visual prosthesis
DESCRIPTION
visual prosthesisTRANSCRIPT
VISUAL PROSTHESIS SEMINAR REPORT 2013
CHAPTER 1
INTRODUCTION
A visual prosthetic is a form of neural prosthesis intended to partially restore lost
vision or amplify existing vision. It usually takes the form of an externally-worn camera that is
attached to a stimulator on the retina, optic nerve, or in the visual cortex, in order to produce
perceptions in the visual cortex.
Visual percepts are the final product of a rich interplay of stimulus processing
that occurs without the intervention of one's consciousness. While this is a fascinating issue to
consider, especially as it pertains to the philosophical and practical definitions of ideas like the
"self," the converse is equally interesting to me. In this modern era of exploding technological
ingenuity, the sum of which is a product of the conscious brain, increasingly more opportunities
exist for the brain to design the input it receives. One method by which this occurs is observable
in the treatment of visual pathologies. A development of particular interest to me is the use of
visual prosthetic devices in the treatment of some forms of progressive blindness. Research in
this area raises numerous conflicts within the realm of bioengineering, but promises, at least, to
challenge the boundaries of current micro technology and instigate further integration of the
rapidly expanding fields of electronics and medicine.
In 1988, a multidisciplinary research team called the "Retinal Implant Project,"
spanning the knowledge bases of Harvard Medical School, the Massachusetts Eye and Ear
Infirmary, and the Massachusetts Institute of Technology's Department of Electrical Engineering
and Computer Science, was formed with the explicit goal of creating an intraocular retinal
prosthetic device to combat the effects of certain types of progressive blindness. The prostheses
are intended to stimulate retinal ganglion cells whose associated photoreceptor cells have fallen
victim to degradation by macular degeneration or retinitis pigmentosa, two currently incurable
but widespread conditions. Their most recent work has been to orchestrate short-term clinical
trials in which blind volunteers receive a temporary intraocular prosthetic implant and undergo a
series of tests to determine the quality of visual percepts experienced over a two- to three-hour
period . The leaders of the Retinal Implant Project, while enthusiastic about their progress, do
not anticipate the realization of a workable prosthetic within the next five years.
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The goal of retinal prosthetic proposed by the collaborators is to bypass
degenerate photoreceptors by providing electrical stimulation directly to the underlying ganglion
cells. The ganglion cell axons compose the optic nerve, which travels from the eye and
terminates in various regions of the brain, where the combined input is processed along multiple
routes and ultimately results in the experience of sight . Ganglion cell excitation will be
accomplished by attaching a two-silicon-microchip system onto the surface of the retina, which
will be powered by a specially designed laser mounted on a pair of glasses worn by the patient .
This laser will also be receiving visual data input from a small, charge-coupled camera, whose
output will dictate the pattern intensity of the laser beam . The laser's emitted radiation will be
collected by the first microchip within the eye on an array of photodiodes and transferred to the
second chip, which will be responsible for electrically stimulating a set of retinal ganglion cells
via fine microelectrodes . Because the ganglion cells in a healthy retina are stimulated by
photoreceptors, this activation process is designed to mimic the electrical activity within a retinal
ganglion cell corresponding to a visual stimulus, with the hope that some measure of sight can be
restored to individuals with faulty photoreceptors.
The team selected the retina as the site of artificial stimulation after careful
consideration of the effects of the target diseases and the successes and limitations of electrical
excitation at various regions along the visual pathway. Dr. T. Hambrecht of the National
Institutes of Health and Dr. R. Normann of the University of Utah are two neurobiologists
examining the effects of microelectrode stimulation of various regions of the visual cortex, a
portion of the brain believed to be involved in visual perception. Upon administration of
electrical stimuli to subsurface regions of the visual cortex of a blind patient, the patient
identified spots of light, called phosphenes, which varied in color and depth, depending on the
location of the stimulus. While this is exciting in its implications for elucidating the physical
arrangement of the neuronal cells involved in the visual pathway, it fails to replicate the
experience of sight because the stimuli are independent of external factors. Also, the visual
percept is the product of neuronal activity in more than one brain region, a fact that renders the
proposition that artificial stimulation in any single cortical area (or small collection of cortical
areas) could recreate the elaborate perception of vision rather dubious.
The researchers involved with the Retinal Implant Project hypothesize that
higher quality visual perceptions will be experienced with retinal than with intracortical
stimulation. Joseph Wyatt and John Rizzo, III, the co-heads of the Retinal Implant Project write,
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". . . in principle, the earlier the electronic input is fed into the nerves along the visual pathway,
the better, inasmuch as neural signals farther down the pathway are processed and modified in
ways not entirely well understood". This hypothesis is validated by the observation that
photoreceptors are the sole neurons decimated by macular degeneration and retinitis pigmentosa,
leaving the remaining cells involved in the visual process unharmed. Therefore, with the proper
artificial input, it is reasonable to expect that those with prosthetic photoreceptive apparatuses
will experience some returned vision.
While this proposal is exciting in its scope and purpose, it is not without
drawbacks and complications. While the prosthetic's design offsets many potential biological
problems by having most of its functional parts external to the body, this fails to solve every
obstacle attendant upon the insertion of an inorganic and electrically active device into a living
eye. Rizzo and Wyatt explain, "Biocompatibility, which encompasses biological, material,
mechanical, and electrochemical issues, is the most significant obstacle to the development of a
visual prosthesis".
Specifically, the electrical components of the prosthesis must be sequestered
from all intraocular fluids, which could corrode the thin metal of the diodes and ruin the chips'
ability to transmit electrical impulses from the laser to the retinal ganglion cells. Likewise, the
by-products of electrical impulse transmission through metallic electrodes are toxic to living
cells, and must be diminished in order to insure minimal chemical devastation of the retina. The
electrodes themselves must also be anchored to the retina with sufficient strength to
accommodate physical agitation due to daily activity. This promises to be a trying procedure.
The retina is a slim 0.25 millimeters thick, a dauntingly thin fabric onto which to stitch a
complex, albeit tiny, piece of machinery. As in all retinal surgical procedures, the implantation
of a prosthetic poses a risk of retinal detachment and infection of the associated membranes,
both of which would exacerbate, rather than prevent, vision loss. These concerns have not been
seriously addressed in this stage of the research, because no long-term clinical trials of the
prosthesis have been undertaken.
A final barrier to the project, and perhaps the most complex to
troubleshoot, is determining whether the engineered apparatus will be effective in restoring sight
with chronic implantation. Although short-term tests of the photodiode array have been
undertaken, their success was only measured in the ability of the diodes to generate output once
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inserted into the eye. While this was a necessary experimental step to prove the short-term
mechanical soundness of the diode apparatus to fluids of the inner eye, the diodes have never
been attached to the retinal tissue, and therefore, their viability as conduits of visual information
has not been examined. The data the researchers cite in their preliminary investigations and those
of their colleagues report that the single visual percept accomplished by artificial stimulation to
date is phosphene recognition. This, however, is not equivalent to true sight, and certainly falls
short of the lofty goal claimed by its spearheads: to "improve quality of life by providing gross
perception with some geometric detail that would increase independence by making it easier for
a blind person to walk down the street, for instance".
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CHAPTER 2
HISTORY OF VISUAL PROSTHESIS
Scientific research since at least the 1950s has investigated interfacing electronics at
the level of the retina, optic nerve, thalamus, and cortex. Visual prosthetics, which have been
implanted in patients around the world both acutely and chronically, have demonstrated proof of
principle, but do not yet offer the visual acuity of a normally sighted eye.
2.1 THE ARTIFICIAL EYE SYSTEM
In the past 20 years, biotechnology has become the fastest-growing area of scientific
research, with new devices going into clinical trials at a breakneck pace. A bionic arm allows
amputees to control movements of the prosthesis with their thoughts. A training system called
BrainPort is letting people with visual and balance disorders bypass their damaged sensory
organs and instead send information to their brain through the tongue. Now, a company called
Second Sight has received FDA approval to begin U.S. trials of a retinal implant system that
gives blind people a limited degree of vision.
The Argus II Retinal Prosthesis System can provide sight -- the detection of light to
people who have gone blind from degenerative eye diseases like macular degeneration and
retinitis pigmentosa. Ten percent of people over the age of 55 suffer from various stages of
macular degeneration. Retinitis pigmentosa is an inherited disease that affects about 1.5 million
people around the globe. Both diseases damage the eyes' photoreceptors, the cells at the back of
the retina that perceive light patterns and pass them on to the brain in the form of nerve impulses,
where the impulse patterns are then interpreted as images. The Argus II system takes the place of
these photoreceptors.
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2.2 MAIN PARTS:
The second incarnation of Second Sight's retinal prosthesis consists of five main parts:
A digital camera that's built into a pair of glasses. It captures images in real time
and sends images to a microchip.
A video-processing microchip that's built into a handheld unit. It processes
images into electrical pulses representing patterns of light and dark and sends the
pulses to a radio transmitter in the glasses.
A radio transmitter that wirelessly transmits pulses to a receiver implanted
above the ear or under the eye.
A radio receiver that sends pulses to the retinal implant by a hair-thin implanted
wire.
A retinal implant with an array of 60 electrodes on a chip measuring 1 mm by 1
mm.
The entire system runs on a battery pack that's housed with the video processing
unit. When the camera captures an image -- of, say, a tree -- the image is in the form of light and
dark pixels. It sends this image to the video processor, which converts the tree-shaped pattern of
pixels into a series of electrical pulses that represent "light" and "dark." The processor sends
these pulses to a radio transmitter on the glasses, which then transmits the pulses in radio form to
a receiver implanted underneath the subject's skin. The receiver is directly connected via a wire
to the electrode array implanted at the back of the eye, and it sends the pulses down the wire.
When the pulses reach the retinal implant, they excite the electrode array. The
array acts as the artificial equivalent of the retina's photoreceptors. The electrodes are stimulated
in accordance with the encoded pattern of light and dark that represents the tree, as the retina's
photoreceptors would be if they were working (except that the pattern wouldn't be digitally
encoded). The electrical signals generated by the stimulated electrodes then travel as neural
signals to the visual center of the brain by way of the normal pathways used by healthy eyes --
the optic nerves. In macular degeneration and retinitis pigmentosa, the optical neural pathways
aren't damaged. The brain, in turn, interprets these signals as a tree and tells the subject, "You're
seeing a tree."
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It takes some training for subjects to actually see a tree. At first, they see mostly
light and dark spots. But after a while, they learn to interpret what the brain is showing them, and
they eventually perceive that pattern of light and dark as a tree. The first version of the system
had 16 electrodes on the implant and is still in clinical trials at the University of California in
Los Angeles. Doctors implanted the retinal chip in six subjects, all of whom regained some
degree of sight. They are now able to perceive shapes (such as the shaded outline of a tree) and
detect movement to varying degrees. The newest version of the system should offer greater
image resolution because it has far more electrodes. If the upcoming clinical trials, in which
doctors will implant the second-generation device into 75 subjects, are successful, the retinal
prosthesis could be commercially available by 2010. The estimated cost is $30,000.
Researchers are already planning a third version that has a thousand electrodes
on the retinal implant, which they believe could allow for facial-recognition capabilities
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CHAPTER 3
ARTIFICIAL VISION
There are a number of blinding disorders which are primarily due to
photoreceptor or outer retinal degeneration/destruction. These include but are not exclusive to
diseases such as retinitis pigmentosa and age related related macular degeneration. We have
tested the feasibility of developing a retinal implant/Chip which could provide form vision to
this subset of blind patients. This visual prosthesis would be situated in the eye cavity on the
retinal surface. It would create the sensation of seeing light by electrical stimulation of the
remaining retinal cells which remain relatively intact despite severe photoreceptor loss.
Moreover, by converting images into pixels and then electrically stimulating the retina by a
pattern of electrodes, this device would recreate at least in part the visual information/scene.
Visual prosthetics can be broken into three major groups. First, there are the
devices that use either ultrasonic sound or a camera to sample the environment ahead of an
individual and render the results into either a series of sounds or a tactile display. From this the
person is supposed to be able to discern the shape and proximity of objects in their path. The
second major form is retina enhancers. These machines supplement functions of the retina by
stimulating the retina with electrical signals which in turn causes the retina to send the results
through the optic nerve to the brain. The third major category of visual prosthetic is a digital
camera that samples an image and stimulates the brain with electrical signals--either by
penetrating into or placing electrodes on the surface of the visual cortex.
Fig 1: Normal Eye
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Fig 2: Artificial eye
3.1 BIOLOGICAL CONSIDERATIONS:
The ability to give sight to a blind person via a bionic eye depends on the
circumstances surrounding the loss of sight. For retinal prostheses, which are the most prevalent
visual prosthetic under development (due to ease of access to the retina among other
considerations), vision loss due to degeneration of photoreceptors (retinitis pigmentosa,
choroideremia, geographic atrophy macular degeneration) is the best candidate for treatment.
Candidates for visual prosthetic implants find the procedure most successful if the optic nerve
was developed prior to the onset of blindness. Persons born with blindness may lack a fully
developed optical nerve, which typically develops prior to birth.
3.2 TECHNOLOGICAL CONSIDERATIONS:
Visual prosthetics are being developed as a potentially valuable aide for
individuals with visual degradation. The visual prosthetic in humans remains investigational.
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CHAPTER 4
DEVICE
The device consists of a tiny camera and transmitter mounted in eyeglasses, an
implanted receiver, and an electrode-studded array that is secured to the retina with a microtack
the width of a human hair. A wireless microprocessor and battery pack worn on the belt powers
the entire device.
Fig 3: View of the device
The camera on the glasses captures an image and sends the information to the
video processor, which converts the image to an electronic signal and sends it to the transmitter
on the sunglasses. The implanted receiver wirelessly receives this data and sends the signals
through a tiny cable to the electrode array, stimulating it to emit electrical pulses. The pulses
induce responses in the retina that travel through the optic nerve to the brain, which perceives
patterns of light and dark spots corresponding to the electrodes stimulated. Patients learn to
interpret the visual patterns produced into meaningful images.
Second Sight’s first generation Argus 16 implant consists of a 16 electrode array
and a relatively large implanted receiver implanted behind the ear. The second generation Argus
II is designed with a 60 electrode array and a much smaller receiver that is implanted around the
eye.
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CHAPTER 5
WORKING
Normal vision begins when light enters and moves through the eye to strike
specialized photoreceptor (light-receiving) cells in the retina called rods and cones. These cells
convert light signals to electric impulses that are sent to the optic nerve and the brain. Retinal
diseases like age-related macular degeneration and retinitis pigmentosa destroy vision by
annihilating these cells.
With the artificial retina device, a miniature camera mounted in eyeglasses
captures images and wirelessly sends the information to a microprocessor (worn on a belt) that
converts the data to an electronic signal and transmits it to a receiver on the eye. The receiver
sends the signals through a tiny, thin cable to the microelectrode array, stimulating it to emit
pulses. The artificial retina device thus bypasses defunct photoreceptor cells and transmits
electrical signals directly to the retina’s remaining viable cells. The pulses travel to the optic
nerve and, ultimately, to the brain, which perceives patterns of light and dark spots
corresponding to the electrodes stimulated. Patients learn to interpret these visual patterns.
Fig 4: Device implemention
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5.1 STEPS OF THE PARTS BEING USED:
1: Camera on glasses views image.
2: Signals are sent to hand-held device.
3: Processed information is sent back to glasses and wirelessly transmitted to
receiver under surface of eye.
4: Receiver sends information to electrodes in retinal implant.
5: Electrodes stimulate retina to send information to brain.
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CHAPTER 6
TECHNOLOGY OVERVIEW
6.1 INFORMATION PROCESSING IN THE VISUAL PATHWAY :
The global goal of our research program is to understand how information
about the outside world is encoded in the neuronal activity in the central nervous system. The
effects of a continuous exogenous input (the visual world) are manifest through discrete
electrical events in the early visual pathway. The basic anatomy is shown in Figure 1, where
light entering the eye falls onto the photoreceptors of the retina and is transduced into electrical
signals that are processed through layers in the retina, and then passed through the lateral
geniculate nucleus (LGN) to the visual cortex. Individual neurons in each of these areas respond
to light within a restricted region of visual space, known as the receptive field (RF). More
generally, we refer to the spatiotemporal RF as the characteristics of the integration of visual
input over space and time, giving rise to the neuronal response.
Fig 5: The early mammalian visual pathway.
It is important to quantify the manner in which information is encoded in
these stages of the early visual pathway, so that we may, in turn, precisely control neural
function to produce desired visual percepts, in situations where function has been lost to trauma
or disease. Note that current attempts at visual prosthetics are still in the nascent stages, and
there are major signal processing, estimation, prediction, and control-related problems that must
be overcome before such technology becomes truly viable. Despite the fact that the anatomy and
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physiology of the visual pathway have been studied for some time, much is still not known about
the true nature of the neural code that enables us to interact with the external visual world.
6.2 ENCODING OF NATURAL SCENCES:
Our early work led us to study encoding in the early visual pathway through
experimental and computational approaches. Neurons in the visual pathway encode information
about the outside visual world in a causal manner, but the task of higher centers in the brain is to
somehow interpret the outside world from the spiking activity of neurons that project to them.
Taking this perspective, we decoded or reconstructed natural visual inputs from
population activity in the visual thalamus (which is an intermediate stage of processing between
the retina and cortex) (Stanley et al., 1999), providing a description of the information about raw
light intensity being encoded in specific cell types within the early pathway. Figure 1 shows the
reconstructed light intensity of 4 adjacent pixels from 8 LGN neurons on the left, and a
reconstruction of a much larger region of visual space on the right (from Stanley et al., 1999)
This work was critical in defining our direction of research for the next several
years. The large majority of experimental work on the functional aspects of coding in the visual
pathway has utilized artificial classes of visual stimuli. To understand the true functionality of
the visual pathway and thus to make long term clinical impact, it is absolutely imperative that we
explore more behaviorally and practically relevant scenarios. Despite the surprising amount of
detail that was extracted from the ensemble neuronal activity in the LGN, as shown in Figure 2,
there are many unresolved issues. Specifically, when studying neural encoding in the natural
environment, questions are raised concerning the role of adaptation in the transient natural
environment, the effects of spatial and temporal correlation structure on neural coding, the
relationship between functional encoding properties and the information carrying properties of
the pathway, and the role of the early visual pathway in the detection of salient features in the
environment. Figure 3 shows examples of the differences between the evolution of the light
intensity at a point in visual space for natural vs. artificial (white noise) visual stimuli, along
with the corresponding second order statistics (power spectra) in both temporal
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The overall perspective that we have taken in this work is that the early visual
pathway has (at least) two distinct roles in processing of information about the outside world:
transmission and detection, as shown in Figure 4.
Fig 6: The early visual pathway serves to detect changes in the outside visual world, and to
transmit fine details about relevant features.
In certain contexts, it is important for the visual pathway to transmit fine
details concerning features of the outside visual world. We may think of this as the what
question: given that something of interest is in my visual field, what is it? Is it predator or prey,
or perhaps a potential mate? In other ethologically relevant contexts, it is important to detect the
presence of an object or to signal novelty, in a "bottom-up" context, potentially for the "top-
down" allocation of attentional resources. We may think of this as a yes or no question: is
something of interest there or not? The fast and robust detection of changes in the external
environment may be critical for the survival of the organism. The startling aspect of this
dichotomy is that the seemingly disparate tasks may in fact be accomplished by the same
neuronal circuitry.
6.3 ADAPTATION:
A common thread through much of our current work is in understanding how
encoding properties of the neuronal pathways change over time. One of the most striking
properties of the visual system is that it can faithfully encode visual stimuli over an enormous
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operating range of light intensity. This important property exists as a result of adaptive
mechanisms that effectively shift the neuronal sensitivity in response to changes in the light
level. The adaptive mechanisms are continually active in all but the most artificial of laboratory
conditions, as we move our eyes across the visual field, and objects move in and out of our view.
These aspects of encoding are ignored in many studies, and are the subject of much controversy
as to what the functional significance might be. This is an extremely critical issue in prosthetics,
and in other types of biomimetic applications which seek to process visual information with the
efficiency of the true biological systems.
Adaptation mechanisms affect the encoding of information in the pathway,
which is reflected in the properties of the spatio-temporal receptive field and corresponding
spatial and temporal frequency properties. We have developed novel approaches to track
changes in the linear and nonlinear encoding dynamics in the visual pathway through adaptive
estimation schemes (Stanley, 2002; Lesica et al., 2003; Lesica and Stanley, 2005a; Lesica and
Stanley 2005b), testing in the retina, LGN, and visual cortex. A block diagram of the encoding
framework is shown in Figure 5, along with the evolution of a spatial receptive field (RF) of an
LGN X cell over several seconds of exposure to a visual stimulus that induces adaptation.
Specifically, this particular example is of a retinal ganglion cell response in a
contrast switching experiment (data provided by Baccus and Meister). The left column
demonstrates that the gain and offset (theta) of the imposed model (top of figure) can be
estimated over a single trial of experimental data, as the contrast switching in panel A invokes
dramatic adaptation. The second column illustrates that the proper estimation/representation of
linear and nonlinear components of the encoding process is necessary to accurately capture the
true dynamics of the adaptation process.
We have established a recent collaboration with the laboratory of Dr. Jose-
Manuel Alonso in the Department of Optometry at SUNY, in Manhattan. In this collaboration,
we have been able to design experiments and collect data from the early visual pathway that
specifically address issues related to encoding during adaptation, both with artificial stimuli
designed to specifically probe contrast adaptation, and with natural scene stimuli.
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6.4 DETECTION:
The lateral geniculate nucleus (LGN) of the thalamus is the gateway to the
visual cortex, controlling the flow of visual information from the retina [for a review of LGN
function, see Sherman (2001a)]. Understanding the neural code of the LGN is an essential first
step in characterizing the processing of visual information in higher-level neurons.
After prolonged periods of hyperpolarization, voltage-dependent calcium
channels in the membrane of the neuron are de-inactivated, and subsequent depolarization causes
a stereotyped burst of closely spaced action potentials. It has been suggested that bursts serve to
signal the appearance of a salient stimulus (detection), whereas tonic firing relays detailed
features of the stimulus (transmission) (Crick, 1984; Guido et al., 1995). Bursts may serve as a
wake-up call, alerting the visual cortex to the presence of a stimulus in the receptive field (RF)
and signaling the beginning of tonic relay (Sherman, 2001b).
We investigated the role of LGN bursts in encoding correlated natural
stimuli by analyzing the responses of LGN neurons to natural scene movies. Across a sample of
LGN X-cells, a significant increase in bursting was observed during natural scene stimulation
(relative to white noise stimulation).
The stimulus features preceding burst events and tonic spikes were
characterized, revealing that the type of visual stimulus evoking a burst was fundamentally
different from that evoking tonic activity, and was in fact a feature characteristic of the
correlation structure of natural scenes. Taken together, our results support the detect/transmit
framework described above, and suggest that LGN bursts may be an important part of the neural
code of the LGN, providing an amplification of stimulus features that are typical of correlated
natural scenes.
The LGN resting membrane potential can vary widely according to behavioral
state, from its lowest level during sleep to its highest level during active waking (Hirsch et al.,
1983). We hypothesized that the resting potential would affect the particular features of the
visual stimulus that evoke bursts, and therefore be a function of behavioral state. In a recent
study with our collaborators (the laboratory of Dr. Jose-Manuel Alonso at SUNY), we
characterized the visual features that evoke bursts at different resting potentials using simulated
and experimental LGN responses to natural scene movies, and our results support this claim. To
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investigate the functional consequences of the effects of resting potential on burst generation, we
tested the effects of changes in resting potential on the extent to which bursts enhance the
detection of different visual features (Guido et al., 1995; Sherman, 2001a; Smith and Sherman,
2002). Although comparing the LGN response with and without bursts in vivo is not possible
(Porcello et al., 2003), these experiments can be simulated using an integrate-and-fire-or burst
(IFB) model, which can accurately reproduce the LGN response during both tonic and burst
firing (Smith et al., 2000; Lesica and Stanley, 2004). We simulated the LGN response to
different visual features at different resting potentials with and without the burst mechanism, and
compared the results using signal detection theory. Our results show that bursts enhance
detection of the onset of excitatory features at low resting potentials and the offset of inhibitory
features at high resting potentials, suggesting that bursts may play a dynamic role in visual
processing that changes with behavioral state.
Most recently, we have also developed algorithms that are inspired by the
transmit/detect framework of the early visual pathway, specifically for the robust relay of visual
information in situations with constraints on bandwidth.
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CHAPTER 7
INFORMATION TRANSMISSION
For decades, the visual receptive field (RF) has served as the fundamental building
block for our current understanding of the visual pathway (Kuffler, 1953; Hubel and Weisel,
1962). Spatiotemporal integration of visual stimuli, when combined with functional mechanisms
representative of non-linear spike generation, has been shown to be a good predictor of firing
rate for many neurons in the early visual pathway (Dan et al., 1996; Stanley, 2002). However,
the temporal resolution of the stimulus representation is limited by the photoreceptor
transduction process and takes place over a time course of tens to hundreds of milliseconds
(Barlow, 1952), limiting a receptive-field-based description of the firing rate to this relatively
coarse temporal scale.
In contrast, information theoretic studies of these same neurons reveal
significant temporal structure in the neural responses on the order of one millisecond (Reinagel
and Reid, 2000; Liu et al., 2001). The discrepancy of temporal scales between stimulus
representation and neural response has been the seed of a far ranging debate concerning temporal
precision and variability of neural responses, and their corresponding role in neural coding of
dynamic stimuli (e.g., de Ruyter van Steveninck et al. (1997); Warzecha and Egelhaaf (1999)).
Figure 8 shows the ability of a simple linear-nonlinear (LN) model to capture the firing activity
of an LGN neuron at a coarse temporal resolution (bottom), while failing at finer time
resolutions (middle).
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Fig 7: Raster of the spike times of a simulated LGN neuron to full-field Gaussian white noise,
with the resulting instantaneous spike rate (below, solid line) and LN prediction (dashed line), at
a binsize of 0.3 ms. Dashed horizontal line shows the mean firing rate. Bottom, actual (solid) and
LN model prediction (dashed) of firing rate at binsize of 8.3 ms.
In recent work, we have established a direct link between receptive field
descriptions of neurons and their information encoding properties by incorporating elements that
capture finer time resolutions into the relatively coarse representation of the receptive field. Such
a framework results in “sparse” representations with large fluctuations in firing rates that match
experimental observations, and thus provides an understanding of how elements of neural
encoding directly relate to information transmission.
Furthermore, these sparse representations translate into structure in the
neuronal response on time scales of the order of a millisecond. We have demonstrated that such
structure conveys a significant fraction of the total information about the stimulus. As a result,
two neurons with subtle differences in their receptive fields could produce distinct responses that
would be indistinguishable at coarse times scales, allowing information about small differences
in visual stimuli to be easily read out by downstream neurons.
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CHAPTER 8
ONGOING PROJECTS
8.1 ARGUS RETINAL PROSTHESIS:
Drs. Mark Humayun and Eugene DeJuan at the Doheny Eye Institute (USC) were
the original inventors of the active epi-retinal prosthesis and demonstrated proof of principle in
acute patient investigations at Johns Hopkins University in the early 90s. In the late 90s the
company Second Sight was formed to develop a chronically implantable retinal prosthesis. Their
first generation implant had 16 electrodes and was implanted in 6 subjects between 2002 and
2004. Five of these subjects still use the device in their homes today. These subjects, who were
all completely blind prior to implantation, can now perform a surprising array of tasks using the
device. More recently, the company announced that it has received FDA approval to begin a trial
of its second generation, 60 electrode implant, in the US. Additionally they have planned clinical
trials worldwide, all getting underway in 2007. Three major US government funding agencies
(National Eye Institute, Department of Energy, and National Science Foundation) have
supported the work at Second Sight and USC.
8.2 MICROSYSTEM-BASED VISUAL PROSTHESIS (MIVIP):
Designed by Claude Veraart at the University of Louvain, this is a spiral cuff
electrode around the optic nerve at the back of the eye. It is connected to a stimulator implanted
in a small depression in the skull. The stimulator receives signals from an externally-worn
camera, which are translated into electrical signals that stimulate the optic nerve directly.
8.3 IMPLANTABLE MINIATURE TELESCOPE:
Although not truly an active prosthesis, an Implantable Miniature Telescope is one
type of visual implant that has met with some success in the treatment of end-stage age-related
macular degeneration. This type of device is implanted in the eye's posterior chamber and works
by increasing (by about three times) the size of the image projected onto the retina in order to
overcome a centrally-located scotoma or blind spot.
8.4 TUBINGEN MPDA PROJECT:
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A Southern German team led by the University Eye Hospital in Tübingen, was
formed in 1995 by Eberhart Zrenner to develop a subretinal prosthesis. The chip is located
behind the retina and utilizes microphotodiode arrays (MPDA) which collect incident light and
transform it into electrical current stimulating the retinal ganglion cells. As natural
photoreceptors are far more efficient than photodiodes, visible light is not powerful enough to
stimulate the MPDA. Therefore, an external power supply is used to enhance the stimulation
current. The German team commenced in vivo experiments in 2000, when evoked cortical
potentials were measured from Yucatan micropigs and rabbits. At 14 months post implantation,
the implant and retina surrounding it were examined and there were no noticeable changes to
anatomical integrity. The implants were successful in producing evoked cortical potentials in
half of the animals tested. The thresholds identified in this study were similar to those required in
epiretinal stimulation. The latest reports from this group concern the results of a clinical pilot
study on eight participants suffering from RP. The results will be presented in detail on the
ARVO 2007 congress in Fort Lauderdale.
8.5 HARVARD/MIT RETINAL IMPLANT:
Joseph Rizzo and John Wyatt at MIT and the Massachusetts Eye and Ear
Infirmary have developed a stimulator chip that sits on the retina and is in turn stimulated by
signals beamed from a camera mounted on a pair of glasses. The stimulator chip decodes the
picture information beamed from the camera and stimulates retinal ganglion cells accordingly.
8.6 ARTIFICIAL SILICON RETINA (ASR):
The brothers Alan Chow and Vincent Chow have developed a microchip
containing 3500 solar cells, which detect light and convert it into electrical impulses, which
stimulate healthy retinal ganglion cells. The ASR requires no externally-worn devices.
8.7 OPTOELECTRONIC RETINAL PROSTHESIS:
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Daniel Palanker and his group at Stanford University have developed an
optoelectronic system for visual prosthesis that includes a subretinal photodiode array and an
infrared image projection system mounted on video goggles. Information from the video camera
is processed in a pocket PC and displayed on pulsed near-infrared (IR, 850-900 nm) video
goggles. IR image is projected onto the retina via natural eye optics, and activates photodiodes in
the subretinal implant that convert light into pulsed bi-phasic electric current in each pixel.
Current can be further increased by approximately an order of magnitude using a common bias
voltage provided by a radiofrequency-driven implantable power supply Close proximity between
electrodes and neural cells necessary for high resolution stimulation can be achieved utilizing
effect of retinal migration.
8.8 THE DOBELLE EYE:
Similar in function to the Harvard/MIT device, except the stimulator chip sits
in the primary visual cortex, rather than on the retina. Many subjects have been implanted with a
high success rate and limited negative effects. Still in the developmental phase, upon the death of
Dr. Dobelle, selling the eye for profit was ruled against in favor of donating it to a publicly
funded research team.
8.9 INTRACORTICAL VISUAL PROSTHESIS:
The Laboratory of Neural Prosthesis at Illinois Institute Of Technology
(IIT), Chicago, is developing a visual prosthetic using Intracortical Iridium Oxide (AIROF)
electrodes arrays. These arrays will be implanted on the occipital lobe. External hardware will
capture images, process them and generate instructions which will then be transmitted to
implanted circuitry via a telemetry link. The circuitry will decode the instructions and stimulate
the electrodes, in turn stimulating the visual cortex. The group is developing a wearable external
image capture and processing system. Studies on animals and psyphophysical studies on humans
are being conducted to test the feasibility of a human volunteer implant.
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CHAPTER 9
CONCLUSION
This is a revolutionary piece of technology and really has the potential to
change people's lives. Artificial Eye is such a revolution in medical science field. It’s good news
for patients who suffer from retinal diseases. A bionic eye implant that could help restore the
sight of millions of blind people could be available to patients within two years. Retinal implants
are able to partially restore the vision of people with particular forms of blindness caused by
diseases such as macular degeneration or retinitis pigmentosa. About 1.5 million people
worldwide have retinitis pigmentosa, and one in 10 people over the age of 55 have age-related
macular degeneration. The invention and implementation of artificial eye could help those
people.
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CHAPTER 10
REFERENCES
10.1 BOOKS:
1. Visual prosthesis: Edwin M. Maynard
Center for Neural Interfaces, Department of Bioengineering, University of Utah,
Salt Lake City, Utah 84112.
2. Visual Prosthesis : Artificial Vision
Brig A Banarji, Col VS Gurunadh, Col S Patyal, Col TS Ahluwalia, Maj Gen DP Vats, SM,
VSM,Col M Bhadauria (Retd).
10.2 WEBSITES:
http://www.google.com
http://www.wired.com
http://www.wikipedia.org
http:// [email protected]
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