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Transcript of Artificial Eye
ARTIFICIAL EYE SEMINAR REPORT 2008
INTRODUCTION
A visual prosthetic or bionic eye 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 microtechnology 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
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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.
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
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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
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with intracortical stimulation. Joseph Wyatt and John Rizzo, III, the co-heads of the
Retinal Implant Project write, ". . . 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
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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 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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THE BIONIC 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.
The second incarnation of Second Sight's retinal prosthesis consists of five main parts:
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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 Dept. of Computer Engineering 7 GPTC
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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."
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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HISTORY
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.
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
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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.
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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.
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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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.
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
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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.
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.
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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
TECHNOLOGY OVERVIEW:
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 Dept. of Computer Engineering 14 GPTC
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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.
Figure 1. 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
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processing, estimation, prediction, and control-related problems that must be
overcome before such technology becomes truly viable. Despite the fact that the
anatomy and 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.
ENCODING OF NATURAL SCENES:
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)
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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
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.
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Figure 4. 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.
ADAPTATION:Dept. of Computer Engineering 18 GPTC
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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 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
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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.
DETECTION:
The lateral geniculate nucleus (LGN) of the thalamus is the
gateway to the visual cortex, controlling the flow of visual information from the
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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
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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 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
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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.
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.
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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).
Figure 8. 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.
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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.
ONGOING PROJECTS:
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 Dept. of Computer Engineering 25 GPTC
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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.
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.
IMPLANTABLE MINIATURE TELESCOPE:
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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.
TÜBINGEN MPDA PROJECT:
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
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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.
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.
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.
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OPTOELECTRONIC RETINAL PROSTHESIS:
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.
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.
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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.
THE VIRTUAL RETINAL DISPLAY (VRD):
Laser - based system for projecting an image directly onto the
retina. This could be useful for enhancing normal vision or bypassing an
occlusion such as a cataract, or a damaged cornea.
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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
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55 have age-related macular degeneration. The invention and implementation of
artificial eye could help those people.
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REFERENCES :
http://www.google.com
http://www.wired.com
http://www.wikipedia.org
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