTER III
DATA ANALYSES, THE MODIFIED BEER-LAMBERT LAW,
BRAIN ATLAS ESTABLISHMENT, AND RESULTS
Data Analyses
The results associated with this study are strictly taken from the following brain
areas: MNTB, VNTB, LSO, PPT, SC, CA3, and Cerebellum. Although the images have
been stored, yet they are still considered to be raw data and it is required to make it
through a series of data analysis steps before they can be scientifically illustrated
corresponding to multi-data presentations that serve to answer the fundamental questions
and aims of this study.
The results could be introduced by following these steps: the pre-stored images in
a specific folder are reloaded to another viewer program that is programmed in Lab VIEW
software as well, that allows retrieving the intensities from those images according to a
cursor location that is also adjustable by the analyzer. Then, these intensities that are
corresponding to each tissue thickness will be saved in an appropriate format. This
process still be pursued by a sorting one and thereby, they are ready to be depicted now.
A snap shot for the viewer program is illustrated in figure III. 1.
32


£ Tissue Light Scattering Viewer.vi Front Panel nfelfxl
File Edit View project Operate Tods Window tlelp |0|tH | ll| | l3pt Application Font {ISo'll SSI'! |0*| r?i?3

plot o
Mtin'Appicatlon Instance] <
* Tissue Light Scatterln.,. JE Tissue Light Scattertn,.
Figure III.1 A snap shot for the viewer program front panel screen that is used for
retrieving the intensities from the images and plotting them as a function of
tissue thickness according to the specific cursor location
Two programs that have been used in order to graph the resultant data are:
MATLAB R2010a and Igor 6. That resulted curves are normalized so that they are in a
comparable forms. It is of fundamental importance that these data are being fitted with
the most suitable equation form to make it possible to extract some valuable parameters
like the one mentioned sooner- the effective attenuation coefficient (jit) that belongs to
each region under investigation. The first equation that had been used to fit the data was
33


the modified Beer-Lambert law for light scattering and absorption in biological tissues,
which has the form of:
/(x) = I0e~^x
In which:
/(x): is the optical power intensity as a function of tissue thickness (mW/mm2)
I0 : is the initial optical power intensity (mW/mm ) (when x=0 mm)
/it: is the effective attenuation coefficient (1/mm)
x: is the tissue thickness (mm)
More elaborate theoretical background pertaining to the modified Beer-Lambert
law is presented in the following section.
Some of the results that had adopted this approach are shown in the figures III.4-6
using MATLAB. In these figures, the one and two words refer to the first and second
measurements on the first and second slices used in that experiment, respectively. A full
comprehensive description for the experiment that the following figures have been based
on is elucidated as follows:
In this experiment, a 600 pm thick slice is used and punched through different
depth following the multiple different step-sizes of the motor (5 pm step-size are used).
The total moving distance was 500 pm in depth making the smallest thickness taking into
our consideration to be 100 pm. The optical source used in this experiment is a blue LED
light (453 nm) coupled to a 100 pm core diameter optical fiber with an output power of
4.33 mW/mm from this fiber. The LED source is driven by a 28 mA current to get this
power. The CCD camera was set on 50 ms exposure time throughout the experiment.
34


The aims of these data analyses are to extract the pixels digital intensities from
the images taken. Then, get rid of the saturation values. After that, the raw data are drawn
and their exponential curves are obtained. These raw data and fitting curves are
normalized, as well, in order to make the results comparable to each other properly.
Digital Intensity (Normalized) Versus Tissues Thickness (um)
Figure III.2 A cerebellum one raw data and fitting curve. Note the offset in the fit.
This issue will be addressed below
35


Digital Intensity (Normalized) Versus Tissues Thickness (um)
Figure III.3 A comparison between PPT one and PPT two. Note the offset in the fit.
This issue will be addressed below
Digital Intensity (Normalized) Versus Tissue's Thickness (um)
Figure III.4 A comparison between CA3 one and CA3 two. Note the offset in the fit.
This issue will be addressed below
36


The obtained data follows an exponentially decaying curve as predicted by the
modified Beer-Lambert law. However, due to the electronic offset and other optical
background, there is an artificial offset needed to be accounted in the data. Having taken
that into account, the new fitting equation, for now, looks like the following:
/(x) = Y0 + I0e~^x
One can simply see that this equation is of the same format as the old one with
only one term added to it which is Y0 which refers to that initial intensity. Thus, the same
data reanalyzed applying the latter approach and this time using Igor programming, and
the results are demonstrated in the following figures (Figure III.5 and Figure III.6). It is
also important to indicate that "Tau" in these figures accounts for the effective attenuation
coefficients.
Dsarce(um)
Figure HI.5 A comparison between PPT one and PPT two after taking the offset
factor Y0 into account which demonstrates its significant impact on the
reanalyzed and refitted the data
37


Figure III.6 A comparison between CA3 one and CA3 two after taking the offset
factor Y0 into account which demonstrates its significant impact on the
reanalyzed and refitted the data
The Modified Beer-Lambert Law and the Effective Attenuation Coefficients for
Highly Scattering Neural Targets
The full mathematical treatment of light travelling in biological tissue that absorbs
and scatters light-waves (or optical photons) is described by the Radiative Transport
Equation (RTE) [13], [14],
- 8L(rs^ + .v V/.(/%s,t) + (jua+ jus)/.(/%s,t)- us f L(r,s,t)p(s'-s)dn'= S(r,s,t)
c ot Jo
Where L(f,s,t) is the radiance (W m_2sr_1) of the propagating light-wave;
and fis are the absorption, scattering coefficients (m-1) of the biological tissue; /'(.s'-.s)
38


is the phase function describing the probability of a photon scattered to the radiation
direction s' from its original radiation direction s ; S(r,s,t) is the optical energy density
(W m_3sr_1) generated in the biological tissue; c is the speed of light in vacuum and fl
is the solid angle.
The RTE is a complex equation which has no analytical solution, since L(f,s,t)
depends on both the spatial coordinate (r) and the radiation direction (s) and time (t),
resulting in a function with seven independent variables. L(f,s,t) can be evaluated
computationally with the RTE but requires an involved computational algorithm such as
a Monte-Carlo stochastic simulation [15], [16], Therefore, to extract quantitative
parameters from our empirical measurements, a simplification of the RTE is needed. For
most biological samples, including the brain, the scattering coefficient at the wavelengths
tested here is typically one to two orders of magnitude higher than the absorption
coefficient (jis jia). In addition, the phase function /'(.s'-.s) can be approximated by the
Heyney-Greenstein function [17]:
p(s'-s) = P(cosP) =
l~g2
3/2
2(1 + g2 -2gcos0j
Where g is the anisotropy factor and is generally assumed to be larger than ~0.9
(0.9 < g < 1) in most biological tissues, indicating that the scattering light is
predominantly forward-scattered. Under these conditions, the RTE can be approximated
by the diffusion equation (the details of the simplification can be found in [13]:
1 dl(r,t)
c dt

1
APa+P^-g)]
V2I(f,t) = S(f,t)
39


4 n
Where/(r,t) = ^L(f,s,t)d£l is the irradiance (W m-2), or in the laboratory
0
commonly (but erroneously) called intensity of the light wave, and
4 n
S(r,t) = 4ft jS(r,s,t)dQ. To further simply the diffusion equation, we further assume
0
that the optical propagation is in a steady-state condition (dl(f,t)/dt = 0) and there is no
light being generated in the biological tissue S(r,t) = 0. Therefore, the ID diffusion
equation can simply be written as a ID second-order differential equation [14]:
d2I(z)
dz2
Where geff = ^3/ia[/ia + /is(l g)] is the effective attenuation coefficient.
Hence, the solution of the ID diffusion equation is the modified Beer-Lambert Law [14]:
~~ = T{z) = exp(-//e^.z)
*0
With /0 being the irradiance measured at the fiber output of the optical fiber, and
z being the longitudinal distance from the fiber output. The ratio of /(z) against /0 is the
optical transmittance T(z) which follows an exponential decay against the longitudinal
distance z. In this study, we attempt to estimate the optical penetration depth within a
brain nucleus to determine optical fiber source excitation efficacy of the opsin expressed
within this neural target. It is clear from the above equation that it is not necessary -at the
three wavelengths tested hereto individually measure /ia, jis and g. Rather, simply
measuring the effective attenuation coefficient geff is sufficient for this estimation.
40


The Brain Atlas, and a Technique of Mapping the Effective Attenuation Coefficients
across the Entire Brain
The technique of using an optical fiber to punch through a brain slice allows
collecting data from well identified brain areas at very precise depths. However, it would
be impractical to use this technique to map the effective attenuation coefficients //e/7 (r)
of many (i.e. hundreds) of brain areas, which would be required to obtain a quantitative
picture across the entire brain. However, imaging brain slices using bright-field light
transmission microscopy with monochromatic light and combining these images with the
measured effective attenuation coefficients obtained from the punch-through method on
selected neural targets allowed us to calculate and map out the effective attenuation
coefficients across the entire brain. Whole brain slice imaging was performed on an
Olympus VS 120 microscope, using transmitted light filtered via 546 /20 nm band-pass
filter and a lOx (N.A. 0.40) objective. To allow seamless, quantitatively correct tiling of
multiple images of a single brain section, the manufacturer calibrated the microscope to
normalize for uniform illumination and data acquisition across the entire imaging area.
With this normalization, the illumination irradiance /0 can be assumed to be a constant
across the whole brain slice scan.
The illumination irradiance /0 of the microscope is difficult to measure directly,
instead brain slices containing the brain areas measured previously with the punch-
through method were used to quantify and normalize /0. For a previously measured brain
area, using the modified Beer-Lambert law, the illumination irradiance /0 can be
estimated by
41


j I(x0,y0,z0)
exp \-fieff(x0,y0) z0\
Effective attenuation coefficients Fe/y(x with the punch-through method can subsequently be calculated using
Me//0.y)
1
--loge[
Z0
/(x, y, z0)
lo
]
The Effective Excitation Distance for Optogenetic Proteins
In optogenetic experiments, it is important to estimate the minimum optical
irradiance required to effectively excite the desired neural area longitudinally to
maximize excitation of the optogenetic proteins. Assuming the minimum excitation
irradiance threshold for an optogenetic protein is Imin and the irradiance at the fiber
output is Ifiber, the effective excitation distance d in the longitudinal direction of a neural
target, which has an effective attenuation coefficient of jieff can be calculated by the
following equation
1 /
d = -------loge ["----]
fteff *fiber
Integration of All Relevant Data in a Computer Program
From a practical point of view, an investigator wishing to perform optogenetic
manipulations in-vivo in the brain area of his/her choice needs to be able to estimate the
required light intensity that needs to be fed into an optical fiber to obtain optimal
illumination of the brain area to be manipulated. A situation where too much light energy
is used may result in tissue damage and is therefore undesirable. Furthermore, feeding too
much light energy into an optical fiber may result in unspecific activation of optogenetic
42


proteins outside the intended brain area, potentially compromising the experimental
design. On the other hand, in a situation where not enough light energy is used,
optogenetic proteins will fail to be activated. To aid with determining the correct amount
of light energy for a given experimental situation, we prepared a brain atlas that maps
effective attenuation coefficients across the entire mouse brain. This atlas is integrated
into a computer program that an investigator may use to estimate the required amount of
light energy for an individual experimental situation based on brain area, desired
penetration depth, and light frequency used. For further information, see
www.optogeneticsapp.com.
Results
The main goal of this study was to test the hypothesis that different brain neural
targets scatter light differently, and that these differences are significantly large such that
they need to be considered for successful optogenetic activation in deep brain nuclei. A
secondary goal was to establish a database of light scattering values for different regions
of the mouse brain that could be used as a reference in future experiments in which
illumination of neural tissue is required. The most common approach to bring light into
deep brain areas invivo is via optical fibers that are stereotactically placed above the brain
area of interest. Our experimental approach of advancing a light emitting optical fiber
through brain tissue modeled such a situation well, and enabled us to precisely determine
light intensity at any depth along the longitudinal axis with respect to the fiber tip.
43


Light Intensity Decreases Exponentially in Brain Tissue
An acute brain slice was placed into a perfusion chamber under an inverted
microscope, and an optical fiber attached to a LED was placed directly on the tissue
surface. Light emitted from this fiber propagated through the slice and was then collected
by the objective and the chip of the attached monochromatic camera. A sketch of this
configuration is shown in figure 11.21, and an example of an original image acquired with
this setup is shown in figure 11.23. This configuration of imaging the light emitted from
an optical fiber tip after it passed through a piece of brain tissue of known origin and of a
known thickness d allowed effective measurement of the remaining light intensity at
tissue depth d. From this value we could then calculate the ratio of the intensity of
remaining light at depth d over the original light intensity at the optical fiber tip.
Subsequently, the optical fiber was lowered into the section in 5 pm steps, and
similar images were acquired with each step. Control experiments verified that advancing
the fiber into the tissue caused it to reliably slice through the section rather than compress
the section (data not shown). Advancing the fiber into the tissue (referred to as the fiber
punch-through method), and taking repeated images at various depths effectively
created a dataset of light intensity measurements in brain tissue at points progressively
closer to the fiber tip. An alternative approach would have been to cut brain slices of
different thicknesses and measuring light transmitted through each one of these slices.
However, the fiber punch-through method allowed us to control for tissue depth
(thickness) much more precisely than cutting sections of various thicknesses would have
allowed us to do, and furthermore allowed us to measure the exact same piece of tissue at
different depths.
44


From the measurements obtained at various tissue depths, light intensity ratios
were calculated and plotted. Curve fitting indicated that the data points were best
described by a single exponential function. An example of such a fit is shown in figure
11.24, representing a set of measurements with blue light (453 nm) recorded from a
section of PPT. The + symbols represent the measured luminance at each tissue
thickness, and the superimposed line represents the exponential fit.
Light Scattering Properties Vary across Different Brain Regions
Eight different brain regions were measured with 453 nm light in the same way as
the PPT shown before (Figure IIT7). The data points (colored symbols) were plotted
against the distance from the fiber tip, and the set of measurements from each brain area
were fitted with a single exponential function (colored lines).
Figure III.7 Optical transmittance through different types of brain tissue.
Measurements using the fiber punch-through technique were taken in eight
different brain areas with blue (453 nm) light. In each case, optical
transmittance decreased exponentially with tissue thickness; however, the
exponential decreases observed varied greatly with the type of tissue. Single
measurements are represented by the respective symbols while the solid lines
represent exponential fits of the data
45


The results indicate that light intensity dropped at least 10-fold within a 200 pm
distance from the tip of the optical fiber in each brain region tested. Importantly, the data
suggest that this drop differs substantially among the brain regions tested. To
systematically examine these differences, we calculated scattering coefficients from the
data (Figure III. 8). Average coefficients ranged from 19.96 +/- 0.26 for VNTB tissue,
representing the lowest light transmittance of any region tested, to 9.76 +/- 0.78 for
cerebellum, representing the highest transparency of all brain regions tested. For all
values and SEMs, see figure HI.8 and corresponding figure caption.
Figure III.8 Effective attenuation coefficients with SEMs for the eight brain areas:
VNTB 19.96 +/- 0.26 (1/mm); CA3 19.12 +/- 0.84 (1/mm); MNTB 18.16 +/- 0.69
(1/mm); LSO 17.92 +/- 0.80 (1/mm); PPT 15.26 +/- 0.78 (1/mm); OB 14.88 +/-
0.74 (1/mm); SC 13.91 +/- 0.83 (1/mm); Cerebellum 9.76 +/- 0.78 (1/mm)
The MNTB, VNTB and LSO were measured with three wavelengths of light,
while all other nuclei were measured with one wavelength, (see table III. 1 for summary).
One set of measurements was performed per brain nucleus per hemisphere.
46


Table III.l Brain areas that were measured with three different wavelengths, and
sample size (the unit of the effective attenuation coefficient is 1/mm) [12]
Brain Area Effective Attenuation Coefficient peff (1/mm)
71 = 453 (nm) 72= 528 (nm) 73= 940 (nm)
MNTB 18.16 (n=ll) 15.86 (n=9) 13.86 (n=8)
VNTB 19.96 (n=6) 17.69 (n=7) 14.39 (n=7)
LSO 17.92 (n=4) 15.91 (n=7) 14.01 (n=6)
PPT 15.26 (n=10)
SC 13.91 (n=10)
CA3 19.12 (n=8)
Cerebellum 9.76 (n=8)
Olfactory 14.88 (n=5)
Figures III.9 and figure III 10 show the practical consequences of these
differential coefficients on light penetration through the different types of tissue. Figure
III.9 plots the optical power required to illuminate neurons up to a tissue depth of 300 pm
below the optical fiber tip with a light intensity of at least 10 mW/mm (the light power
required for ChR2 activation 8-12mW/mm [3]). To achieve this goal in cerebellar cortex,
about 1.5 mW need to be emitted from the tip of the optical fiber, while in the case of
VNTB, about 20 times as much optical power is required to achieve the same goal.
47


300 |jm Depth
30-
25-
E
20-
o
CL 15-
Q.
O
10-
5-
r
1

VNTB
CA3'MNTB [io
PPT
Brain Area
OB
SC
Cerebellum
Figure III.9 Optical power values that would need to be fed into a 100 pm diameter
optical fiber when 300 pm of tissue needs to be illuminated at intensities typically
used for Channelrhodopsin activation
Due to the nonlinear nature of light distribution in tissue, these differences
become more dramatic for deeper penetration. For example, doubling the illumination
depth from 300 pm to 600 pm would require about 20x the light intensity in the case of
cerebellar cortex tissue (28 mW). By contrast, illuminating 600 pm of VNTB tissue to the
same degree would require 12 W of light intensity, or 400 times the intensity required to
illuminate 300 pm (Figure III. 10).
48


Brain Area
Figure III.10 Same as figure IEL11 except that in this example the illumination was
calculated to hypothetically activate Channelrhodopsin over a distance of 600
pm from the fiber tip
These calculations suggest substantial differences in light scattering among
different brain areas, and make the point that certain manipulations are possible in some
brain areas but not others.
Light Scattering Varies with Wavelength
A traveling wave interferes with objects that are larger than its wavelength, but
tends to bend around objects smaller than its wavelength. Thus, long wavelength light
penetrates tissue deeper than short wavelength light. Since different lightsensitive
molecules are optimally excited at a variety of wavelengths, we tested the influence of
light wavelength on the penetration depth of light in brain tissue. Figure III. 11 represents
experiments in which MNTB was tested with three wavelengths: 453 nm, 528 nm, and
940 nm. As expected, the longest wavelength (940 nm) showed the most effective
penetration, i.e. the smallest attenuation of light intensity with increasing distance from
49


Optical Transmittance
the fiber tip (red line), while the blue light (453 nm) attenuated within the shortest
distance from the fiber tip (blue line).
Figure IILllEffects of wavelength on optical transmittance. Optical transmittance
in the MNTB as a function of tissue thickness and optical wavelengths. The three
colorcoded data sets represent corresponding measurements with light of three
different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)).
Longer-wavelength light penetrates tissue deeper, resulting in a higher
transmittance at any given tissue thickness [12]
Similar observations were made for a second brain area (VNTB) that was tested
in the same way (Figure III 12).
50


Optical Transmittance
Figure III. 12 Optical transmittance in the VNTB as a function of tissue thickness
and optical wavelengths. The three colorcoded data sets represent corresponding
measurements with light of three different optical wavelengths (blue (453 nm),
green (528 nm), and red (940 nm)). Longer-wavelength light penetrates tissue
deeper, resulting in a higher transmittance at any given tissue thickness
Note that optical absorption cannot be neglected at all light frequencies (an
assumption made for the three single light frequencies tested in this study), and thus there
is no simple linear extrapolation between the points shown in figure III. 13 [18],
51


O MNTB
VNTB
E
E
22-,
'g
it
O
o
c
o
to
c
CD
>
O
.CD
20-
18-
16-
14-
12 n
400

*
500
600 700 800
Wavelength (nm)
[]
0
900 1000
Figure III. 13 Effects of light wavelength on transmittance in two brain areas
(MNTB and VNTB). The effective attenuation coefficient decreases with
wavelength for the three wavelengths tested. MNTB measurements are
represented by round symbols while VNTB measurements are represented by
square symbols. Measurements in the three different colors are indicated by the
color-code of the symbols [12]
While the datapoints can be fitted with a single exponential (Figure III 14), the
relationship may be more complex [18],
c
g
'o
it
(D
O
O
c
o
CO
c
CD
CD
>
o
£
LU
20-
18-
16-
14-
12V
400
O MNTB
VNTB
---MNTB Proposed Fitting Curve
- VNTB Proposed Fitting Curve
500 600 700 800 900 1000
Wavelength (nm)
Figure III.14 MNTB and VNTB proposed fitting curves for the effective attenuation
coefficients as a function of wavelengths
52


Light Scattering Brain Atlas
While the fiber punch-through method allowed for measurements of light
scattering properties in anatomically defined brain areas, it is a relatively slow method.
Measuring many different brain areas with this technique would not be feasible.
However, to extend usage of our data to other areas of the brain without the need for
additional punch-through measurements, we prepared a brain atlas containing light
scattering values from the entire mouse brain. For this atlas, sections of 300 pLm thickness
were prepared from mouse brains, and imaged with an Olympus virtual microscopy
system (Olympus VS 120) using monochromatic transmitted light (546 nm band pass
filtered with a 20 nm band-pass width). The resulting images consist of relative
differences in tissue translucency in grey scale between different brain areas in the
section. Figure III. 15 shows an example of such an image, with several nuclei marked
with colored lines on the section.
53


Figure III.15 Relating fiber punch-though measurements to brain atlas
measurements. An image of a 300 pm coronal section of mouse brain stem, taken
on a calibrated virtual microscopy system with monochromatic light. Areas with
higher optical transmittance appear brighter on the image, while areas with
lower transmittance appear darker. MNTB, VNTB, and LSO are outlined in
red, orange, and yellow, respectively [12]
For brain areas that were also measured with the punch-though method, the
relative grey values of the images correlated very well with the effective attenuation
coefficients measured with the punch-through method (Figure III. 16), suggesting that the
grey values of the images can be used as a basis to calculate the effective attenuation
coefficients for brain areas that have not been tested with the punchthrough method.
54


Normalized digital irradiance from punch-through technique
1.0
0.8 -
Normalized digital irradiance from Olympus images
Figure III.16 Correlation in digital irradiance for brain areas tested with both the
fiber punch-through and the virtual microscopy method. Digital irradiance was
measured in six brain areas (MNTB (red), VNTB (orange), LSO (yellow), PPT
(green), SC (light blue), and cerebellum (dark blue) with both the fiber punch
through and the virtual microscopy technique. Results were normalized and
plotted against each other. Each colored symbols represents the measurements
from one brain area with two methods, the solid line indicates complete overlap
between the measurements. The bars attached to each data point represent the
standard error [12]
55


Importantly, the grey value images in combination with the effective attenuation
coefficients measured with the punch-through method allowed us to establish an atlas of
brain translucency that can be used to calculate the light scattering properties of any brain
area in the adult mouse brain.
Applying the Data to Experimental Design
An investigator planning an experiment involving light activation of a given
protein in-vivo is typically interested in the amount of light required to activate the
protein at a distance d, from the fiber tip. In order to correctly determine the required
amount of light, the following parameters must be considered: 1) The wavelength of the
light, 2) the largest distance from the fiber tip at which proteins are to be activated, 3) the
specific light scattering properties of the brain area involved, and 4) the diameter of the
fiber tip. We produced a computer program that calculates the required amount of light
for a given experiment based on user input of these parameters. Screenshots from this
computer program can be seen in the following figures. The program also incorporates
the brain atlas described above. For further information, see www.optogeneticsapp.com.
56


20:39
97% S
Optogenetics
Fiber Optical Power
r From 1 mW >
To 100 mW >
Fiber Core Diameter
100 um >
Optogenetic Protein
ChR2 \ >
Protein Activation Percentage
50% >
Neural Target
Target at Brain Atlas N >
Plot
>
e O
Parameter Entry Brain Allas Manual
Figure III.19 The desired input parameters control panel
57


Penetration Depth (um)
20:39
97% a>
Penetration Depth
660
600
540
480
420
360
300
240
180
120 f
60
0 i
00 10 20
Figure III.20 The attainable penetration depth as a function of optical power at the
fiber tip for the desired entered input parameters
30 40 50 60 70 80 90 100 1
Optical Power at the Fiber Tip (mW)
?
Parameter Entry Brain Atlas Manual
58


i
20:39
96%
Image No : 12
This version does not contain a full brain atlas.
For complete brain atlas, please see Optogentics Pro, the full version of this APP.
Plate 12/43
approximately Bregma +1.0 mm
Popneuron Limited
www.popneuron.com
?
Parameter Entry Brain Atlas Manual
Figure III.21 A sample image from the brain atlas where the investigator can select
the area of interest precisely such that its optical properties are designated, and
the corresponding penetration depth and optical power at the fiber tip are
calculated, accordingly
59



Optogenetics
Version 2.2
User Manual
20:40
96% S
Overview:
Optogenetics is a tool that aids an investigator in calculating the required optical power for a given in-vivo
experiment involving optogenetics or any other experimental approach that includes light delivery to deep brain
areas via optical fibers. To estimate the amount of light required for a given experimental design, knowledge about
the specific scattering properties of the brain region of choice, the specific opsin to be used, and the properties of the
optical fiber are required. A user enters these parameters into the APP, which then calculates the light scattering for
the specific experimental situation. The APP includes a full brain atlas for the adult mouse brain (Pro Version), from
which a user can look up the specific scattering properties of the brain area of choice. All data and all computations
that are used in this APP are published in: Al-Juboori, Dondzillo, Stubblefield, Felsen, Lei, and K.lug: Light
scattering properties vary across different regions of the adult mouse brain. PlosONE, in press.
For more information, pis see www.optOiieneticsapp.com.
Parameter Entry' Screen:
ci vi t

The Parameter Entry screen has six data entry fields into which the desired experimental parameters can be entered,
either via drop-down menus, or via the keyboard.
The six parameters are:
Fiber Optical Power:
Enter the minimum and maximum optical power you wish to use, or that your equipment is able to produce. The
penetration depth plot (see below) will plot the maximum penetration depth for each power value between the
minimum and maximum power values set here.
Fiber core diameter:
e fir-
Parameter Entry Brain Atlas Manual
Figure III.22 A screenshot for the user manual that is available in the computer
program also, in which the user can be taken through details about how to use
this application to its full extent
60


CHAPTER IV
DISCUSSION AND MAIN FINDINGS
Discussion
This study has been dealing with a lot of cardinal questions about the best
approach that these measurements must be conducted in order to make its main tasks
achievable. It has also been tackling many technical and practical issues; however, these
problems have eventually been overcome by modifications for the system setup.
So far this study has shown that it could be a necessity to choose different
illumination profiles and sources to activate some brain areas maybe through various
light profiles or side emitting fibers... etc. It has also been acknowledged that the regions
under study can be arranged from the densest to the least optically dense as VNTB, CA3,
MNTB, LSO, PPT, OB, SC,and Cerebellum, respectively, as illustrated in figure III. 8.
Another crucial aspect that this study has explored is the optical properties age
dependence for those brain tissues within the same species. Moreover, it has also shown
how important the tissue health is and how it affects the measurements all in all, and how
the time degradation rate for those brain tissues play a major role in their optical
characteristics. Most importantly, it shed light on the situation when there is a
photosensitive florescent material within the same region that is highly likely to emit
light back after being shining with a certain wavelength which gives awkwardly incorrect
results. And definitely this phenomenon should be avoided or resolved somehow.
On the flip side, there are still few "on stage" complexities that should be
mitigated. One of which is the camera saturation when it comes to very thin sample
61


thickness and that decreases the number of points that are taken for curves construction
and narrow the total moving distance, and eventually, it becomes obscure for the fitting
program to establish the best fitting approach. Another problem that has happened
sometimes is what so-called, humorously, "the pillow effect". Simply, it's the same
response that a pillow might respond when it is pushed from the middle and that will be
lifting its sides up higher. Applying this on a sample with one of the threads or strings in
the middle will lead to the same results and might alter the readings severely, sometimes.
Yet, altogether, this study is still promising, especially, for the methodology of
doing it this way that has not been done widely.
Main Findings
There are four main findings of this study: 1) Light emitted into brain tissue from
a point source such as an optical fiber declines exponentially in intensity with increasing
distance from the fiber tip 2) There are substantial differences in light scattering
properties among different brain neural areas, resulting in a need for specific knowledge
about any given brain area to be illuminated 3) The light wavelength used in a particular
experiment additionally influences the scattering properties, with longer wavelength light
penetrating deeper into the tissue 4) The results obtained in this study could be integrated
into a brain atlas of light scattering in the mouse brain, as well as a computer program
that allows a user to easily determine the light requirements for any given experimental
situation.
The most important finding is the observation that there are substantial
differences in the optical properties across different brain areas. For simplicity, previous
studies have assumed that light propagation through brain tissue is similar throughout the
62


brain, and have calculated the light requirements for optogenetic experiments with a
single effective attenuation coefficient [1], [10], [11], Our results show that a differential
approach is needed, because the observed differences in effective attenuation coefficients
can have substantial consequences on experimental design. Figure III.9 and figure III. 10
illustrates this point and suggest that certain manipulations are possible in some brain
areas but not others.
In some experiments, one might want to restrict the volume of illumination, e.g. if
an opsin is widely expressed in the brain [19] but only a certain region is to be
manipulated with light. Thus, specific knowledge of the light requirements for a given
experimental situation can inform an optimal experimental design, and this includes
knowledge about the specific light attenuation properties of the brain area to be
manipulated, as well as knowledge about how different light wavelengths will affect the
illumination.
63


CHAPTER V
IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES,
AND FUTURE PUANS
Improvements
A handful of improvements that would shift the accuracy and performance to the
edge are being thought seriously to be incorporated at this stage of doing this research
toward perfecting a three-dimensional (3D) light attenuation model for the brain. One of
these enhancements is to find out a more positive way to tell whether the fiber tip is right
at the top of sample surface neither far away from it, nor punched through it. Another
interesting scheme to measure would be obtainable by inserting some mechanical
properties that the sample could be described with to resolve the mystery behind the
actual act that is happening while the optical fiber is punching through, for instance; is it
punching through smoothly, pushing it to other sides through a random process, or
tearing the sample (which might be one of the reasons why there has been CCD camera
intensity saturations happening at some points when the fiber tip gets closer to the bottom
of the chamber). Hopefully, that will lead to an optomechanical three-dimensional (3D)
model for the light being attenuated in those brain areas.
Another empirical idea that has been come up with, recently, is what it could be
established by some minor adjustments to the system setup by changing the optical
intensities for the optical fibers that will be traversing a specific sample thickness through
tuning the current intensity. That allows erecting, at least, two handy graphs for each
sample thickness associated with a certain optical fiber manufacturer specifications and
64


the wavelength used. One of them would be the actual initial optical power intensity
measured at the sample surface as a function of current intensity- for a specific laboratory
experimental setup. The other one is the optical power intensity measured after the light
makes it through the whole sample thickness as a function of the initial one that has been
started with. Having done that, it will provide actual real numerical values for the optical
intensities needed to be delivered to carry out the desired action with the corresponding
initial ones that they should be started with in hand for the targeted brain area embedded
under certain depth. The results of this experiment could be incorporated with and used
for further examination, solidification, and confirmation to the results of this study.
Comparison with Previous Studies
Aravanis and colleagues [1] first characterized the optical scattering effect in
mouse brain cortical tissue by measuring the optical attenuation at different slice
thicknesses. In their work, the Kubelka-Munk model (T = 1/(5 z + 1) where 5 is the
scattering coefficient) was used in their data fitting. However, our measurements were
best fitted with an exponential function and the data cannot be satisfactory fitted with the
Kubelka-Munk equation. The discrepancy mainly occurs at larger distances (z >
200 fim), and our data show that light attenuates much faster than predicted by the
Kubelka-Munk model, resulting in a much reduced excitation distance of neural targets in
our results. A comparison between the two different fitting equations on a PPT raw data
is shown in figure V. 1.
65


Figure V.l A comparison between our exponential fit and Kubelka-Munk fit for a
PPT raw data showing that it is best fitted with a single exponential curve
More recently, Stark et al. [20] report that their measurements of optical attenuation
at larger distances from the fiber tip cannot be well fitted with the Kubelka-Munk
equation, although at shorter distances the data fit with the equation is good. The
differences are likely due to the different optical detectors being used in these
experiments. In our measurements, a single pixel of the CCD camera along the center of
the propagation axis of the optical fiber was used to construct the optical transmittance
curve. By contrast, the previous studies used a large area photodetector to measure the
optical attenuation, which also collects light not strictly propagating along the optical
axis. This difference could potentially result in differences in the data. Having taken that
into account, total intensity measurements were calculated and averaged over the entire
detectors area, and the results still indicate that the data can not be well fitted with the
Kubelka-Munk equation but rather a single exponential curve as shown in figure V.2.
66


Figure V.2 A comparison between our exponential fit and Kubelka-Munk fit for an
MNTB total intensity measurements of the raw data averaged over the entire
detectors area showing that it is best fitted with a single exponential curve
When light comes out of an optical fiber tip, light spread as well as the radius of
light increases as light propagates further away from the fiber output. This cone shape of
light propagation increases the beam area (i4), thus reducing the optical irradiance of the
light beam (/ = P/A). However, this reduction of optical irradiance due to beam
spreading from the optical fiber is much more gradual than the optical scattering in the
brain tissue, so this beam spreading effect can be neglected or considered to be absorbed
in the effective attenuation coefficient [ieff. For example, the numerical aperture (NA) of
the 100 [im core (r = 50 [mi) diameter optical fiber that was used in Our measurement is
0.22, such that the acceptance angle 9 of the light cone is 9.5 degree (NA =
n sin-1 9 where n = 1.33 in water). The radius of the beam increases over a
propagation distance of d = 500 [im by 83 [im (5r = d tan 9); thus the beam area
increases by a factor of 7, resulting in an optical irradiance reduction to 14% of its
67


original output. At the same time, according to our measurements, the optical
transmittance of the MNTB due to optical scattering after 500 jim of propagation is
0.01% at 453nm wavelength. Therefore, we conclude that the optical fiber beam
spreading is not a significant effect in estimating the optical irradiance in brain tissues.
Future Plans
Application of the Findings to Future Experiments
One goal of this study was to provide a body of knowledge on light scattering
properties of the mouse brain that could be used by investigators as a tool to optimize the
light stimulation for a specific experimental situation. To this end, data from several brain
areas were collected but the fiber punch-through method, while allowing us to obtain data
in great detail, was not efficient enough to use for a multitude of brain areas. Therefore
we resorted to virtual microscopy to image the entire mouse brain with monochromatic
transmitted light. The resulting images consisted of gray-value pixels, which represented
the differences in optical properties between these different brain areas. The differences
in grey values between different brain areas obtained with virtual microscopy
corresponded well with the differences observed in the fiber punch-through method,
allowing us to calibrate the results from the two approaches to each other. Thus, we
obtained data on the light scattering properties of the entire mouse brain, allowing an
investigator to look up the brain area of choice in the light scattering atlas, and
determining the associated specific effective attenuation coefficient for that area. This
coefficient can be entered into a computer program, together with information on the
desired stimulation wavelength and volume of brain tissue to be illuminated super-
68


threshold. The computer program then estimates the required light intensity at the optical
fiber tip to meet the desired criteria. The use of these tools should allow an experimenter
to design optogenetic manipulation in-vivo with better precision and more confidence that
the brain area to be activated by light will actually be illuminated at a super-threshold
intensity. Moreover, the delivered light can be adjusted to be super-threshold for opsin
activation in the desired brain area, and fall to sub-threshold values at the borders of the
brain area of interest, reducing unspecific activation of adjacent neuronal areas. For
further information, see www.optogeneticsapp.com.
Research Proposal for Determining Diffusivity Constants for Individual Brain
Areas
While the concept of using Optogenetics is growing tremendously and becoming
more involved in a variety of research and development studies in the field of
neuroscience and some other relevant branches which could be: robotics and neural
networks and fuzzy control soft computing (maybe in the future), there are still a handful
of related parameters to this methodology that require more investigation and some of
which are still undetermined. For example, the optical, mechanical, and thermal
properties of different brain areas. The knowledge about those parameters is of
significant importance to achieve the desired activation or stimulation for those targeted
brain areas precisely, accurately, and without damaging the brain tissues. In this
experiment we are interested in determining the conductivity or diffusivity constants for
individual brain areas. This will introduce the idea of delivering above the threshold
amount of optical power intensity assumed to activate the neurons from cortex, without
having the optical fiber punch through them; using a pulsed laser with specific
69


parameters. For instant, the pulse energy, the pulse duration or the pulse width, and the
Pulse Repetition Rate (PRR)- that match those conductivity or diffusivity constants under
study. Having done that, the heat accumulation and the consequent brain tissue damage
that is expected to happen via using Continuous Wave (CW) lasers of high-power will be
compensated for. If the threshold optical power intensity for a targeted area, the effective
attenuation coefficient due to scattering and absorption phenomena per unit length, and
the conductivity or diffusivity constant (unit power per unit length per unit time; i.e.
(mW mm~1s~1) were known, and after a few calculations, all it is needed to do is to
match the time required for that pulse to reach a certain depth with PRR for the laser. In
that case, the energy will be transferred to the targeted spot, and at the same time, get rid
of the excessive energy that will be building up if the laser source was functioning in a
CW mode; through the diffusing process of that energy during the off-mode between
pulses. In order to carry out this experiment, a sample from the area under investigation
will be labeled by two different types of fluorophores: Midori-Ishi Cyan (MiCy)- one of
the Cyan Fluorescent Proteins (CFP)s, and mRFPl- one of the Red Fluorescent Proteins
(RFP)s. Those two Fluorophores have the properties shown in table V. 1.
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Table V.l Midori-Ishi Cyan and mRFPl properties [21]
Fluorophore Type Excitation Maximum (nm) Emission Maximum (nm) Molar Extinction Coefficient Quantum Yield In vivo Structure Relative Brightness (% of EGFP)
Midori-Ishi Cyan (MiCy) 472 495 27,300 0.90 Dimer 73
mRFPl 584 607 50,000 0.25 Monomer 37
In addition to that, their excitation and emission spectra are illustrated in figure
V.3 and figure V.4.
MiCy and mKO Fluorescent Protein FRET Pair Spectral Profiles
350 400 450 500 550 600 650
Wavelength (Nanometers)
Figure V.3 MiCy excitation and emission spectra [22]
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Wavelength (nm)
Figure V.4 mRFPl absorption (solid line), excitation (dotted line), and emission
(dashed line) spectra [23]
Those probes are suitable for conducting this experiment for their excitation peaks
pretty close to the activation maxima for Channelrhodopsin-2 (ChR2) which is
approximately 470 nm and Halorhodopsin (NpHR) which is approximately 580 nm [9];
where ChR2 and NpHR are the fundamental constituents of any Optogenetics study.
Their activation spectra are depicted in figure V.5.
c
o
1.0-
0.8-

g 0.6-
§ -4-l
<
0.2-
0-
ChR2
I ----------
325 425 525 625 725
Wavelength (nm)
Figure V.5 ChR2 and NpHR activation spectra [4]
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From light sources perspectives, this experiment can be operated with one of the
EPL series of Picosecond (ps) Pulsed Diode Lasers; like the ones from Edinburgh
Instruments with a wavelength of 470 nm and featuring 10 set repetition frequencies from
20 kHz to 20 MHz and pulse widths down to ca. 70 ps [24], Whereas, the 580 nm
wavelength could be obtained from an Nd:YAG laser (1064 nm) after a frequency
doubling process followed by Q-switching operation to get the desired pulse shape [25],
These light sources will be attached and coupled to optical fibers, and some of their
specifications such as: energy, both duration or width, and PRR would be highly
preferred to be adjustable and tunable. Moreover, some wavelength selection filters could
be used, as well, to improve and optimize the system experimental set-up and
performance.
73


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12. Al-Juboori SI, Dondzillo A, Stubblefield EA, Felsen G, Lei TC, et al. (2013) Light
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15. Wilson RH, Mycek MA (2011) Models of light propagation in human tissue
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18. Sardar DK, Zapata BM, Howard CH (1993) Optical absorption of untreated
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Ehlers MD, Feng G (2007) In vivo light-induced activation of neural
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205-18.
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Full Text

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LIGHT SCATTERING PROPERTIES VARY ACROSS DIFFERENT REGIONS OF THE ADULT MOUSE BRAIN by SAIF I. AL JUBOORI B.S. Nahrain University 2008 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Master of Science Electrical Engineering 2013

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ii This thesis for the Master of Science degree by Saif I. Al Juboori has been approved for the Electrical Engineering Program by Tim Lei Chair Achim Klug Yiming Deng July 8, 2013

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iii Al Juboori, Saif, I. ( M.S. Electrical Engineering) Light Scattering Properties Vary a cross Different Regions o f the Adult Mouse Brain Thesis directed by Assistant Professor Tim Lei ABSTRACT Recently developed optogenetic tools provide powerful approaches to optically excite or inhibit neural activity. I n a typical in vivo experiment, light is delivered to deep nuclei via an implanted optical fiber. Light intensity attenuates with increasing distance from the fiber tip, determinin g the volume of tissue in which optogenetic proteins can successfully be act ivated. However, whether and how this volume of effective light intensity varies a s a function of brain region or wavelength has not been systematically studied. The goal of this study was to measure and compare how light scatters in different areas of the mouse brain. We delivered different wavelengths of light via optical fibers to acute slices of mouse brainstem, midbrain and forebrain tissue. We measured light intensity as a function of distance from the fiber tip, and used the data to model the spread of light in specific regions of the mouse brain. We found substantial differences in effective attenuation coefficients among different brain areas, which lead to substantial differences in light intensity demands for optogenetic experiments. The use of li ght of different wavelengths additionally changes how light illuminates a given brain area. We created a brain atlas of effective attenuation coefficients of the adult mouse brain, and integrated our data into an application that can be used to estimate li ght scattering as well as required light intensity for optogenetic manipulation within a given volume of tissue.

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iv The form and content of this abstract are approved. I recommend its publication. Approved: Dr. Tim Lei

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v DEDICATION I dedicate this work to those beloved ones whom I have lost and I still remember; to those who are suffering, not only every single day, but every single moment hoping that there will be a day in which researchers, like us, will come up with treatment for their illness es to mi tigat e their suffering and alleviate their pain ; to those whom I have promised that I am going to do my best in participating in whatever is going to be available for me to pave the way for breakthroughs that will lead to a better life with less pain and m ore pleasure for them and their dearest ones ; to those whom I gave my words to that I will never let them down; to people who m I am always looking forward to putting a smile on their faces

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vi ACKNOWLEDGMENTS I ack nowledge my fellowship from the Higher Committee for Education Development in Iraq (HCED). I would like to thank my consultant, advisor, and mentor, Dr. Tim Lei for all his encouragement, support, consultation, and advising that he has bestowed upon me thr oughout my graduate studies. Without his help, I would not have been able to spend my time, day by day, in a scientific and intellectual milieu which has been giving me the chance to learn from, study, meet, and colla borate with incredible researchers and students who have had a great influence on me. I am honored to w ork under his supervision. Here, I would also like to thank Dr. Achim Klug, Dr. Gidon Felsen, Dr. Anna Dondzillo, and Dr. Elizabeth Stubblefield for their collaboration in this work. I am indeed grateful for having this wonderful opportunity collaborating with all of them. It has been such an enriching experience being around people of knowledge like them.

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vii TABLE OF CONTENTS CHAPTER I. INTRODUCTION ................................ ................................ ................................ ....... 1 Optogenetics Era ................................ ................................ ................................ ..... 1 Neuroscience Optogenetics Experimental Insights ................................ ................ 3 Main Goals of This Study ................................ ................................ ....................... 4 Ethics Statement ................................ ................................ ................................ ...... 5 Animal Subjects ................................ ................................ ................................ ...... 5 Thesis Orientation ................................ ................................ ................................ ... 5 II. EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED BRAIN AREAS, EXPERIMENTAL PROCEDURE, AND LIGHT PROFILE AND TISSUE DAMAGE CONTROL EXPERIMENTS ................................ ................ 7 Experimental Setup ................................ ................................ ................................ 7 Optical Fiber Assembly ................................ ................................ .................... 8 Linearity Tests ................................ ................................ ................................ 11 The Importan ce of These Linearity Tests ................................ ................. 11 LEDs Power Intensity Linearity Tests ................................ ...................... 11 CCD Camera Linearity Tests ................................ ................................ .... 16 Sample Preparation ................................ ................................ ............................... 19 Targeted B rain Areas ................................ ................................ ............................ 20 Experimental Procedure ................................ ................................ ........................ 21 Manually Controlled Method ................................ ................................ ......... 21 Pico Motor Controlled Fiber Punch Through Method ................................ ... 23 Light Profile and Tissue Damage Control Experiments ................................ ....... 29

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viii III. DATA ANALYSES, THE MODIFIED BEER LAMBERT LAW, BRAIN AT LAS ESTABLISHMENT, AND RESULTS ................................ ................................ 32 Data Analyses ................................ ................................ ................................ ....... 32 The Modified Beer Lambert Law and the Effective Attenuation Coefficients for Highly Scattering Neural Targets ................................ ................................ ......... 38 The Brain Atlas, and a Technique of Mapping the Effective Attenuation Coefficients across the Entire Brain ................................ ................................ ..... 41 The Effective Excitation Distance for Optogenetic Proteins ................................ 42 Integr ation of All Relevant Data in a Computer Program ................................ .... 42 Results ................................ ................................ ................................ ................... 43 Light Intensity Decreases Exponentially in Brain Tissue ............................... 44 Light Scattering Properties Vary across Different Brain Regions .................. 45 Light Scattering Varies with Wavelength ................................ ....................... 49 Light Scattering Brain Atlas ................................ ................................ ........... 53 Applying the Data to Experimental Design ................................ .................... 56 IV. DISCUSSION AND MAIN FINDINGS ................................ ................................ ... 61 Discussion ................................ ................................ ................................ ............. 61 Main Findings ................................ ................................ ................................ ....... 62 V. IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES, AND FUTURE PLANS ................................ ................................ ................................ .................. 64 Improvements ................................ ................................ ................................ ....... 64 Comparison with Previous Studies ................................ ................................ ....... 65 Future Plans ................................ ................................ ................................ .......... 68 Application of the Findings to Future Experiments ................................ ........ 68 Research Proposal for Determining Diffusivity Constants for Individual Brain Areas ................................ ................................ ................................ ............... 69

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ix REFERENCES ................................ ................................ ................................ ................. 74

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x LIST OF TABLES Table III.1 Brain areas that were measured with three different wavelengths, and sample size (the unit of the effective attenuation coefficient is 1/mm) [12] ................................ ........ 47 V.1 Midori Ishi Cyan and mRFP1 properties [21] ................................ .......................... 71

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xi LIST OF FIGURES Figure ............................ 7 II.2 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile ................................ ................................ ...................... 9 II.3 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile after traversing a 100 sample thickness ................ 9 II.4 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile after t raversing a 200 sample thickness .............. 10 II.5 A 500 core, coupled to a 453 nm blue LED and driven by a 100 mA current source optical fiber output profile after traversing a 100 sample thickness at 10 ms exposure time ................................ ................................ ................................ .................... 10 II.6 A 500 core, coupled to a 453 nm blue LED and driven by a 100 mA current source, optical fiber output profile after traversing a 100 sample thickness at 20 ms exposure time ................................ ................................ ................................ .................... 11 II.7 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 518 nm green (LED), when the room light is turned off .............................. 12 II.8 The data fitting line for the output power density of the 100 m core optical fiber, ............................ 13 II.9 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 528 nm green (LED), when the room light is turned off .............................. 13 II.10 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 528 nm green ............................ 14 II.11 The data fitting line for the output power density of the 100 m core optical fi ber, coupled to a 453 nm blue (LED), when the room light is turned off ................................ 14 II.12 The data fitting line for the output power density of the 100 m core optical fiber, .............................. 15 II.13 The data fitting lin e for the output power density of the 500 m core optical fiber, coupled to a 453 nm blue (LED), when the room light is turned off ................................ 15 II.14 The data fitting line for the output power density of the 500 m core optical fiber, .............................. 16

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xii pixel image ................................ ................................ ................................ ........................ 17 pixel image ................................ ................................ ................................ ........................ 17 pixel image ................................ ................................ ................................ ........................ 18 II.18 Linearity pixel image ................................ ................................ ................................ ........................ 18 II.19 Linearity test for the CCD camera at pixel image ................................ ................................ ................................ ........................ 19 ickness for a PPT region. This is a one single set of measurements ................................ ................................ .......... 22 II.21 Basic experimental setup of the punch through method. On an inverted microscope, an optical fiber was placed on a section of brain tissue such that light from the fiber would pass through the tissue and subsequently be imaged by an objective attached to a CCD camera [12] ................................ ................................ ................................ .............. 24 II.22 A snap shot for the controlling program front panel expressing the adjustable significant parameters and other details ................................ ................................ ............ 26 II.23 An example of an original image captured by the CCD camera, showing light emitted from an optical fiber after it passed though a section of brain tissue [12] ........... 27 II.24 Optical transmittance as a function of tissue thickness. As the optical fiber was advanced through the section of brain tissue and repeated images such as the one in figure II.23 were taken, the decrease in optical transmittance as a function of tissue transmittance of blue light (453 nm) through a section of PPT at various thicknesses, while the solid line represents an exponential fit [12] ................................ ...................... 28 II.25 (Left) it is an overlapp ed picture of two images that are taken for a PPT region, in 300 m of thickness and 1300 m from the midline of depth slide. The background image (which is in black and white colors) shows the PPT area, while the blue one is, the output optical power inte nsity profile for the 100 m core optical fiber connected to a 453 nm blue LED, driven by a 28 mA current source. This picture is evidence that the blue LED light is not sufficient to cover the whole PPT region. These two images are taken on an integration time of 100 ms. (Right) it is an overlapped picture of two images that are taken for a PPT region, in 300 m of thickness and 1300 m from the midline of depth slide. The background image (which is in black and white colors) shows the PPT area, while the green one is, the output optical power intensity profile for the 100 m core optical fiber connected to a 518 nm green LED, driven by a 100 mA current source. This

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xiii picture is evidence that the green LED light is not sufficient to cover the whole PPT region These two images are taken on an integration time of 100 ms ............................. 29 II.26 (Top left) a 300 m of thickness and a 1500 image, showing the actual image that is taken from the CCD camera, of the CA3 Hippocampus region under white light illumination and before the laser damage. This image is taken on an integration time of 100 ms. (Top righ t) a 300 m of thickness and a 1500 Hippocampus region under white light illumination and before the laser damage. This image is taken on an integration time of 100 ms. (Bottom left) a 300 m of thickness and a 1500 taken from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5 mW laser source illumination, being applied for 3 minutes of time. The image shows a real tissue damage which is caused by the laser source under these circumstances. This image is taken on an integration time of 100 ms. (Bottom right) A 300 m of thickness and a 1500 ing the false color of the CA3 Hippocampus region under 405 nm and 3.5 mW laser source illumination, being applied for 3 minutes of time. The image shows a real tissue damage which is caused by the laser source under these circumstances. This image is take n on an integration time of 100 ms 30 III.1 A snap shot for the viewer program front panel screen that is used for retrieving the intensities from the images and plotting them as a function of tissue thickness according to the specific cursor location ................................ ................................ ........................... 33 III. 2 A cerebellum one raw data and fitting curve. Note the offset in the fit. This issue will be addressed below ................................ ................................ ................................ .... 35 III.3 A comparis on between PPT one and PPT two. Note the offset in the fit. This issue will be addressed below ................................ ................................ ................................ .... 36 III.4 A comparison between CA3 one and CA3 two. Note the offset in the fit. This issue will be addressed below ................................ ................................ ................................ .... 36 III.5 A comparison between PPT one and PPT two after taking the offset factor into account which demonstrates its significant impact on the reanalyzed and refitted the data ................................ ................................ ................................ ................................ ........... 37 III.6 A comparison between CA3 one and CA3 two after taking the offset factor into account which demonstrates its significant impact on the reanalyzed and refitted the data ................................ ................................ ................................ ................................ ........... 38 III.7 Optical transmittance through different types of brain tissue. Measurements using the fiber punch through technique were taken in eight different brain areas with blue (453 nm) light. In each case, optical transmittance decreased exponentially with tissue thickness; however, the exponential decreases observed varied greatly with the type of tissue. Single measurements are represented by the respective symbols while the solid lines represent exp onential fits of the data ................................ ................................ ........ 45

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xiv III.8 Effective attenuation coefficients with SEMs for the eight brain areas: VNTB 19.96 +/ 0.26 (1/mm); CA3 19.12 +/ 0.84 (1/mm); MNTB 18.16 +/ 0.69 (1/mm ); LSO 17.92 +/ 0.80 (1/mm); PPT 15.26 +/ 0.78 (1/mm); OB 14.88 +/ 0.74 (1/mm); SC 13.91 +/ 0.83 (1/mm); Cerebellum 9.76 +/ 0.78 (1/mm) ................................ ............................... 46 Channelrhodopsin activation ................................ ................................ ............................ 48 III.10 Same as figure III.11 except that in this example the illumination was calculated to hypothetically activate Channelrhodopsin over a distance of 60 49 III.11Effects of wavelength on optical transmittance. Optical transmittance in the MNTB as a function of tissue thickness and optical wavelengths. The three colorcoded data sets represent corresponding measurements with light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)). Longer wavelength light penetrates tissue deeper, resulting in a higher transmittance at any given tissue thickness [12] ....... 50 III.12 Optical transmittance in the VNTB as a function of tissue thickness and optical wavelengths. The three colorcoded data sets represent corresponding measurements with light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)). Longer wavelength light penetrate s tissue deeper, resulting in a higher transmittance at any given tissue thickness ................................ ................................ ...... 51 III.13 Effects of light wavelength on transm ittance in two brain areas (MNTB and VNTB). The effective attenuation coefficient decreases with wavelength for the three wavelengths tested. MNTB measurements are represented by round symbols while VNTB measurements are represented by square symbols. Meas urements in the three different colors are indicated by the color code of the symbols [12] ............................... 52 III.14 MNTB and VNTB proposed fittin g curves for the effective attenuation coefficients as a function of wavelengths ................................ ................................ ............................. 52 III.15 Relating fiber punch though measurement s to brain atlas measurements. An image microscopy system with monochromatic light. Areas with higher optical transmittance appear brighter on the image, while areas with lower transmittance appear darker. MNTB, VNTB, and LSO are outlined in red, orange, and yellow, respectively [12] ...... 54 III.16 Correlation in digital irradiance for brain areas tested with both the fiber punch through and the virtual microscopy method. Digital irradiance was measured in six brain areas (MNTB (red), VNTB (orange), LSO (yellow), PPT (green), SC (light blue), and cerebellum (da rk blue) with both the fiber punch through and the virtual microscopy technique. Results were normalized and plotted against each other. Each colored symbols represents the measurements from one brain area with two methods, the solid line indicates complet e overlap between the measurements. The bars attached to each data point represent the standard error [12] ................................ ................................ .............. 55

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xv III.19 The desired input parameters control panel ................................ ............................ 57 III.20 The attainable penetration depth as a function of optical power at the fiber tip for the desired entered input parameters ................................ ................................ ................. 58 III.21 A sample image from the brain atlas where the investigator can select the area of inter est precisely such that its optical properties are designated, and the corresponding penetration depth and optical power at the fiber tip are calculated, accordingly ............. 59 III.22 A screenshot for the user manual that is available in the computer program also, in which the user can be taken through details about how to use this application to its full extent ................................ ................................ ................................ ................................ 60 V.1 A comparison between our exponential fit and Kubelka Munk fit for a PPT raw data showing that it is best fitted with a single exponential curve ................................ ........... 66 V.2 A comparison between our exponential fit and Kubelka Munk fit for an MNTB total intensity measurements of the raw data ave that it is best fitted with a single exponential curve ................................ .......................... 67 V.3 MiCy excitation and em ission spectra [22] ................................ ................................ 71 V.4 mRFP1 absorption (solid line), excitation (dotted line), and emission (dashed line) spectra [23] ................................ ................................ ................................ ........................ 72 V.5 ChR2 and NpHR activation spectra [4] ................................ ................................ ..... 72

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1 CHAPTER I INTRODUCTION Optogenetics Era Deep brain stimulation (DBS) technology is one of the most effective technologies that have been used as a treatment and a cure for a wide spectrum of psychiatric disorders and diseases. The key function of this technology is making various functions by either activate or deactivate them to compensate for the malfunction that is happening i n them. The conventional approach to this technology is by doing the stimuli electrically by inserting metal electrodes in those areas and implementing that required current intensity to achieve the pre decided aim. However, as one can see, there are some downsides to this method though C predisposed by this invasive method [1] It might a lso have a severe effect on the surrounding and the intact cells. In addition, metal electrodes can not specifically target a cer tain cell type in the neural target, making the treatment much less specific and could lead to adverse treatment outcomes. Moreover, it is not possible to specifically control stimulation or suppression of the neural signals in the brain. Nonetheless, DBS using metal electrodes is the current state of the art method of deep brain stimulation After discovering some photosensitive materials especially photosensitive proteins that could stimuli, but this time optically, came out to the surface as a safer a nd noninvasive breakthrough to deal with these conditions and diseases [ 2 ] In this method, the light is

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2 shining specific areas which have already those photosensitive proteins, and some parts of the neural networks start to fire or suppress that firing an d control some brain functions to deliver the desired treatment. This is what i in brief! [ 2 ] And nowadays, it i s considered as one of the recent cutting edge technologies in this field And from this point forward, manipul ating neural function with light is becoming an increasingly important technique. This is particularly important for this recently emerging field of optogenetics, which provides powerful tools to either activate or suppress neural activity with light at a relatively fast time scale (sub milli second ) (e.g. [ 3 ] [ 5 ]). Controlling neuronal firing with light has opened up not only a number of exciting new avenues to study neural circuits, but also treatment options of a number of medical conditions such as Parki 6 ] [ 8 ]. As it has been known for the conventional approach that the amount of charge intensity will specify the demanded treatment as the brain areas have different electrical properties, the amount of light (o r the light intensity) required to serve the same purpose should be pre specified as well, as those brain areas may show different optical properties. Having said that, the first question that have been asked is; how much optical power intensity that i s re quired to deliver light to a specific neural target with a specific optical penetration depth to get the stimulation, activation or deactivation, and the neural responses desired will be. After determining this amount of the power intensity required to do the process, the second question is, what i s the initial optical power intensity that the physician should start with at the outer boundary of the neural target as it is not preferable to punch through it, yet instead, shining light directly on top of it

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3 The latter question requires the knowledge of the optical properties for those areas under study or investigation, because it i s related to the light transmission, absorption, and the scattering phenomena that are happening within the targeted area. There fore, the idea of having a three dimensional (3D) light scattering model has become a necessity in order to give a comprehensive expectation of how light behaves inside different brain areas. Yet, it has been required to collect the constructing optical pa rameters of this light scattering model. Thus, the scientific journey has started by conducting this study to achieve this goal by extracting the effective attenuation coefficient which is one of the main optical parameters that this model will be c omposed of. Neuroscience Optogenetics Experimental Insights For experiments using cell cultures or brain slices, the precise and reliable delivery of light to the neurons to be manipula ted is relatively simple and is typically achieved by attaching a suitable li ght source to a microscope, and subsequently delivering light stimuli with the desired parameters directly to the neural tissue. For in vivo experiments, howeve r, light delivery to deep brain areas is much more challenging. Typically, invest igat ors use stereotaxic methods to place an optical fiber just above the brain neural target to be illuminated, suc h that light emitting from the fiber effectively illuminates the tissue below the fiber tip [ 9 ]. Depending on the optical properties of the speci fic tissue, light emitted from the fiber tip propagates deeper or less deep throug h the tissue, with neurons more distant from the fiber tip receiving higher or low er light intensities. All light sensitive molecules (such as the various opsin s typically us ed in optogenetic experiments, but also caged compounds and fluore scent dyes) have a threshold of activation, (for the purpose of this

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4 publication de fined in practical terms as the minimum light intensity required to effectively tr igger or inhibit the desi red neural action potential ). Therefore, light sensitive molecules can only be activated at a certain maximum distance from the light source, and th is distance depends on both the optical properties of the tissue and the activation threshold of the molecul e used in the experiment. Most studies involving delive ry of light to deep brain areas assume, for simplicity, that all brain tissue scatt ers light in the same way, i.e. different brain areas behave similarly if not identica lly as far as light propagation in the tissue is concerned [ 1 ] [ 10] [ 1 1 ]. However, som e brain areas consist primarily of cell bodies while others consist primarily of neural fibers, and some brain areas with significant myelination appear darker while others appear lighter w hen observed under a microscope with transmitted light, suggesting difference s in optical properties between different brain areas. Main Goals of This Study The primary goal of this study was to test the hypothesis that different brain areas scatter and pr opagate light to different degrees. If correct, specific knowledge about the brain area to be manipulated would be required for the appropriate design of experimental manipulations. A sec ondary goal of the study was to create an easy to use computer progra m to estimate light scattering values f or different areas of the mouse brain that could be used as a reference in future experiments. Our experimental approach was to use sections of fresh brain tissue in combination with light emitting optical fibers that were advanced through the tissue to precisely measure light scattering propert ies. The results presented here are supplemented with a light scattering mouse brain atlas programmed as an iPhone application These

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5 tools are intended to aid an investigator in determining the required light intensity to be delivered for successful optogenetic manipulation. Ethics Statement All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Colorado Medical Campus (Permit number B 88412(05)1D. Furthermore, all applicabl e laws and regulations, as well the PHS Policy were strictly followed. Animal Subjects 34 male and female C57BL/6J mice were used in these experiments. All animal procedures were approved by the University of Colorado Institutio nal Animal Care and Use Committee, and were conduc ted in accordance with National Institutes of Health standards on humane treatment of laboratory animals. Thesis Orientation In the following chapters, the e xperimental setup, sample preparation, targeted brain areas, and experimental procedure needed to measure effective attenuation coefficients will be presented (Chapter II ). The results of these sets of experiments and the brain atlas establishment will be shown, as well, in both graphical and numerical presentations in Chapter III These results will also be discussed summarizing the main findings of this study in Chapter IV and some impairment will be illustrated in one of these sections. Finally, solut ions for those difficulties that have worked out so far, improvements that have been come up with, some other suggestions, comparison with previous studies and future plans (research proposal for gathering more parameters to

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6 perfect a three dimensional (3D) light scattering model of the mouse brain ) will also be available to the researcher in Chapter V

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7 CHAPTER II EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED BRAIN AREAS, EXPERIMENTAL PROCEDURE AND LIGHT PROFILE AND TISSUE DAMAGE CONTROL EXPERIMENTS Experimental Setup The experimental setup is mainly composed of the following devices: an inverted microscope (Nikon Diaphot 200, Nikon Corp., Japan) with a monochromatic 12bit Charged Coupled Device ( CCD ) camera (Mightex CCE B013 U) a ttached to it, a current derive source a Mightex LED power supply (SLB 1200 1) which derives the optical fibers, a computer, a CCD video camera and a monitor. The latter two components have been added afterward to adjust the fiber tip precisely on top of the sample before starting running the experiment. The investigational bench is pictured in figure I I.1 Figure I I 1

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8 Optical Fiber Assembly Three different optical fiber assemblies were used for the measurements. All three assemblies consis ted of 100 m core dia meter optical fibers (UM22 100, Thorlabs, Newton, NJ)) attached to 453 nm (bl ue), 528 nm (green), and 940 nm (near infra red) LEDs, respectively. All LEDs wer e purchased from Digikey (Thief River Falls, MN). The optical fiber was line d up wi th its respective LED using two precision manipulators. The alignment was c arefully done to obtain maximum optical throughput but avoiding crashing the fib er tip into the LED. UV optical epoxy was used to set the optical fiber in place and to secure the alignment between the LED and the optical fiber. In e ach case, the LED optical fiber assemblies were powered by the Mightex LED powe r supply allowing the optical power output to be adjusted by changing the electrical current running through the LEDs. Each and every experiment, the fiber optics should be examined not only to make sure that the output optical power intensity is steady but also the fiber tips are still intact and having a uniform light profile. Figure I I.2 shows the optical fiber output light profile, whereas figure I I.3 and figure I I.4 illustrate how this light profile would be after traveling through 100 m and 200 m tissue thickness for the same exposure time (2500 ms). Another example when the exposure time has changed for the same t issue thickness is presented in figure I I .5 and figure I I.6

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9 Figure I I 2 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile Figure I I 3 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile after traversing a 100 sample thickness

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10 Figure I I 4 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current source, optical fiber output profile after traversing a 200 sample thickness Figure I I 5 A 500 core, coupled to a 453 nm blue LED and driven by a 100 mA current source, opti cal fiber output profile after traversing a 100 sample thickness at 10 ms exposure time

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11 Figure I I 6 A 500 core, coupled to a 453 nm blue LED and driven by a 100 mA current source, optical fiber output profile after traversing a 100 sam ple thickness at 20 ms exposure time Linearity Tests The Importance of These Linearity Tests Now that these first sets of graphs had been collected and made as empirical references for the next following sets of experiments that have been launched after. And that has given the flexibility required to modify and adjust some experimental parameters without changing the setup or the procedure entirely. In addition to that, comparable ways of presenting the analyzed data and the results have been allowe d by the aid of those graphs. LEDs Power Intensity Linearity Tests Four different types of optical fibers coupled to four different LEDs having different wavelengths had been tested to incorporate within this experiment; those fibers

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12 are: green 518 (nm), 1 00 (m) core diameter, green 528 (nm), 100 (m) core diameter, blue 453 (nm), 100 (m) core diameter, blue 453 (nm), 500 (m) core diameter. The power intensity graph as a function of current intensity had been measured for those four optical fibers and dr awn as they can be seen in the following figures. The CCD camera sensitivity for LEDs power intensity linearity responses illumination versus when the room light is turned off had been tested taking into account the different LEDs wavel engths and different optical fibers core diameters. The results show very reliable linearity responses for the camera. Figure II 7 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 518 nm green (LED), wh en the room light is turned off

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13 Figure II 8 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 518 nm green (LED), u illumination Figure II 9 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 528 nm green (LED ), when the room light is turned off

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14 Figure II 10 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 528 nm green (LED), u nde illumination Figure II 11 The data fitting line for the output power density of the 100 m core optical fiber, coupled to a 453 nm blue (LED ), when the room light is turned off

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15 Figure II 12 The data fitting line for the output pow er density of the 100 m core optical fiber, coupled to a 453 nm blue (LED), under Figure II 13 The data fitting line for the output power density of the 500 m core optical fiber, coupled to a 453 nm blue (LED ), when the room light is turned off

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16 Figure II 14 The data fitting line for the output power density of the 500 m core optical fiber, coupled to a 453 nm blue (LED), u CCD Camera Linearity Test s The CCD camera linearly tests had also been experimented as a function of various exposure times and these graphs can be shown in the following figures. Five different pixel locations had been taken into consideration which are (100, 100), (100, 1292), (520, 696), (940, 100), and (940, 1292) of (1040 x 1392) pixels image to show the consistency and robustness of the linearity responses across the entire detection area.

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17 Figure II 15 location of (1040 x 1392) pixel i mage Figure II 16 on of (1040 x 1392) pixel image

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18 Figure II 17 on of (1040 x 1392) pixel image Figure II 18 Linearity test for on of (1040 x 1392) pixel image

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19 Figure II 19 on of (1040 x 1392) pixel image Sample Preparation Another significant and vital part before initiating these experiments is the case study sample preparation. This operation has had a lot of impacts on the results, on the whole, and during the course of action through conducting these experiments. This process is started by getting the animal dow n, decapitated after being briefly anesthetized via isoflurane inhalation (IsoFlo, Abbott Laboratories, USA) All animals that are allocated for those sets of experiments were six to eight weeks old mice from which c oronal and sagittal brain slices were p repared Then the brain is being taken out of th e skull through a neat procedure and w as dissected out under ice cold dissection Ringer containing either (in mM): Ringer 1: 125 NaCl, 2.5 KCl, 1 MgCl 2 0.1 CaCl 2 25 glucose, 1.25 NaH 2 PO 4 25 NaHCO 3 0.4 asc orbic acid, 3 myo inositol, and 2 pyruvic acid; or Ringer 2 : 200 sucrose, 1.25 NaH 2 PO 4 26 NaHCO 3 10 glucose, 3.5 KCl, 7 MgCl, 1.5 as corbic acid (all chemicals from Sigma)

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20 slicing machine to different slices thicknesses (mainly 600 m) Those slices were cut wit h a vibratome (VT1000S, Leica), transferred to an incubation chamber containi ng extracellular solution (ECS) [ECS; containing (in mM) 125 NaCl, 2.5 KCl, 1 MgCl 2 2 CaCl 2 25 glucose, 1.25 NaH 2 PO 4 25 Na HCO 3 0.4 ascorbic acid, 3 myo in ositol, and 2 pyruvic acid, all chemicals from Sigma] and bubbled with 5% CO 2 95% O 2 Slices were incubated in ECS for 15 30 minutes at 37C and then c ooled down to room temperature. All measurements were obtained within 2 3 h of slicing. Targeted Brain Areas The brain areas that have been dealt with throughout this study are: Medial Nucleus of the Trapezoid Body (MNTB), Ventral Nucleus of the Trapezoid Body (VNTB), Lateral Superior Olive (LSO) Pedunculopontine Tegmental nucleus (PPT), Superior Colliculus (SC), Cornu Ammonis 3 of hippocampus ( CA3), the cerebellar cortex molecular layer Olfactory Bulb (OB) The brain regions were chosen because previous knowledge suggested that they would represent a wide range of scatter ing coefficients, but also to perform control experiments for future optogenetics manipulations. And since in these experiments, the thicknesses of the samples play a significant role in determining how the results would look like, this issue has been always borne in mind and taken into account by having those brain areas completely confined within the sample thickness by making its surface as a flat as it could be, and by immersing it i n the ECS while doing the slicing process and when the measurements are being taken. Moreover, sometimes it's also being bubbled throughout the experiment to keep it oxygenated. The truth of the matter behind these strict sample preparations is the

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21 tendenc y to mimic almost the same "in vivo" environment and maintain the metabolism of the sample as long as possible. This study has shown how this aspect has an absolute relevance with how those biological tissues respond optically (more details will be present ed in the discussion section). Experimental Procedure Manually Cont r olled Method After the sample is prepar ed with a certain thickness, it i s tran sferred to a small chamber that i s transparent from the bottom to make it more convenient for using with the inverted microscope. That chamber will have been already cleaned using special lens papers. The sample will be floating in side the preserving fluid (that i s bubbled sometimes to keep i t oxygenated and healthy, as it i s mentioned b efore). And for that reaso n, it i s required to add a piece of metal with strings as a mass to keep it from that random movement. However, the latter has undesirable effects on the sample as well; these effects will be elucidated in the discussion section. T he earlier stages of thes e sets of experiments had been done manually without having a pico motor and the CCD video camera and the monitor, by trying to land the fiber tip on the top of the sample and get it to be centered on the targeted area without forgetting having the sample being in focus by moving the stage up and down, and take an image that represents arbitrary digital intensities for the original optical power intensities after passing through that specific thickness. Then, that sample will be replaced by another one with another thickness and the same procedure is being repeat ed. The current intensity that is corresponding to the aimed optical power intensity is set up based on the optical power intensities curves fo r

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22 each individual optical fiber. R urned off to avoid any other illumination sources. The main goal for those types of experiments was to construct a curve for the arbitrary digital intensities or the optical power intensities as a function of sample thickness. E ach point accounts for the m aximum intensity accompanied with the fact that this fiber optic output profile is Gaussian (Some results belongs to this approach can be seen in figure II.20 ). Figure II 20 PPT region This is a one single set of measurements As it stated earlier, the first sets of experiments had been performed without having the pico motor which is implemented later in order to make punching through the curacy (see next section) Before that, all the punching trials had been done manually w hich had been considered to be a vague process since there are no enough clues to determine how far the fiber tip inside the sample goes.

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23 Pico Motor Controlled Fiber Pu nch Through Method The other approach that has been launched after that pico motor and the CCD punch es with different thicknesses in order to construct that formerly mentioned graph, there will be only one sample with the thickness that contained the whole area under investigation from the top to the bottom, and now the fiber tip can punch through driven by that pico motor through precisely determined step sizes to trace the total moving distance after making sure that the fiber tip is properly landed on the top of the sample surface. After the incubation period, a slice was placed into a measurement cham ber and continuously superfused with bubbled extracellul ar solution for the duration of the experiment. The measurement chamber was then positioned on the inverted microscope in which the standard transmitted light source was replaced by an asse mbly consisting of a three axis manual micromanipulator (Narishige model M M 3), a calibrated piezo driven one axis micromanipulator (Model 8302 Picom otor Actuator, Newport, Irvine, CA), and a custom made optical fiber holder to hold one of the three fiber/ LED assemblies in place. The output end of the optical fiber was placed directly onto the surface of the brain slice under the guidance of the CCD video camera using macro optics, such that the emitted light was f acing the brain section and the s objective (EF 10x, N.A. 0.25, Leitz Wetzlar, Germany). The light was then captured by the monochromatic 12bit camera attach ed to the microscope via the camera port (see figure II.21 for a sketch of the setup).

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24 Figure II 21 Basic experimental setup of t he punch through method. On an inverted microscope, an optical fiber was placed on a section of brain tissue such that light from the fiber would pass through the tissue and subsequently be imaged by an obj ective attached to a CCD camera [12] Exposure time and the irradiance of the optical fiber ( I o ) were adjusted to optimally utilize the Mightex camera dynamic r ange throughout the entire data set. Subsequently, the fiber was lowered into the slice in 5 precision piezo micromanipulato r, starting from the surface of the s ection and ending at a depth of 500 At every step, the camera will be taking a number of images and get them to be averaged by a number which can be manipulated from the controlling program front panel. Instantaneo usly, a graph will be drawn for arbitrary digital intensities as a function of sample thickness after allocating the cursor in the right position. Consequently, the images taken will be stored in a chosen folder to pave the way for more data analysis to be acco mplished upon them succeedingly

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25 Computer software, Lab VIEW 2009 Service Pack 1 (National Instruments, Austin, TX) has been installed on the computer, and a computer program was written in this software to control the pico motor and get it to move up and down in very precise step sizes and to control the Mightex camera Other very important parameters can be changed or adjusted through the program panel; for example, the CCD camera exposure time, total moving distance, the number of pictures that are going to be taken and averaged for each individual step size measurement. It i s also allowed to change the cu rsor position to another pixel location rather than the central one to read the digital intensities from those pixels locations (a snap shot for the controlling program front panel screen can be seen in figure II.22 )

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26 Figure II 22 A snap shot for the controlling program front panel expres sing the adjustable significant parameters and other details Images taken at different steps were stored for further data analysis. An example of such an image is shown in figure II.23

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27 Figure II 23 An example of an original image captured by the CC D camera, showing light emitted from an optical fiber after it pas sed t hough a section of brain tissue [12] The data was extracted from images by locating the pixel representing the fiber center, a nd collecting that pixel 12 bit gray scale value for the digitized optical irradia nce This process was repeated for each image. was normalized to to o btain the optical transmittance which was then fitted by a single exponential function ( Figure II.24 ) according to the modified Beer lambert law (see Chapter III ) to ex tract the effective at tenuation coefficient eff of the measured neural target.

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28 Figure II 24 Optical transmittance as a function of tissue thickness. As the optical fiber was advanced through the secti on of brain tissue and repeated images such as the one in figure II.23 were taken, the decre ase in optical transmittance as a function of tissue thickness could be evaluate symbols) represent transmittance of blue light (4 53 nm) through a section of PPT at various thicknesses, while the solid lin e r epresents an exponential fit [12] Eventually, the output optical power intensity and the light profile will be tested again to be certain that the fiber tip has not been defected and the light profile is not distorted throughout the experiment. Control experiments determined that the forces applied on the tissue by the advancing glass fiber are comparable to thos e created by an advancing sharp hus concluded that lowering the fiber into the tissue caused the fiber tip to slice through, rather than squish the tissue together, such that measurements at ma ny different tissue thicknesses could be taken reliably from the same tissue section at precisely controlled depths through ).

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29 Light Profile and Tissue Damage Control Experiments Incidentally, and as it is referred to the idea of whether the light profile is enough to cover the targeted areas or not, it is convenient to show the results regarding this part of the study as shown in figure II.25. Figure II 25 (Left) it is an overlapped picture of two images that are taken for a PP T region, in 300 m of thickness and 1300 m from the midline of depth slide. The background image (which is in black and white colors) shows the PP T area, while the blue one is, the output optical power intensity profile for the 100 m core optical fiber connected to a 453 nm blue LED, driven by a 28 mA current source. This picture is evidence that the blue LED light is not sufficient to cover the who le PP T region. These two images are taken on an integration time of 100 ms. (Right) it is an overlapped picture of two images that are taken for a PP T region, in 300 m of thickness and 1300 m from the midline of depth slide. The background image (which i s in black and white colors) shows the PP T area, while the green one is, the output optical power intensity profile for the 100 m core optical fiber connected to a 518 nm green LED, driven by a 100 mA current source. This picture is evidence that the gree n LED light is not sufficient to cover the whole PP T region. These two images are taken on an integration time of 100 ms Another potential trial which has emerged from the eagerness of showing how the laser light intensity could expose a therm al damage in the targeted area had been performed and its results are nicely presented in figure II.2 6

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30 Figure II 2 6 (Top left) a 300 m of thickness and a 1500 m from the midline of e CCD camera, of the CA3 Hippocampus region under white light illumination and before the laser damage. This image is taken on an integration time of 100 ms. (Top right) a 300 m of thickness and a 1500 m from the midline of depth he false color of the CA3 Hippocampus region under white light illumination and before the laser damage. This image is taken on an integration time of 100 ms. (Bottom left) a 300 m of thickness and a 1500 m showing the actual image, that is taken from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5 mW laser source illumination, being applied for 3 minutes of time. The image shows a real tissue damage which is caused by the laser source unde r these circumstances. This image is taken on an integration time of 100 ms. (Bottom right) A 300 m of thickness and a 1500 image, showing the false color of the CA3 Hippocampus region under 405 nm and 3.5 mW laser sou rce illumination, being applied for 3 minutes of time. The image shows a real tissue damage which is caused by the laser source under these circumstances. This image is taken on an integration time of 100 ms

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31 Now that tissue damage was checked Therefore, it was concluded that it needs to illuminate the section with much higher light intensities and exposure times to cause damage than what has been used during this study measurements.

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32 CHAPTER II I DATA ANALYSES, THE MODIFIED BEER LAMBERT LAW, BRAIN ATLAS ESTABLISHMENT, AND RESULTS Data Analyses The results associated with this study are strictly taken from the following brain areas: MNTB, VNTB, LSO, PPT, SC, CA3, and Cerebellum Although the images have been stored, yet they are still considered to be raw data and it is required to make it through a series of data analysis steps before they can be scientifically illustrated corresponding to multi data presentations that serve to answer the fundamental questions and aims of thi s study. The results could be introduced by following these steps: the pre stored images in a specific folder are reloaded to another viewer program that is programmed in LabVIEW software as well that allows retrieving the intensities from those images a ccording to a cursor locatio n that is also adjustable by the analyzer. Then, these intensities that are corresponding to each tissue thickness will be saved in an appropriate format. This process still be pursued by a sorting one and thereby, they are read y to be depicted now A snap shot for the viewer prog ram is illustrated in figure III. 1

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33 Figure III 1 A snap shot for the viewer program front panel screen that is used for retrieving the intensities from the images and plotting them as a function of tissue thickness according to the specific cursor location Two programs that have been used in order to graph the resultant data are: MATLAB R2010a and Igor 6. That resulted curves are normalized so that they are in a comparable forms. It is of fundamental importance that these data are being fitted with the most suitable equation form to make it possible t o extract some valuable parameters like the one mentioned sooner the effective attenuation coefficient that belongs to each region under investigation. The first equation that had been used to fit the data was

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34 the modified Beer Lambert law for ligh t scattering and absorption in biological tissues, which has the form of: In which: : is the optical power intensity as a function of tissue thickness (mW/mm 2 ) : is the initial optical powe r intensity (mW/mm 2 ) ( when x=0 mm) : is the effective attenuation coefficient (1/mm) : is the tissue thickness (mm) More elaborate theoretical background pertaining to the modified Beer Lambert law is prese nted in the following section Some of the results that had adopted this approach are shown in the figures III.4 6 using MATLAB. In these figures, t refer to the first and second measurements on the first and second slices used i n that experiment, respectively A full comprehensive description for the experiment that the following figures have been based on is elucidated as follows: In this experiment, a 600 m thick slice is used and punched through different depth following the multiple differe nt step sizes of t he motor (5 m step size are used). The total moving distance was 500 m in depth making the smallest thickness taking into our considerati on to be 100 m The optical source used in this exper iment is a blue LED light (453 nm) coupled to a 100 m core dia meter optical fibe r with an output power of 4.33 mW/mm 2 from this fiber. Th e LED source is driven by a 28 mA current to get this power The CCD camera was set on 50 ms exposure time throughout the experiment

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35 The aims of these data analyses are to extract the images taken. Then, get rid of the saturation values. After that, the raw data are drawn and their exponential curves are obtained. These raw data and fitting curves are normalized, as well, in order to make the re sults comparable to each other properly. Figure III. 2 A cerebellum one raw data and fitting curve N ote the offset in t h e fit. T his issue will be addressed below

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36 Figure III 3 A compari son between PPT one and PPT two N ote the offset in t h e fit. T his is sue will be addressed below Figure III 4 A compari son between CA3 one and CA3 two N ote the offset in t h e fit. T his issue will be addressed below

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37 The obtained data follows an exponentially decaying curve as predicted by the modified Beer L ambert law. However, due to the electronic offset and other optical background, there is an artificial offset needed to be accounted in the data. Having taken that into account, the new fitting equation, for now, looks like the following: One can simply see that this equation is of the same format as the old one with only one term added to it which is which refers to that initial intensity. Thus, the same data reanalyzed applying the latter approach and this time using Igor prog ramming, and the results are demonstrated in the following figures ( Figure III. 5 and Figure III. 6 ). It is also important to indicate that "Tau" in th e se figures accounts for the effective attenuation coefficients Figure III. 5 A comparison between PPT on e and PPT two after taking the offset factor into account which demonstrates its significant impact on the reanalyzed and refitted the data

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38 Figure III. 6 A compari son between CA3 one and CA3 two after taking the offset factor into account which demonstrates its significant impact on the reanalyzed and refitted the data The Modified Beer L ambert Law and the Effective Attenuation Coefficients for Highly Scattering Neural Targets The full mathematical treatment of light trave lling in biological tissue that absorbs and scatters light waves (or optical photons) is described by the Radiative Transport Equation (RTE) [ 13 ], [ 14 ]. Where is the radiance of the propagating light wave; and are the absorption, scattering coefficients of the biological tissue;

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39 is the phase function describing the proba bility of a photon scattered to the radiation direction from its original radiation direction ; is the optical energy density generated in the biological tissue; is the speed of light in vacuum and is the solid angle. The RTE is a complex equation which has no analytical solution, since depends on both the spatial coordinate ( ) and the radiation direction ( ) and time (t) resulting in a function with seven independent variables. can be evaluated computationally with the RTE but requires an i nvolved computational algorithm such as a Monte Carlo stochastic simulation [ 1 5 ], [ 1 6 ]. Therefore, to extract quantitative parameters from our empirical me asurements, a simplification of the RTE is needed. For most biological sa mples, including the brain, the scattering coefficient at the wavelengths tested here is typically one to two orders of magnitude higher than the absorption coef ficient In addition, the phase function can be approximated by the Hey ney Greenstein function [1 7 ]: Where is the anisotropy factor and is generally assumed to be larger than in most biological tissues, indicating that the scattering light is predominantly forward scattered. Under t hese conditions, the RTE can be approximated by the diffusion equation (the detai ls of the simplification can be found in [ 1 3 ]:

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40 Where is the irradiance or in the laboratory commonly (but erroneously) called intensity of the light wave, and To further simply the diffusion equat ion, we further assume that the optical propagation is in a steady state condition ( ) and there is no light being generated in the biological tissue Therefore, the 1D diffusion equation can simply be written as a 1D second order differential equation [ 1 4 ]: Where is the effective attenuation coefficient. Hence, the solution of the 1D diffusion equati on is the modified Beer Lambert Law [ 1 4 ]: With being the irradiance measured at the fiber output of the optical fiber, and being the longitudinal distance from the fiber output. The ratio of against is the optical transmittance which follows an exponential decay against the longi tudinal distance In this study, we attempt to estimate the optical penetration depth within a brain nucleus to determine optical fiber source excitation efficacy of the opsin expressed within this neural target. It is clear from the above equation that it is not necessary at the three wavelengths tested hereto individually measure and Rather, simply measuring the effective attenuation coefficient is sufficient for this estimation.

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41 The Brain Atlas, and a Technique of Mapping the Effective Attenuation Coefficients across the Entire Brain The technique of using an optical fiber to punch through a brain slice allows collecting data from well identified brain areas at v ery precise depths. However, it would be impractical to use this technique t o map the effective attenuation coefficients of many (i.e. hundreds) of brain areas, which would be required to obtain a quantitative picture ac ross the entire brain. However, imaging brain slices using bright field lig ht transmission microscopy with monochromatic light and combining these ima ges with the measured effective attenuation coefficients obtained from the punch thr ough method on selected neural targets allowed us to calculate and ma p out the effective attenuation coefficients across the entire brain. Whole brain slice imaging was performed on an Olympus VS 120 microscope, using transmitted light filtered via 546 /20 nm band pass filter and a 10x (N.A. 0.40) objective. To allow seamless, quantitatively correct tiling of multiple images of a single brain section, the manufacturer calibrated the microscope to normalize fo r uniform illumination and data acquisition across the entire imaging are a. With this normalization, the illumination irradiance can be assumed to be a constant across the whole brain slice scan. The illumination irradiance of the microscope is difficult to measure directly, instead brain slices containing the brain are as measured previously with the punch through method were used to quantify and normalize For a previously measured brain area, using the modified Bee r Lambert law, the illumination irradiance can be estimated by

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42 Effective attenua tion coefficients of other brain areas not measured with the punch through method can subsequently be calculated using The Effective Excitation Distance for Optogenetic Proteins In optogenetic experiments, it is important to estimate the minimum optical irradiance required to effectively excite the desire d neural area longitudinally to maximize excitation of the optogenetic proteins. Assuming the minimum excitation irradiance threshold for an o ptogenetic protein is and the irradiance at the fiber output is the effective excitation distance in the lon gitudinal direction of a neural target, whi ch has an effective attenuation coefficient of can be calculated by th e following equation Integration of All Relevant Data in a Computer Program From a practical point of view, an investigator wishing to perform optogenetic manipulations in vivo in the brain area of his /her choice ne eds to be able to estimate the required light intensity that needs to be fed into an optical fiber to obtain optimal illumination of the brain area to be manipulated. A situation where too much light energy is used may result in tissue damage and is theref ore undesirable. Furthermore, feeding to o much light e nergy into an optical fiber may result in unspecific activation of optogenetic

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43 prot eins outside the intended brain area, potentially compromising the experimental design. On the other hand, in a situation where not enough light energy is used, op togenetic proteins will fail to be activated. To aid with determining the corre ct amount of light energy for a given experimental situation, we prepared a br ain atlas that maps effective attenuation coeffi cients across the entire mouse brain. This atlas is integrated into a computer program that an investigator may use to estimate the required amount of light energy for an individual experimental si tuation based on brain area, desired penetration depth, and light frequency use d. For further information, see www.optogeneticsapp.com Results The main goal of this study was to test the hypothesis that different brain neural targets scatter light different ly and th at these differences are significantly large such that they need to be consid ered for successful optogenetic activation in deep brain nuclei. A secondary goal was to establish a database of light scattering values for different regions of the mouse brain t hat could be used as a reference in future experiments in which illumination of neural tissue is required. The most common approach to bring light into deep brain areas invivo is via optical fibers that are stereotactically placed above the brain area of i nterest. Our experimental approach of advancing a light emitting optical fiber through brain tissue modeled such a situation we ll, and enabled us to precisely determine light intensity at any depth along the longitu dinal axis with respect to the fiber tip.

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44 Light Intensity Decreases Exponentially in Brain Tissue An acute brain slice was placed into a perfusion chamber under an inverted microscope, and an optical fiber attached to a LED was placed directly on the tissue surface. Light emitted from this fiber propa gated through the slice and was then collected by the objective and the chi p of the attached monochromatic camera. A sketch of this configuration is shown in figure II.21 and an example of an original image acquired with this setup is shown in figure II.23 This configuration of imaging the light emitted from an optical fiber tip after it passed through a piece of brain tissue of known origin and of a known thickness allowed effective measurement of the remaining light intensity at tissue depth From this value we could then calculate the ratio of the intensity of remaining light at depth over the original light intensity at the optical fiber tip. similar images we re acquired with each step. Co ntrol experiments verified that advancing the fiber into the tissue caused it to rel iably slice through the section rather than compress the section (data not shown ). Advancing the fiber into the ber punch throug images at various depths effectively creat ed a dataset of light intensity measurements in brain tissue at points progressively closer to the fiber tip. An alternative approach would have been to cut brain sli ces of different thicknesses and measuring light transmitted through each on e of these slices. However, the fiber punch through method allowed us to contr ol for tissue depth (thickness) much more precisely than cutting sections of variou s thicknesses would have allowed us to do, and furthermore allowed us to measure the exact same piece of tissue at different depths.

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45 From the measurements obtained at various tissue depths, light intensity ratios were calculated and plotted. Curve fitting indicated that the data points were best described by a single exponential function. An ex ample of such a fit is shown in figure II.24 representing a set of measurements wi th blue light (453 nm) recorded from a re d luminance at each tissue thickness, and the superimposed line represents the exponential fit. Light Scattering Properties Vary a cross Different Brain Regions Eight different brain regions were measured with 453 nm light in the same way as the PPT shown b efore ( Figure III. 7 ). The dat a points (colored symbols) were plotted against the distance from the fiber tip, a nd the set of measurements from each brain area were fitted with a single exponential function (colored lines). Figure III 7 Optical transmittance through different types of brain tissue. Measurements using the fiber punch through technique were taken in eight different brain areas with blue (453 nm) light. In each case, optical transmittance decreased exponentially with tissue thicknes s; however, the exponential decreases observed varied greatly with the type of tissue. Single measurements are represented by the respective symbols while the solid lines represent exponential fits of the data

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46 The results indicate that light intensity d ropped at least 10 distance from the tip of the optical fiber in each brain region tested. Importantly, the data suggest that this drop differs substantially among the brain regions tested. To systematically examine these differences, we calculated scattering coefficients from the data ( Figure III. 8 ). Average coefficients ranged from 19.96 +/ 0.26 for VNTB tissue, representing the lowest light transmittance of any region tested, to 9.76 +/ 0.78 for cerebellum, representing the highest transparency of all brain regions tested. F or all values and SEMs, see figure III. 8 and corresponding figure caption Figure III 8 Effective attenuation coefficients with SEMs for the eight brain areas: VNTB 19.96 +/ 0.26 (1/mm); CA3 19.12 +/ 0.84 (1/ mm); MNTB 18.16 +/ 0.69 (1/mm); LSO 17.92 +/ 0.80 (1/mm); PPT 15.26 +/ 0.78 (1/mm); OB 14.88 +/ 0.74 (1/mm); SC 13.91 +/ 0.83 (1/mm); Cerebellum 9.76 +/ 0.78 (1/mm) The MNTB, VNTB and LSO were measured with three wavelengths of light, while all oth er nuclei were measured with one wavelength, (see table I I I.1 for summary). One set of measurements was performed per brain nucleus per hemisphere.

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47 Table I I I. 1 Brain areas that were measured with three different wavelengths and sample size (the unit of the effective attenuation coefficient is 1/mm) [12] Brain Area Effective Attenuation Coefficient eff (1/mm) MNTB 18.16 (n=11) 15.86 (n=9) 13.86 (n=8) VNTB 19.96 (n=6) 17.69 (n=7) 14.39 (n=7) LSO 17.92 (n=4) 15.91 (n=7) 14.01 (n=6) PPT 15.26 (n=10) SC 13.91 (n=10) CA3 19.12 (n=8) Cerebellum 9.76 (n=8) Olfactory 14.88 (n=5) Figures III. 9 and figure III. 10 show the practical consequences of these differential coefficients on light penetration through the different types of tissue. Figure III. 9 plots the optical power required to illuminate neurons up to a below the optical fiber tip with a light intensity of at least 10 mW/mm 2 (the light power required for ChR 2 activation 8 12mW/mm 2 [ 3 ]). To achieve this goal in cerebellar cortex, about 1.5 mW need to be emitted from the tip of the optical fiber, while in the case of VNTB, about 20 times as much optical power is required to achieve the same goal.

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48 Figure III 9 used for Channelrhodopsin activation Due to the nonlinear nature of light distribution in tissue, these differences become more dramatic for deeper penetration. For example, doubling the illumi nation n the case of cerebellar cortex tissue (28 m W). By contr ast, illuminating 60 same degree would require 1 2 W of light intensity, or 400 times the intensity required to ( Figure III. 1 0 )

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49 Figure III 1 0 Same as figure III.11 except that in this example the illumination was calculated to hypothetically activate Channelrhodopsin over a distance of 600 These calculations suggest substantial differences in light scattering among different brain areas, and make the point that certain manipulations are possi ble in some brain areas but not others. Light Scattering Varies with Wavelength A traveling wave interferes with objects that are larger than its wavelength, but tends to bend ar ound objects smaller than its wa velength. Thus, long wavelength light penetrates tissue deeper than short wavelength light. Since different lightsensitive molecules are optimally excited at a va riety of wavelengths, we tested the influence of light wavelen gth on the penetration depth of light in brain tissue. Figure III. 1 1 represents experiments in w hich MNTB was tested with three wavelengths: 453 nm, 528 nm, and 940 nm. As e xpected, the longest wavelength (940 nm) showed the most effective penetration, i.e. the smallest attenuation of light intensity with increasing distance from

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50 the fiber tip (red line), while the blue light (453 nm) attenuated within the shortest di stance from the fiber tip (blue line). Figure III 1 1 Effects of wavelength on optical t ransmittance. Optical transmittance in the MNTB as a function of tissue thickness and optical wavelengths. The three colorcoded data sets represent corresponding measurements with light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)). Longer wavelength light penetrates tissue deeper, resulting in a higher transmittance at any given tissue thickness [12] Similar observations were made for a second brain area (VNTB) that was tested in the same way ( Figure III. 1 2 ).

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51 Figure III 1 2 Optical transmittance in the VNTB as a function of tissue thickness and optical wavelengths. The three colorcoded data sets represent corresponding measurements with light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)). Longer wavelength light penetrates tissue deeper, resulting in a higher transmittance at any given tissue thickness Note that optical absorption cannot be neglected at all light frequencies (an assumption made for the three single lig ht frequencies tested in this study), and thus there is no simple l inear extrapolation between the points shown in figure III. 1 3 [ 1 8 ].

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52 Figure III 1 3 Effects of light wavelength on transmittance in two brain areas (MNTB and VNTB). The effective attenuat ion coefficient decreases with wavelength for the three wavelengths tested. MNTB measurements are represented by round symbols while VNTB measurements are represented by square symbols. Measurements in the three different colors are indicated by the color code of the symbols [12] W hile the datapoints can be fit ted with a single exponential (Figure III.14), the relationship may be more complex [18]. Figure III 1 4 MNTB and VNTB proposed fitting curves for the effective attenuation coefficients as a function of wavelengths

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53 Light Scattering Brain Atlas While the fiber punch through method allowed for measurements of light scattering properties in anatomically defined brain areas, it is a relatively slow method. Measuring many different brain areas with this technique would not be feasible. However, to extend usage of our data to other areas of the brain without the need for additional punch through measurements, we prepared a brain atlas containing light scattering values from the entire mouse brain. Fo r this atlas, sections of 300 thickness were prepared from mouse brains, and imaged with an Olympus virtual microscopy system (Olympus VS 120) using monochromatic transmitted light (546 nm band pass filtered with a 20 nm band pass width). The resultin g images consist of relative differences in tissue translucency in grey scale between different brain areas in the section. Figure III. 1 5 shows an example of such an image, with several nuclei marked with colored lines on the section.

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54 Figure III 1 5 Relating fiber punch though measurements to brain atlas measurements. on a calibrated virtual microscopy system with monochromatic light. Areas with higher optical transmittance appear bright er on the image, while areas with lower transmittance appear darker. MNTB, VNTB, and LSO are outlined in red, orange, and yellow, respectively [12] For brain areas that were also measured with the punch t hough method, the relative grey values of the image s correlated very well with the effective attenuation coefficients measured with the punch through me thod ( Figure III. 1 6 ), suggesting that the grey values of the images can be used as a b asis to calculate the effective attenuation coefficients for brain ar eas that have not be en tested with the punchthrough method.

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55 Figure III 1 6 Correlation in digital irradiance for brain areas tested with both the fiber punch through and the virtual microscopy method. Digital irradiance was measured in six brain areas (MNTB (red), VNTB (orange), LSO (yellow), PPT (green), SC (light blue), and cerebellum (dark blue) with both the fiber punch through and the virtual microscopy technique. Results were normalized and plotted against each other. Each colored symbols represen ts the measurements from one brain area with two methods, the solid line indicates complete overlap between the measurements. The bars attached to each data point represent the standard error [12]

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56 Importantly, the grey value images in combination with th e effective attenuation coefficients measure d with the punch through method allowed us to establish an atlas of brain translucency that can be used to calcul ate the light scattering properties of any brain area in the adult mouse brain. Applying the D ata to E xperimental D esign An investigator planning an experiment involving light activation of a given protein in vivo is typically interested in the amount of lig ht required to activate the protein at a distance from the fiber tip. In o rder to correc tly determine the required amount of light, the following parame ters must be considered: 1) The wavelength of the light, 2) the largest distance from the fiber tip at which proteins are to be activated, 3) the specific light scatteri ng properties of the br ain area involved, and 4) the diameter of the fiber tip. We produced a computer program that calculates the required amount of light for a given experiment based on user input of these parameters. Screenshots from this computer program can be seen in the following figures. The program al so incorporates the brain atlas described abov e. For further information, see www.optogeneticsapp.com

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57 Figure III 19 The desired input parameters control panel

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58 Figure III 20 The attainable penetration depth as a function of optical power at the fiber tip for the desired entered input parameters

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59 Figure III 21 A sample image from the brain atlas where the investigator can select the area of interest precisely such that its optical properties are designated, and the corresponding penetration depth and optical power at the fiber tip are calculated, accordingly

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60 Figure III 22 A screenshot for the user manual that is available in the computer program also, in which the user can be taken through details about how to use this application to its full extent

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61 CHAPTER I V DISCUSSION AND MAIN FINDINGS Discussion This study has been dealing with a lot of cardinal questions about the best approach that these measurements must be conducted in order to make its main tasks achievable. It has also been tackling many technical and practical issues; however, these problem s have eventually been overcome by modifications for the system setup. So far this study has shown that it could be a necessity to choose different illumination profiles and sources to activate some brain areas maybe through various light profiles or side under study can be arranged from the densest to the least optically dense as VNTB, CA3, MNTB, LSO, PPT, OB, SC,and Cerebellum, respectively, as illustrated in figure III. 8 Another crucia l aspect that this study has explored is the optical properties age dependence for those brain tissues within the same species. Moreover, it has also shown how important the tissue health is and how it affects the measurements all in all, and how the time degradation rate for those brain tissues play a major role in their optical characteristics. Most importantly, it shed light on the situation when there is a photosensitive florescent materi al within the same region that i s highly likely to emit light back after being shining with a certain wavelength which gives awkwardly incorrect results. And definitely this phenomenon should be avoided or resolved somehow. On the flip side, there are still few "on stage" complexities that should be mitigated. One of whi ch is the camera saturation when it comes to very thin sample

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62 thickness and that decreases the number of p oints that are taken for curves construction and narrow the total moving distance, and eventually, it becomes obscure for the fitting program to estab lish the best fitting approach. Another problem that has happened sometimes is what so called, humorously, "the pillow effect". Simply, it's the same response that a pillow might respond when it i s pushed from the middle and that will be lifting its sides up higher. Applying this on a sample with one of the threads or strings in the middle will lead to the same results and might alter the readings severely, sometimes. Yet, altogether, this study is still promising, especially, for the methodology of doing i t this way that has not been done widely. Main F indings There are four main findings of this study: 1) Light emitted into brain tissue from a point source such as an optical fiber declines exponentially in intensity with increasing distance from the fiber tip 2) There are substantial dif ferences in light scattering properties among different brain neural areas, r esulting in a need for specific knowledge about any given brain area to be illu minated 3) The light wavelength used in a particular experiment addi tionally influences the scattering prop erties, with longer wavelength light penetrating deeper into the tissue 4) The results obtained in this study could be integrated into a bra in atlas of light scattering in the mouse brain, as well as a computer progra m that allows a user to easily determine the light requirements for any given experimental situation. The most important finding is the observation that there are substantial differences in the optical properties across differe nt brain areas. For simplicit y, previous studies have assumed that light prop agation through brain tissue is similar throughout the

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63 brain, and have calcul ated the light requirements for optogenetic experiments with a single effective attenuation co efficient [ 1], [10], [1 1 ]. Our result s show that a differential approach is needed, beca use the observed differences in effective attenuation coefficients can have substantial conse quences on experimental design. Figure III. 9 and figure III. 1 0 illustrates this point and suggest that certain m anipulations are possible in some brain areas but not others. In some experiments, one might want to restrict the volume of illumination, e.g. if an opsin is widely expressed in the brain [ 1 9 ] but only a certain region is to be manipulated with light. Thus, specific knowledge of the light requirements for a given experimental situation can inform an optimal e xperimental design, and this includes knowledge about the specific light attenuation properties of the brain area to be man ipulated, as well as knowledge about how different light wavelengths will affect the illumination.

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64 CHAPTER V IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES, AND FUTURE PLANS Improvements A handful of improvements that would shift the accuracy and performance to the edge are being thought seriously to be incorpor ated at this stage of doing this research toward perfecting a three dimensional (3D) light attenuation model for the brain One of these enhancements is to find out a more positive way to tell whether the fiber tip is right at the top of sample surface neither far away from it, nor punched through it. Another interesting scheme to measure would be obtainable by inserting some mechanic al properties that the sample could be described with to resolve the mystery behi nd the actual act that i s happening while the optical fiber is punching through, for instance; is it punching through smoothly, pushing it to other sides through a random proc ess, or tearing the sample (which mi ght be one of the reasons why there has been CCD camera intensity saturations happening at some points when the fiber tip gets closer to the bottom of the chamber). Hopefully, that will lead to an optomechanical three di mensional (3D) model for the light being attenuated in those brain areas. Another empirical idea that has been come up with, recently, is what it could be established by some minor adjustments to the system setup by changing the optical intensities for the optical fibers that will be traversing a specific sample thickness through tuning the current intensity. That allows erecting, at least, two handy graphs for each sample thickness associated with a certain optical fiber manufacturer specifications and

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65 the wavelength used. One of them would be the actual initial optical power intensity measured at the sample surface as a function of current intensity for a specific laboratory experimental setup. The other one is the optical power intensity measured after t he light makes it through the whole sample thickness as a function of the initial one that has been started with. Having done that, it will provide actual real numerical values for the optical intensities needed to be delivered to carry out the desired act ion with the corresponding initial ones that they should be started with in hand for the targeted brain area embedded under certain depth. The results of this experiment could be incorporated with and used for further examination, solidification, and confi rmation to the results of this study. Comparison with P revious S tudies Aravanis and colleagues [ 1 ] first characterized the optical scattering effect in mouse brain cortical tissue by measuring the optical attenuation at different slice thicknesses. In thei r work, the Kubelka Munk model where is the scattering coefficient) was used in t heir data fitting. However, our measurements were best fitted with an exponenti al function and the data cannot be satisfactory fitted with the Kubelka Munk equation. The discrepancy mainly occurs at larger distances and our data show that light attenuates much faster than predicted by the Kubelka Munk model, resulting in a much reduced excitation distance of neural targets in our results. A com parison between the two differen t fitting equations on a PPT raw data is shown in figure V.1

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66 Figure V 1 A comparison between our exponential fit and Kubelka Munk fit for a PPT raw data showing that it is best fitted with a single exponential curve More recently, Stark et al. [ 20 ] report that their measurements o f optical attenuation at larger distances from the fiber tip cannot be we ll fitted with the Kubelka M unk equation, although at shorter distances the data fit with the equation is good. The differences are likely due to the different optica l detectors being used in these experiments. In our measurements, a single pi xel of the CCD camera along the center of the propagation axis of the optical fiber was used to construct the optical transmittance curve. By contrast, the pre vious studies used a large area photodetector to measure the optical attenuation which also collects light not strictly propagating along the optical axis. This difference could potentially result in differences in the data. Having taken that into account, total intensity measurements were calculated and averaged over the entire can not be well fitted with the Kubelka Munk equation but rather a single exponential cur v e as shown in figure V.2

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67 Figure V 2 A comparison between our exponential fit and Kubelka Munk fit for an MNTB total intensity measurements of the raw data averaged over the entire When light comes out of an optical fiber tip, light spread as well as the radius of light increases as light propagates further away f rom the fiber output. This cone shape of light propagation increases the beam area thus reducing the optical irradiance of the light beam How ever, this reduction of optical irradiance due to bea m spreading from the opt ical fiber is much more gradual than the optical scattering in the brain tissue, so this beam spreading effect can be neglected or considered to be absorbed in the effective attenuation coefficient For example, the numeric al aperture (NA) of the core diameter optical fiber that was used in 0ur measurement is 0.22, such that the acceptance angle of the light cone is 9.5 degree The radius of the beam increases over a propagation distance of ; thus the beam a rea increases by a factor of 7, resulting in an optical irradiance reduction to 14% of its

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68 original output. At the same time, according to our measurements, t he optical transmittance of the MNTB due to optical scattering after o f propagation is 0.01% at 453nm wavelength. Therefore, we conclude that the optica l fiber beam spreading is not a significant effect in estimating the optical irradiance in brai n tissues. Future Plans Application of the Findings to Future Experiments One goal of this study was to provide a body of knowledge on light scattering properties of the mouse brain that could be use d by investigators as a tool to optimize the light stimul ation for a specific exper imental situation. To this end, data from several brain areas were collected but the fiber punch through method, while allowing us to obtain data in great detail, was not efficient enough to use for a multitude of brain areas. The refore we resorted to virtual microscopy to image the entire mouse brain with monochromatic t ransmitted light. The resulting images consisted of gray value pixels, which represented the differences in optical properties between these different brain areas. The differences in grey values between different brain areas obtained with virtual microscop y corresponded well with the differences obse rved in the fiber punch through method, allowing us to calibrate the results from the two approaches to each other. Th us, we obtained data on the light scat tering properties of the entire mouse brain, allowing an investigator to look up the br ain area of choice in the light scattering atlas, and determining the associated specific effective attenuation coefficient for tha t area. This coefficient can be entered into a computer program, together with information on the desired stimulation wavelengt h and volume of brain tissue to be illuminated super

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69 threshold. The comp uter program then estimates the required light intensity at the optical fiber tip to mee t the desired criteria. The use of these tools should allow an experimenter to design optogenetic manipulation in vivo with better precision and more confi dence that the brain area to be activated by light will actually be il luminated at a super threshold intensity. Moreover, the delivered light can be adjusted to be super threshold for opsin activation in the desired brain area, and fall to sub threshold values at the borders of the brain area of interest, reducing un specific activation of adjacent neuronal areas. For further information, see www.optogeneticsapp.com Research Proposal for Determining Diffusivity Constants for Individual Brain Areas While the concept of using Optog enetics is growing tremendously and becoming more involved in a variety of research and development studies in the field of neuroscience and some other relevant branches which could be: robotics and neural networks and fuzzy control soft computing (maybe i n the future), there are still a handful of related parameters to this methodology that require more investigation and some of which are still undetermined. For example, the optical, mechanical, and thermal properties of different brain areas. The knowledg e about those parameters is of significant importance to achieve the desired activation or stimulation for those targeted brain areas precisely, accurately, and without damaging the brain tissues. In this experiment we are interested in determining the con ductivity or diffusivity constants for individual brain areas This will introduce the idea of delivering above the threshold amount of optical power intensity assumed to activate the neurons from cortex without having the o ptical fiber punch through them ; using a pulsed laser with specific

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70 parameters. F or instant, the pulse energy, the pulse duration or the pulse width, and the Pulse Repetition Rate (PRR) that match those conductivity or diffusivity constants under study. Having done that, the heat accum ulation and the consequent brain tissue damage that is expected to happen via using Continuous Wave (CW) lasers of high power will be compensated for. If the threshold optical power intensity for a targeted area, the effective attenuation coefficient due to scattering and absorption phenomena per unit length and the conductivity or diffusivity const ant (unit power p er unit length per unit time; i.e. were known and after a few calculations, all it is needed to do is to match the time req uired for that pulse to reach a certain depth with PRR for the laser. In that case, the energy will be transferred to the targeted spot, and at the same time, get rid of the excessive energy that will be building up if the laser source was functioning in a CW mode; through the diffusing process of that energy during the off mode between pulses. In order to carry out this experiment, a sample from the area under investigation will be labeled by two different types of fluorophores: Midori Ishi Cyan (MiCy) on e of the Cyan Fluorescent Proteins (CFP)s, and mRFP1 one of the Red Fluorescent Proteins (RFP)s. Those two Fluorophores have the properties shown in table V.1

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71 Table V 1 Midori Ishi Cyan and mRFP1 properties [ 2 1 ] Fluor ophore Type Excitation Maximum (nm) Emission Maximum (nm) Molar Extinction Coefficient Quantum Yield In vivo Structure Relative Brightness (% of EGFP) Midori Ishi Cyan (MiCy) 472 495 27,300 0.90 Dimer 73 mRFP1 584 607 50,000 0.25 Monomer 37 In addition to that, their excitation and emission spectra are illustrated in figure V.3 and figure V.4 Figure V 3 MiCy excitation and emission spectra [ 2 2 ]

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72 Figure V 4 mRFP1 absorption (solid line), excitation (dotted line), and emission (dashed line) spectra [ 2 3 ] Those probes are suitable for conducting this experiment for their excitation peaks pretty close to the activation maxima for Channelrhodopsin 2 (ChR2) whic h is approximately 470 nm and Halorhodopsin (NpHR) which is ap proximately 580 nm [ 9 ] ; where ChR2 and NpHR are the fundamental constituents of any Optogenetics study. Their activation spectra are depicted in figure V.5 Figure V 5 ChR2 and NpHR activation spectra [ 4 ]

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73 From light sources perspectives, this experiment can be operated with one of the EPL series of Picosecond (ps ) Pulsed Diode Lasers; like the ones from Edinburgh Instruments with a wavelength of 470 nm and featuring 10 set repetition frequencies from 20 kHz to 20 MHz and pulse widths down to ca. 70 ps [ 2 4 ] Whereas, the 580 nm wavelength could be obtained from an Nd:YAG laser (1064 nm) after a frequency doubling process followed by Q switching operation to get the desired pulse shape [ 2 5 ] These light sources will be attached and coupled to optical fibers, and some of their specifications such as: energy, both dura tion or wi d th, and PRR would be highly preferred to be adjustable and tunable. Moreover, some wavelength selection filters could be used, as well, to improve and optim ize the system experimental set up and performance.

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74 REFERENCES 1 Aravanis AM, Wang LP, Zhang F, Meltzer LA, Mogri MZ, Schneider MB, Deisseroth K (2007) An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology. J Neural Eng 4: S143 56. 2 Boyden ES (2011) A history of optogenetics: the development of tools for controlling brain circuits with light. F1000 Biol Rep 3: 11. 3 Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K (2005) Millisecondtimescale, genetically targeted optical control of neural activity. Nat Neurosci 8: 1263 1268. 4 Zhang F, Wang L P, Brauner M, Liewald JF, Kay K, Watzke N, Wood PG, Bamberg E, Nagel G, Gottschalk A, Deisseroth K (2007) Multimodal fast optical interrogation of neural circuitry. Nature 446: 633 639. 5 Bernstein JG, Garrity PA, Boyden ES (2012) Optogenetics and thermogenetics: technologies for controlling the activity of targeted cells within intact neural circuits. Curr Opin Neurobiol 22: 61 71. 6 Nowak VA, Pereira EA, Green AL, Aziz TZ (2010) Optogenetics shining light on neurosurgical conditions. Br J Neurosurg 24: 618 24. 7 Henderson JM, Federici T, Boulis N (2009) Optogenetic neuromodulation. Neurosurgery 64: 796 804. 8 Lagali PS, Balya D, Awatramani GB, Mnch TA, Kim DS, Buss kamp V, Cepko CL, Roska B (2008) Light activated channels targeted to ON bipolar cells restore visual function in retinal degeneration. Nat Neurosci 11: 667 675. 9 Zhang F, Aravanis A, Adamantidis A, de Lecea L, Deisseroth K (2007) Circuit breakers: optical technologies for probing neural signals and systems. Nat Rev Neurosci 8: 577 581. 10 Gradinaru V, Mogri M, Thompson K, Henderson J, Deisseroth K (2009) Optical Deconstruction of Parkinsonian Neural Circuitry. Science 324: 354 359. 11 Chow B, Ha n X, Dobry A, Qian X, Chuong A, Li M, Henninger M, Belfort G, Lin Y, Monahan P, Boyden E (2010) High performance genetically targetable optical neural silencing by light driven proton pumps. Nature 463: 98 102.

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75 12. Al Juboori SI, Dondzillo A, Stubblefield EA, Felsen G, Lei TC, et al. (2013) Light Scattering Properties Vary across Different Regions of the Adult Mouse Brain. PLoS ONE 8(7): e67626. doi:10.1371/journal.pone.0067626 1 3 Wang LV, Wu HI (2007) Biomedical Optics: Principles and Imaging. Wiley Interscience. 1 4 Cheong WF, Prahl SA, Welch AJ (1990) A review of the optical properties of biological tissues. IEEE Journal of Quantum Electronics 26: 2166 2185. 1 5 Wilson RH, Mycek MA (2011) Models of light propagation in human tissue applied to cancer diagnostics. Technology in cancer research & treatment 10: 121 134. 1 6 Boas D, Culver J, Stott J, Dunn A (2002) Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. Optics express 10 :159 170. 1 7 Henyey LC, Greenstein JL (1941) Diffuse radiation in the galaxy. Astrophysics Journal 93: 70 83. 1 8 Sardar DK, Zapata BM, Howard CH (1993) Optical absorption of untreated and laser irradiated tissues. Lasers in Med. Science 8: 2 05 209. 1 9 Arenkiel BR, Peca J, Davison IG, Feliciano C, Deisseroth K, Augustine GJ, Ehlers MD, Feng G (2007) In vivo light induced activation of neural circuitry in transgenic mice expressing channelrhodopsin 2. Neuron 54: 205 18. 20 Stark E, Koos T, Buzski G (2012) Diode probes for spatiotemporal optical control of multiple neurons in freely moving animals. J Neurophysiol 108: 349 363. 2 1 Piston DW, Patterson GH, Lippincott Schwartz J, Claxton NS, Davidson MW Introduction to Fluorescent Proteins. N ikon Microscopy Website. 2 2 Piston DW, Claxton NS, Olenych SG, Davidson MW Applications in Confocal Microscopy: The Fluorescent Protein Color Palette. Olympus Website. 2 3 Campbell RE, Tour O, Palmer AE, Steinbach PA, Baird GS, et al. (2002) A monomeric red fluorescent protein. Proc Natl Acad Sci U S A 99: 7877 7882. 2 4 group EIT EPL series of Picosecond (ps) Pulsed Diode Lasers from Edinburgh Instruments. Direct INDUSTRY website.

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76 2 5 Pask HM, Piper JA (1998) Practical 580 nm source based on frequency doubling of an intracavity Raman shifted Nd:YAG laser. Optics Communications Volume 148: p. 285 288.