THE MATURATION OF GABAERGIC CIRCUITRY IN ...

THE MATURATION OF GABAERGIC CIRCUITRY IN FERRET VISUAL CORTEX By Dominick Joseph Casciato

A Thesis Submitted to the Faculty of The Wilkes Honors College in Partial Fulfillment of the Requirement for the Degree of Bachelor of Arts in Liberal Arts and Sciences with a Concentration in Biological Chemistry

Wilkes Honors College of Florida Atlantic University Jupiter, Florida May 2015

THE MATURATION OF GABAERGIC CIRCUITY IN FERRET VISUAL CORTEX by Dominick Joseph Casciato This thesis was prepared under the direction of the candidate’s two thesis advisors, Dr. Amanda Jacob and Dr. Paul Kirchman, and has been approved by the members of his supervisory committee. It was submitted to the faculty of The Honors College and was accepted in partial fulfillment of the requirements for the degree of Bachelor of Arts in Liberal Arts and Sciences.

SUPERVISORY COMMITTEE:

Dr. Amanda Jacob

Dr. Gregory Macleod

Dr. Paul Kirchman

Dean Jeffrey Buller, Wilkes Honors College

Date

ii

ABSTRACT Author: Dominick Joseph Casciato Title:

The maturation of GABAergic circuitry in ferret visual cortex

Institution:

Wilkes Honors College of Florida Atlantic University

Thesis Advisor:

Dr. Amanda Jacob & Dr. Paul Kirchman

Degree:

Bachelor of Arts in Liberal Arts and Sciences

Concentration:

Biological Chemistry

Year:

2015

Experience plays a critical role in maturation of cortical circuits. In visual cortex, experience-dependent development has been linked to the maturation of inhibitory interneurons. Parvalbumin-containing (PV) interneurons, a subtype of GABAergic interneurons, play an important role in cortical circuit function; however, it remains unknown

how

visual

experience

shapes

their

organization.

We

used

immunohistochemistry to observe the organization of PV expression in visual cortex through visual maturity. Before visual experience, PV cell bodies and processes are most pronounced in layer 5, less in layer 2/3, and generally lacking in layer 4. Within 3 days of the onset of visual experience, PV organization undergoes a major shift, with PV expression found throughout layers 2-6. We performed dark rearing which determined that these morphological changes are due to visual experience. This rapid change in parvalbumin organization may play a role in functional changes associated with the onset of visual experience.

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DEDICATION As I have experienced throughout this project, science entails much more than microscope slides and literature searches. The field requires support and teamwork, two entities that have undoubtedly made a significant impact on my life. I dedicate this thesis to… John, Natalie, Michael, and Mom. Your encouragement throughout my undergraduate studies motivated me to be the best student, researcher, and friend possible. The Max Planck Florida Institute for Neuroscience. Without the support of the administration, staff, and scientists, I would not have been able to conduct research in such an enthusiastic and passionate environment. Dr. David Fitzpatrick and the entire laboratory. Each member of this laboratory contributed to my experience as a researcher, and for that I am thankful. Dr. Amanda Jacob. Thank you for allowing me to take part in your project. The time, effort, and dedication you put into your work inspires me to continue that excellence in my future career. You made an immense impact on me, and your mark will follow me throughout my career as a physician. Thank you for being my mentor, teacher, life coach, and most importantly my friend.

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TABLE OF CONTENTS List of Figures ................................................................................................vi Introduction....................................................................................................1 Materials and Methods...................................................................................7 Results............................................................................................................11 Discussion ......................................................................................................15 Figures............................................................................................................17 References ......................................................................................................22

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LIST OF FIGURES AND TABLES Figure 1: Western Blot of Gad 67 and NeuN ............................................................17 Figure 2: Organization of Parvalbumin-Positive Neurons.........................................17 Figure 3: Image Quantification ..................................................................................18 Figure 4: Parvalbumin Development in Layer 4........................................................18 Figure 5: Parvalbumin Quantification .......................................................................19 Figure 6: Parvalbumin and Synaptotagmin 2 Colocalization ....................................19 Figure 7: Synaptotagmin 2 Development in Layer 4 .................................................20 Figure 8: Synaptotagmin 2 Quantification.................................................................20 Figure 9: Development of Dark Reared tissue...........................................................21 Figure 10: Quantification of Dark Reared Tissue......................................................21

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INTRODUCTION The cerebral cortex, the area of the brain responsible for the most advanced cognition, serves as the benchmark for defining higher species. The cerebral cortex is divided into two regions: allocortex and neocortex. Neocortex is only present in mammalian brains, and is the most developed region of cerebral cortex. It is responsible for brain functions such as sensory perception, language, and spatial reasoning (Lui, Hansen, and Kriegstein 2011). All neocortex has a similar layered structure containing different types and concentrations of neurons, divided into six horizontal layers numbered I to VI, where layer I is the outermost and layer VI is the innermost. Visual system and cortical organization The visual cortex is the area of cortex that processes the sensation of sight and is divided into several subregions involved in different levels of visual processing. Visual information initially enters the eyes and travels down the optic nerve and separates in the optic chiasma. This information is then sent through the optic tract to lateral geniculate nucleus (LGN) in the thalamus. Inputs from LGN enter primary visual cortex, or striate cortex, the cortical area responsible for basic visual processing such as orientation and direction selectivity. When entering cortex, information flow becomes complex. Visual information generally enters cortical layer 4 and then travels to layers 2/3. From layer 2/3 information either travels to higher-order cortical area within layer 2/3 or leaves the cortex from layer 5 and 6 to go to deeper brain regions. This dispersion of information through different pathways creates the canonical circuit of neocortex (Douglas, Martin, and Whitteridge 1989). Higher order visual areas, otherwise known as extrastriate regions of visual cortex, are responsible for higher visual processing and sending signals

to the dorsal and ventral pathways. The dorsal pathways send signals to forward regions of the brain, and are responsible for spatial recognition and motion (Lyon, Nassi, and Callaway 2010). The ventral pathway directs output towards forward regions of the brain such as the temporal lobe, and is responsible for object recognition and representation (Lamme, Supèr, and Spekreijse 1998). Primary visual cortex has a columnar organization, where neurons in a vertical column have similar properties and functions. These cortical columns are the fundamental unit of cortex; moreover, their presence and activity forms numerous functional maps in V1 (Bonhoeffer and Grinvald 1991). Several different types of columnar organization exist in visual cortex, including ocular dominance, orientation and directionselectivity columns. Ocular dominance columns contain neurons that receive visual input from primarily the eyes. They develop due to differences in axon terminals from both eyes forming a mosaic in layer 4 of cortex that extend into other cortical layers. These clusters of neurons, differing in their axon terminals, produce ocular dominance columns spread throughout visual cortex (Shatz and Stryker 1978). Orientation selectivity describes a neuron’s preference to fire when encountering a stimulus with a unique orientation. Neurons with similar orientation preferences are found clustered together and comprise orientation columns (Maldonado et al. 1997). The highly ordered orientation columns are believed to overlap with ocular dominance columns (Hubel and Wiesel 1974). Unlike ocular dominance columns, orientation

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selectivity is an emergent property that arises from multiple types of cortical connections rather than stemming from a single type of connection. Direction selectivity is defined as the response of cortical neurons when a stimulus moves in a distinct direction, but a damped or no response when the same stimulus is moved in the opposite direction (Hubel and Wiesel 1968). Layers IV and VI of primary visual cortex contain the largest number of direction selective neurons (Hawken, Parker, and Lund 1988), indicative of their role as the primary recipients from more distant brain regions. Moreover, direction selectivity columns are found within orientation columns (Hubel and Wiesel 1974). While orientation maps maintain sensitivity to experience in cortex, direction maps prove far more dependent on early vision (White and Fitzpatrick 2007). The development of these different cortical maps occurs during a window of time called the critical period. During the critical period, visual experience is required to establish circuitry that is essential for the normal maturation of neuronal response properties (Crair, Gillespie, and Stryker 1998). The development of cortical maps is influenced by both genetics and experience. For example, the LGN axon targeting in layer IV of primary visual cortex that forms ocular dominance columns is determined by a genetic code. Whereas, orientation and direction selectivity are heavily influenced by visual experience (Li, Fitzpatrick, and White 2006). Ferret as a Model System Ferrets (Mustela putorius furo) are an excellent experimental animal for studying the adult and developing visual system (Jackson and Hickey 1985). These mammals are

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born with their eyes closed, and open their eyes thirty days after birth (postnatal day 30, P30), providing a prolonged period of development where animals receive little organized visual information. The ability to control visual stimulation during this prolonged period provides an exquisite model for studying cortical circuitry throughout maturation. Though sensory experience begins when circuits in cerebral cortex are immature, visual perturbation through suturing or dark rearing can investigate the effects of dependency (White, Coppola, and Fitzpatrick 2001). In addition, the neurons in ferret primary visual cortex are arranged in cortical columns, a trait that is conserved among humans and other higher mammals, but not found in rodents (Chapman, Zahs, and Stryker 1991). Moreover, these organisms maintain experience-dependent plasticity, a prominent feature of the mammalian visual cortex (Karmarkar and Dan 2006). Inhibition To complete the variety of functions tasked with, the central nervous system relies on the actions of different classes of neurons. Two types of neurons, excitatory and inhibitory transduce, modulate, and communicate stimuli throughout the brain. Inhibitory neurons use the neurotransmitter GABA (γ-Amino butyric acid) as the main source of inhibition in the mammalian brain (Le Magueresse and Monyer 2013). GABAergic interneurons comprise between 10%-25% of the total cortical neurons (DeFelipe 2002; Le Magueresse and Monyer 2013). Inhibitory neurons serve many roles in cortical development and function. Inhibitory neurons are also thought to play a role in the regulation of excitatory and inhibitory cell signals (Kepecs and Fishell 2014). The functional maturation of local inhibitory connections defines the critical period, and continues with the assistance of late-developing interneurons (Hensch 2005). Alterations 4

in GABAergic interneurons development are thought to play a role in psychiatric and neurological disorders (Le Magueresse and Monyer 2013). . GABAergic interneurons can be divided into subclasses defined by their morphology, molecular, and physiological features (Ascoli 2008). Based on molecular markers, cortical GABAergic neurons fall into one of three classes: parvalbumin, somatostatin, or 5HT3aR-containing cells (Kelsom and Lu 2013). These three types of interneurons are believed to account for 100% of GABAergic cells in cortex (Rudy et al. 2011). Within these main three classes, at least 20 unique subtypes of GABAergic interneurons exist in cortex (Fishell and Rudy 2011). One molecular marker defined subtype of interneurons, parvalbumin positive (PV) neurons, contains the calcium binding protein parvalbumin (Hu, Gan, and Jonas 2014). PV neurons account for approximately 40% of GABAergic neurons, and vary in their firing patterns, molecular expression, axonal projections, somatodendritic size, and excitatory input (Rudy et al. 2011). The most common morphology for PV cells is either basket or chandelier. Basket cells are given their name because they form “baskets” of inhibitory synapses around the soma of neighboring cells. Chandelier cells are identified by their resemblance to a chandelier when forming synapses onto the axon initial segment of cells. PV neurons typically are fast spiking and target both excitatory and inhibitory cell soma and proximal dendrites (Tamás, Buhl, and Somogyi 1997; Galarreta and Hestrin 2002). PV interneurons create a strong GABAergic circuitry in cortex. This circuitry is responsible for developmental and adult plasticity in cortex (Sale et al. 2010). Though the

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function of PV in the neurons is not completely understood, PV neurons are thought to regulate the output of excitatory neurons by serving as a hub for communication and computation.

(Runyan et al. 2010). Moreover, this cell type only impacts specific subsets

of neurons within their projection fields (Wilson et al. 2012). The integration of PV interneurons into cortical organization improves selectivity and visual perception by sharpening orientation tuning and enhancing direction selectivity of nearby neurons (Lee et al. 2012). Through activity of PV cells, visual coding and perception can ultimately be improved by dividing responses, preserving stimulus selectivity, and altering response gain (Wilson et al. 2012). Here we study the maturation of PV interneuron innervation around the period of eye opening in ferrets. We investigated the contribution visual experience makes to this development of PV interneuron innervation over normal development. In addition, we find a reduction in PV innervation in the visually perterbated tissue compared to agematched, normal reared animals. These findings provide evidence for a potential connection between interneuron development and cortical function.

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METHODS Animals All animals were in compliance with the IACUA standards. For this study we used twenty-six ferrets and two mice. Mice were anesthetized with isofluorane before a lethal euthasol injection. Ferrets were anesthetized with dexmedetomidine and ketamine injections before a lethal euthasol injection. For western blots, we removed visual cortex, placed it in a buffer, and pulverized the tissue. For immunohistochemistry, ferrets underwent cardiac perfusion with 0.9% saline before being fixed with ~2 times their weight of paraformaldehyde in PB at 6.8 pH. Tissue was postfixed overnight, before being cryoprotected in 30% sucrose in PB at 7.2 pH. Parasagital sections were cut on a freezing sliding microtome. SDS-Page and immunoblot analysis Tissue was collected from adult mouse and ferret visual cortex. This tissue was washed with a solution of PBS and protease inhibitor (cOmplete ULTRA Tablets, Mini, EDTA-free, EASY-pack) and cut into smaller sections. Using a 20 mL then 15 mL tissue homogenizer, these sections were ground into a slurry. Homogenate was transferred into cryogenic vials and stored at -20ºC. Before use, these vials were allowed to thaw on ice, then further pulverized using syringes of needle gauge size 19, 23, then 27 (PrecisionGlide). Dilutions of tissue in 1xPB were prepared, with concentrations of 1:8, 1:4, and 1:2, totaling a protein sample volume of 7.5 µL. Loading buffer was prepared, containing 90% lammli sample buffer (BIO-RAD) and 10% β-mercaptoethanol (Sigma-Aldrich). The 7.5 µL protein sample was combined with 7.5 µL of loading buffer and inserted into a Thermal Cycler (BIO-RAD) for 10 7

minute heat cycles reaching 37ºC. Mini-Protean TGX Gels (4-15% gradient) were placed into Western Blot Tank (BIO-RAD) filled with 1x TGS. Lanes in the gel were washed with buffer, and then loaded with 15 µL of protein sample. Precision Plus Protein Standards Dual Color (Bio-Rad) was also used as the molecular size marker The wet electro-blotting system was set at 150 volts and allowed to run until the protein ran to the bottom of the gel. The gel then was removed from the tank, and allowed to equilibrate in a 20% methanol in 1xTG transfer buffer. A 0.45 µm pore size Immobilon Membrane (MILLIPORE) was washed for five minutes in solutions of 100%, and 50% methanol, and then transfer buffer. The membrane, filter paper, and gel were soaked in transfer buffer and placed into a transfer apparatus (BIO-RAD) set at 10 volts for 30 minutes. The immobilon membrane was removed and placed into 5% milk PBST blocking solution for an hour at room temperature, followed by three washes with PBST. The membrane was incubated overnight at 4ºC with the following primary antibody concentrations: rabbit anti-NeuN polyclonal (1:2000, MILLIPORE, ABN78) and mouse anti-Gad67 monoclonal (1:5000, MILLIPORE, MAB5406). Following three washes with PBST, these antibodies were conjugated with Goat-anti rabbit and mouse HRP (1:10,000) and visualized with SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific). Immunohistochemistry Slices of tissue were immunoreacted with either mouse anti-PV (1:2500, SWANT, PVG-214), mouse anti-Syn2 (1:1000, ZIRC, znp-1), or mouse anti-Gad67 (1:1000, MILLIPORE, MAB5406) with rabbit anti-NeuN (1:1000, MILLIPORE,

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ABN78). In brief, sections were blocked with a blocking buffer containing 0.5% Goat Serum and 0.3% Triton in Phosphate Buffer (PB) for thirty minutes. The sections were then incubated overnight in primary antibody. Sections were then washed three times in PB and incubated in Alexa Fluor goat anti-mouse 488 (1:500) and Alexa Fluor goat antirabbit 594 (1:500) (Life technologies). Tissue was then mounted and coverslipped with SouthernBiotech Fluoromount-G mounting media. Microscopy All tissue was imaged using a confocal microscope (Zeiss 780 LSM). For each section, an overview image of visual cortex was taken with a 10x objective lens. Using the position scan, we then took ten images were taken from layer 5, 4, and 2/3 at a magnification of 63x in water immersion (Zeiss LCI Plan-Neofluar 63x/ Nan 1.3). To rule out variable expression levels due to automated confocal image optimization, each image was obtained using the same laser power and gain. The channels on each image were then separated using ImageJ and saved for digital processing. Dark Rearing To determine the role visual experience plays in inhibitory circuit formation, we dark reared animals from postnatal day 15 (P15) to P30-P40. Animals were raised in complete darkness and perfused in the dark and sampled. Digital Neuroanatomy Images from each animal were then processed using specially designed program in MatLab. The program thresholded the PV, Syn2 or GAD67 (green) and NeuN (red) channels of each image. Two methods were used to quantify PV immunostaining.

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The first method counted the percentage of PV positive (green) pixels in the entire image after thresholding. The second method studied perisomatic intervation on the NeuN cell bodies. Images were once again thresholded and separated into their respective channels. NeuN+ cells were then encircled by a shell that extended a 1 µm radius beyond the membrane. The channels were then merged, and the percentage of PV (green) pixels within the shell was measured.

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RESULTS Western Blot Gad67 and NeuN antibody specificity has previously been shown for mouse, but not for ferret. Before immunohistochemistry was performed, antibody specificity against ferret needed to be confirmed (Figure 1). Both antibodies against Gad67 (ms) and NeuN (rb) conjugated to mouse (lane 1) as well as ferret (lanes 2, 3 and 4) tissue at the correct molecular weights, 67 and 46/48 kDA respectively. Cortical Layer Development Organization of PV cells in area 17 of visual cortex (Figure 2A) differed between visually naïve and experienced ferrets, ranging in age from P27 to P40. In the visually inexperienced cortex, PV immunostaining had a laminar organization. Layer 5 had prominent immunostaining, layer 2/3 contained a modest amount, and layer 4 had very little staining (Figure 2B). In visual experienced cortex, layers 2-6 exhibited fairly uniform PV immunostaining, and unlike the young ferret, the adult did not maintain a laminar distribution of PV (Figure 2C). Closer investigation of the adult cortex revealed the presence of baskets, or potential synapses (Figure 2E) not present in the immature cortex (Figure 2D). Parvalbumin Development and Quantification To quantify PV (green) innervation around eye opening, we used a custom digital neuroanatomy program (Figure 3A). to measure the amount of PV (green) innervation in each image (Total PV) and within a one micron radius around each NeuN-defined cell

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(Perisomatic PV Fluorescence) from P27 to P40 for layers 2/3, 4 and 5.

Across all

cortical layers we saw a rapid increase in both total and perisomatic fluorescence, with layer 4 showing the most significant increase (Figure 4). Most notably, PV fluorescence experienced a significant increase near one day of visual experience (Figure 4C). Perisomal PV in each image showed a dramatic increase in PV fluorescence as days of visual experience increased (Figure 5B).As with total fluorescence, layer 4 increased at a greater rate than both layers 2/3 and 5. It is important to note that perisomatic PV increased more than total PV. This potentially indicates more directed growth of PV near the soma, which is likely to be perisomatic synapses. Parvalbumin and Synaptotagmin- 2 Colocalization Synaptotagmin-2 (Syn2) functions as a membrane trafficking protein, and is found on the presynaptic axon terminal. Previous studies suggest that Syn2 is a reliable marker for PV inhibitory boutons (Sommeijer and Levelt 2012).

We confirmed the

reliability of Syn2 as a marker for PV synapses (Figure 6). As expected, Syn2 was not within PV soma; however, Syn2 and PV both colocalized (Figure 6A, B) perisomatically, consistent with Syn2 as a marker for PV synapses (Figure 6C). Synaptotagmin 2 Development Similar to PV, Syn2 immunostaining increased during visual maturity in all layers. Syn2 immunostaining occurs slightly before changes in PV immunoreactivity, thus we began our quantification at P24. Little Syn2 immunostaining is present before visual experience (Figure 7 A,B), but increase on the day of eye opening (Figure 7C). Potential perisomal innervation began forming around zero days of visual experience

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(Figure 7C). With one day of visual experience (Figure 7D), immunostaining levels increased dramatically and continued developing throughout maturity (Figure 7E,F). The quantification of total and perisomal Syn2 fluorosence mirrored that of PV. The total synaptotagmin fluorescence increased as the animal gained visual experience (Figure 8A). Moreover, layer 4 continued to exhibit a greater rate of fluorescence throughout maturity than layers 2/3 and 5. The percent fluorescence of perisomatic Syn2 followed this maturation trend as well: increasing fluorescence over time, with a notable rate of increase in layer 4 among other layers (Figure 8B). Experience Independent Development Dark- rearing was conducted to determine the contribution of visual experience to PV neuron development. Comparing dark- reared animal tissue (Figure 9 rows B and D) to normally reared time-matched animals (Figure 9 A and C) shows the impact of visual experience. Both the development of PV (Figure 9 row A,B) and Syn2 (Figure 9 row C,D) were observed. Dark reared tissue showed delayed expression of PV throughout development. In time-matched comparisons between regularly reared and normally reared animals, the ferrets raised in the dark exhibited significantly less immunoreactivity against PV. Dark reared Syn2 expression shared the same delay in immunoreactivity compared to the normally reared animal. Quantification of this experience dependent plasticity confirmed the observation that visual perturbation delayed, or prolonged, normal development of PV and Syn2 (Figure 10). Dark reared perisomatic PV fluorescence significantly lagged behind that of

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the normally reared animal (Figure 10A). Moreover, dark reared perisomatic Syn2 fluorescence also trailed behind that of the normally reared animal (Figure 10B).

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DISCUSSION Overview Cortical inhibitory neurons are suggested to play a major role in the maturation of cortical function. During the critical period, solidification of neuronal interactions leads to the development of many functional properties such as orientation and direction selectivity. It is around the eye opening period that we observed an increase in inhibitory neuron connectivity through the integration of PV cells into the cortical circuit.

PV

interneurons have been shown to affect cortical communication by modulating cell responses within its projection field and their integration into cortical circuitry correlates with the generation of orientation and direction selectivity, suggesting PV interneurons may play an important role in the development of these cortical properties. Layer Specific Implications The increase of PV expression in layer 2/3, 4, and 5 may indicate the PV expressing neuron’s importance in response modulation. Interestingly, layer 4, has the greatest rate increase in PV innervation. Layer 4 is the first region of cortex to receive visual information from thalamus, and information processing and dissemination are the primary function of the layer. As a result, the largest increase in PV interactions in layer 4 out of all cortical layers could potentially reflect its role as a cortical circuit modulator. Experience-dependent Implications The absence of PV immunostaining in dark reared animals implicates that the maturation of this GABAergic neuron is experience dependent. Moreover, lack of expression as a result of visual perturbation reveals the significance of the critical period

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in cortical development. This insight into the development of the PV interneuron may contribute to the functional activity of visual cortex. Moreover, the organization and development of GABAergic interneurons in visual cortex may serve as a model for neural circuits throughout cortex.

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FIGURES

Figure 1: Western Blot of Gad 67 and NeuN. Band at 67kDa shows homology between mouse (Lane 1) and ferret (Lanes 2, 3, and 4) for Gad 67 antibody. Band at 46/48 kDa shows homology between mouse (Lane 1) and ferret (Lanes 2, 3, and 4) for NeuN antibody.

A

Before Eye Opening

Before Eye Opening

Adult

Adult

Figure 2: Organization of Parvalbumin-Positive Neurons. (A) Parasagital overview of ferret cortex. The red box indicates area 17, our area of interest. (B,C) 10x magnification of ferret visual cortex from insert in Figure 1 A. (B) Visual cortex before eye opening. (C) Adult visual cortex. (D) 63x image of layer 4 in ferret before eye opening. (E) 63x image of layer 4 in adult ferret

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A

B

C

Cell Body 1.0 µm shell

Figure 3: Image Quantification. (A) Original Image. (B) NeuN cell detection and Parvalbumin thresholding provide total parvalbumin fluorescence. (C) Parvalbumin shell is determined and provides the parvalbumin perisomal fluorescence.

A

B

C

D

E

F

10 µm

Figure 4: Parvalbumin Development in Layer 4. PV+ cell development at (A) P27Visual Experience (BE); (B) P30, 0 Days of visual experience (DVE); (C) P33, 1DVE; (D) P35, 2DVE; (E) P39, 5DVE; (F) P42, 9DVE.

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A

B

Figure 5: Parvalbumin Quantification. (A Parvalbumin flurorescence from before visual experience (BVE), zero days of visual experience (DVE 0), and 1-2, 3-5, and 7-10 DVE from (A) total parvalbumin fluorescence and (B) perisomatic parvalbumin.

Synaptotagmin 2

Synaptotagmin 2 Parvalbumin Colocalization

Parvalbumin

A

B

Figure 6: Parvalbumin and Colocalization.

C 10 um

Synaptotagmin 2 Colocalization. (A) Synaptotagmin 2 and (B) Parvalbumim (C)

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A

B

C

D

E

F

Figure 1: 7: Synaptotagmin Synaptotagmin 22 development Development in in Layer Layer 44.(A) Syn2+ (A)(D) P24, Before Figure P 24cell BVEdevelopment (B) P 27, (C) Pat30, P33, (E) P Visual 36, andExperience (F) P 40. (BVE); (B) P27 BVE: (C) P30, 0DVE;(D) P33, 3DVE: (E) P36, 6DVE; (F) P40, 10DVE.

A

B

Figure 8: Synaptotagmin 2 Quantification. (A) Synaptotagmin 2 fluorescence from before visual experience (BVE), zero days of visual experience (DVE 0), 1-2, 3-5, and 7-10 DVE from (A) total synaptotagmin 2 fluorescence and (B) perisomatic synaptotagmin.

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Figure 9: Development of Dark Reared Tissue. Time-Matched Comparison of normally reared PV (A) and Syn2 (C) with dark reared PV (B) and Syn2 (D) ferret visual cortex.

A

B

Figure 10: Quantification of Dark Reared tissue. Perisomatic Parvalbumin (A) and Synaptotagmin 2 (B) increase during development, but exhibit less fluorescence than the normally reared tissue (shadow graphs).

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