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Cortical and subcortical responses to electrical stimulation of rat retina
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Content
Cortical and Subcortical Responses to Electrical Stimulation of
Rat Retina
by
Kiran Nimmagadda
————————————————————–
ADissertationPresentedtothe
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(NEUROSCIENCE)
August 2017
Dedication
To the two loves of my life: T.L.K. & J.K.N.
ii
Acknowledgments
They say it takes a village to raise a child. I think the same could be said of a
dissertation. The chief of this village for my dissertation would undoubtedly be my
advisor, Dr. James Weiland. I am thankful for his sustained support over the many
yearsittooktoproducethiswork. OneofthefirstemailsIgotfromJimafterIjoined
the lab contained an essay on being productively stupid and embracing failure on the
journey that is scientific research. I failed repeatedly on the road to finishing this
thesis, and I’m very grateful for Jim’s patient support throughout the journey. I also
became a parent during this time – research is hard and parenthood is hard, and the
two together may be the hardest thing I’ve ever done. I’m deeply thankful that Jim
allowed and encouraged me and all his students to maintain a balanced professional
and personal life.
I owe many thanks to Dr. Mark Humayun for his inspirational leadership and
establishing the Bioelectronics Research Lab and the Institute for Biomedical Ther-
apeutics at USC. I am also thankful for his advice over the years and for his service
on my dissertation committee. I would also like to thank Drs. Alapakkam Sampath,
Greg Field, Judith Hirsch, Michael Jakowec, and Aaron McGee for serving on my
guidance and dissertation committees. They all provided valuable advice during the
many meetings and conversations over the years. Special thanks to Dr. Jakowec for
adviceonperformingGolgistainsandanalysisonratbrainsectionsandhisgenerosity
in allowing me access to the microscope in his laboratory.
iii
IwouldliketothankallthestudentsandfellowsintheBioelectronicsResearch
Lab that I have interacted with over the years. I shall cherish the diverse discussions
andexperiencesIsharedwiththemall. IoweaspecialthankstoDr. NavyaDavuluri
and Alejandra Gonzalez-Calle for imparting their knowledge and wisdom in surgical
techniques and performing in vivo animal experiments. Special thanks also to Drs.
Artin Petrossians and Curtis Lee for coating my stimulation electrodes with the high
surface area Pt/Ir thin film that was vital for performing experiments with blind
rats. I’m also deeply thankful for the support provided by Fernando Gallardo and
LinaFloresinthevivariumandduringmyanimalexperiments. I’malsoverythankful
for the administrative support from Doris Lee, Ellis Troy, and Rachel Spencer. A big
part of my dissertation required the breeding of blind rats, and I’m very thankful for
the advice and support from Dr. Sumanth Putta from the Department of Animal
Resources at USC.
Last but not least, I’d like to thank my family for their unconditional love and
support through all my endeavours.
iv
Abstract
Retinal degenerative disorders are one of the leading causes of human blindness in
adult life. Electronic retinal prostheses aim to restore vision in blind people who
have photoreceptor cell loss by electrically stimulating the retina. Previous research
has shown that in a large number of blind patients, the inner retina has surviving
electrically-excitable cells despite degenerative loss of all photoreceptor cells. This
finding provides the impetus for utilizing implantable electronic retinal prostheses
to provide functional vision for such patients with blindness due to photoreceptor
degeneration.
One of the overarching research goals in our laboratory has been the study of
scientific principles underlying the therapy of electronic retinal prostheses. Studies
using rat and mouse models of retinal degeneration have been performed with in
vitro and in vivo experimental preparations. All of the experiments in these animal
models of outer retinal degeneration have focused the study on either the retina or
the superior colliculus. As a significant number of retinal cell ganglion axons synapse
in the superior colliculus (SC), electrophysiology and anatomical studies performed
in the SC have been used as a marker for retinal output. Since functional vision is
mediatedbyactivityinthevisualcortexandthelateralgeniculatenucleus(equivalent
function in thalamus in humans) in rats, I performed the bulk of my thesis work
studying responses in the visual cortex elicited by electrical stimulation of the retina
The human (and rat) visual cortex has an orderly arrangement of visual field
v
processing, termed retinotopy. This retinotopic organization represents specificity in
the spatial organization of connections in the various layers of the visual system with
respect to the visual field, and is an important element of functional vision. This
thesis presents the first work in the study of visual cortex retinotopy in response to
electrical stimulation of the retina.
My experiments using electrophysiology studies show retinotopic cortical activity
in response to focal electrical stimulation of the rat retina in normally sighted ani-
mals. The location in the visual cortex where activity is seen in response to electrical
stimulation of normal retina matches well with previously published maps of cortical
activity elicited by light stimulus. For blind rats with outer retinal degeneration (rd),
it appears that retinotopy is not well preserved in the visual cortex in response to
electrical stimulation of the diseased retina.
Thecorticalactivityelicitedbyelectricalstimulationoftheretinaforbothnormal
and rd rats shows a dose response characteristic with respect to the stimulus ampli-
tude. However, the rd rats with outer retinal degeneration required higher amplitude
stimulus pulses to be delivered to the diseased retina in order to elicit responses in
the visual cortex.
vi
Table of Contents
Dedication ii
Acknowledgments iii
Abstract v
List of Figures x
1 Introduction 1
1.1 Retina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Outer Retinal Degeneration . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.1 Retinitis Pigmentosa . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.2 Age-related Macular Degeneration . . . . . . . . . . . . . . . . 7
1.2.3 Impact of Outer Retinal Disease . . . . . . . . . . . . . . . . . 8
1.2.4 Therapies for Outer Retinal Degeneration . . . . . . . . . . . 9
1.3 Electrical Stimulation of Neurons . . . . . . . . . . . . . . . . . . . . 10
1.3.1 Physiological Excitation of Neurons . . . . . . . . . . . . . . . 11
1.3.2 Artificial Excitation of Neurons . . . . . . . . . . . . . . . . . 14
1.4 Animal Models of Retinal Degeneration . . . . . . . . . . . . . . . . . 19
1.5 Methods for Studying Brain Activity . . . . . . . . . . . . . . . . . . 22
1.6 Plasticity in the Visual System . . . . . . . . . . . . . . . . . . . . . 24
vii
1.7 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2 Evaluation of Current, Voltage, and Charge Controlled Pulses for
Retinal Prostheses 29
2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.2.1 Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.2.2 Stimulation Electrodes and Experimental Groups . . . . . . . 32
2.2.3 Modifying the Surface of the Stimulation Electrode . . . . . . 33
2.2.4 Surgical Procedures . . . . . . . . . . . . . . . . . . . . . . . . 34
2.2.5 SC Exposure and Recording Electrode Positioning . . . . . . . 34
2.2.6 Stimulation Electrode Insertion . . . . . . . . . . . . . . . . . 35
2.2.7 Electrical Stimulation of Retina . . . . . . . . . . . . . . . . . 36
2.2.8 Data Acquisition and Analysis . . . . . . . . . . . . . . . . . . 37
2.3 Results: Voltage vs Current Stimulation Pulses . . . . . . . . . . . . 39
2.3.1 EER Strength Comparison . . . . . . . . . . . . . . . . . . . . 39
2.3.2 Power Consumption Comparison . . . . . . . . . . . . . . . . 43
2.3.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.4 Qstim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.4.1 EER Strength Measurement with Qstim . . . . . . . . . . . . 49
2.4.2 Power Consumption with Qstim . . . . . . . . . . . . . . . . . 54
2.4.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3 Cortical Responses to Electrical Stimulation of Rat Retina 58
3.1 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.1.1 Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.1.2 Surgical Procedures . . . . . . . . . . . . . . . . . . . . . . . . 60
3.1.3 Craniotomy and Recording Electrodes . . . . . . . . . . . . . 60
viii
3.1.4 Stimulation Electrodes . . . . . . . . . . . . . . . . . . . . . . 61
3.1.5 Electrical Stimulation of the Retina . . . . . . . . . . . . . . . 62
3.1.6 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.1.7 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.2.1 Cortical Activity Maps for Normal Rats . . . . . . . . . . . . 65
3.2.2 Cortical Activity Maps for RD Rats . . . . . . . . . . . . . . . 74
3.2.3 Cortical EER versus LER . . . . . . . . . . . . . . . . . . . . 85
3.2.4 Cortical EER Strength vs Amplitude . . . . . . . . . . . . . . 87
3.2.5 Spontaneous Activity in the Visual Cortex of rd rats . . . . . 93
3.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4 Cortical Neuroanatomy of Sighted versus Blind Rats 104
4.1 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.1.1 Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.1.2 Golgi Staining . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.1.3 Morphological Analysis of Visual Cortex Neurons . . . . . . . 107
4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
4.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5 Conclusions and Future Work 114
5.1 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
6 Appendix: Tools and Methods 118
6.1 Electrophysiology Rig . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
6.1.1 Electrophysiology Experiment Protocol . . . . . . . . . . . . . 120
6.2 Breeding Retinal Degenerate Rats . . . . . . . . . . . . . . . . . . . . 125
6.3 Design of a Low-cost Chronic Stimulator . . . . . . . . . . . . . . . . 126
ix
References 131
x
List of Figures
1.1 Anatomy of the eye and retina . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Layers of the retina . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Cell types of the retina . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Vision with retinitis pigmentosa . . . . . . . . . . . . . . . . . . . . . 6
1.5 Vision with age-related macular degeneration . . . . . . . . . . . . . 7
1.6 Overview of an electronic retinal prosthetic system . . . . . . . . . . 10
1.7 Action potential propagation . . . . . . . . . . . . . . . . . . . . . . . 12
1.8 Signal propagation in a synpase . . . . . . . . . . . . . . . . . . . . . 13
1.9 E↵ect of extracellular current stimulus on axon membrane voltage . . 15
1.10 Electrical model of neuron membrane . . . . . . . . . . . . . . . . . . 17
2.1 Comparison of stimulus waveforms . . . . . . . . . . . . . . . . . . . 30
2.2 Charge-controlled stimulus waveforms . . . . . . . . . . . . . . . . . . 31
2.3 Bode plot of high surface area Pt/Ir electrode . . . . . . . . . . . . . 33
2.4 Representative trace of SC EER . . . . . . . . . . . . . . . . . . . . . 35
2.5 SC electrophysiology experiment setup . . . . . . . . . . . . . . . . . 37
2.6 EER versus charge for normal rats . . . . . . . . . . . . . . . . . . . 40
2.7 EER versus charge using high surface area Pt/Ir electrode . . . . . . 41
2.8 EER versus charge in rd rats. . . . . . . . . . . . . . . . . . . . . . . 42
2.9 Power versus charge for current-controlled pulses . . . . . . . . . . . . 44
xi
2.10 Power versus charge for voltage-controlled pulses . . . . . . . . . . . . 45
2.11 Power for voltage-controlled versus current-controlled pulses . . . . . 46
2.12 Power for voltage-controlled versus current-controlled pulses with high
surface area electrode . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.13 SC EER with Datawave stimulator . . . . . . . . . . . . . . . . . . . 50
2.14 SC EER with Qstim stimulator . . . . . . . . . . . . . . . . . . . . . 51
2.15 SC EER with Qstim; DAQ gain 8x . . . . . . . . . . . . . . . . . . . 52
2.16 SC EER with Qstim; DAQ gain 4x . . . . . . . . . . . . . . . . . . . 52
2.17 SC EER with Qstim; DAQ gain 2x . . . . . . . . . . . . . . . . . . . 53
2.18 SC EER with Qstim; DAQ gain 1x . . . . . . . . . . . . . . . . . . . 53
2.19 Power versus charge for Qstim charge-controlled pulses . . . . . . . . 55
2.20 Power versus charge for Qstim current-controlled pulses . . . . . . . . 55
2.21 Power versus charge for Qstim stimulator . . . . . . . . . . . . . . . . 56
3.1 Visual cortex electrophysiology experiment setup . . . . . . . . . . . 63
3.2 V1 EER map for normal rat ventral temporal retina stimulation . . . 66
3.3 V1 EER map for normal rat ventral temporal retina stimulation . . . 67
3.4 V1 EER map for normal rat ventral temporal retina stimulation . . . 68
3.5 V1 EER map for normal rat ventral temporal retina stimulation . . . 69
3.6 V1 EER map for normal rat ventral nasal retina stimulation . . . . . 70
3.7 V1 EER map for normal rat ventral nasal retina stimulation . . . . . 71
3.8 V1 EER map for normal rat ventral nasal retina stimulation . . . . . 72
3.9 V1 EER map for normal rat dorsal nasal retina stimulation . . . . . . 73
3.10 V1 EER map for normal rat dorsal temporal retina stimulation . . . 74
3.11 V1 EER map for rd rat ventral temporal retina stimulation . . . . . . 75
3.12 V1 EER map for rd rat ventral temporal retina stimulation . . . . . . 76
3.13 V1 EER map for rd rat ventral temporal retina stimulation . . . . . . 77
3.14 V1 EER map for rd rat ventral nasal retina stimulation . . . . . . . . 78
xii
3.15 V1 EER map for rd rat ventral nasal retina stimulation . . . . . . . . 79
3.16 V1 EER map for rd rat ventral nasal retina stimulation . . . . . . . . 80
3.17 V1 EER map for rd rat dorsal nasal retina stimulation . . . . . . . . 81
3.18 V1 EER map for rd rat dorsal nasal retina stimulation . . . . . . . . 82
3.19 V1 EER map for rd rat dorsal nasal retina stimulation . . . . . . . . 83
3.20 V1 EER map for rd rat dorsal nasal retina stimulation . . . . . . . . 84
3.21 V1 EER map for rd rat dorsal temporal retina stimulation . . . . . . 85
3.22 Light evoked and electrical evoked potentials in V1 . . . . . . . . . . 86
3.23 Light evoked and electrical evoked potentials in V1 . . . . . . . . . . 86
3.24 V1 representative EER for 25 µAstimulus . . . . . . . . . . . . . . . 87
3.25 V1 representative EER for 50 µAstimulus . . . . . . . . . . . . . . . 88
3.26 V1 representative EER for 75 µAstimulus . . . . . . . . . . . . . . . 88
3.27 V1 representative EER for 100 µAstimulus . . . . . . . . . . . . . . 89
3.28 V1 EER SNR versus stimulus amplitude . . . . . . . . . . . . . . . . 90
3.29 V1 EER SNR versus stimulus amplitude . . . . . . . . . . . . . . . . 91
3.30 V1 EER SNR versus stimulus amplitude for rd rats . . . . . . . . . . 92
3.31 V1 EER SNR versus stimulus amplitude for rd rats . . . . . . . . . . 93
3.32 Visual cortex spontaneous activity. . . . . . . . . . . . . . . . . . . . 94
3.33 Spontaneous activity power in normal versus rd rats . . . . . . . . . . 95
3.34 V1 spontaneous activity power histogram for normal rats . . . . . . . 96
3.35 V1 spontaneous activity power histogram for rd rats . . . . . . . . . 96
3.36 Composite V1 activity map for normal rats . . . . . . . . . . . . . . . 98
3.37 Composite V1 activity map for rd rats . . . . . . . . . . . . . . . . . 99
3.38 Composite V1 activity map centroids for normal rats . . . . . . . . . 100
3.39 Composite V1 activity map centroids for rd rats . . . . . . . . . . . . 101
3.40 Composite V1 activity map boundaries and centroids for normal rats 102
3.41 Composite V1 activity map boundaries and centroids for rd rats . . . 103
xiii
4.1 Visual cortex neuron morphology . . . . . . . . . . . . . . . . . . . . 108
4.2 Golgi stained rat brain section at 1.25x . . . . . . . . . . . . . . . . . 109
4.3 Golgi stained rat brain section at 10x . . . . . . . . . . . . . . . . . . 110
4.4 Golgi stained section at 60x . . . . . . . . . . . . . . . . . . . . . . . 111
4.5 Dendritic Spine Density . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.1 Stereotaxic bench for small animal experiments . . . . . . . . . . . . 119
6.2 Plexon headstage amplifier . . . . . . . . . . . . . . . . . . . . . . . . 120
6.3 Low cost chronic neural stimulator . . . . . . . . . . . . . . . . . . . 126
6.4 Low cost chronic neural stimulator test setup. . . . . . . . . . . . . . 128
6.5 Stimulator interface board . . . . . . . . . . . . . . . . . . . . . . . . 129
6.6 Current waveforms from low cost chronic neural stimulator . . . . . . 130
xiv
Chapter 1
Introduction
The visual system provides an ecient way of gathering information from the envi-
ronment to aid behavior. Light, the visual signal, is focused by the cornea and lens
in the front of the eyes onto the retina, a light-sensitive membrane in the back of
the eye (Figure 1.1). The retina serves as a transducer for the conversion of patterns
of light into neural signals. The perception of vision depends on the ability of the
photoreceptor cells in the retina to convert light in the visual space into an elec-
trochemical signal transmitted by neurons in the retina to cortical and subcortical
structures in the visual pathway. The retinal ganglion cell axons bundle together to
form the optic nerve, which carries the visual signal from the retina to the brain. The
neural signal from the retina is transmitted by the optic nerve to the visual cortex in
atopographicallyaccuratefashion.
1
Figure 1.1: Anatomy of the eye and retina
A cross-sectional overview of the eye and the retina. From
http://webvision.med.utah.edu
1.1 Retina
The retina is a light sensitive neural network that is anatomically and functionally
layered, as seen in Figure 1.2. It consists of five primary cells types: photoreceptor,
bipolar, horizontal, amacrine, and retinal ganglion cells. There is extensive process-
ing of the visual signal in this network from the photoreceptors enroute to the optic
nerve. The photoreceptors in the outer retina transduce light and transmit an elec-
trochemicalsignalthroughsynapticconnectionstothebipolarcells. Thebipolarcells
in turn form synaptic connections with retinal ganglion cells in the inner retina. The
retinal ganglion cell axons bundle together to form the optic nerve, which carries the
visual signal to the brain. Among other functions, the horizontal and amacrine cells
play a role in the center-surround receptive field properties of the bipolar and retinal
ganglion cells, respectively, and in shaping the signal that is carried by the retinal
ganglion cell axons.
2
Figure 1.2: Layers of the retina
Adiagramshowingtheoverallarrangementofretinallayers(left),andthebasic
circuitry of the retina (right). From Neuroscience, 2nd ed.
The function of the retina is to transduce the multiple di↵erent physical qualities
present in the visual environment such as luminance, color, contrast, depth, shape,
motion etc. into signals that the optic nerve can transmit to the visual system in
the brain. There is a lot of parallel processing in the retina to handle these disparate
physical inputs from the visual environment. The di↵erent types of specialized cells
in the retina (Figure 1.3) functionally complement each other and provide diverse
information about the visual scene to the cerebral cortex for further processing and
to enable the visual cortex to build an unified percept of the visual scene.
3
Figure 1.3: Cell types of the retina
Diversity of retinal cell types that are distinct in morphology and function. From
Masland 2011.
The retina is one of the most accessible parts of the central nervous system.
As a result, it has been one of the most intensely studied tissues in neuroscience.
While the study of the plasticity of the cerebral cortex has a history spanning over
half a century, the details of retinal plasticity under pathologic conditions have only
emerged in the past two decades. The structural remodeling, physical rewiring, and
molecular reprogramming seen in the retina under stress are important discoveries
for clinical translational work targeting retinal degenerative diseases. The emerging
neuroscience-basedunderstandingofthepathologyunderlyingdiseasessuchasretini-
tis pigmentosa and age-related macular degeneration is vital to advancing therapies
against such diseases (Marc 2009).
4
1.2 Outer Retinal Degeneration
The two most common outer retinal degenerative diseases are age-related macular
degeneration (AMD) and retinitis pigmentosa (RP). AMD is more prevalent, but
RP is more severe and both are characterized by progressive loss of photoreceptors.
Photoreceptor cells in the retina are essential for human vision. They transduce
incoming light into an electrochemical signal. After retinal processing, this signal is
transmittedbytheopticnervetothethalamusandonwardstothevisualcortex. The
progressivelossofphotoreceptorsinAMDandRPcanleadtocompleteblindnessand
profound disability. It is estimated that about 15 million people su↵er from vision
loss due to these diseases worldwide, and these numbers are expected to rise as the
population ages.
1.2.1 Retinitis Pigmentosa
Retinitispigmentosa(RP)isageneraltermforadisparategroupofinheriteddiseases
with progressive degeneration of photoreceptors. The hallmark symptoms of retinitis
pigmentosa are night blindness and gradually progressive peripheral visual field loss
(Figure 1.4). An electroretinogram (ERG) shows either markedly reduced or absent
retinal function. It occurs in a sporadically or in an autosomal recessive, dominant,
or X-linked pattern. Most cases are due to a mutation in the gene for rhodopsin,
the rod photopigment, or in the gene for peripherin, a glycoprotein located in the
photoreceptor outer segments. Genetic mutations in the RHO gene that codes for
rhodopsin, a key protein in the photortansduction system, accounts for 30-40 % of
the cases of autosomal dominant retinitis pigmentosa.
In the early stages of RP, patients experience night blindness and a progressive
loss of the visual field, the area of space that is visible at a given instant without
moving the eyes. In the late stages of RP, people tend to lose more of the visual
5
field, developing tunnel vision (Figure 1.4). They may have diculty performing
essential activities of daily living like driving, reading, recognizing faces and objects,
and walking without assistance.
Figure 1.4: Vision with retinitis pigmentosa
Visual scene perceived by normally sighted people versus patients with retinitis
pigmentosa. From NEI.
In RP retina, the death of rod photoreceptor cells leads to a reorganization of the
cone mosaic into an orderly array of rings. At the end of the major phase of rod
death, cones are still functional but move to the inner nuclear layer (INL). As the
rod cells die and leave holes behind, remodeled Muller cell processes fill the center
of the holes after the disappearance of active microglial cells. The death of rod cells
leads to deprivation and de-a↵erentation induced remodeling of the downstream reti-
nal circuits, especially the rod pathway. Rod bipolar cells undergo reduction of their
cell density, regression of their dendrites, and changes in their axon morphology and
distribution of mGluR6 receptors, and make connections with cone photoreceptors.
Horizontal cells also undergo changes: their cell density drops and they start to make
axonal connections in the inner retina. With progressive death of cones, cone bipolar
cells undergo a process of progressive retraction with changes in axon terminal mor-
phology and regression of dendrites and this leads to further remodeling of horizontal
cells. In contrast, the retinal ganglion cells continue to be viable and retain their
6
characteristic morphology (Lee 2011).
1.2.2 Age-related Macular Degeneration
Age-relatedmaculardegneration(AMD)a↵ectscellsinthefovealregionoftheretina
and subsequently leads to loss of central vision (Figure 1.5), which lets us see objects
that are straight ahead. The macula is the most sensitive region of the retina and is
made up of millions of photoreceptors that provide sharp, central vision. The fovea
is the center of the macula, and is responsible for the sharpest central vision. The
etiology of AMD is multi-factorial and includes genetic mutations in photoreceptors
and accumulation of drusen (Schuman 2009, Medeiros 2000). Age is the major risk
factor for being diagnosed with AMD and the prevalence of AMD in the United
States is highest among patients older than 55 years (Schuman 2009). Other risk
factors include smoking, race (more common among Caucasians than among African-
Americans or Hispanics/Latinos), and family history.
Figure 1.5: Vision with age-related macular degeneration
Visual scene perceived by normally sighted people versus patients with age-related
macular degeneration. From http://optos.com.
Intheearlystagesofage-relatedmaculardegneration(AMD),sub-retinaldeposits
called drusen are formed in between the Bruch’s membrane and the retinal pigment
epithelium (RPE). As the disease progresses, two main phenotypes of the disease
result: dry AMD and wet AMD. Both the forms are due to dysfunction in the RPE
7
leadingtophotoreceptordamage. Itisnowunderstoodthatgrowthfactorsplayakey
role in RPE dysfunction in both forms of the disease, and the di↵erent actions of the
growthfactorsleadstodi↵erentphenotypes(Lee2011). IndryAMD,oxidativestress
leads to the expression of BMP4, which causes senescence of RPE cells and early cell
death, leading to a slow progressive loss of central vision. In wet AMD, inflammation
causes the growth factors VEGF and HGF to be secreted, which cause choroidal
neovascularizationandRPEactivation,respectively. Hemorrhageofthenewlyformed
choroidal vessels can lead to a rapid severe loss of vision. When inflammation is
resolved,anothergrowthfactor,CTGF,promotesfibrosisresultingintheformationof
aretinalscar. SincetheRPEcellsprovidecrucialsupporttothephotoreceptors,their
dysfunction and loss leads to vision loss in AMD. Since various growth factors have
been shown to drive disease progression, using antibodies to block the action of these
growth factors guides current therapies for AMD. In case of advanced disease, using
embryonic stem cells to regenerate RPE cells that are functional is being intensely
investigated for future therapies.
1.2.3 Impact of Outer Retinal Disease
The societal impact of outer retinal degenerative disorders is tremendous. These
disorders are one of the leading causes of adult-onset blindness. A multi-country
studyofpatientswithAMDhasshownthatthediseasehasasignificantemotionaland
functional impact on patients, providers, and society overall (Soubrane 2007, Lotery
2007). IntheUnitedStates, thereareapproximately700,000newAMDpatientseach
year, 10% of whom will become legally blind (Curcio 1996, Margalit 2003). As the
United States population ages, it is estimated that more elderly persons will become
blind from AMD than from glaucoma and diabetic retinopathy combined (Leonard
2002). Avalue-basedanalysisofthesocietalburdenofAMDestimatestheyearlycost
of the disease borne by the United States economy to be $30 billion (Brown 2005).
8
Since these studies are restricted to AMD, they underestimate the societal impact of
the full spectrum of outer retinal degenerative diseases.
1.2.4 Therapies for Outer Retinal Degeneration
There is currently no known cure for vision loss caused by outer retinal degeneration.
Postmortem histological analysis of retinal tissue in RP and AMD patients has given
usvaluableinsight. Evenwhenphotoreceptorcelllossisvirtuallycomplete, theother
four cell types in the retina generally survive (Humayun 1999a), enough to be acti-
vated by electrical stimulus (Humayun 1999b). This finding provided the impetus
for utilizing implantable electronic retinal prostheses to provide functional vision for
patients with blindness due to photoreceptor degeneration. Electronic retinal pros-
theses electrically stimulate surviving neurons in the inner retina and represent an
emerging technology in the treatment of such diseases.
Figure 1.6 shows a system level view of a typical electronic retinal prosthesis. The
device uses an artificial means (video camera) to detect and convert light into an
electrical signal. This electrical signal is delivered (by a radio link) to an epiretinal
or subretinal electrode array, which stimulates surviving retinal neurons. This arti-
ficially induced neuronal activity is interpreted as vision. While stem cell (Lu 2009)
andoptogenetics(Doroudchi2011,Fortin2011)basedapproachestorehabilitatepho-
toreceptors are experiencing intense research e↵orts, electronic retinal prostheses rep-
resent the best near-term therapeutic solution in treating photoreceptor degenerative
diseases (Chader 2009).
9
Figure 1.6: Overview of an electronic retinal prosthetic system
1.3 Electrical Stimulation of Neurons
The nervous system receives, analyzes and transmits information in the form of ac-
tion potentials. Action potentials are rapid, transient, all-or-none changes in the
membrane potential of neurons. In order for an action potential to occur, the ini-
tial depolarization of the membrane must be sucient for the membrane potential
to reach the threshold value, near -60 mV for many neurons. At that point, the
membrane potential rapidly changes, reaching a peak value of nearly +50 mV, i.e.,
the inside of the cell becomes positive with respect to the outside. The membrane
potential returns to the resting value of -90 mV within a few milliseconds. This is
the stereotyped behavior termed action potential that is found across all types of
10
neurons.
1.3.1 Physiological Excitation of Neurons
Whenaneuronreceivesasignalfromanadjacentneuron,voltagegatedsodium(Na
+
)
channels in the membrane of the neuron open temporarily allowing an influx of Na
+
ions. This is said to depolarize the cell, with the potential inside the cell becoming
more positive with respect to the outside of the cell. This allows even more voltage
sensitive Na
+
channels to open. This is a positive feedback mechanism that proceeds
untilmostoftheavailableNa
+
ionchannelsinthevicinityareopen,andcausesalarge
upswing of the local membrane potential. The Na
+
ion channels rapidly inactivate
after this, and there is a delayed activation of potassium (K
+
)channelsresultingin
an outward current of K
+
ions, which brings the membrane potential back to the
resting state.
The density of voltage-gated sodium channels in the neuron’s membrane is one of
the main factors to determine whether an action potential can be fired or not. The
threshold for firing occurs when the resting net outward current carried by K
+
ions
becomes a net inward current carried by Na
+
ions, which requires a lot of voltage-
gated Na
+
channels. If the number of sodium channels in adjacent regions of the
cell membrane is also suciently high to cause the net current flow to be inward
upon membrane depolarization, the action potential will propagate along the cell
membrane (Figure 1.7). In this way the action potential is said to be self-reinforcing
orregenerative. Actionpotentialsareusuallyinitiatedattheaxonhillockofaneuron
and transmitted down the axon. The all-or-none nature of the change in membrane
potential allows an action potential to be transmitted with a constant amplitude
along the length of an axon.
11
Figure 1.7: Action potential propagation
An illustration of action potential propagation along the length of an axon. From
Neuroscience, 2nd ed.
The action potential signals are typically transmitted from neuron to neuron via
cellular junctions called synapses where a signal is propagated from a presynaptic
neuron to a postsynaptic neuron (Figure 1.8). An action potential in a presynaptic
cell causes the cell membrane of the presynaptic axon terminal to depolarize. This
depolarizationoftheaxonterminalcausesareleaseofachemicalneurotransmitterby
the presynaptic terminal in the synaptic cleft. The neurotransmitters bind to specific
receptors on the cell membrane of the postsynaptic neuron and cause a transient
12
change in the conductance of the postsynaptic cell membrane to specific ions. This
causesa change in the membrane potential ofthe postsynapticcell, which ifsucient
to reach threshold will generate an action potential in the postsynaptic neuron.
Figure 1.8: Signal propagation in a synpase
An illustration of the sequence of events in signal propagation across a synapse.
From Neuroscience, 2nd ed.
In summary, the ability of neurons to generate action potentials is what defines
themtobeexcitablecells. Thetriggerforexcitinganeuronisaninitialdepolarization
of the neuron’s cell membrane. This activates voltage-gated sodium channels to open
and an action potential fires if enough sodium channels open to reach threshold.
13
1.3.2 Artificial Excitation of Neurons
Neurons are capable of being artificially excited by depolarization of their cell mem-
branes, similar to when they are excited physiologically. An action potential can be
generated in a neuron artificially by facilitating current to flow from the inside of
the cell to the outside causing cell membrane depolarization. This would require the
placementofanelectrodeinsideacell, butthetechnologytointerfaceelectrodeswith
large numbers of single axons to facilitate functional stimulation of neurons does not
exist yet (Durand 2006). An alternative method that is widely used is the imposition
of an extracellular electric field that causes current to flow from the inside of the cell
totheoutside. Thisisachievedbythepassageofelectricalcurrentthroughelectrodes
placed in the extracellular space. If the electrodes are near the vicinity of a neuron
that is capable of depolarizing, an action potential is generated when its membrane
depolarization reaches threshold. Thus, current passing through a nearby extracel-
lular electrode can excite a nerve cell. The cellular events that happen after this
artificial depolarization are exactly the same as described above in the physiological
excitation of nerve cells.
Aqualitativesummaryofneuronalexcitationduetoextracellularstimulusis
provided by Figure 1.9. When the neuron is at rest, there is no net current flowing
through the membrane as shown in Figure 1.9(b). When current flows from the
outside to the inside of the cell, the membrane is hyperpolarized (moves farther away
from threshold) as seen in Figure 1.9(c). When current flows from the inside to the
outside of the cell, the membrane is depolarized (moves closer to threshold) as shown
in Figure 1.9(d). The graphical representation in Figure 1.9(a) shows that if an
extracellular electrode provides an anodic current pulse, action potential will not be
generated directly underneath the electrode where the membrane is hyperpolarized.
An action potential may be generated further along the axon where the membrane is
depolarized if the amount of depolarization is enough to reach threshold.
14
Figure 1.9: E↵ect of extracellular current stimulus on axon membrane voltage
From (Durand 2006)
Thedistributionofextracellularpotentialandresultingmembranevoltagepertur-
bation of a nearby nerve cell in response to passing current through an extracellular
electrode is complex. It depends on the electrode geometry, stimulation current am-
plitude and duration, distance of the nerve cell from the electrode, the location of
voltage gated ion channels in the nerve cell, and electrical properties of the extracel-
lular tissue. Computational modeling of electrodes and neural tissue elements using
finite element methods has proven to be a powerful tool to study the complexities
15
of extracellular excitation of neurons (Grill 2006). Computational modeling is a two
stepprocess: first, electricpotentialsgeneratedintissueduetocurrentpassageinthe
electrode are calculated; second, the e↵ect of that potential on surrounding neurons
is calculated.
To obtain useful qualitative insights, certain simplifications can be used to ob-
tain analytically tractable solutions for a neuron’s membrane voltage perturbations
due to extracellular electrode stimulus current. If the electrode is assumed to be a
point source placed in a volume conductor with homogeneous (same everywhere) and
isotropic (same in all directions) conductance, the electric field in the volume con-
ductor (representing extracellular space) can be calculated using Maxwell’s equations
(Durand 2006). However, sophisticated computational approaches and faster com-
puters have made possible more realistic field models that can be used to improve
neural prosthetic systems. For example, recent work in our laboratory used com-
putational finite element modeling and mathematical analysis to predict an optimal
stimulus current waveform that reduces current density at the edge of disk electrodes
typically used for electrical stimulation in neural prostheses (Wang 2014). This mod-
ified stimulus waveform showed significant reduction of corrosion on the periphery
of these electrodes after pulsing in comparison with he control rectangular stimulus
waveforms. Computationalfieldmodelinghasalsobeenusedtocharacterizethetem-
perature increase caused by implantable neural prosthetic systems (Lazzi 2005), and
such modeling is crucial in the proper design of therapeutic devices.
Electrical circuits have been used to model the electrical behavior of neurons, re-
ferred to as core conductor or cable models in literature. These models represent a
nerve fiber as a series of compartments (Hodgkin 1952). Based on the geometry of a
nerve fiber, a series of equivalent cylinders are used to represent the fiber geometry.
Each cylinder consists of a compartment representing the neuronal membrane, and
a resistor representing the intracellular space. Each compartment represents a small
16
portion of a neuronal membrane and is modeled using a combination of a capaci-
tor, resistors, and batteries (Figure 1.10). The capacitor represents the membrane
capacitance of the phospholipid bilayer, resistors represent ionic conductances of the
transmembrane ion channels, and batteries represent the di↵erences in potential de-
veloped across the membrane due to ionic concentration di↵erences across the mem-
brane. Since the ion channels are voltage sensitive, the resistors representing ionic
conductances are variable resistors whose value depends on the membrane voltage.
These variable resistances are described well by Hodgkin-Huxley’s numerical models.
Additionally, the resistors and capacitors in the compartment model can be changed
to have di↵erent values for soma, dendrites, and axons reflecting cell anatomical dif-
ferencesindi↵erentlocationsoftheneuronanddi↵erencesinionchannelpopulations
in di↵erent locations.
Figure 1.10: Electrical model of neuron membrane
From (Hodgkin 1952)
17
The potential generated at a distance r due to a point source monopolar electrode
with current I in a medium of uniform conductivity can be calculated to be: V =
I/4⇡r .Thisvoltagecanbeappliedasaninputtoacompartmentmodelofa
neurondescribedabove. Theelectricalcircuitmodelcanbesimulatedusingnumerical
methods or by using circuit simulation software packages such as Pspice or neuronal
simulationpackagessuchasNeuron. Thevariableofinterestisthemembranevoltage
since the conductivity of voltage gated sodium channels is sensitive to the membrane
voltage. When the stimulus current applied by the extracellular electrode creates an
extracellular voltage di↵erence between two compartments of the neuron enough to
generate a transmembrane voltage greater than threshold, an action potential will
be generated in the nerve fiber (Durand 2006). Models like these are useful to make
some general predictions of how current from an extracellular electrode a↵ects a
nerve cell. Predictions such as: threshold for excitation increases as distance between
the electrode and nerve fiber increases; larger fiber diameters have lower thresholds;
smallerthresholdsforsmallersomaincloseproximitytotheelectrode, butequivalent
threshold in small and large soma farther away from the electrode (Rattay 1999).
The activating function is defined as the rate of transmembrane voltage change in
each compartment. If the compartment model is uniform like when only an axon of
anervecellnearanextracellularelectrodeisbeingmodeled,theactivatingfunc-
tion reduces to the second spatial derivative of the extracellular voltage at that
compartment. If the nerve cell anatomy that needs to be modeled is non-uniform,
computational methods need to be used to calculate the activating function at each
node/compartment of the nerve cell.
The artificial excitation of neurons using an extracellular electrode depends on
the interaction of the stimulus current induced electric field with the voltage sensitive
ion channels present in the membrane of the neuron. Since the location, number, and
density of voltage sensitive ion channels in the membrane of a neuron varies with the
18
anatomicalfeaturesofdi↵erenttypesofneurons,itcanbeexpectedthatcellanatomy
plays a big role in the ecacy of artificial neural excitation. Also, the geometry of an
electrode through which stimulus current is delivered has a bearing on the pattern of
electrical potentials generated in the surrounding tissue, which in turn has an e↵ect
on neural activation.
The retina is a biological tissue with complex electrical properties. This has
definite implications for how stimulus current applied by an epiretinal (or subretinal)
electrodewillresultinacomplexelectricfieldpattern. Itishardtoformintuitiveand
analytical models for such an electrically complex piece of tissue, and computational
modeling of the tissue and electrodes is imperative in understanding the e↵ects of
electrical stimulation. The bulk tissue resistivity properties of various layers of tissue
in the eye have been studied more than half a century ago by Brindley. Using frog
eyes, he was able to make measurements of the resistivity of the retina, choroid, and
sclera using current pulses applied radially perpendicular to the surface of the retina
(Brindley 1956). Karwoski et al. also used frog eyes to measure resisitivies of the
various layers of the retina. While some layers like the inner plexiform layer, ganglion
cell layer, and optic nerve layer were too thin to reliably resolve individually, they
made measurements of the resistivity of subretinal space (970⌦cm), inner and outer
nuclear layer (6800 ⌦cm), inner plexiform layer (1750 ⌦cm), and ganglion cell and
optic nerve fiber layer (7900 ⌦cm) (Karwoski 1985). More recently, studies in our
laboratory measured the resistivity profiles in mice with healthy and diseased retinas
(Wang 2015).
1.4 Animal Models of Retinal Degeneration
Animal models are very helpful in evaluating the ecacy and safety of novel thera-
peutics and havebecomean indispensablepart of research in fighting human disease.
19
The development of animal models of retinal degeneration has greatly aided our un-
derstanding of the pathophysiology of photoreceptor degenerative diseases (Chader
2002). Animal models of retinal degeneration have been useful to study how the loss
ofphotoreceptorcellsa↵ectsthedi↵erentpartsofthevisualpathway: fromtheretina
to subcortical structures (superior colliculus and lateral geniculate) to the circuitry
of the visual cortex.
One of the most commonly studied naturally occurring models of RP is the Royal
College of Surgeons (RCS) rat, which has an autosomal recessive mutation originat-
ing in retinal pigment epithelial (RPE) cells. The RCS rat model aligns most closely
with indirect forms of retinitis pigmentosa caused by defects of the RPE and may
provide a useful model for age-related macular degeneration (Sauv 1998). Intracel-
lular electrophysiology recordings show marked changes in visual receptive field size,
threshold, and intrinsic membrane properties in the RCS rat (Chen 2005, Pu 2006).
Structural changes as well as biophysical alterations have also been documented in
this particular model of RP (Cuenca 2005, Vugler 2008).
Transgenic models with a mutation in the rhodopsin gene have been developed
as well. They include the P23H and S334ter rats and these rats express autosomal
dominantrecessivetraitsofRP.TheprogressionofRPintheP23Hratmodelsclosely
mirrors that seen in humans (Cuenca 2004, Kolomiets 2010). The P23H rat model
exhibits degeneration that is very similar to the human progression of autosomal
dominant RP and serves as an excellent source for extrapolating information about
this particular mutation. Unlike studies conducted in other models, morphological
assessment in the P23H rat has shown a decrease in ganglion cell density with age
(Kolomiets,2010). However,thismodelalsoexhibitschangesininnerretinalcircuitry
similar to that seen in other animal models as well as the presence of rhythmic spon-
taneous firing (Cuenca 2004, Sekirnjak 2009). The transgenic S334ter rat is a well-
established model of photoreceptor degeneration and is available in five distinct lines
20
(3, 4, 5, 7 and 9) with di↵erent characteristic rates of retinal degeneration (Thomas
2004). Studies in our laboratory using S334ter line 3 rats have been instrumental in
documenting structural, morphological, and functional changes in the retina due to
photoreceptor cell death (Ray 2008, Chan 2008, Ray 2009, Ray 2010, Chan 2011).
An important finding from studies in these rat models is that despite structural al-
terations in the inner retina, ganglion cells still remain electrically excitable and are
capable of short latency responses.
There are many mouse models used to study retinal degeneration, and they can
be broadly split into induced models and inherited models (Samardzija 2010). The
induced models are derived by exposing mice to physical (e.g., light) or chemical
(e.g., N-methyl-N-nitrosourea; MNU) treatments that cause photoreceptor cell death
leading to varied levels of retinal degeneration. These models have the advantage
of controlling disease onset, and the level of severity of degeneration. The inherited
models are derived from animals that express a genetic mutation or the expression of
atransgene. Forexample,inthe rd1 mouse model, a spontaneous genetic mutation
occurs in the subunit of the rod cGMP phosphodiesterase. More than a hundred
mousemodelsofretinaldegenerationhavebeengeneratedthroughvarioustechniques
of genetic modification (Samardzija 2010). These models are very useful to study the
consequences of gene mutations on a molecular, cellular, tissue, or system level.
In the rd1 mouse model of RP, photoreceptors cells are completely dead by the
end of the first month. Almost all the cells in the inner retina and especially the
bipolar cells show pronounced morphological changes with age in the rd1 mouse
model (Strettoi 2000, Strettoi 2002, Marc 2007, Lin 2009). Without input from
the photoreceptors, migration of glutamate receptors takes place in bipolar cells and
their dendritic processes retract. After the photoreceptor cells disappear, there is a
pronounced decrease in bipolar cell density. Despite these structural alterations in
the inner retina, the ganglion cells appear to be functionally viable in the rd1 mouse
21
model (Margolis 2008, Stashe↵ 2008).
The rd10 mouse model exhibits a slower progression of photoreceptor degenera-
tion in comparison to the rd1 mouse. In the rd1 mouse, the photoreceptors begin to
degenerate before all the retinal processes are fully developed. In contrast, onset of
photoreceptor degeneration occurs after the retina undergoes normal development in
the rd10 mouse. These retinal changes in the rd10 mice mirror the changes seen in
human patients with retinitis pigmentosa (RP), making it an excellent choice for re-
search studies. The morphological changes seen in the rd10 mouse model are similar
to the ones seen in the rd1 mouse model, but occur at a slower pace. The dendritic
structure and density of retinal ganglion cells in the rd10 mice up to 9 months of age
are not di↵erent from normal controls (Mazzoni 2008). As degeneration progresses,
the inner retina appears to undergo structural and functional alterations but the
retinal ganglion cells remain intact and viable (Gargini 2007, Barhoum 2008, Maz-
zoni 2008, Puthussery 2009). While these studies have produced a large amount of
evidence of morphological preservation in retinal ganglion cells during retinal degen-
eration, onlyrecentlyhavephysiologicale↵ectsbeenstudiedinourlaboratory. Inthe
rd10 mouse model, the retinal ganglion cells have distinct sub-populations requiring
normalorstronglyelevatedthresholdsforartificialexcitationwhencomparedtowild-
type retinas. The rd10 retinal ganglion cells with normal threshold were observed to
bemoredepolarizedatrestandexhibitperiodicoscillations, andtheretinalganglion
cells without spontaneous activity exhibit increased thresholds for activation (Cho
2016).
1.5 Methods for Studying Brain Activity
The methods to observe and measure brain activity can be broadly classified into two
forms: electricalrecordingsandelectromagneticimaging. Manyseminaldiscoveriesin
22
our understanding of the basic mechanisms of information processing in the nervous
system have resulted from electrical recordings from electrodes implanted into, or
placed on the surface of the brain. For example, electrical recordings have been used
in the discovery of place cells (O’Keefe 1976), grid cells in rats (Sargolini 2006), and
border cells in rats (Solstad 2008). They have also shown that electrical oscillations
are very common in the brain (Buzsaki 2004).
Electrodes that are placed on the surface of the brain are also used to record
local field potentials (LFPs) that represent the summation of the electrical activity of
entire neural networks. Such electrodes are routinely used these days in the clinical
environmentwithstereoencephalographyandelectrocorticography(ECoG)probesfor
the functional mapping of the brain before and after surgeries for epilepsy treatment.
Recording electrodes that penetrate the surface of the brain are used to capture
LFPs from a small population of neurons. The LFPs are generated by the spatiotem-
poral summation of the current sources and sinks caused by the flux of ions through
ionchannelslocalizedinthecellmembranesofneuronsinthevicinityoftherecording
electrode. The advantage of using a single microelectrode to record cortical signals
is that it has high spatial (point) resolution and a millisecond level temporal resolu-
tion that is fast enough to measure real-time changes in neural activity. To obtain a
functional representation of a sensory organ, defined as the cortical region containing
neurons that respond to stimulation of that organ, many recordings across a large
cortical area will have to be obtained. This is a big disadvantage in the use of single
microelectrode recordings, which can be somewhat mitigated by the use of multi-
electrode arrays. Other disadvantages are that the animal is typically anesthetized,
penetrating recording electrodes are invasive to the cortex, and recordings obtained
in a serial fashion require many hours to complete.
Electromagneticimagingofneuralactivityinthebraincanbroadlybedividedinto
magnetic resonance imaging (MRI) and optical imaging. The development of two-
23
photon excited laser scanning microscopes alongside fluorescent proteins that label
neural activity has allowed optical imaging to become a major driver of advancement
in neuroscience. The big advantage of optical methods is the micrometer scale reso-
lution of measurement of spatial distribution of neural activity in the cerebral cortex.
Intrinsic changes in reflected light measured from the cortical surface have provided
high spatial resolution maps of cortical organization (Frostig 2009). These intrinsic
signals result primarily from hemodynamic changes, in a similar way to the BOLD
fMRI signal, and are only indirectly related to neuronal electrical activity. To over-
come this, voltage-sensitive dyes have been developed that change their absorption or
emission spectra in a manner depending upon membrane potential, making possible
optical measurements that relate directly to electrical activity (Ferezou 2009).
1.6 Plasticity in the Visual System
In the nervous system, plasticity can be broadly defined as involving some form of
activeordynamicmodificationofneuralpropertiesresultingfromalteredinput. This
hasbigramificationsforanytherapeuticdevicethatartificiallystimulatesthenervous
system. A shift in ocular dominance in response to monocular deprivation during a
critical developmental period has been a classically studied model of neural plasticity
for more than half a century (Wiesel 1963, Gordon 1996). Ocular dominance (OD)
is the property of neurons in the visual cortex that enables it to fire more action
potentials when identical visual stimuli are presented to one eye versus the other
(Levelt2012). Theprimaryvisualcortexofmanyhighermammalshasneuronclusters
arranged in columns that are preferentially driven by one eye or the other, and are
termed OD columns. Alteration of visual experience during a time window called
the critical period has been shown to alter the representation of OD columns in the
visual cortex.
24
Adult plasticity is distinct from adolescent critical period plasticity in the ocular
dominance shift due to monocular deprivation. Adult plasticity relies on slow onset
of strengthened inputs from the non-deprived eye rather than a suppression of re-
sponses from the contralateral eye (Frenkel 2004). There is some evidence that vision
deprivation after the critical period does not induce neural plasticity in the visual
cortex (Fine 2003, Baseler 2011). On the other hand, studies performed with adult
amblyopia patients indicate robust induction of experience-dependent visual cortical
plasticity (Levi 1996, Levi 2005, Huang 2008). One recent study found evidence of
dendritic and synaptic plasticity in the retina due to photoreceptor disease (Sullivan
2007). There is also ample evidence from our laboratory of reorganization of the
neural circuits in the retina in response to photoreceptor atrophy (Ray 2008, Ray
2010). Recent unpublished studies in our laboratory using S334ter line 3 rats have
also shown structural and functional changes in the superior colliculus (where most
of the retinal ganglion cell axons terminate in rats (Linden 1983)), when compared
to normal rats.
Functional magnetic resonance imaging (fMRI) studies have been increasingly
used in the past decade to study the e↵ects visual deprivation on visual cortical
circuitry in both animals and humans. Smirnakis et al. used photocoagulation laser
induced retinal lesions that deprived visual input to a part of V1 (primary visual
cortex) to study long-term reorganization in the macaque visual cortex using fMRI
methods. They found that the lesion projection zone in V1 as measured by fMRI in
response to visually driven input remains constant over time even 7.5 months after
retinal lesions were induced and concluded that long-term visual deprivation does
not induce cortical reorganization in macaques. fMRI allowed them to monitor in
vivo cortical activity with a wide field of view and measuring signals from multiple
neurons per unit cortical area over the long term in a non-invasive manner. This
might explain the di↵erence in findings from electrophysiology experiments that tend
25
to sample only a few neurons.
Mendola et al. also used fMRI methods to study the di↵erences in the human
primary visual cortex of adults (n=32, ages 18-35 years) and children (n=42, ages
7-12 years) su↵ering from amblyopia. Using quantitative methods to analyze high
resolutionfMRIimagesofthebrainsofthesepatientsshowedthatadultsandchildren
withamblyopiahavedecreasedgraymattervolumeinvisualcorticalregions(Mendola
2005). In the brain images of the children, additional gray matter reductions in
parietal-occipital areas and ventral temporal cortex were detected, consistent with
reports that amblyopia can result in spatial location and object processing deficits.
While this study showed di↵erences in the visual cortex of amblyopia patients when
comparedonthebasisoftheiragegroups,noage-matchedcontrolswithnormalvision
were used and only limited information about plasticity due to visual deprivation can
be drawn from the results.
More recently, Baseler et al. used fMRI methods to explicitly evaluate visual
cortical maps in patients with juvenile macular degeneration (JMD) and adult age-
related macular degeneration (AMD) su↵ering from photoreceptor degeneration and
compared the two sets to age-matched controls. They did not find any evidence for
large-scale remapping in the early visual cortical areas in adults with acquired retinal
lesions, and found visual cortex activation no di↵erent than predictions based on
normalretinotopicmaps. Theyalsofoundthatthisabsenceofcorticalremappingwas
not dependent on the age at which the patients acquired retinal lesions in adulthood
(Baseler 2011). These results seem to match up with the results found in macaques
with experimentally induced retinal lesions as discussed above.
Foradult-onsetblindnessduetophotoreceptordegeneration,thevisualsystemhas
presumably followed its normal development earlier in life. It may be reasonable to
assumethatthevisualprocessingneuralmachineryisintactandthatitsfunctionmay
besuccessfullyrestoredifadequateinputsignalsareprovided. Ontheotherhand,the
26
retina undergoes considerable remodeling and rewiring (Marc 2003) after it loses the
glutamatergicdrivefromphotoreceptors. Considerableinvestigationisstillneededto
understand the implications of this rewiring on the ecacy of artificial stimulus from
electronic retinal prostheses. The findings from the fMRI studies with retinal lesions
mentioned above support the notion that the visual cortex does not undergo large-
scale remapping and that the visual system that matured before vision loss is largely
intact. Theresultsfromperceptualtrainingofadultpatientssu↵eringfromamblyopia
discussedearlierprovidehopethatthevisualcortexiscapableofbeingtrainedevenin
adulthood. It may be reasonable to expect that a combination of perceptual training
and artificial input from retinal prostheses to activate the dormant visual pathway
will provide a measure of visual function rehabilitation for adult-onset blindness due
to AMD and RP, with an emphasis on training after therapeutic intervention.
1.7 Thesis Overview
One of the overarching research goals in our laboratory has been the study of scien-
tific principles underlying the therapy of electronic retinal prostheses. Studies using
rat and mouse models of retinal degeneration have been performed with in vitro and
in vivo experimental preparations. These experiments have been instrumental in
documenting structural, morphological, and functional changes in the retina due to
photoreceptorcelldeath(Ray2011, Chan2011, Cho2013). Otherstudieshaveinves-
tigatedthee↵ectofstimulusparametersontheselectivity(Weitz2013)andeciency
(Davuluri 2014) of electrically stimulating the retina. All of the experiments in these
animal models of outer retinal degeneration have focused the study on either the
retina or the superior colliculus. As a significant number of retinal cell ganglion ax-
ons synapse in the superior colliculus (SC), electrophysiology and anatomical studies
performed in the SC have been used as a marker for retinal output. Since functional
27
vision is mediated by activity in the visual cortex and the lateral geniculate nucleus
(equivalentfunctioninthalamusinhumans)inrats,Iperformedthebulkofmythesis
work studying responses in the visual cortex elicited by electrical stimulation of the
retina. The human (and rat) visual cortex has an orderly arrangement of visual field
processing, termed retinotopy. This retinotopic organization represents specificity in
the spatial organization of connections in the various layers of the visual system with
respect to the visual field, and is an important element of functional vision. This
thesis presents the first work in the study of visual cortex retinotopy in response to
electrical stimulation of the retina. The rest of the chapters are organized as follows:
In chapter 2, I present in vivo experimental results using SC electrophysiology
in comparing voltage-, current-, and charge-controlled stimulation pulses? eciency
for retinal stimulation. This work allowed me to learn surgical and electrophysiology
techniques that I used for the visual cortex studies. Chapter 3 presents in vivo
experimental results of visual cortex retinotopic mapping using electrophysiology in
normally sighted and blind rats. Chapter 4 presents anatomical comparison of visual
cortex neurons in normally sighted versus blind rats with outer retinal degeneration
usingGolgistaining. Asummaryofthethesisandfutureworkispresentedinchapter
5.
28
Chapter 2
Evaluation of Current, Voltage,
and Charge Controlled Pulses for
Retinal Prostheses
2.1 Background
Electronic stimulators in neural prostheses typically use either current- or voltage-
controlled rectangular pulses for stimulation. More recently, charge-controlled pulses
have also been used in investigational neural stimulation devices (Vidal 2010, Lee
2015). In-vivo and computational studies have shown that stimulus parameters such
as pulse width and waveform shape have an e↵ect on the neural response amplitude
and power eciency (Jezernik 2005, Jezernik 2010, Klafter 1976, Kajimoto 2002,
O↵ner 1946, Fishler 2000, Foutz 2010, Wongsarnpigoon 2010a, Sahin 2007).
Arecentreportofaretinalprosthesisclinicaltrialsuggestsaneedtoimprove
stimulationeciency. Across30patientswithretinalimplants,only55%ofelectrodes
could evoke visual percepts using stimulus below 1 mC/cm2, the charge density limit
for the electrode material platinum gray (Humayun 2012, Sanders 2007). To increase
29
the number of functional electrodes, more ecient methods of stimulation must be
developed, so that visual percepts can be generated within charge density limits.
Stimulation eciency has been studied by manipulation of the waveform used
for stimulation. In this chapter, I present our work in comparing voltage-, current-,
and charge-controlled stimulation pulses’ eciency for retinal stimulation. Eciency
is evaluated in two ways: by measuring the strength of the evoked response in the
superiorcolliculus(SC),andbymeasuringthepowerconsumedattheelectrode-retina
interface. Figure 2.1 shows an illustration of the di↵erences in current-controlled and
voltage-controlled stimulus pulses, the two main stimulus waveforms in commercial
neurostimulation devices.
Figure 2.1: Comparison of stimulus waveforms
Voltage-controlled stimulation waveform (bottom left) and the corresponding
current through the electrode-tissue interface (bottom right). Current-controlled
stimulation stimulation waveforms (top left) and the corresponding voltage at the
electrode-tissue interface (top right). The resistor and capacitor network shown in
the middle is a good electrode model for the electrode-tissue interface. From
(Davuluri 2013)
Charge-controlledstimuluspulseshavebeenusedinsomeresearchstudies. Figure
2.2 shows an illustration comparing the current through the electrode-tissue interface
for charge-controlled stimulus pulses versus current-controlled stimulus pulses.
30
Figure 2.2: Charge-controlled stimulus waveforms
Charge-controlled stimulus waveforms use switched capacitor circuit to deliver a set
amount of charge to the electrode-tissue interface, and the corresponding current
through the electrode-tissue interface shows a decaying exponential. From (Lee
2015)
The first part of this chapter is work I jointly did with a colleague in the labo-
ratory. Dr. Navya Davuluri was the primary surgeon and experimentalist for this
work, and I assisted in electrode placement and data collection in all the experi-
ments. Additionally, I collaborated on data analysis and manuscript preparation
for publication. We compared the e↵ect of voltage-controlled and current-controlled
pulsesonthestrengthofneuralresponseinnormallysightedandretinaldegeneration
rats. Wemeasuredneuralresponsestrengthbyrecordingelectricallyevokedresponses
(EERs) of Superior Colliculus (SC) neurons in response to retinal stimulation. We
also compared two electrode materials: standard platinum-iridium and high-surface
area platinum-iridium (Petrossians 2011). Additionally, we measured the power con-
sumed at the electrode-tissue interface for voltage-controlled and current-controlled
stimulation pulses using both types of electrodes.
The second part of this chapter investigated the use of a novel charge-controlled
stimulator, Qstim, from Virginia Technologies for use in retinal prostheses.
31
2.2 Methods
2.2.1 Animals
We used normal Long Evans [postnatal day P90-P120, n = 15] and heterozygous
S334ter line 3 [P660-P680, n = 4] rats. The heterozygous S334ter line 3 rats, referred
hereafter as RD (retinal degeneration) rats, have a mutation in the rhodopsin gene.
RD rats were bred in the Doheny Vision Research Center vivarium facility by mating
homozygous S334ter line 3 rats with Copenhagen rats (Charles River, Hollister, CA).
We used homozygous S334ter line 3 breeding pairs supplied by Dr. Matthew LaVail
of the University of California San Francisco. Since the mutation is dominant, all o↵-
springhadonecopyofthemutatedgene. Allexperimentalprocedureswereapproved
by the Institutional Animal Care and Use Committee (IACUC) at the University of
Southern California.
2.2.2 Stimulation Electrodes and Experimental Groups
The stimulation electrode was a flat tipped concentric bipolar platinum-iridium elec-
trode (model CBDFG74, FHC, Bowdoin, ME). The inner pole diameter was 75 µm
and the outer pole diameter was 300 µm. The inner pole of the electrode was used
for stimulation and a large surface area platinum needle inserted in the skin adja-
cent to the nose was used as the return electrode. A 1 ml syringe was used to hold
the electrode. A single-axis linear translational micromanipulator (model NT33-475,
Edmund Optics, Barrington, NJ) on a magnetic based articulating arm was used for
handling the syringe mounted electrode.
There were 3 experimental groups. The first group used 10 normally sighted rats
with the commercial platinum-iridium electrode described above for retinal stimula-
tion, hereinreferredtoasthestandardplatinum-iridiumelectrode. Thesecondgroup
used5normallysightedratswithahighsurfaceareaplatinum-iridiumelectrode. The
32
third group used 4 RD rats with the standard platinum-iridium electrode.
2.2.3 Modifying the Surface of the Stimulation Electrode
High surface area platinum-iridium films were formed on the standard platinum-
iridium microelectrode using an electrodeposition method that was previously de-
scribed (Petrossians 2011). Electrochemical impedance spectroscopy (EIS) measure-
mentsofthestandardplatinum-iridiumandelectroplatedplatinum-iridiumelectrodes
were performed in phosphate bu↵ered saline (PBS) solution at room temperature at
the open-circuit potential (OCP) with a +/-10 mV amplitude AC signal in a fre-
quency range of 100 KHz to 0.1 Hz. The film deposition resulted in a significant
decrease in electrode impedance (Figure 2.3).
Figure 2.3: Bode plot of high surface area Pt/Ir electrode
Comparison of impedance spectroscopy data between standard Pt/Ir and high
surface area Pt/Ir electrode measured in PBS at the OCP with a +/- 10 mV
amplitude ac signal in a frequency range of 100 KHz to 0.1 Hz. Image courtesy of
Dr. Artin Petrossians.
33
2.2.4 Surgical Procedures
General anesthesia was used for all surgeries. A cocktail of ketamine (100 mg/kg;
Ketaset,FortDodgeAnimalHealth,FortDodge,IA)andxylazine(100mg/kg;X-Ject
SA,Butler,Dublin,OH)wasusedtoinduceanesthesia. Vaporizedsevoflurane(1%in
100% Oxygen) was used to maintain anesthesia throughout the entire experiment. A
self-regulated heating blanket (model 50-7053-F; Harvard Apparatus, Holliston, MA)
maintained the body temperature at 37 celsius. Animals were euthanized after each
experiment.
2.2.5 SC Exposure and Recording Electrode Positioning
In rats, a large number of axons of the retinal ganglion cells (RGCs) synapse onto
the superficial layers of the Superior Colliculus (SC) (O’Leary 1986, O’Leary 1992).
Thus, recording from the SC provides a convenient measure of retinal output. The
skull was exposed and a craniotomy ((caudal-medial corner: 4 mm caudal and 3
mm lateral to lambda) was performed using a hand-held drill on the right side. The
overlying cortex was aspirated until the SC surface was exposed. Electrically evoked
response (EER) in the SC elicited by retinal stimulation was recorded using epoxy-
coated tungsten microelectrodes (10 M⌦, FHC). A representative EER is shown in
Figure 2.4.
34
Figure 2.4: Representative trace of SC EER
ArepresentativetraceofevokedpotentialrecordedfromtheSCofanormalrat
when the retina is electrically stimulated (average of 25 evoked responses
2.2.6 Stimulation Electrode Insertion
The stimulation electrode was inserted into the rat eye using a surgical method re-
ported in previous work in our laboratory (Colodetti 2007). A few drops each of 1%
tropicamide (Tropicacyl, Akorn, Bu↵alo Grove, IL) and 2.5% phenylephrine (AK-
Dilate, Akorn) were used to dilate the left eye. A 25-guage needle was used for
ascleralincisionnearthelimbus. Thestimulationelectrodewasinsertedthrough
the incision site at a 45 angle with respect to the scleral surface to avoid damaging
the lens. The electrode was positioned in the ventral temporal quadrant without
contacting the retina. The proximity of the stimulation electrode to the retina was
monitored indirectly by measuring the electrochemical impedance with a commercial
potentiostat (Gamry Instruments, Warminster, PA). In all the experiments the elec-
trochemical impedance was maintained between 9.5 k⌦ - 10 k⌦ when measured at
100 kHz.
35
2.2.7 Electrical Stimulation of Retina
Charge-balanced, cathodic first, biphasic current and voltage-controlled pulses were
delivered to the epiretinal surface through the stimulation electrode. Stimulus pulses
were supra-threshold. The amplitude of the pulses was chosen such that the charge
in the cathodic phase was between 10 and 60 nC. Pulse widths of 0.3, 0.5, 1 and 2
ms were used. For each pulse width, voltage and current-controlled pulse trains with
fourdi↵erentchargelevelsweredelivered. Thus,32stimulusconditions(2stimulation
modes x 4 charge levels x 4 pulse widths) were applied to the retina per experiment.
Theinterphaseintervalwaskeptconstantat100 µs. 25pulsesweredeliveredforeach
pulsewidthandamplitudeineachstimulationmode. Theorderinwhichcurrentand
voltage-controlled pulses were delivered was randomized. The stimulus pulses were
generated by A-M systems stimulus isolator (model 2200) driven by a voltage pulse
from a programmable analog output card (DataWave Technologies, Berthoud, CO).
We recorded the voltage and current waveforms applied to the stimulation electrode
and used these waveforms in subsequent analysis. Voltage across the electrode was
recorded via di↵erential measurement with an oscilloscope. Current was recorded
via di↵erential measurement across a 20 k⌦ resistor in series with the stimulator.
A4channeloscilloscopewasusedtosimultaneouslyrecordthesedata(Tektronix
TDS5034B). A schematic of the experiment setup is shown in Figure 2.5.
36
Figure 2.5: SC electrophysiology experiment setup
AschematicoftheSCelectrophysiologyexperimentsetup
2.2.8 Data Acquisition and Analysis
For each retinal stimulation pulse, EERs were recorded in both voltage and current-
controlled stimulation modes. EERs were recorded from the most sensitive response
region within the SC, as described in previous work (Chan 2011). Briefly, the record-
ing electrode was moved in a grid pattern and area that responds most robustly is
deemedthemostsensitivearea. Thefollowinganalyseswereperformedwiththedata
acquired during the electrophysiology experiments:
• Measurement of Injected Charge and Quantification of EERs: Charge delivered
to the retina was calculated by integrating the leading (cathodic) phase of the
current waveform. 25 stimulus pulses were delivered and the resulting EERs
were recorded. An average EER for the 25 stimulus pulses was obtained and
the strength within the average response was calculated using equation 1,
SignalStrength =
N
X
i=0
X(T
i
)
2
(2.1)
whereT
i
definesthetimewindowwithinwhichthesignalstrengthiscalculated.
37
It was the first 50 ms after the stimulus pulse was delivered. X(T
i
)isthe
amplitude of the EER measured in µVandNisthenumberofsampleswithin
the first 50 ms. Stimulus artifact was excluded from this calculation.
• Signal Strength versus Injected Charge: Measured EER signal strength was
plotted against charge delivered and an equation for a line of best fit was
obtained using linear regression. One data set out of 10 experiments in the
first experimental group was a significant outlier and was not included for fur-
ther analysis (Grubb’s outlier test, p < 0.05). Signal strength versus injected
charge curves were obtained across all pulse widths in both voltage and current-
controlledstimulationmodes. StrengthinEERscouldnotbecompareddirectly
as the stimulator did not generate stimulus pulses with the same amount of
charge in both modes. The electrode-retina interface impedance varied slightly,
thus voltage stimulation did not produce the same current across experiments.
To allow a direct comparison, a best fit line was calculated for EER strength as
afunctionofcharge. Comparisonsbetweenthevoltageandcurrent-controlled
stimulus modes were made at 4 charge levels (20, 30, 40 and 50 nC) using the
best fit line. In order to determine if signal strength in both modes was statis-
tically di↵erent from each other for a given charge, paired t-test was used for
statistical analysis andp< 0.05 was considered significant.
• Power Consumption: The power consumed was calculated by integrating the
product of the measured voltage and current waveforms during the leading
(cathodic) phase of the pulse. As with the signal strength data, power con-
sumption measurements were also fit to an equation using linear regression. All
equationshadagoodcorrelationcoecient( R> 0.9)andwereincludedforfur-
ther analysis. The power consumed for pulses with 30, 40 and 50 nC of charge
was inter/extrapolated from the best fit equations. Statistical significance was
38
determined from the processed data. A paired t-test was used for statistical
analysis andp< 0.05 was considered significant.
2.3 Results: VoltagevsCurrentStimulationPulses
2.3.1 EER Strength Comparison
StrengthinEERsgeneratedbyvoltage-controlledpulsesandcurrent-controlledpulses
was used to determine stimulation eciency. In the following figures, signal strength
is plotted against charge, and error bars show standard errors of mean.
Comparison of Signal Strength in EERs Measured in Normally Sighted
Rats Stimulated with Standard Pt-Ir Stimulation Electrode
The strength of EERs generated by electrical stimulation of the retina with voltage-
controlled and current-controlled pulses in 10 normal rats is shown in Figure 2.6. For
0.3 ms pulse width, at every charge level current-controlled and voltage-controlled
pulsesgeneratedEERsthatwerenotsignificantlydi↵erent(pvaluerange: 0.15-0.19).
For 0.5 ms pulse width, voltage-controlled pulses generated EERs with significantly
higher strength than current-controlled pulses across all charge levels (p value range:
0.02-0.045). For 1 ms pulse width, at 3 charge levels (30nC, 40nC and 50nC) current-
controlled pulses generated EERs with significantly higher strength than voltage-
controlled pulses (p value range: 0.014-0.021). And for 2 ms pulse width, current-
controlled pulses generated EERs with significantly higher strength than voltage-
controlled pulses for all charge levels (p value range: 0.0004-0.0019).
39
Figure 2.6: EER versus charge for normal rats
Strength of EERs versus charge measured in 10 normal rats using a standard Pt-Ir
electrode to stimulate the retina with rectangular voltage-controlled and
current-controlled pulses. * indicates statistical significance
Comparison of Signal Strength in EERs Measured in Normally Sighted
Rats Stimulated with the High Surface Area Pt-Ir Stimulation Electrode
The strength in EERs with current-controlled and voltage-controlled retinal stimula-
tionpulseswiththehighsurfaceareaelectrodein5normalratsisshowninFigure2.7.
For0.3mspulsewidthand40nCchargedelivered, voltage-controlledpulsesgenerated
EERs with significantly higher strength than those generated by current-controlled
pulses (p value = 0.046). For 0.5 and 1 ms pulse widths, both current-controlled
and voltage-controlled pulses generated EERs that were not significantly di↵erent in
strength at every charge (p value range: 0.07-0.48). Data for 2 ms pulse width is not
shown since the range of charge applied in current controlled and voltage controlled
40
modes did not overlap, and thus a proper comparison between the two modes could
not be made.
Figure 2.7: EER versus charge using high surface area Pt/Ir electrode
Strength of EERs versus charge in 5 normal rats using a high surface area Pt-Ir
electrode to stimulate the retina with rectangular voltage-controlled and
current-controlled pulses. * indicates statistical significance
Comparison of Signal Strength in EERs Measured in RD Rats Stimulated
with Standard Pt-Ir Stimulation Electrode
The strength of EERs generated by electrical stimulation of the retina with voltage-
controlled and current-controlled pulses with the standard Pt-Ir electrode in 4 retinal
degeneration rats is shown in Figure 2.8. For 0.3 ms pulse width, at every charge
level both current-controlled and voltage-controlled pulses generated EERs that did
not di↵er significantly (p value range: 0.16-0.23). For 0.5 ms pulse width, voltage-
controlled pulses generated EERs with significantly higher strength than current-
41
controlled pulses at the lower charge levels (20 and 30nC, p value range: 0.03-0.047).
For 1 ms pulse width, at 3 charge levels (30, 40 and 50nC) current-controlled pulses
generated EERs with significantly higher strength than voltage-controlled pulses (p
value range: 0.008-0.009). And for 2 ms pulse width, current-controlled pulses gen-
erated EERs with significantly higher strength than voltage-controlled pulses at the
3higherchargelevels(30,40and50nC,pvaluerange:0.018-0.029).
Figure 2.8: EER versus charge in rd rats
Strength of EERs versus charge in 4 retinal degenerate (RD) rats. Rectangular
voltage-controlled and current-controlled pulses stimulated the degenerate retina
and EERs were recorded from SC. A standard Pt-Ir electrode was used for
stimulation. * indicates statistical significance.
42
2.3.2 Power Consumption Comparison
Power consumed at the electrode-retina interface was compared for current versus
voltage-controlled pulses, and for the standard Pt-Ir versus high surface area Pt-Ir
stimulation electrode.
Power Dissipation Comparison Between Standard and High Surface Area
Electrodes for Current-Controlled Stimulation
The power dissipated at the electrode-retina interface for the standard Pt-Ir and
high surface area Pt-Ir stimulation electrode for current-controlled pulses is shown
in Figure 2.9. The high surface area electrode consumed significantly less power to
generate current-controlled pulses for pulse widths of 0.3 ms, 0.5 ms and 2ms. (p
value range:0. 0006-0.04). For pulse width of 1ms, the high surface area electrode
generallyconsumedlesspower, buttheresultwasnotstatisticallysignificant(pvalue
range: 0.11-0.3).
43
Figure 2.9: Power versus charge for current-controlled pulses
Power dissipated at the electrode-retina interface for current-controlled pulses is
compared when a standard Pt-Ir electrode and a high surface area Pt-Ir electrode
are used for stimulation. Power dissipation data at the lowest charge could not be
compared. * indicates statistical significance.
Power Dissipation Comparison between Standard and High Surface Area
Electrodes for Voltage-Controlled Stimulation
The power dissipated at the electrode-retina interface for the standard Pt-Ir and
high surface area Pt-Ir stimulation electrode for voltage-controlled pulses is shown
in Figure 2.10. The high surface area electrode consumed significantly less power to
generatethevoltage-controlledpulsesacrossallpulsewidths(pvaluerange: 0.00001-
0.023) except two stimulus conditions. At pulse width of 0.3 ms with 40 nC charge
delivered and pulse width of 0.5 ms with 50 nC charge delivered, the high surface
area electrode consumed less power, but the result was not statistically significant (p
value range: 0.09-0.15).
44
Figure 2.10: Power versus charge for voltage-controlled pulses
Power dissipated at the electrode-retina interface for voltage-controlled pulses is
compared when a standard Pt-Ir electrode and a high surface area Pt-Ir electrode
are used for stimulation. Power dissipation data at the lowest charge could not be
compared. * indicates statistical significance.
There was no statistically significant di↵erence in the power consumed for voltage
versus current controlled stimulus pulses, with either the standard Pt-Ir electrode
(Figure 2.11 ) or the high surface area coated Pt-Ir electrode (Figure 2.12 ).
45
Figure 2.11: Power for voltage-controlled versus current-controlled pulses
Power dissipated at the electrode-retina interface for voltage-controlled pulses and
current-controlled pulses is compared when a standard Pt-Ir electrode is used for
stimulation. There is no statistically significant di↵erence.
46
Figure 2.12: Power for voltage-controlled versus current-controlled pulses with high
surface area electrode
Power dissipated at the electrode-retina interface for voltage-controlled pulses and
current-controlled pulses is compared when a high surface area Pt-Ir electrode is
used for stimulation. There is no statistically significant di↵erence.
2.3.3 Discussion
The key findings of this study are: 1) Stimulus waveform eciency depends on the
pulse width: voltage-controlled pulses generate stronger neural response when the
pulses have short duration and current-controlled pulses generate stronger neural
response when the pulses have long duration. 2) High surface area Pt-Ir electrode
reduces power consumption significantly in both stimulation modes.
Ingeneral, ourresultsareconsistentwithotherstudiesthatexaminedpulsewidth
and stimulus mode. Wongarnpigoon et al., reported that the stimulation eciency
47
of a given waveform depends on the pulse width and that no given waveform is the
most ecient across all pulse widths (Wongarnpigoon 2010b). Goo et al., compared
the threshold charge density (voltage vs. current pulses) for stimulating RGCs and
found that the threshold charge density was lower when voltage-controlled pulses
were used for stimulation (Goo 2011). The pulse width in their study was fixed at
0.5 ms, which is the same pulse width that favored voltage pulses in our study. The
voltage step led to high current initially, as the capacitive double layers behaved as
a short circuit. As the double layer charges, current flow decreases since impedance
increases and voltage is constant. Decreasing current amplitude at the end of the
voltage pulse contributes minimally if at all to the EER. Stimulation with 0.3 ms
duration pulses showed no di↵erence between EER strength between the two modes.
Examination of the current waveform from a 0.3 ms voltage pulse shows that the
current, while not uniform, is still in the decay phase and approximates a rectangular
current pulse. Thus, both the current pulse and voltage pulse yield a similar current
waveform through the electrode.
We found that when the high surface area Pt-Ir electrode is used for stimulation,
lesspowerisrequiredtogeneratethestimuluspulsesofagivenchargewhencompared
to the standard Pt-Ir electrode. Comparison of bode plots for the two electrodes
(Figure 2.3) demonstrates reduced impedance for the high surface area electrode
resulting in lower power consumption.
TheRDratsshowedasimilarrelationshipbetweenEERresponseandpulsewidth
as seen in the normal rats for current versus voltage stimulus pulses. However, the
RD rats showed lower EER strengths than normal rats at all charge levels and pulse
widths. This could be attributed to the lower number of retinal ganglion cells in
degenerate retina (20), but further studies are needed.
In summary, we demonstrated that pulse width determines whether voltage or
currentstimulationismoreecientforactivatingtheretina. Thesedi↵erencesarere-
48
latedtothecurrentwaveformthatisgeneratedduringthesetwomodesandhowthat
current influences the biophysical response properties. We also o↵ered an e↵ective
strategy toreduce power consumption by usinga high surface area Pt-Ir electrode for
retinal stimulation. Choice of stimulation mode for future devices must also consider
electronic design considerations. Current stimulators can deliver a specified amount
of charge (the product of current and duration), which is important for safety. A
voltage stimulator has the advantage of having a known compliance voltage and may
be a simpler circuit to implement.
2.4 Qstim
Our laboratory collaborated with Virginia Technologies, Inc. to investigate the use of
anovelstimulator. TheQstimstimulatorwasdesignedtodelivercharge-controlled
pulses in addition to voltage-controlled and current-controlled pulses. I investigated
the use of the Qstim device in rat SC electrophysiology experiments. The methods
used are as described in the previous sections of this chapter.
2.4.1 EER Strength Measurement with Qstim
A concentric bipolar Pt/Ir stimulating electrode was placed in the left eye of the rat,
with the tip in close proximity to the retina. The stimulating electrode was used in
a monopolar configuration. A stainless steel needle electrode placed in the nose of
the rat acted as the return electrode. The stimulating and return electrodes were
connected to the Datawave stimulator through an interface board. In addition to DC
blocking capacitors in the stimulus and return paths, the interface board has a 10 k⌦ seriesresistanceinthecurrentpathtobeabletocapturecurrentwaveformsdelivered
to the retina using an oscilliscope. The right superior colliculus (SC) was exposed
and a Tungsten recording electrode was inserted in the SC. The Datawave stimulator
49
was turned on to deliver a 100 µAamplitudeand500 µswidebiphasicpulsesandthe
recording electrode was moved to a location where an evoked potential was elicited.
The stimulating and return electrodes were then switched to the Qstim stimulator.
Figures 2.14 and 2.13 show the electrically evoked response (EER) recorded in
the SC when a 100 µAstimuluspulsewasappliedtotheretinawiththeQstimand
Datawave stimulators, respectively. In the case of the Qstim stimulator, there is a
much larger stimulus artifact that seems to saturate the recording amplifier for a
longer time than with the Datawave stimulator. This swallows a significant portion
of the initial evoked response signal, making good SC evoked potential recordings
dicult with the Qstim system.
Figure 2.13: SC EER with Datawave stimulator
Electrically Evoked Response (EER) recorded in the SC when a 100 µAstimulus
pulse was applied with the Datawave stimulator to the rat retina. The data
acquisition port connected to the recording amplifier was set to a gain of 8.
50
Figure 2.14: SC EER with Qstim stimulator
Electrically Evoked Response (EER) recorded in the SC when a 100 µAstimulus
pulse was applied with the Qstim stimulator to the rat retina. The data acquisition
port connected to the recording amplifier was set to a gain of 8.
To investigate the recording signal saturation with the Qstim stimulator further,
di↵erent stimulus amplitudes and data acquisition voltage range settings were varied.
The Data acquisition system we used with the recording amplifier had multiple gain
settings that traded o↵ resolution with the maximum input voltage range.
51
Figure 2.15: SC EER with Qstim; DAQ gain 8x
Electrically Evoked Response (EER) recorded in the SC when a 200 µAstimulus
pulse was applied with the Qstim stimulator to the rat retina. The data acquisition
port connected to the recording amplifier was set to a gain of 8.
Figure 2.16: SC EER with Qstim; DAQ gain 4x
Electrically Evoked Response (EER) recorded in the SC when a 200 µAstimulus
pulse was applied with the Qstim stimulator to the rat retina. The data acquisition
port connected to the recording amplifier was set to a gain of 4.
52
Figure 2.17: SC EER with Qstim; DAQ gain 2x
Electrically Evoked Response (EER) recorded in the SC when a 200 µAstimulus
pulse was applied with the Qstim stimulator to the rat retina. The data acquisition
port connected to the recording amplifier was set to a gain of 2.
Figure 2.18: SC EER with Qstim; DAQ gain 1x
Electrically Evoked Response (EER) recorded in the SC when a 200 µAstimulus
pulse was applied with the Qstim stimulator to the rat retina. The data acquisition
port connected to the recording amplifier was set to a gain of 1.
53
Figure2.15showstherecordingsignalwiththeQstimstimulatorforadataacqui-
sition gain setting of 8 with a recording voltage range +/- 1.25 V. Figure 2.16 shows
the recording signal with the Qstim stimulator for a data acquisition gain setting of 4
with a recording voltage range +/- 2.5 V. Figure 2.17 shows the recording signal with
the Qstim stimulator for a data acquisition gain setting of 2 with a recording voltage
range +/- 5 V. Figure 2.18 shows the recording signal with the Qstim stimulator for
a data acquisition gain setting of 1 with a recording voltage range +/- 10 V. As these
waveforms show, changing the gain setting of the data acquisition system connected
to the recording amplifier does not change the large stimulus artifact from the Qstim
stimulator. This prevented me from making a meaningful comparison of evoked po-
tential between a current controlled stimulus and a charge controlled stimulus. After
three iterations of working with Virginia Technologies in mitigating the stimulator
induced noise in the electrophysiology recordings, we shelved the project.
2.4.2 Power Consumption with Qstim
Imeasuredthepowerconsumedattheelectrode-retinainterfaceforcharge-controlled
and current-controlled pulses delivered by the Qstim stimulator in three normal Long
Evans rats. Figure 2.19 shows the power consumed at the electrode-retina interface
for di↵erent amounts of charge delivered to the retina using charge-controlled pulses.
Figure 2.20 shows the power consumed at the electrode-retina interface for di↵erent
amounts of charge delivered to the retina using current-controlled pulses. Figure 2.21
shows the power consumed at the electrode-retina interface for di↵erent amounts of
charge delivered to the retina using charge-controlled pulses versus controlled-pulses
onanoverlaidplot. Itcanbeseenthatthereisnoappreciabledi↵erenceinthepower
consumed at the electrode-retina interface for the two modes of stimulation.
54
Figure 2.19: Power versus charge for Qstim charge-controlled pulses
Power consumed at the electrode-retina interface versus the charge delivered to the
retina with the Qstim stimulator for charge-controlled pulses.
Figure 2.20: Power versus charge for Qstim current-controlled pulses
Power consumed at the electrode-retina interface versus the charge delivered to the
retina with the Qstim stimulator for current-controlled pulses.
55
Figure 2.21: Power versus charge for Qstim stimulator
Power consumed at the electrode-retina interface versus the charge delivered to the
retina with the Qstim stimulator.
2.4.3 Discussion
While I could not complete my experiments with the Qstim stimulator due to engi-
neeringdiculties,thelimitedresultsareconsistentwiththerecentpublishedstudies
using charge-controlled stimulus pulses for neural stimulation. Lee et al., performed
in vivo experiments with anesthetized cats and compared the performance of charge-
controlledpulses(whichtheycallSwitchCapacitorStimulation, SCS)versusvoltage-
controlled pulses. They implanted an electrode in the posterior limb of the internal
capsule, and measured the electromyelogram (EMG) activity in the contralateral up-
per arm muscles (Lee 2014, Lee 2015). They found that for the same amount of
energy delivered to brain tissue using the two stimulation modes, the strength of the
56
evoked EMG activity was the same. Their work does not compare the performance
of current-controlled pulses and there is room for original work in performing a more
comprehensive comparison of charge-controlled pulses for retinal stimulation.
I have shown that there is no significant di↵erence in the power consumed at
the electrode-retina interface for charge-controlled pulses versus current-controlled
pulses. Based on the results from (Lee 2014, Lee 2015), it is possible that both
charge-controlled and current-controlled pulses may evoke similar responses when
they are used to stimulate the retina with the same amount of charge. It appears
that the main advantage of a charge-controlled pulse stimulator would be in reducing
the system power consumed by the stimulator that is not delivered to tissue, and
improve the overall eciency of a battery powered stimulator.
57
Chapter 3
Cortical Responses to Electrical
Stimulation of Rat Retina
There has been limited previous research in characterizing in vivo visual cortex elec-
trophysiology response elicited by electrical stimulation of retina epiretinally. Pub-
lished results have been limited to experiments performed on three anesthetized cats
thatprimarilyinvestigatedsafetyandsurgicaltechniqueofstimulatingelectrodearray
implantation (Hesse 2000). A couple of studies have been published that compared
cortical responses elicited by photovoltaic subretinal prostheses to visual evoked po-
tentials (Mandel 2013, Lorach 2014) in normally sighted and blind rats.
I chose to conduct my work in rats due to the many available rat models of retinal
degenerationthatmimichuman outerretinaldegenerativediseases, andtotakebuild
upon prior work in our laboratory. Previous electrophysiology studies of electrical
stimulation of rat retina performed the recordings in the Superior Colliculus (Davu-
luri 2016). While such recordings provide a convenient measure of retinal output, I
chose to perform visual cortex electrophysiology recordings as they may be a better
benchmark to evaluate ecacy of retinal prostheses in providing functional vision.
In addition, the visual cortex is a more suitable area to focus on for studying neural
58
plasticity in response to the artificial stimulus of retinal prostheses.
Ratmodelsofretinaldegenerationhavegreatlyimprovedtheunderstandingofthe
pathophysiologyofphotoreceptordegenerativediseases(Chader2002). Ratshavealso
beenusedtocharacterizeretinotopicmapsofthevisualcortexactivityinresponseto
lightstimulus(Gias2005). Inthischapter,Icharacterizeelectrophysiologicalresponse
in the visual cortex of normal Long Evans rats and retinal degenerate S334ter line 3
rats elicited by electrical stimulation of the retina. Electrophysiology recording using
microelectrodesinthevisualcortexprovidesafunctionalreadoutinthevisualsystem
of the e↵ect of electrically stimulating the retina. This will provide baseline data to
compare cortical responses in chronic stimulation of the retina.
3.1 Methods
3.1.1 Animals
Normal Long Evans [postnatal day P90-P120, n = 9] rats and S334ter line3 rats with
retinaldegeneration[postnataldayP120-P300,n=11]wereusedforcorticalresponse
mappingofelectricalstimulationofretinainfourquadrantsoftheretina. Theretinal
degenerate rats were bred in the USC animal care facilities by mating homozygous
S334ter line 3 rats with Long Evans rats (Envigo, Hayward, CA). The homozygous
S334ter line 3 breeding pairs were obtained from the Rat Resource Research Center
of the University of Missouri. Since the mutation is dominant, all o↵spring had one
copy of the mutated gene, and all experiments were conducted on these o↵spring.
The rats were housed in covered cages and fed a standard rodent diet and water
ad libitum while kept on a 12:12-hour light-dark cycle in the animal facility. All
experimental procedures were approved by the Institutional Animal Care and Use
Committee (IACUC) at the University of Southern California.
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3.1.2 Surgical Procedures
All surgeries were performed under general anesthesia. An intramuscular injection
of a cocktail of ketamine (100 mg/kg; Ketaset, Fort Dodge Animal Health, Fort
Dodge, IA) and xylazine (100mg/kg; X-Ject SA, Butler, Dublin, OH) was used to in-
duce anesthesia. Sevoflurane (0.5-1% in 100% Oxygen) administered through a mask
attachedtothestereotaxicbenchwasusedtomaintainanesthesiathroughouttheen-
tire experiment. The rat’s vital signs were monitored and the body temperature was
maintained at 37
o
C with a self-regulated heating blanket (model 50-7053-F; Harvard
Apparatus, Holliston, MA). Animals were euthanized after the experiment using an
overdose of pentobarbital (0.5 ml; Euthasol, Virbac US, Fortworth, TX) intracardiac
injection.
3.1.3 Craniotomy and Recording Electrodes
The anesthetized rat was axed to a stereotaxic bench using ear bars (Model 900,
DavidKopfInstruments, Tujunga, CA).Theskullwasexposedandacraniotomywas
performed on the right side ((caudal-medial corner: 5 mm caudal and 5 mm lateral
to lambda) using a hand-held drill. A three electrode (recording, reference, ground)
recording system was used to capture electrophysiological signals in the visual cortex
elicitedbyelectricalstimulationoftheretina. Epoxy-coatedtungstenmicroelectrodes
(10 M⌦ impedance, FHC, Bowdoin. ME) were used for electrophysiology recording
from the visual cortex. The recording electrode was axed to an electrode holder
with a digital readout of its three dimensional position in space that was attached to
thestereotaxicbench. Theratskulllandmarklambdawheretheposteriorsuturelines
meet was used as the origin for recording electrode positioning. The visual cortex
in rat brains generally spans a depth of 1.5 mm from the cortical surface (Paxinos
2013), and the recording electrode was positioned midway within the visual cortex at
adepthof700-750 µmfromthecorticalsurface. Thereferenceelectrodewasplaced
60
in the anterior cortex at a similar depth, and the ground electrode was connected to
a bone screw implanted into the left side of the skull.
3.1.4 Stimulation Electrodes
A flat-tipped concentric bipolar Pt-Ir electrode (model CBDFG74, FHC, Bowdoin,
ME) was used to electrically stimulate the rat retina. The inner pole diameter was
75 µmandtheouterpolediameterwas300 µm. For all the experiments with rd
rats, the stimulation electrode tip was coated to e↵ectively have a high surface area
of charge injection, allowing the electrode to safely deliver higher levels of stimulus to
the retina. High surface area Platinum-Iridium thin film coating was formed on the
standard platinum-iridium microelectrode using electrodepostion methods developed
in our laboratory (Petrossians 2011). Briefly, electrodeposition was performed in a
custom electrochemical cell using a three-electrode setup (working, reference, ground
electrodes) and a potentiostat (Reference 600/1000, Gamry Instruments, Warmin-
ster, PA) to drive the electrodeposition. A potential sweep technique in the potential
range of E = +0.2V to -0.2V versus Ag/AgCl at scan rate of 0.2 mV/s was used
for electrodeposition of 60:40 percent Pt-Ir film on the tip of the commercially pur-
chased stimulation electrode. The plating solution was agitated using an ultrasonic
homogenizer (Misonix, Inc. Newtown, CT, USA) at a frequency of 20kHz to main-
tain constant mass transfer during electrodeposition. The electrode was used in a
monopolar configuration with either the inner pole or outer pole used for stimulating
the retina. The return electrode was a large surface area platinum needle inserted
in the skin adjacent to the nose. To insert the stimulation electrode, the left eye
of the rat was first dilated with a few drops each of 1% tropicamide (Tropicacyl,
Akorn, Bu↵alo Grove, IL) and 2.5% phenylephrine (AK-Dilate, Akorn). A small
piece of a latex surgical glove was used to proptose the eye. A glass coverslip covered
with an ophthalmic demulcent gel (Goniosol, Gonak) pressed to the cornea allowed
61
focused viewing of the fundus through an operating microscope. The stimulation
electrode was inserted through a scleral incision near the limbus. The distance of the
stimulation electrodefrom theretinawasmonitored indirectly by measuring theelec-
trochemical impedance with a potentiostat (Gamry Instruments, Warminster, PA),
and an increase in impedance indicated that the electrode was 50-100 µmfromthe
epiretinal surface.
3.1.5 Electrical Stimulation of the Retina
Charge balanced biphasic stimulus current pulses of amplitude ranging from 30 to
1000 µAand0.5mspulsewidthweredeliveredtotheretinaattherateof1Hz.
The cathodic first biphasic pulses had an interphase interval between the cathodic
and anodic phases of 100 µs. 50 pulses were delivered for each amplitude for each
corticalrecordinglocation. Thestimuluspulsesweregeneratedbyacurrenttovoltage
converter (model 2200, A-M Systems, Sequim, WA), driven by a voltage pulse from
aprogrammableanalogoutputcard(DataWaveTechnologies,Berthoud,CO)ona
personal computer running Datawave’s software.
3.1.6 Data Acquisition
Electrically evoked responses (EERs) in the primary visual cortex elicited by elec-
trical stimulation of the retina were acquired using recording microelectrodes. The
recording electrode was moved in a grid pattern with a pitch of 250 µm, generally
starting in the middle of the visual cortex or in the middle of the expected cortical
area of response for light stimulus (Gias 2005). Not all grid points could be recorded
since blood vessels on the cortical surface interfered. The EER was amplified with a
gain of 2000 and band-pass filtered with a pass frequency of 150 Hz to 8 kHz. Since
thetimescaleoftheactionpotentialsandthelocalfieldpotentialsinthevisualcortex
have a time scale in the hundreds of microseconds to a few millisecond range, this
62
band pass filters rejects higher frequency noise as well as low frequency noise primar-
ily from the power supply. The amplified EER is captured by acquisition software
withasamplingrateof20kHz, whichisaboutanorderofmagnitudehigherthanthe
highest frequency component of the EER signal. Figure 3.1 illustrates an overview of
the experimental setup and representative visual cortex EER traces.
Figure 3.1: Visual cortex electrophysiology experiment setup
A schematic of the experimental setup, shown with representative traces of the
electrically evoked response recorded from the visual cortex in response to electrical
stimulation of the retina.
63
3.1.7 Data Analysis
For each stimulus condition, the EER was averaged over 50 stimulus pulses and
digital filtering was applied to remove high frequency and 60 Hz noise before further
analysis. EERs were recorded at multiple sites in the visual cortex of each rat. The
digitalbandstopfilterwitha60HzcenterfrequencywasimplementedinMatlabusing
a least squares FIR (finite impulse response) filter with a 20 kHz sampling frequency
and a minimum order to generate a bandstop range of +/ 2 Hz from the center
frequency. The root mean square (rms) value of the EER after the stimulus pulse
over 40 ms (signal) was compared with the rms value of baseline noise before stimulus
to calculate signal to noise ratios (SNR) for each stimulus condition. The strength of
theaverageEERforeachstimulusconditionwascalculatedbycomputingtheintegral
of the mean square of the evoked potential over the first 40 ms after the stimulus.
Stimulusartifactwasnotincludedinthiscalculation. Forstimuluscurrentamplitudes
below 250 µA, the cortical recording returned to baseline within 2 ms of the end of
stimulus pulse, and the evoked response strength was calculated starting 3 ms after
delivery of the stimulus pulse. For large stimulus current amplitudes needed for the
blind rats, the stimulus artifact extended up to 5 ms after the end of the stimulus
pulse. In such cases, the strength of the stimulus artifact from the cortical location
withthelowestSNRwassubtractedfromtheevokedresponsestrengthmeasurement.
Idefined EERsto bedetectableat a given cortical location iftheSNR isgreater than
10 dB for suprathreshold stimulation of the retina. In previous published studies
of superior colliculus electrophysiology in response to electrical stimulation of the
retina(Chan2011),detectableresponsewasdefinedasneuralactivitycorrelatedwith
stimulus that exceeded 5 times the baseline noise level, which translates to around
14 dB in SNR. But, visual inspection of the raw data of responses of a wide sample
of cortical locations showed consistent responses at an SNR of 10 dB.
64
3.2 Results
3.2.1 Cortical Activity Maps for Normal Rats
Cortical activity maps for nine normal Long Evans rats were obtained. The location
of detectable EERs measured in the visual cortex corresponded to the retinotopic
location described in previous studies with light stimulation (Gias 2005).
Cortical Activity Maps for Ventral Temporal Retinal Stimulation
In four rats where the stimulation electrode was placed in the ventral temporal quad-
rant of the retina, detectable EERs (defined as greater than 10 dB SNR with 100 µA
to 250 µAcurrentamplitudeand500 µswidestimuluspulses)wererecorded3.25to
4 mm lateral to lambda and 0.75 mm anterior to 0.5 mm posterior to lambda. The
electrophysiology cortical activity maps for the four normal rats with ventral tempo-
ral retina stimulation are shown in Figures 3.2, 3.3, 3.4, and 3.5. Light stimulus of
ventral temporal retina (dorsal nasal visual field) has been shown to evoke cortical
activity in the region 3 to 5 mm lateral to lambda and 2 mm anterior to 0.5 mm
posterior to lambda (Gias 2005).
65
Figure 3.2: V1 EER map for normal rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in normal rat 1 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
66
Figure 3.3: V1 EER map for normal rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in normal rat 2 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
67
Figure 3.4: V1 EER map for normal rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in normal rat 3 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
68
Figure 3.5: V1 EER map for normal rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in normal rat 4 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Ventral Nasal Retinal Stimulation
Inthreeratswherethestimulationelectrodewasplacedintheventralnasalquadrant
oftheretina,detectableEERsweremeasured1.5to3.2mmlateraltolambdaand0.5
mm anterior to 0.5 mm posterior to lambda. The electrophysiology cortical activity
maps for the three normal rats with ventral nasal retina stimulation are shown in
Figures 3.6, 3.7, and 3.8. Light stimulus of ventral nasal retina (dorsal temporal
visual field) has been shown to evoke cortical activity in the region 2 to 3.5 mm
lateral to lambda and 1 mm anterior to 1.5 mm posterior to lambda (Gias 2005).
69
Figure 3.6: V1 EER map for normal rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in normal rat 5 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
70
Figure 3.7: V1 EER map for normal rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in normal rat 6 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
71
Figure 3.8: V1 EER map for normal rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in normal rat 7 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Dorsal Nasal Retinal Stimulation
In one rat where the stimulation electrode was placed in the dorsal nasal quadrant of
the retina, detectable EERs were measured 1.75 to 2.25 mm lateral to lambda and 0
mm to 0.75 mm anterior to lambda. Inserting the stimulation electrode in the dorsal
half of the retina is challenging. The retina is very sensitive to mechanical pressure
and the incision for the electrode insertion followed by the placement of the electrode
frequently caused retinal detachment in the dorsal retina, limiting the number of
cortical maps I could obtain for dorsal retinal stimulation. The electrophysiology
cortical activity map for the normal rat with dorsal nasal retina stimulation is shown
in Figure 3.9. Light stimulus of dorsal nasal retina (ventral temporal visual field) has
72
been shown to evoke cortical activity in the region 1.25 to 2.5 mm lateral to lambda
and 1.25 mm anterior to 0.5 mm posterior to lambda (Gias 2005).
Figure 3.9: V1 EER map for normal rat dorsal nasal retina stimulation
Visual cortex electrically evoked response map in normal rat 8 with the stimulation
electrode placed in the dorsal nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Dorsal Temporal Retinal Stimulation
A partial activity map was also obtained in one normal rat (Figure 3.10) where
the stimulation electrode was placed in the dorsal temporal quadrant of the retina.
Detectable EERs were recorded 1.75 to 2 mm lateral to lambda and 1.5 to 2.5 mm
anterior to lambda. Light stimulus of dorsal temporal retina (ventral nasal visual
field) has been shown to evoke cortical activity in the region 1.5 to 4 mm lateral to
lambda and 1.5 to 3.5 mm anterior to lambda (Gias 2005).
73
Figure 3.10: V1 EER map for normal rat dorsal temporal retina stimulation
Visual cortex electrically evoked response map in normal rat 9 with the stimulation
electrode placed in the dorsal temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
3.2.2 Cortical Activity Maps for RD Rats
Cortical activity maps for eleven retinal degenerate (RD)S334terline3ratswere
obtained. All of the rd rats required higher amplitude stimulation of the retina to
show cortical activity, ranging from 400 µAto1000 µAofcurrentperpulse. Apulse
width of 500 µswasusedforthecathodicandanodicphasesofthebiphasicstimulus
pulse, with an interphase interval of 100 µs.
Cortical Activity Maps for Ventral Temporal Retinal Stimulation
The electrophysiology cortical activity maps for the three rd rats with ventral tem-
poral retina stimulation are shown in Figures 3.11, 3.12, and 3.13. Light stimulus
74
of ventral temporal retina (dorsal nasal visual field) has been shown to evoke cor-
tical activity in the region 3 to 5 mm lateral to lambda and 2 mm anterior to 0.5
mm posterior to lambda (Gias 2005). All three rd rats with ventral temporal retinal
stimulation show cortical activity outside the region of cortical activity seen for light
stimulus.
Figure 3.11: V1 EER map for rd rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in RD rat 1 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
75
Figure 3.12: V1 EER map for rd rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in RD rat 2 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
76
Figure 3.13: V1 EER map for rd rat ventral temporal retina stimulation
Visual cortex electrically evoked response map in RD rat 3 with the stimulation
electrode placed in the ventral temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Ventral Nasal Retinal Stimulation
The electrophysiology cortical activity maps for the three rd rats with ventral nasal
retinastimulationareshowninFigures3.14, 3.15, and3.16. Lightstimulusofventral
nasalretinahasbeenshowntoevokecorticalactivityintheregion2to3.5mmlateral
to lambda and 1 mm anterior to 1.5 mm posterior to lambda (Gias 2005). In general,
all three rats with ventral nasal retinal stimulation do show cortical activity in the
same cortical region as seen in light stimulus experiments. However, the borders of
activity do not seem as well defined as seen in normal rats.
77
Figure 3.14: V1 EER map for rd rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 4 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
78
Figure 3.15: V1 EER map for rd rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 5 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
79
Figure 3.16: V1 EER map for rd rat ventral nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 6 with the stimulation
electrode placed in the ventral nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Dorsal Nasal Retinal Stimulation
The electrophysiology cortical activity maps for the four rd rats with dorsal nasal
retina stimulation are shown in Figures 3.17, 3.18, 3.19, and 3.20. Light stimulus
of dorsal nasal retina has been shown to evoke cortical activity in the region 1.25
to 2.5 mm lateral to lambda and 1.25 mm anterior to 0.5 mm posterior to lambda
(Gias 2005). Three of the four rd rats with dorsal nasal retinal stimulation show
activity outside the region of cortical activity seen for light stimulus of dorsal nasal
retina. Additionally, in two rd rats, the boundaries of activity were less defined with
locations of response and no response intermingled with each other.
80
Figure 3.17: V1 EER map for rd rat dorsal nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 7 with the stimulation
electrode placed in the dorsal nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
81
Figure 3.18: V1 EER map for rd rat dorsal nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 8 with the stimulation
electrode placed in the dorsal nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
82
Figure 3.19: V1 EER map for rd rat dorsal nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 9 with the stimulation
electrode placed in the dorsal nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
83
Figure 3.20: V1 EER map for rd rat dorsal nasal retina stimulation
Visual cortex electrically evoked response map in RD rat 10 with the stimulation
electrode placed in the dorsal nasal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
Cortical Activity Maps for Dorsal Temporal Retinal Stimulation
Theelectrophysiologycorticalactivitymapforone rd ratwithdorsaltemporalretina
stimulationisshowninFigure3.21. Lightstimulusofdorsaltemporalretinahasbeen
shown to evoke cortical activity in the region 1.5 to 4 mm lateral to lambda and 1.5
to 3.5 mm anterior to lambda (Gias 2005). The rd rat with dorsal temporal retinal
stimulation shows cortical activity outside the region of cortical activity seen for light
stimulus of dorsal temporal retina.
84
Figure 3.21: V1 EER map for rd rat dorsal temporal retina stimulation
Visual cortex electrically evoked response map in RD rat 11 with the stimulation
electrode placed in the dorsal temporal quadrant of the retina, with co-ordinates
referenced to lambda as origin.
3.2.3 Cortical EER versus LER
In three rats, I measured light evoked responses at the same cortical locations where
I recorded electrically evoked responses. Figures 3.22 and 3.22 show representative
visual cortex recordings for light and electrical stimulation of normal rats. It can be
seen that the latency of the visual cortex response, defined as the time to maximum
local field potential negative deflection from stimulus onset, is between 9 to 14 ms
and 54 to 58 ms for electrical stimulus and light stimulus, respectively.
85
Figure 3.22: Light evoked and electrical evoked potentials in V1
Acomparisonoflightevokedandelectricallyevokedvisualcortexresponsesin
normal rat LErat4.
Figure 3.23: Light evoked and electrical evoked potentials in V1
Acomparisonoflightevokedandelectricallyevokedvisualcortexresponsesin
normal rat LErat5.
86
3.2.4 Cortical EER Strength vs Amplitude
The cortical responses to electrical stimulus of the retina in normal rats generally
show a dose response relationship in both normal and rd rats. Figures 3.24, 3.25,
3.26, and 3.27 are representative plots of visual cortex electrically evoked response at
onecorticallocationinanormalratforincreasingcurrentstimuluscurrentamplitudes
from 25 µAto100 µAappliedtotheretina.
Figure 3.24: V1 representative EER for 25 µAstimulus
A representative visual cortex electrically evoked response in a normal rat when 25
µA current stimulus pulses are applied to the retina.
87
Figure 3.25: V1 representative EER for 50 µAstimulus
A representative visual cortex electrically evoked response in a normal rat when 50
µA current stimulus pulses are applied to the retina.
Figure 3.26: V1 representative EER for 75 µAstimulus
A representative visual cortex electrically evoked response in a normal rat when 75
µA current stimulus pulses are applied to the retina.
88
Figure 3.27: V1 representative EER for 100 µAstimulus
Arepresentativevisualcortexelectricallyevokedresponseinanormalratwhen100
µA current stimulus pulses are applied to the retina.
Visual Cortex EER vs Stimulus Amplitude in Normal Rats
Figures 3.28 and 3.29 show the measured EER strength (n=14 cortical locations) in
normal Long Evans rats as the stimulus amplitude was varied from 30 to 100 µA. A
dose response relationship was observed in the cortical EER strength with respect to
stimulus current delivered to the retina. Some locations showed monotonic behavior
(n = 5; Figure 3.28) and some locations showed peak EER strength at intermediate
current (n = 9; Figure 3.29).
89
Figure 3.28: V1 EER SNR versus stimulus amplitude
Visual cortex EER signal to noise ratio at 6 locations in normal rats plotted against
the current amplitude delivered to the retina. The curves show monotonic increase
in signal strength with current amplitude.
90
Figure 3.29: V1 EER SNR versus stimulus amplitude
Visual cortex EER signal to noise ratio at 8 locations in normal rats plotted against
the current amplitude delivered to the retina. The curves show a non-monotonic
increase in signal strength with current amplitude, with the highest signal strength
at an intermediate stimulus amplitude.
Visual Cortex EER vs Stimulus Amplitude in rd Rats
Figures 3.30 and 3.31 show the measured EER strength (n=15 cortical locations) in
rd S334ter line 3 rats as the stimulus amplitude was varied from 100 to 1000 µA. A
dose response relationship was observed in the cortical EER strength with respect to
stimulus current delivered to the retina. Some locations showed monotonic behavior
(n = 4; Figure 3.30) and some locations showed peak EER strength at intermediate
current (n = 11; Figure 3.31).
91
Figure 3.30: V1 EER SNR versus stimulus amplitude for rd rats
Visual cortex EER signal to noise ratio at 4 locations in rd rats plotted against the
current amplitude delivered to the retina. The curves show monotonic increase in
signal strength with current amplitude.
92
Figure 3.31: V1 EER SNR versus stimulus amplitude for rd rats
Visual cortex EER signal to noise ratio at 10 locations in rd rats plotted against the
current amplitude delivered to the retina. The curves show a non-monotonic
increase in signal strength with current amplitude, with the highest signal strength
at an intermediate stimulus amplitude.
3.2.5 Spontaneous Activity in the Visual Cortex of rd rats
During the course of the experiments for retinotopic mapping of the visual cortex
in the rd rats, I discovered that the recordings in rd S334ter line 3 rats exhibited
significantly more spontaneous activity than the normally sighted Long Evans rats.
93
Figure 3.32 shows a representative image of visual cortex recordings without any
stimulus applied to the retina. On the left,
Figure 3.32: Visual cortex spontaneous activity
Representative visual cortex electrophysiology recordings with no retinal stimulus in
rd rats (left) compared to normal rats (right).
Visual cortex recordings without retinal stimulation were performed in n = 29
cortical locations in 7 normal Long Evans rats and in n = 78 cortical locations in 18
rd S334ter line 3 rats. The recordings spanned a time window of 0.5 s with 50 trials
at each cortical recording location. The dc o↵set in the recorded signal was removed
by subtracting the mean of the recorded signal over each 0.5 s time window. The
power at each cortical location was measured by rectifying and integrating the signal
over the 0.5 s time window and averaged over the 50 trials.
Figure 3.33 shows a bar graph comparing the mean power in the visual cortex
electrophysiology recordings with no retinal stimulus between normal and rd rats.
The error bars show standard deviation calculated from pooled variance across all
the cortical locations and trials. A student’s t-test shows that the power in the visual
94
cortex recording of rd rats is statistically significantly more than in normal rats with
p=0.0002.
The bar graph in Figure 3.33 may be a bit misleading when compared to the
representative traces showing spontaneous cortical activity in Figure 3.32. This is
because both of the bars include many experiments where the baseline noise in the
recording signal is much higher than shown in the representative traces.
Figure 3.33: Spontaneous activity power in normal versus rd rats
Comparison of the mean power in visual cortex electrophysiology recordings of 500
ms duration with no retinal stimulus in n = 29 cortical locations in 7 normal rats
versus n = 78 cortical locations in 18 rd rats. The error bars indicate standard
deviation and * shows statistical di↵erence with p = 0.0002.
Figures 3.34 and 3.35 show the distribution of the mean power measured in visual
cortex electrophysiology recordings for normal and rd rats, respectively when no
retinal stimulation was applied. The histograms show a shift to the right for the
rd rats in comparison with normal rats, indicating that there is more spontaneous
95
activity in the visual cortex of rd rats in comparison with normal rats.
Figure 3.34: V1 spontaneous activity power histogram for normal rats
Distribution of the mean power in visual cortex electrophysiology recordings with no
retinal stimulus at n = 29 cortical locations in 7 normal rats.
Figure 3.35: V1 spontaneous activity power histogram for rd rats
Distribution of the mean power in visual cortex electrophysiology recordings with no
retinal stimulus at n = 78 cortical locations in 18 rd rats.
96
3.3 Discussion
In this chapter, I presented results that showed systematic mapping of retinotopic
visual cortex activity in response to electrical stimulation of the rat retina.
The experiments with normal rats show that focal electrical stimulation of rat
retina elicits visual cortex activity in the same region where light stimulus generates
cortical activity, for all four quadrants of the retina where the stimulation electrode
was placed. A composite activity map of visual cortex responses elicited by electrical
stimulation of the normal rat retina in the four quadrants is shown in Figure 3.36.
The cortical locations mapped are color coded with the location of the stimulation
electrode: blue for ventral temporal retina, red for ventral nasal retina, orange for
dorsal nasal retina, and green for dorsal temporal retina. There is a good separation
in the regions of cortical activity for the di↵erent regions of retinal stimulation.
The thresholds for eliciting cortical activity in response to electrical stimulation
of the retina in normal rats ranged from 10 to 15 nC of charge per stimulus pulse for
0.5 ms wide pulses. This is generally in the same range as seen in previous studies
of superior colliculus electrophysiology (Chan 2011, Davuluri 2014). Additionally, a
dose response characteristic was seen in the strength of the cortical responses elicited
by increasing current amplitude of the retinal stimulation pulses. At some cortical lo-
cations, therewasamonotonicincreaseinstrengthoftheresponse, andsomecortical
locations showed maximal strength of response at intermediate current amplitudes.
This could be attributed to the specifics of the visual system microcircuit that the
stimulationelectrodea↵ected. Thismodulationofcorticalresponseisconsistentwith
the results from experiments with subretinal photovoltaic stimulation which showed
that increasing the stimulus intensity (of the near infrared light used to stimulate
the photovoltaic cells) increases cortical response (Mandel 2013, Lorach 2014, Lorach
2015).
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Figure 3.36: Composite V1 activity map for normal rats
AcompositemapofcorticalactivityinnineLongEvansratsinresponseto
electrical stimulation of the retina. The four colors represent the four quadrants of
the retina where the stimulation electrode was placed: blue for ventral temporal
retina, red for ventral nasal retina, orange for dorsal nasal retina, and green for
dorsal temporal retina.
The thresholds for eliciting cortical activity in response to electrical stimulation
of the retina in rd rats were significantly higher and ranged from 100 to 200 nC of
charge per stimulus pulse for 0.5 ms wide pulses. The use of high surface area Pt/Ir
thin film at the tip of the stimulation electrode was necessary to be able to deliver
such high charge densities.
The experiments with rd rats show that retinotopy is not preserved in the visual
cortex of the blind rats in response to electrical stimulation of the diseased retina. A
composite activity map of visual cortex responses elicited by electrical stimulation of
rd rat retina in the four quadrants is shown in Figure 3.37. The cortical locations
98
mappedarecolorcodedwiththelocationofthestimulationelectrode: blueforventral
temporal retina, red for ventral nasal retina, orange for dorsal nasal retina, and green
for dorsal temporal retina. It can be seen that there is a large overlap in the regions
of cortical activity for the di↵erent quadrants of retina that were stimulated.
Figure 3.37: Composite V1 activity map for rd rats
A composite map of cortical activity in eleven S334ter line 3 rats in response to
electrical stimulation of the retina. The four colors represent the four quadrants of
the retina where the stimulation electrode was placed: blue for ventral temporal
retina, red for ventral nasal retina, orange for dorsal nasal retina, and green for
dorsal temporal retina.
Figures 3.38 and 3.39 show the centroids of the cortical areas of response elicited
bystimulationinthefourquadrantsoftheretina,fornormalandrd rats,respectively.
Thecolorcodedmapsuseblueforventraltemporalretina,redforventralnasalretina,
orange for dorsal nasal retina, and green for dorsal temporal retina, It can be seen
that the centroids for the four retinal quadrants get closer for rd rats when compared
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to normal rats, and is due to a loss of retinotopy in the diseased rats.
Figure 3.38: Composite V1 activity map centroids for normal rats
The centroids of the four cortical areas where response is seen for the four quadrants
of retina stimulated in normal rats: blue for ventral temporal retina, red for ventral
nasal retina, orange for dorsal nasal retina, and green for dorsal temporal retina.
100
Figure 3.39: Composite V1 activity map centroids for rd rats
The centroids of the four cortical areas where response is seen for the four quadrants
of retina stimulated in rd rats: blue for ventral temporal retina, red for ventral nasal
retina, orange for dorsal nasal retina, and green for dorsal temporal retina.
Figures 3.40 and 3.41 show the centroid maps with the boundaries of cortical
response locations for the four quadrants of the retina stimulated for normal and
rd rats, respectively. The maps for the rd rats show a loss of retinotopy and more
overlap in the boundaries of the response areas. The use of higher stimulus currents
to stimulate the retina in rd rats, and the uneven sample size for the four quadrants
of retina stimulated may be a confounding factors in these results.
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Figure 3.40: Composite V1 activity map boundaries and centroids for normal rats
The centroids of the four cortical areas and the boundaries where response is seen
for the four quadrants of retina stimulated in normal rats: blue for ventral temporal
retina, red for ventral nasal retina, orange for dorsal nasal retina, and green for
dorsal temporal retina.
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Figure 3.41: Composite V1 activity map boundaries and centroids for rd rats
The centroids of the four cortical areas and the boundaries where response is seen
for the four quadrants of retina stimulated in rd rats: blue for ventral temporal
retina, red for ventral nasal retina, orange for dorsal nasal retina, and green for
dorsal temporal retina.
Thevisualcortexrecordingsof rd ratsalsoshowedsignificantlymorespontaneous
activity than normal rats when no retinal stimulation is applied. This is consistent
with recently reported in vitro experiments of patch clamp recordings from diseased
retina of rd10 mouse retinal ganglion cells that show periodic spontaneous activity
(Cho 2016). Another recently published study reported spontaneous neural activity
in the primary visual cortex of S334ter rd rats (Wang 2016).
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Chapter 4
Cortical Neuroanatomy of Sighted
versus Blind Rats
One of the universal themes in biology is the relation between the structure and
function at all levels of organization from cells to tissues to organ systems. Over the
lasttwocenturies, therehavebeensignificant research e↵ortsinneurosciencetowards
understanding the relationship between the structure (neuroanatomy) and function
(neurophysiology, neuropsychology and neurobehavior) of the nervous system.
In this chapter, I present the results of neuroanatomical comparison of visual
cortex neurons in normally sighted versus blind rats with outer retinal degeneration
using Golgi staining. The comparison was made in the same visual cortex layer and
locationsasintheelectrophysiologystudiespresentedinthepreviouschapter. Similar
to the baseline functional data provided by electrophysiology studies of visual cortex
function discussed previously, this study will provide baseline neuroanatomical data
to study neural plasticity in response to chronic electrical stimulation of the retina.
The Golgi staining technique, invented by Camillo Golgi in the second half of
the 19th century and improved by Ramon y Cajal through tireless experiments has
withstoodthetestoftimeinprovidingamethodtovisualizewholeneurons. Through
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intracellular staining with microcrystalline silver chromate, this technique allows the
visualizationofcompleteneuronsashighcontrastblackbodiesinbrainsections. The
highcontrastnatureofthestainingcombinedwiththesparselyselectivenatureofthe
cells that are stained has allowed a tremendous amount of discovery in neuroscience
(Koyama 2013, Zaqout 2016).
Dendriticspinedensityhasbeenusedasamarkerforsynapticstrengthandneural
plasticity in a wide range of studies. Neuronal spines located on dendrites are protru-
sions that receive electric signals from other neurons, typically from one excitatory
synapse. They contain neurotransmitter receptors, organelles, and signaling systems
essential for synaptic function and plasticity. It has been shown that sensory expe-
rience and synaptic activity can modulate the formation and plasticity of dendritic
spines, and numerous brain disorders are associated with abnormal dendritic spines
(Nimchinsky 2002).
TheGolgistainingtechniquehasbeenusedinnumerousstudiesofdendriticspine
density, with a few in the visual cortex. Experiments in young and adult albino
rats investigating the e↵ect of monocular deprivation on dendritic spine density in
Golgi stained brain section showed evidence of a sensitive period in the development
of the visual system (Rothblat 1979). The Golgi technique was also used in the
study of dendritic spines in the visual cortex of albino rats in response to continuous
exposure to light. Dendritic spine density was shown to be significantly increased in
the visual cortex of rats exposed to continuous illumination from birth to 35 days,
perhapsreflectinganincreaseddemandofsensoryinformationprocessingbythebrain
(Parnavelas 1973).
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4.1 Methods
4.1.1 Animals
Normal Long Evans [postnatal day P200-P300, n = 6] rats and S334ter line 3 rats
with retinal degeneration [postnatal day P250-P300, n = 6] were used for comparing
the neuroanatomy of the visual cortex.
4.1.2 Golgi Staining
The rat brains were processed using the Golgi stain. An intramuscular injection of a
cocktail of ketamine (100 mg/kg; Ketaset, Fort Dodge Animal Health, Fort Dodge,
IA) and xylazine (100mg/kg; X-Ject SA, Butler, Dublin, OH) was used to induce
anesthesia. Once the rat was deeply anesthetized, an overdose of sodium pentobar-
bitol (0.5 ml of Euthasol) was injected in the heart to euthanize the rat. Golgi-Cox
staining (PK401 Rapid GolgiStain Kit, FD NeuroTechnologies, Ellicott City, MD)
was used to visualize neurons in the visual cortex. The brains were dissected imme-
diately after euthanasia and the tissue was impregnated for 2-3 weeks in the dark in
aGolgi-Coxsolutioncontainingmercuricchloride,potassiumdichromate,andpotas-
siumchromatewiththesolutionreplacedafterthefirst24hours. Thebraintissuewas
then moved to a cryoprotection solution for 48-72 hours. They were then sectioned
coronally into 100-150 µmsectionsonavibratome. Thesectionsweremountedon
gelatin-coated slides and dried overnight. The slides were developed the next day us-
ingRapidGolgiStainkitdevelopingsolution. Briefly,theslideswererinsedindistilled
water twice for 4 minutes each and placed in a developing solution for 10 minutes.
The slides were then rinsed and dehydrated in 50%, 70%, 95% and pure alcohol for 4
minutes each and cleared in Xylene three times for 4 minutes each. The slides were
then coverslipped with Permount and stored in the dark until morphological analysis
was performed.
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4.1.3 Morphological Analysis of Visual Cortex Neurons
In the Golgi stained rat brain sections, neurons in the visual cortex with somas lying
about 700 - 900 µmbelowthecorticalsurfacewereanalyzedasthatregioncorre-
sponded to the placement of recording electrodes for electrophysiology experiments.
In previous studies of dendritic spines in the visual cortex of rats, it has been
found that most of the excitatory synapses are located in a roughly spherical volume
centered about the soma that contains the basal and proximal majority of oblique
dendrites (Larkman 1991). Accordingly, basal and oblique dendrites were sampled at
di↵erent visual cortex locations across the sampled brain sections from all the rats.
Figure 4.1 shows a schematic of the typical morphology of a visual cortex pyramidal
cell (Parnavelas 1973).
Dendritic spine density was calculated by dividing a neuron’s traced dendritic
length by the spine count total along the traced dendrite, and expressed as number
of dendrites per 10 µm length of dendrite. Dendritic length was obtained by tracing
dendrites starting about 30 to 40 µmawayfromthesomauntilthedendritewascut
o↵ focus or near the terminus where the number of spines tapers o↵. Spine counts
were obtained by manually counting dendritic spines along the traced dendrites.
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Figure 4.1: Visual cortex neuron morphology
Aschematicofthetypicalmorphologyandelementsofavisualcortexpyramidal
cell, from (Parnavelas 1973)
108
All morphological data was collected at 60x and 83x magnification with an Olym-
pusCorporationBX50microscope(Shinjuku,Tokyo,Japan)usingaQImagingQIClick
camera (Surrey, British Columbia, Canada) to acquire images that were analyzed
using ImageJ. GraphPad QuickCalcs software was used for statistical analysis of den-
dritic spine density. A student’s t-test was used to compare the mean dendritic spine
density of the visual cortex neurons between normal and blind rats. A p-value of less
than 0.05 is considered as a statistically significant di↵erence.
Figures 4.2 and 4.3 shows representative coronal sections of the visual cortex
processed using the Golgi stain at 1.25x and 10x magnifications, respectively.
Figure 4.2: Golgi stained rat brain section at 1.25x
ArepresentativecoronalsectionofthevisualcortexprocessedusingtheGolgistain
at 1.25x magnification
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Figure 4.3: Golgi stained rat brain section at 10x
ArepresentativecoronalsectionofthevisualcortexprocessedusingtheGolgistain
at 10x magnification
4.2 Results
Dendritic spine density was sampled at 58 cortical locations in 4 normal Long Evans
rat brain sections, and at 56 cortical locations in 5 rd S334ter line 3 rat brain sec-
tions. The cortical locations where the spine counts were performed were all in the
visual cortex in the regions where electrophysiology measurements were performed as
discussed in the previous chapter.
Figure 4.4 shows a representative image of a rat brain section with the Golgi stain
viewed at high magnification (60x) used for dendritic spine counting.
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Figure 4.4: Golgi stained section at 60x
ArepresentativecoronalsectionofthevisualcortexprocessedusingtheGolgistain
at 60x magnification used for dendritic spine counting.
Figure 4.5 shows a comparison of the spine density between the normal and rd
rats, expressed as the mean number of spines counted per 10 µmlengthofdendrite.
The visual cortex of rd rats shows about a 10 percent higher spine density than in
the normal rats, and is statistically significant (student’s t-test p = 0.0433).
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Figure 4.5: Dendritic Spine Density
Comparison of dendritic spine density measured at 58 visual cortex locations in 4
Long Evans rats versus 56 visual cortex locations in 3 rd rats. The rd rats show a
10% higher spine density that is statistically significant; student’s t-test p = 0.0433.
The error bars show standard deviation.
4.3 Discussion
Whileplasticityofdendriticspinesisanareaofrobustresearchinneuroscience, there
arenotmanypublishedstudiesthathaveinvestigatedchangesindendriticspinesdue
to blindness.
In general, an increase in sensory experience increases the dendritic spine density
in the corresponding cortical area, and a decrease in sensory experience lowers the
dendriticspinedensity. Forexample,thereisanincreaseindendriticspinedensityon
hippocampal CAl pyramidal neurons following spatial learning in adult rats (Moser
1994). Enucleation of mouse eyes lowers the incidence of dendritic spines along the
apical shafts of visual cortex pyramidal cells (Valverde 1967). Based on this, it would
be expected that blind rats have lower dendritic spine density unlike the results I
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obtained in my comparison between the visual cortex neurons of normally sighted
and blind rats.
In a study with rats, it has also been shown that there is an increase in dendritic
spinedensityintheauditorycortexfollowingvisualorsomaticdea↵erentation(Ryugo
1975),suggestingthatlowereddendriticspinedensityduetoablockageofonesensory
modality may be accompanied by an increase in a di↵erent cortical area.
In general, it appears that while there is a strong correlation between synaptic
plasticityandmorphologicalchangesinspines,itisnotyetknownifthesemorpholog-
ical changes are necessary or sucient for functional plasticity (Yuste 2001, Alvarez
2007). It is possible that the increased dendritic spine density I report here for neu-
rons in the visual cortex of rd rats may be correlated or may be coincidental to the
increased spontaneous activity I reported in the previous chapter.
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Chapter 5
Conclusions and Future Work
The work presented in this thesis investigated visual cortex and superior colliculus
response to electrical stimulation of the retina in normally sighted rats and blind
rats with outer retinal degeneration. This chapter provides a brief summary of this
research and recommendations for future research directions. The key findings of this
work are itemized as follows:
• Electrophysiology studies show retinotopic cortical activity in response to focal
electrical stimulation of the rat retina.
• The cortical activity map for electrical stimulation of the retina in normally
sighted rats matches well with previously published maps of cortical activity
elicited by light stimulus.
• For blind rats with outer retinal degeneration, it appears that retinotopy is not
well preserved in the visual cortex in response to electrical stimulation of the
diseased retina.
• The cortical activity elicited by electrical stimulation of the retina for both
normal and rd rats shows a dose response characteristic with respect to the
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stimulus amplitude. Some of the cortical locations where the recordings were
performed showed monotonic increase in the strength of response, while some
locations showed peak strength of response at intermediate stimulus current
levels.
• The rd rats with outer retinal degeneration required higher amplitude stimulus
pulses to be delivered to the diseased retina in order to elicit responses in the
visual cortex. The thresholds for stimulus were higher by about an order of
magnitude for rd rats when compared to normal rats. This is significantly
higher than the increased thresholds reported in the range of 2-3x for retinal
recordings of diseased retina.
• Basedontheelectrophysiologyexperimentsinthesuperiorcolliculusinresponse
to electrical stimulation of the retina, the power consumed at the electrode -
retina interface for delivering the same amount of charge showed no signifi-
cant di↵erence for voltage-controlled, current-controlled, and charge-controlled
stimulus pulses.
• Based on the electrophysiology experiments in the superior colliculus, voltage-
controlled stimulus pulses delivered to the retina generate stronger neural re-
sponse in the superior colliculus when the pulses have short duration; current-
controlled pulses generate stronger neural response when the pulses have long
duration.
5.1 Future Directions
The retinotopic cortical activity maps presented in this thesis are the first published
maps for electrical stimulation of the retina. They can be used as a baseline to inves-
tigate if and how the maps change with chronic electrical stimulation of the retina. A
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key question to answer would be whether or not the remodeling of retinotopic orga-
nization seen in rd rats is reversed by chronic electrical stimulation of the retina. In
the case of cochlear implants, it has been shown that the loss of normal cochleotopic
organization in the auditory cortex of deafened cats was almost completely reversed
by chronic reactivation of the auditory pathway with the use of an electronic cochlear
prosthesis (Fallon 2009). It is an open question whether such reversal is possible with
retinal prostheses.
TheexperimentsIperformedusedasinglestimulatingelectrodefortheretinaand
a single recording electrode for the visual cortex. It will be much more ecient use of
experimental animals if electrode arrays are used for both stimulation and recording
electrodes. The technology for such electrodes and stimulation and recording elec-
tronics is already available, but an investment of time and e↵ort is required to adapt
them to in vivo animal experiments, and modified surgical approaches will be needed
for such experiments.
The use of general anesthesia for the experiments measuring cortical responses
may be a confounding factor. Measuring cortical activity and plasticity with freely
behaving animals will provide a better experimental platform for obtaining a more
accurate understanding of how the artificial input from electrical stimulation of the
retinaa↵ectsthevisualcortex. Wirelessstimulatingandrecordingelectronicsystems
that are small and portable enough to be implanted in small animals are rapidly
becoming available to experimentalists and can be used for future experiments.
While electrophysiology studies in rat models of retinal degeneration are a good
modelforfuturestudies,theexperimentalchallengesandaddedcomplexityofchronic
stimulation may require the use of other techniques to measure cortical responses.
There is also an inherent bias of coarse spatial sampling in electrophysiology studies
of the visual cortex that results in a low spatial resolution for the cortical activity
mapsobtained. Opticalimagingoftheintrinsicsignalsinthevisualcortexinresponse
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toelectricalstimulationoftheretinamaybeoneapproachtoobtainhigherresolution
cortical activity maps. Another approach with potentially higher signal to noise ratio
would be the use of genetically encoded calcium indicators expressed in the visual
cortex neurons to measure cortical activity. These optical imaging approaches are
especially useful for studies of the visual cortex as it is situated superficially, and
chronic imaging windows can be easily implanted allowing long term animal studies.
These approaches are already in use by other research groups for vision research with
light stimulus and are good choices for future studies of electrical stimulation of the
retina.
It would also be useful to study how the cortical reorganization seen in the blind
rats a↵ects their behavior, and if any behavioral changes observed are reversed with
chronic electrical stimulation of the retina.
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Chapter 6
Appendix: Tools and Methods
6.1 Electrophysiology Rig
The electrophysiology rig used for all the in vivo animal experiments in this thesis
was designed to measure electrically evoked potentials in the brain elicited by elec-
trical stimulation and full field light stimulation of the retina. The anesthetized rats
were placed on a stetereotaxic bench (KOPF Instruments, Model 900 Small Animal
Stereotaxic Instrument) with a recording electrode holder (Figure 6.1).
The rat was held in place using ear tip bars and a two port nose cone attached to
the stereotaxic bench. The left port of the nose cone was attached to the anesthetic
machine that delivered vaporized Sevoflurane in 100 % Oxygen, and the second port
was connected to a charcoal filter that captured exhaled gases from the rat and excess
anesthetic gas mixture.
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Figure 6.1: Stereotaxic bench for small animal experiments
The KOPF Model 900 small animal stereotaxic bench that formed the base for the
electrophysiology rig.
Oncethecraniotomywasperformedandretinalstimulationelectrodewasinserted,
the recording electrode was axed in the electrode holder attached to the stereotaxic
bench. Theelectrodeholderwasalsoattachedtoathreedimensionalmicromanipula-
tor with a digital position readout with micrometer accuracy. The electrode position
was zeroed at lambda – the point on the rat skull where the posterior suture lines
intersected at midline.
The recording electrode was connected to a Plexon headstage amplifier axed
to the electrode holder with a clip. The headstage amplifier (gain x20) output was
connected to a Plexon pre-amplifier (gain x100). The amplifiers have connections for
8 separate channel, but I used only one channel for all of my experiments. Figure
6.2 shows an image of the headstage amplifier with a broken connector, which was
repaired for further use. The output of the pre-amplifier was connected to a breakout
119
board with BNC connectors. The channel 1 output from this breakout board was
sentto a speakerand thedataacquisition box (DatawaveTechnologies). Thespeaker
provided auditory confirmation of the electrode being inserted into the cortex. The
data acquisition box output was connected to a personal computer for capturing the
recording signal.
Figure 6.2: Plexon headstage amplifier
The Plexon headstage amplifier
6.1.1 Electrophysiology Experiment Protocol
The steps below summarize the experiment protocol for performing the electrophys-
iology experiments described in this thesis.
• Prepare the electrophysiology rig for an experiment. Typical pre-experiment
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check would include: assembling clean surgical tools, making sure there is
enough liquid sevoflurane in the anesthesia machine, cleaning the surface of
the stimulating electrode using cyclic voltammetry (if deemed necessary after
checking impedance in phosphate bu↵ered saline(PBS)), and checking that the
recording system is functional with recording electrodes in PBS.
• Transport the rat from the vivarium to the laboratory, and induce anesthesia
with an intramuscular or intraperitoneal injection of a ketamine and xylazine
cocktail (4:1 Ket:Xyl 100mg/ml concentration). Dosage depends on strain of
the rat: for Long Evans rats I used 0.05 ml per 100 g of weight of rat, and for
S334ter rats I used 0.075 ml per 100 g of weight of rat. Older rats, especially
for age greater than P300, also may need more anesthetic to induce anesthesia.
• It may take 10-15 mins for the rat to be anesthetized after the ketamine and
xylazineinjection. Inthemeantime,turnonthehomeothermicheatingblanket
and place an underpad on top of the blanket and place them on the stereotaxic
bench, arrange surgical tools next to the stereotaxic bench, and insert the drill
bit into the drill used for craniotomy.
• Check the toe pinch reflex to make sure rat is deeply anesthetized, and shave
the hair top of the skull from in between the eyes to in between the ears.
• Place the rat on the stereotaxic bench, and secure the head in between the ear
bars with the nose placed in the nose cone. Turn on the sevoflurane vaporizer
and set it to 2% in 100 percent oxygen with a flow rate of 1 L/min.
• Place the thermometer for the heating blanket under the abdomen of the rat.
• Turn on the pulse oxygen and heart rate monitor and attach the sensor clip to
a hind paw of the rat. The pulse oxygen levels should be above 90%. If not,
increase the flow rate of Oxygen.
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• Applyartificialtearsgeltotheeyes;failuretodosowillresultinthedehydration
of the cornea and its becoming opaque which will make the insertion of the
electrode into the eye impossible. If artificial tears gel is not available, apply
artificial tears drops every 15 minutes or eye wash liquid every 5 minutes to
keep the cornea hydrated.
• After making sure that the rat is deeply anesthetized by checking the toe pinch
reflex, make a midline incision on top of the skull of about 3-4 cm using a #15
bladescalpel. Usethescalpeltocleartheperiosteumoftheskull. Usekimwipes
to clear any surface bleeding. Once the bleeding is cleared, use retractors to
open a good field of view for craniotomy.
• Use a dental drill to perform a craniotomy on the right side of the skull over
the visual cortex. Apply saline (0.9% NaCl) and wipe away with kimwipes
periodically to control bleeding and cool the skull. Care should be taken not
to penetrate dura mater. Care should also be taken to drill a millimeter or so
away from the skull suture lines to avoid puncturing the venous sinus.
• After the craniotomy, use a handheld drill to make a hole for the bone screw on
the left side of the skull. Care should be taken to avoid penetration of the dura
mater with the drill bit. Once the hole is drilled, screw in a metal bone screw
for the recording amplifier ground connection.
• Periodically apply saline to the open cranial window while the retinal electrode
is being inserted.
• Remove the artificial tears gel from the left eye using a cotton swab, and apply
eye wash liberally. Apply 2 drops each of Tropicamide and Phenylephrine to
dilate the pupil. Use a 1 inch x 1 inch piece of latex (cut from a disposable
glove) with a pinpoint hole in the center to proptose the eye ball.
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• Once the pupil is dilated, use ophthalmic demulcent gel (Gonak) with a glass
coverslip pressed gently to the cornea to visualize the retina through the op-
erating microscope. Adjust the microscope position so that the optic nerve is
readily visible when a glass coverslip with Gonak is gently pressed against the
cornea. Lock the microscope position.
• Insertthereturnelectrodeforstimulation(astainlesssteelneedle)inthesubder-
mal space on the nose of the rat, and the reference electrode (another stainless
steelneedle)forimpedancemeasurementofthestimulationelectrodeinthetail
of the rat.
• Using a 30 gauge needle, make an incision at the limbus on top of the eyeball.
Controlbleedingwithdirectpressureusingacottonswab. Withaglasscoverslip
covered with Gonak gently pressing against the cornea to visualize the retina,
insert the stimulation electrode into the eye through the incision. Have an
assistant nearby to lock the stimulation electrode micromanipulator in place.
• Connect the retinal stimulation electrode, nose electrode (return) and tail elec-
trode(reference)toapotentiostattomeasurethestimulationelectrodeimpedance
at 100 kHz. Monitor the impedance as the electrode is moved closer to the
retina. For a typical stimulation electrode impedance of 4-6 k⌦ in PBS, lock
the stimulation electrode position where the impedance is 8-10 k⌦ and the tip
of the electrode is 50 - 100 µmfromthesurfaceoftheretina.
• Lowerthesevofluranesettingto0.5%fortheelectrophysiologyrecordingsession.
• Move the operating microscope to the cranial window and insert electrodes for
cortical electrophysiology recording. The main recording electrode (tungsten
needle) is placed in the electrode holder attached to the stereotaxic bench. The
(x,y)locationoftherecordingelectrodeiszeroedatlambda(wheretheposterior
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suture lines intersect at midline) with care taken to avoid parallax error.
• Placethereferenceelectrode(tungstenneedle)inamicromanipulatorandinsert
it in the anterior midline corner of the cranial window away from the visual
cortex.
• Connect the recording and reference electrodes and the bone screw to the head-
stageamplifier,andturnontherecordingpre-amplifier(Plexonbluebox)which
also powers the headstage amplifier.
• Move the recording electrode to the desired cortical (x,y) location and insert it
into the visual cortex; about 700-750 µm below the surface of the dura mater.
Use the audio feedback from speakers connected to the output of the recording
pre-amplifier to zero the z-setting at the surface of the dura mater.
• Once the stimulation electrode and recording electrodes are placed in a sat-
isfactory location, connect the stimulation electrode to the stimulator via the
interface board and launch the SciWorks software from Datawave Technologies,
and execute an experiment. The typical experiment delivers a trigger to the
stimulator to deliver one pulse and turns on the data acquisition system con-
nected to the recording pre-amplifier to record for a time window that includes
some time before (typically 150 ms in this thesis) and some time after the stim-
ulus pulse (typically 350 ms in this thesis). This is repeated 50 times for each
experiment.
• Move the location of the recording electrode and repeat the Datawave experi-
ment.
• Periodically monitor the heart rate and pulse oxygen levels throughout the
experiment. If the heart rate rises about 300 beats per minute, increase the
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concentration of the sevoflurane delivered to the nose cone for 10 minutes, and
lower it back to 0.5% before continuing the electrophysiology recording.
6.2 Breeding Retinal Degenerate Rats
TheblindratsusedinthisthesiswerebredintheanimalcarefacilitiesatUSC.Iused
theRatResearchResourcecenterattheUniversityofMissouritoobtainhomozygous
S334ter line 3 rats with an autosomal dominant mutation in the rhodopsin gene. I
established breeding pairs using these homozygous S334ter rats and normal Long
Evans rats of the opposite sex. The o↵spring were all heterozygous and had a single
copy of the mutated rhodopsin gene. These heterozygous rats were well characterized
at the University of California, San Francisco and many published studies show them
tobeagoodmodelforhumanretinitispigmentosa. Sincethemutationwasautosomal
dominant, no genetic testing was required to verify that the o↵spring would acquire
blindness.
During the initial phase of breeding, the female rats were monitored for weight
gain and visual observation of a vaginal mucus plug indicating mating behavior. If
neither were observed for more than two weeks, the breeding pairs were rotated to be
caged with other mates.
Once a litter of heterozygous o↵spring was produced, the date of birth was noted
and the male parent was moved to a di↵erent cage. The litter was weaned from the
female parent on post natal day 22. During the initial weeks after weaning, care was
taken to include food and water within the cage while the young rats learned to use
the water spouts.
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6.3 Design of a Low-cost Chronic Stimulator
It is impractical to use neural stimulators developed for human use in animal ex-
periments due to size and cost limitations. There has been a fair amount of recent
research in the development of custom microchip based electronics for use in animal
experimentsofneuralstimulation(Arfin2009,Azin2011). Designingsuchstimulators
requires a considerable amount of time and resources. The use of such sophisticated
stimulators is not necessary to answer fundamental questions in researching neural
plasticity elicited by chronic neural stimulation.
Icompletedadesignthatismoresuitableforretinalstimulationthatimproves
upon a low-cost method for chronic neural stimulation in autonomously behaving
small animals published recently (Zhang 2011). This low-cost wireless stimulator can
bebuiltusingcommercialo↵-the-shelfelectroniccomponents. Itisdesignedbeplaced
on a pedestal on top of a rat’s head can used for chronic animal experiments. Figure
6.3 shows a schematic of the chronic stimulator.
Figure 6.3: Low cost chronic neural stimulator
Schematic of a battery-powered low cost chronic neural stimulator.
The stimulator is powered by two Panasonic ML621 lithium ion coin batteries
126
connected in series. To provide a stable power source to the stimulator, the battery
outputisconnectedtoalowdrop-outregulatorthatprovidesa5Voutput. Theheart
of the stimulator is a low frequency oscillator, LTC6991 from Linear Technology with
aprogrammableperiodrangeof1.024msto9.54hours(29.1µHz to 977 Hz), suitable
for generating timing for neural stimulation applications that range from 1 Hz to
100 Hz. The oscillator output is used to generate timing signals S1, S2, S3, S4 as
shown in figure 6.3. The signals S1 and S2 are used to generate the cathodic phase
of the biphasic stimulus pulse, and the signals S3 and S4 are used to generate the
anodic phase. The programmable time interval between these two sets of signals
sets the interphase gap. For proof of concept testing of the stimulator, the digital
logic to generate these timing signals was accomplished with parts available in our
laboratory, and for a final implementation could be accomplished using a small field
programmable gate array (FPGA). The stimulator itself is comprised of switches
S1, S2, S3, S4, current mirrors CMN1, CMP1, CMN2, CMP2, and programmable
resistors R1 and R2. The programmable resistors and the current mirrors allow the
current output of the stimulator to be varied. During the cathodic phase, switches
S1 and S2 are on and switches S3 and S4 are o↵, and current flows from electrode E1
to electrode E2. During the anodic phase, S1 and S2 are o↵ and switches S3 and S4
are on, and current flows from electrode E2 to electrode E1.
I have demonstrated a proof-of-concept version of this stimulator. Figure 6.4
shows the test setup used for the demonstration. The stimulating electrode and
return electrode are placed in PBS and the voltage and current waveforms through
the electrodes are captured on the oscilloscope.
127
Figure 6.4: Low cost chronic neural stimulator test setup
Test setup for proof of concept demonstration of low cost wireless neural stimulator.
The stimulating electrode and return electrode are placed in PBS and the voltage
and current waveforms through the electrodes are captured on the oscilloscope
The electrodes are connected to the stimulator using an interface board, shown
in figure 6.5. The interface board consists of a six position switch used to select the
currentsenseresistorthatisusedtorecordthecurrentflowingthroughtheelectrodes.
Theinterfaceboardalsocontainsconvenienttestpointstoconnectoscilloscopeprobes
for recording voltage across the stimulating and return electrodes and the current
flowing through tissue between the stimulating and return electrodes.
128
Figure 6.5: Stimulator interface board
Apictureofthestimulatorinterfaceboardusedtoconnectthestimulatortothe
electrodes. The board contains convenient test points to connect oscilloscope probes
for recording electrode voltages and currents, and a six position switch used to
select the current sense resistor.
The results of the benchtop test of the low cost chronic neural stimulator is shown
in figure 6.6. The oscilloscope traces show voltages at the stimulating and return
electrodesontop(yellowandblue). Thecurrentwaveformbetweenthetwoelectrodes
isshownintheredtraceillustratingabiphasicstimuluspulsewithnointerphasegap.
129
Figure 6.6: Current waveforms from low cost chronic neural stimulator
Oscilloscope traces of the current waveforms generated by the low cost neural
stimulator
130
131
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Abstract (if available)
Abstract
Retinal degenerative disorders are one of the leading causes of human blindness in adult life. Electronic retinal prostheses aim to restore vision in blind people who have photoreceptor cell loss by electrically stimulating the retina. Previous research has shown that in a large number of blind patients, the inner retina has surviving electrically-excitable cells despite degenerative loss of all photoreceptor cells. This finding provides the impetus for utilizing implantable electronic retinal prostheses to provide functional vision for such patients with blindness due to photoreceptor degeneration. ❧ One of the overarching research goals in our laboratory has been the study of scientific principles underlying the therapy of electronic retinal prostheses. Studies using rat and mouse models of retinal degeneration have been performed with in vitro and in vivo experimental preparations. All of the experiments in these animal models of outer retinal degeneration have focused the study on either the retina or the superior colliculus. As a significant number of retinal cell ganglion axons synapse in the superior colliculus (SC), electrophysiology and anatomical studies performed in the SC have been used as a marker for retinal output. Since functional vision is mediated by activity in the visual cortex and the lateral geniculate nucleus (equivalent function in thalamus in humans) in rats, I performed the bulk of my thesis work studying responses in the visual cortex elicited by electrical stimulation of the retina. ❧ The human (and rat) visual cortex has an orderly arrangement of visual field processing, termed retinotopy. This retinotopic organization represents specificity in the spatial organization of connections in the various layers of the visual system with respect to the visual field, and is an important element of functional vision. This thesis presents the first work in the study of visual cortex retinotopy in response to electrical stimulation of the retina. ❧ My experiments using electrophysiology studies show retinotopic cortical activity in response to focal electrical stimulation of the rat retina in normally sighted animals. The location in the visual cortex where activity is seen in response to electrical stimulation of normal retina matches well with previously published maps of cortical activity elicited by light stimulus. For blind rats with outer retinal degeneration (rd), it appears that retinotopy is not well preserved in the visual cortex in response to electrical stimulation of the diseased retina. ❧ The cortical activity elicited by electrical stimulation of the retina for both normal and \emph{rd} rats shows a dose response characteristic with respect to the stimulus amplitude. However, the rd rats with outer retinal degeneration required higher amplitude stimulus pulses to be delivered to the diseased retina in order to elicit responses in the visual cortex.
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Creator
Nimmagadda, Kiran
(author)
Core Title
Cortical and subcortical responses to electrical stimulation of rat retina
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Neuroscience
Publication Date
07/17/2017
Defense Date
05/12/2017
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electrical stimulation,electrophysiology,OAI-PMH Harvest,outer retinal degeneration,rat models of blindness,rat retina,rat visual cortex,retinotopy
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Hirsch, Judith (
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), Weiland, James (
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), Humayun, Mark (
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), Jakowec, Michael (
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)
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Tags
electrical stimulation
electrophysiology
outer retinal degeneration
rat models of blindness
rat retina
rat visual cortex
retinotopy