We study how the circuitry of the retina translates the visual scene into electrical impulses in the optic nerve. Visual perception is initiated by the molecules, cells and synapses of the retina, acting together to process and compress visual information into a sequence of spikes in a population of nerve fibers. One of the largest gaps in neuroscience lies in the explaining of systems-level processes like visual processing in terms of cellular-level mechanisms. This problem is tractable in the retina because of its experimental accessibility, and the substantial amount already known about basic retinal cell types and functions.
Our goal is to extract general principles of computation in neural circuits, and to explain specific retinal visual processes such as adaptation to contrast and image statistics, and the detection of moving objects. To do this, we use a versatile set of experimental and theoretical techniques. While projecting visual scenes from a video monitor onto the isolated retina, an extracellular multielectrode array is used to record a substantial fraction of the output of a small patch of retina. Simultaneously, we record intracellularly from retinal interneurons in order to monitor and perturb single cells as the circuit operates. To measure the activity of both populations of interneurons and output neurons, we record visual responses optically using two-photon imaging while simultaneously recording with a multielectrode array. Finally, all of this data is assembled and interpreted in the context of mathematical models to predict and explain the output of the retinal
circuit.
An additional focus of the lab is to develop approaches to stimulate the nervous system using focused ultrasound. Recent studies have shown that ultrasound can activate the retina with high spatial and temporal precision. This technology holds promise as a noninvasive tool to study the brain and treat diseases of the nervous system both in the retina and elsewhere in the brain.
Focused ultrasound has been shown to stimulate excitable cells, but the biophysical mechanisms behind this phenomenon remain poorly understood. To provide additional insight, we devised a behavioral-genetic assay applied to the well-characterized nervous system of Caenorhabditis elegans nematodes. We found that pulsed ultrasound elicits robust reversal behavior in wild-type animals in a pressure-, duration-, and pulse protocol-dependent manner. Responses were preserved in mutants unable to sense thermal fluctuations and absent in mutants lacking neurons required for mechanosensation. Additionally, we found that the worm's response to ultrasound pulses rests on the expression of MEC-4, a DEG/ENaC/ASIC ion channel required for touch sensation. Consistent with prior studies of MEC-4-dependent currents in vivo, the worm's response was optimal for pulses repeated 300-1000 times per second. Based on these findings, we conclude that mechanical, rather than thermal, stimulation accounts for behavioral responses. Further, we propose that acoustic radiation force governs the response to ultrasound in a manner that depends on the touch receptor neurons and MEC-4-dependent ion channels. Our findings illuminate a complete pathway of ultrasound action, from the forces generated by propagating ultrasound to an activation of a specific ion channel. The findings further highlight the importance of optimizing ultrasound pulsing protocols when stimulating neurons via ion channels with mechanosensitive properties.SIGNIFICANCE STATEMENT How ultrasound influences neurons and other excitable cells has remained a mystery for decades. Although it is widely understood that ultrasound can heat tissues and induce mechanical strain, whether or not neuronal activation depends on heat, mechanical force, or both physical factors is not known. We harnessed Caenorhabditis elegans nematodes and their extraordinary sensitivity to thermal and mechanical stimuli to address this question. Whereas thermosensory mutants respond to ultrasound similar to wild-type animals, mechanosensory mutants were insensitive to ultrasound stimulation. Additionally, stimulus parameters that accentuate mechanical effects were more effective than those producing more heat. These findings highlight a mechanical nature of the effect of ultrasound on neurons and suggest specific ways to optimize stimulation protocols in specific tissues.
View details for DOI 10.1523/JNEUROSCI.1458-17.2018
View details for Web of Science ID 000428156900016
View details for PubMedID 29463641
View details for PubMedCentralID PMC5864152
View details for Web of Science ID 000434867200080
View details for Web of Science ID 000434867200065
Sensory stimuli have varying statistics influenced by both the environment and by active sensing behaviors that rapidly and globally change the sensory input. Consequently, sensory systems often adjust their neural code to the expected statistics of their sensory input to transmit novel sensory information. Here, we show that sudden peripheral motion amplifies and accelerates information transmission in salamander ganglion cells in a 50 ms time window. Underlying this gating of information is a transient increase in adaptation to contrast, enhancing sensitivity to a broader range of stimuli. Using a model and natural images, we show that this effect coincides with an expected increase in information in bipolar cells after a global image shift. Our findings reveal the dynamic allocation of energy resources to increase neural activity at times of expected high information content, a principle of adaptation that balances the competing requirements of conserving spikes and transmitting information.
View details for DOI 10.7554/eLife.09266
View details for Web of Science ID 000373848100001
View details for PubMedID 26568312
View details for PubMedCentralID PMC4749570
Computation in the brain involves multiple types of neurons, yet the organizing principles for how these neurons work together remain unclear. Information theory has offered explanations for how different types of neurons can maximize the transmitted information by encoding different stimulus features. However, recent experiments indicate that separate neuronal types exist that encode the same filtered version of the stimulus, but then the different cell types signal the presence of that stimulus feature with different thresholds. Here we show that the emergence of these neuronal types can be quantitatively described by the theory of transitions between different phases of matter. The two key parameters that control the separation of neurons into subclasses are the mean and standard deviation (SD) of noise affecting neural responses. The average noise across the neural population plays the role of temperature in the classic theory of phase transitions, whereas the SD is equivalent to pressure or magnetic field, in the case of liquid-gas and magnetic transitions, respectively. Our results account for properties of two recently discovered types of salamander Off retinal ganglion cells, as well as the absence of multiple types of On cells. We further show that, across visual stimulus contrasts, retinal circuits continued to operate near the critical point whose quantitative characteristics matched those expected near a liquid-gas critical point and described by the nearest-neighbor Ising model in three dimensions. By operating near a critical point, neural circuits can maximize information transmission in a given environment while retaining the ability to quickly adapt to a new environment.
View details for DOI 10.1073/pnas.1418092112
View details for PubMedID 25675497
View details for DOI 10.1371/journal.pbio.1001973
View details for Web of Science ID 000344461700012
The retina performs a diverse set of complex, nonlinear, computations, beyond the simple linear photoreceptor weighting assumed in the classical understanding of ganglion cell receptive fields. Here we attempt to organize these computations and extract rules that correspond to three distinct goals of early sensory systems. First, the retina acts efficiently to transmit information to the higher brain for further processing. We observe that although the retina adapts to a number of complex statistics, many of these may be explained by local adaptation to the mean signal strength at that stage. Second, ganglion cells signal the detection of a diverse set of features. Recent results indicate that feature selectivity arises through the action of specific inhibition, rather than through the convergence of excitation as in classical cortical models. Finally, the retina conveys predictions about the stimulus, a function usually attributed only to the higher brain. We expect that computational and mechanistic rules associated with these classes of functions will be an important guide in the study of other neural circuits.
View details for DOI 10.1016/j.conb.2013.11.012
View details for Web of Science ID 000335628800013
View details for PubMedID 24709602
Sensory systems change their sensitivity based on recent stimuli to adjust their response range to the range of inputs and to predict future sensory input. Here, we report the presence of retinal ganglion cells that have antagonistic plasticity, showing central adaptation and peripheral sensitization. Ganglion cell responses were captured by a spatiotemporal model with independently adapting excitatory and inhibitory subunits, and sensitization requires GABAergic inhibition. Using a simple theory of signal detection, we show that the sensitizing surround conforms to an optimal inference model that continually updates the prior signal probability. This indicates that small receptive field regions have dual functionality-to adapt to the local range of signals but sensitize based upon the probability of the presence of that signal. Within this framework, we show that sensitization predicts the location of a nearby object, revealing prediction as a functional role for adapting inhibition in the nervous system.
View details for DOI 10.1016/j.neuron.2013.06.011
View details for PubMedID 23932000
One of the largest mysteries of the brain lies in understanding how higher-level computations are implemented by lower-level operations in neurons and synapses. In particular, in many brain regions inhibitory interneurons represent a diverse class of cells, the individual functional roles of which are unknown. We discuss here how the operations of inhibitory interneurons influence the behavior of a circuit, focusing on recent results in the vertebrate retina. A key role in this understanding is played by a common representation of the visual stimulus that can be applied at different stages. By considering how this stimulus representation changes at each location in the circuit, we can understand how neuron-level operations such as thresholds and inhibition yield circuit-level computations such as how stimulus selectivity and gain are controlled by local and peripheral visual stimuli. Expected final online publication date for the Annual Review of Neuroscience Volume 36 is July 08, 2013. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
View details for DOI 10.1146/annurev-neuro-062012-170315
View details for PubMedID 23724996
Focused ultrasound is a promising noninvasive technology for neural stimulation. Here we use the isolated salamander retina to characterize the effect of ultrasound on an intact neural circuit and compared these effects with those of visual stimulation of the same retinal ganglion cells. Ultrasound stimuli at an acoustic frequency of 43 MHz and a focal spot diameter of 90 μm delivered from a piezoelectric transducer evoked stable responses with a temporal precision equal to strong visual responses but with shorter latency. By presenting ultrasound and visual stimulation together, we found that ultrasonic stimulation rapidly modulated visual sensitivity but did not change visual temporal filtering. By combining pharmacology with ultrasound stimulation, we found that ultrasound did not directly activate retinal ganglion cells but did in part activate interneurons beyond photoreceptors. These results suggest that, under conditions of strong localized stimulation, timing variability is largely influenced by cells beyond photoreceptors. We conclude that ultrasonic stimulation is an effective and spatiotemporally precise method to activate the retina. Because the retina is the most accessible part of the CNS in vivo, ultrasonic stimulation may have diagnostic potential to probe remaining retinal function in cases of photoreceptor degeneration, and therapeutic potential for use in a retinal prosthesis. In addition, because of its noninvasive properties and spatiotemporal resolution, ultrasound neurostimulation promises to be a useful tool to understand dynamic activity in pharmacologically defined neural pathways in the retina.
View details for DOI 10.1523/JNEUROSCI.3521-12.2013
View details for Web of Science ID 000315926300033
View details for PubMedID 23467371
In multiple sensory systems, adaptation to the variance of a sensory input changes the sensitivity, kinetics, and average response over timescales ranging from < 100 ms to tens of seconds. Here, we present a simple, biophysically relevant model of retinal contrast adaptation that accurately captures both the membrane potential response and all adaptive properties. The adaptive component of this model is a first-order kinetic process of the type used to describe ion channel gating and synaptic transmission. From the model, we conclude that all adaptive dynamics can be accounted for by depletion of a signaling mechanism, and that variance adaptation can be explained as adaptation to the mean of a rectified signal. The model parameters show strong similarity to known properties of bipolar cell synaptic vesicle pools. Diverse types of adaptive properties that implement theoretical principles of efficient coding can be generated by a single type of molecule or synapse with just a few microscopic states.
View details for DOI 10.1016/j.neuron.2011.12.029
View details for Web of Science ID 000301558600014
View details for PubMedID 22405209
Inhibitory interneurons help transform the input of a neural circuit into its output. Such interneurons are diverse, and most have unknown function. To study the function of single amacrine cells in the intact salamander retina, we recorded extracellularly from a population of ganglion cells with a multielectrode array, while simultaneously recording from or injecting current into single Off-type amacrine cells that had linear responses. We measured how visual responses of the amacrine cell interacted both with other visual input to the ganglion cell and with transmission between the two cells. We found that on average, visual responses from Off-type amacrine cells inhibited nearby Off-type ganglion cells. By recording and playing back the light-driven membrane potential fluctuations of amacrine cells during white noise visual stimuli, we found that paradoxically, increasing the light-driven modulations of inhibitory amacrine cells increased the firing rate of nearby Off-type ganglion cells. By measuring the correlations and transmission between amacrine and ganglion cells, we found that, on average, the amacrine cell hyperpolarizes before the ganglion cell fires, generating timed disinhibition just before the ganglion cell spikes. In addition, we found that amacrine to ganglion cell transmission is nonlinear in that increases in ganglion cell activity produced by amacrine hyperpolarization were greater than decreases in activity produced by amacrine depolarization. We conclude that the primary mode of action of this class of amacrine cell is to actively gate the ganglion cell response by a timed release from inhibition.
View details for DOI 10.1073/pnas.1107994108
View details for Web of Science ID 000296700000059
View details for PubMedID 22031693
The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization-a persistent elevated sensitivity following a strong stimulus. This newly observed dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails.
View details for DOI 10.1038/nn.2906
View details for Web of Science ID 000295254200021
View details for PubMedID 21909086
Our understanding of how mammalian sensory circuits are organized and develop has long been hindered by the lack of genetic markers of neurons with discrete functions. Here, we report a transgenic mouse selectively expressing GFP in a complete mosaic of transient OFF-alpha retinal ganglion cells (tOFF-alphaRGCs). This enabled us to relate the mosaic spacing, dendritic anatomy, and electrophysiology of these RGCs to their complete map of projections in the brain. We find that tOFF-alphaRGCs project exclusively to the superior colliculus (SC) and dorsal lateral geniculate nucleus and are restricted to a specific laminar depth within each of these targets. The axons of tOFF-alphaRGC are also organized into columns in the SC. Both laminar and columnar specificity develop through axon refinement. Disruption of cholinergic retinal waves prevents the emergence of columnar- but not laminar-specific tOFF-alphaRGC connections. Our findings reveal that in a genetically identified sensory map, spontaneous activity promotes synaptic specificity by segregating axons arising from RGCs of the same subtype.
View details for DOI 10.1016/j.neuron.2008.07.018
View details for Web of Science ID 000258565500011
View details for PubMedID 18701068
Certain ganglion cells in the retina respond sensitively to differential motion between the receptive field center and surround, as produced by an object moving over the background, but are strongly suppressed by global image motion, as produced by the observer's head or eye movements. We investigated the circuit basis for this object motion sensitive (OMS) response by recording intracellularly from all classes of retinal interneurons while simultaneously recording the spiking output of many ganglion cells. Fast, transient bipolar cells respond linearly to motion in the receptive field center. The synaptic output from their terminals is rectified and then pooled by the OMS ganglion cell. A type of polyaxonal amacrine cell is driven by motion in the surround, again via pooling of rectified inputs, but from a different set of bipolar cell terminals. By direct intracellular current injection, we found that these polyaxonal amacrine cells selectively suppress the synaptic input of OMS ganglion cells. A quantitative model of these circuit elements and their interactions explains how an important visual computation is accomplished by retinal neurons and synapses.
View details for DOI 10.1523/JNEUROSCI.4206-07.2008
View details for Web of Science ID 000257418300006
View details for PubMedID 18596156
Due to fixational eye movements, the image on the retina is always in motion, even when one views a stationary scene. When an object moves within the scene, the corresponding patch of retina experiences a different motion trajectory than the surrounding region. Certain retinal ganglion cells respond selectively to this condition, when the motion in the cell's receptive field center is different from that in the surround. Here we show that this response is strongest at the very onset of differential motion, followed by gradual adaptation with a time course of several seconds. Different subregions of a ganglion cell's receptive field can adapt independently. The circuitry responsible for differential motion adaptation lies in the inner retina. Several candidate mechanisms were tested, and the adaptation most likely results from synaptic depression at the synapse from bipolar to ganglion cell. Similar circuit mechanisms may act more generally to emphasize novel features of a visual stimulus.
View details for Web of Science ID 000251306600011
View details for PubMedID 18031685
In an effort to restore visual perception in retinal diseases such as age-related macular degeneration or retinitis pigmentosa, a design was recently presented for a high-resolution optoelectronic retinal prosthesis having thousands of electrodes. This system requires real-time image processing fast enough to convert a video stream of images into electrical stimulus patterns that can be properly interpreted by the brain. Here, we present image-processing and tracking algorithms for a subretinal implant designed to stimulate the second neuron in the visual pathway, bypassing the degenerated first synaptic layer. For this task, we have developed and implemented: 1) A tracking algorithm that determines the implant's position in each frame. 2) Image cropping outside of the implant boundaries. 3) A geometrical transformation that distorts the image appropriate to the geometry of the fovea. 4) Spatio-temporal image filtering to reproduce the visual processing normally occurring in photoceptors and at the photoreceptor-bipolar cell synapse. 5) Conversion of the filtered visual information into a pattern of electrical current. Methods to accelerate real-time transformations include the exploitation of data redundancy in the time domain, and the use of precomputed lookup tables that are adjustable to retinal physiology and allow flexible control of stimulation parameters. A software implementation of these algorithms processes natural visual scenes with sufficient speed for real-time operation. This computationally efficient algorithm resembles, in some aspects, biological strategies of efficient coding in the retina and could provide a refresh rate higher than fifty frames per second on our system.
View details for DOI 10.1109/TBME.2007.894828
View details for Web of Science ID 000246821500005
View details for PubMedID 17554819
In the vertebrate inner retina, the second stage of the visual system, different components of the visual scene are transformed, discarded, or selected before visual information is transmitted through the optic nerve. This review discusses the connections between higher-level functions of visual processing, mathematical descriptions of the neural code, inner retinal circuitry, and visual computations. In the inner plexiform layer, bipolar cells deliver spatially and temporally filtered input to approximately ten anatomical strata. These layers receive a unique combination of excitation and inhibition, causing cells in different layers to respond with different kinetics to visual input. These distinct temporal channels interact through amacrine cells, a diverse class of inhibitory interneurons, which transmit signals within and between layers. In particular, wide-field amacrine cells transmit transient inhibition over long distances within a layer. These mechanisms and properties are combined into computations to detect the presence of differential motion and suppress the visual effects of eye movements.
View details for DOI 10.1146/annurev.physiol.69.120205.124451
View details for Web of Science ID 000245334100015
View details for PubMedID 17059359
In this issue of Neuron, Nagel and Doupe make a quantitative assessment of temporal adaptation in the avian auditory forebrain, capturing seemingly complex responses with a simple linear-nonlinear (LN) model of kinetics and gain. A comparison of these findings with similar results in the early visual system shows an important unifying picture of efficient sensory processing and adaptation.
View details for DOI 10.1016/j.neuron.2006.09.007
View details for Web of Science ID 000240997900007
View details for PubMedID 16982414
Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode local differences in space and changes in time rather than the raw image intensity. This can be seen as a strategy of predictive coding, adapted through evolution to the average image statistics of the natural environment. Yet animals encounter many environments with visual statistics different from the average scene. Here we show that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new image statistics. We show that a network model with plastic synapses can account for the large variety of observed adaptations.
View details for DOI 10.1038/nature03689
View details for Web of Science ID 000230296600041
View details for PubMedID 16001064
It has been demonstrated that electrical stimulation of the retina can produce visual percepts in blind patients suffering from macular degeneration and retinitis pigmentosa. However, current retinal implants provide very low resolution (just a few electrodes), whereas at least several thousand pixels would be required for functional restoration of sight. This paper presents the design of an optoelectronic retinal prosthetic system with a stimulating pixel density of up to 2500 pix mm(-2) (corresponding geometrically to a maximum visual acuity of 20/80). Requirements on proximity of neural cells to the stimulation electrodes are described as a function of the desired resolution. Two basic geometries of sub-retinal implants providing required proximity are presented: perforated membranes and protruding electrode arrays. To provide for natural eye scanning of the scene, rather than scanning with a head-mounted camera, the system operates similar to 'virtual reality' devices. An image from a video camera is projected by a goggle-mounted collimated infrared LED-LCD display onto the retina, activating an array of powered photodiodes in the retinal implant. The goggles are transparent to visible light, thus allowing for the simultaneous use of remaining natural vision along with prosthetic stimulation. Optical delivery of visual information to the implant allows for real-time image processing adjustable to retinal architecture, as well as flexible control of image processing algorithms and stimulation parameters.
View details for PubMedID 15876646
View details for DOI 10.1088/1741-2560/2/1/012
View details for Web of Science ID 000209672200012
View details for DOI 10.1117/12.590964
View details for Web of Science ID 000229038000028
Human vision adapts to the contrast of patterns by changing its sensitivity, but the origins of this perceptual adaptation have been disputed. In this issue of Neuron, Solomon et al. show that contrast adaptation in the primate arises mostly in the retina for the magnocellular pathway and mostly in the cortex for the parvocellular pathway. It appears that adaptation arises most strongly at sites that pool over many inputs.
View details for Web of Science ID 000221458400003
View details for PubMedID 15066260
An important task in vision is to detect objects moving within a stationary scene. During normal viewing this is complicated by the presence of eye movements that continually scan the image across the retina, even during fixation. To detect moving objects, the brain must distinguish local motion within the scene from the global retinal image drift due to fixational eye movements. We have found that this process begins in the retina: a subset of retinal ganglion cells responds to motion in the receptive field centre, but only if the wider surround moves with a different trajectory. This selectivity for differential motion is independent of direction, and can be explained by a model of retinal circuitry that invokes pooling over nonlinear interneurons. The suppression by global image motion is probably mediated by polyaxonal, wide-field amacrine cells with transient responses. We show how a population of ganglion cells selective for differential motion can rapidly flag moving objects, and even segregate multiple moving objects.
View details for DOI 10.1038/nature01652
View details for Web of Science ID 000183012000033
View details for PubMedID 12754524
The visual system adapts to the magnitude of intensity fluctuations, and this process begins in the retina. Following the switch from a low-contrast environment to one of high contrast, ganglion cell sensitivity declines in two distinct phases: a fast change occurs in <0.1 s, and a slow decrease over approximately 10 s. To examine where these modulations arise, we recorded intracellularly from every major cell type in the salamander retina. Certain bipolar and amacrine cells, and all ganglion cells, adapted to contrast. Generally, these neurons showed both fast and slow adaptation. Fast effects of a contrast increase included accelerated kinetics, decreased sensitivity, and a depolarization of the baseline membrane potential. Slow adaptation did not affect kinetics, but produced a gradual hyperpolarization. This hyperpolarization can account for slow adaptation in the spiking output of ganglion cells.
View details for Web of Science ID 000179667800015
View details for PubMedID 12467594
