Biology subjects

Litke, A. M.

Publications and source records attributed to Litke, A. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Electrical stimulation precisely reproduces naturalistic spiking activity in complete and intermixed neural populations in the primate retina

Neurostimulation technologies have the potential to restore complex brain functions by evoking naturalistic patterns of neural activity. However, faithfully mimicking the brains natural neural code in diverse neuron types remains an unsolved challenge. Here we exploit focal electrical stimulation and recording to reproduce natural visual signals at cellular resolution in two intermixed and oppositely-tuned neural populations in the isolated macaque retina. We calibrated and delivered electrical stimulation sequences to precisely mimic recorded visually-evoked responses to natural images in complete populations of ~50 ON and OFF parasol cells uniformly sampling ~4{degrees} x 4{degrees} of visual angle. Distinct and opposing visually-evoked response patterns in the two intermixed populations were closely replicated spike-by-spike in 5 retinal preparations using electrical stimulation, reproducing spike trains with 51 {+/-} 17% lower variability than repeated presentations of the same visual stimulus. Focal electrical stimulation also replicated traveling waves of neural activity in response to visual motion, and highly structured artificial response patterns. These findings demonstrate for the first time that neurostimulation can match or exceed biological signaling fidelity in large, complete and intermixed neural populations.

bioengineering↗

bioRxiv2026

Population decoding of sound source location by receptive field neurons in the mouse superior colliculus

Identifying the location of a sound source in a complex environment and assessing its importance can be crucial for survival. The superior colliculus (SC), a midbrain structure involved in sensorimotor functions, contributes to sound localization and contains auditory responsive neurons that have spatially restricted receptive fields (RFs) that are organized into a topographic map along the azimuth. However, individual auditory SC neurons have large spatial RFs, are noisy, and do not respond to the same stimulus at each trial. Therefore, when an animal is presented with a "single trial" sound, and it needs to rely on a single neuron to locate the sound source direction, the location measurement may be erroneous, missing, or have poor spatial resolution. It is expected that a more reliable and accurate determination of the sound source location will come from a population of neurons. We therefore built a population pattern Maximum Likelihood Estimation (MLE) decoder to build a model that can accurately predict the location of a stimulus given the population response. We compared three models that use either strict firing rate (FR), weighting based on equal (EW) or mutual information (MIW) and show that the MIW model works best, needing only 92 neurons to localize a stimulus with behaviorally relevant precision. Furthermore, by comparing the models fit using the responses from non-RF and RF auditory neurons, we show that only RF neurons contain the information needed to localize a sound source. These results are consistent with the hypothesis that the SC uses a population of RF neurons to determine sound source location. Author SummaryBeing able to tell where a sound is coming from and how important it is can be critical for survival. The superior colliculus, a midbrain region involved in orienting behaviors, contains neurons that respond best to sounds coming from specific locations. This suggests that the combined activity of many neurons in the SC is used to determine sound location from a single sound event. To test this idea, we modeled responses from mouse SC neurons while sounds were played from different positions in space, both along the elevation and horizon. A model that weighted the most informative neurons performed best in both directions needing only 92 neurons to localize a stimulus with behaviorally relevant precision along the azimuth. Comparing the models fit using the responses from non-RF and RF auditory neurons, we show that only RF neurons contain the information needed to localize a sound source Overall, our findings show that the SC can accurately locate sounds in both horizontal and vertical space using a population-based strategy, providing a simple and effective solution for rapid sound localization.

neuroscience↗

bioRxiv2025

Characterization of auditory responsive neurons in the mouse superior colliculus to naturalistic sounds

Locating the source of a specific sound in a complex environment and determining its saliency is critical for survival. The superior colliculus (SC), a sensorimotor midbrain structure, plays an important role in sound localization and has been shown to have a topographic map of the auditory space in a range of species. In mice, previous studies using broadband white noise stimuli found that neurons use high-frequency monaural spectral cues and interaural level differences (ILDs) to compute spatially restricted receptive fields (RFs), and that these RFs are organized topographically along the azimuth. However, in a naturalistic environment, the auditory stimuli that an animal encounters may have rich spectral components; however, these sound sources can still be localized efficiently. It remains unknown whether and how the SC neurons respond to naturalistic sounds and, in turn, compute a spatially restricted RF. Here, we show results from large-scale in vivo physiological recordings of SC neurons in response to white noise, naturalistic ultrasonic pup calls and chirps. We find that mouse SC auditory neurons respond to pup calls with distinct temporal patterns and a spatial preference predominantly at [~]60 degrees in contralateral azimuth. In addition, we categorized auditory SC neurons based on their spectrotemporal receptive field patterns and demonstrated that there are at least 4 distinct subtypes of auditory responsive SC neurons. Significance StatementThe superior colliculus (SC) receives visual and auditory information that is used to localize objects. While the organization and composition of visually responsive SC neurons is well described, much less is known about the types and response properties of auditory SC neurons. Here, we presented white noise, ultrasonic mouse pup calls, and chirp stimuli to mice while recording from SC neurons. Analysis of neuronal responses defines 4 distinct classes of auditory neurons. We also show that while auditory neurons respond to naturalistic stimuli, these responses mainly occur when presented from the side but not the front of the animal. These results lead to the hypothesis that mice use different strategies to localize sound depending on the spectral composition of the source.

neuroscience↗

bioRxiv2024

Understanding responses to multi-electrode epiretinal stimulation using a biophysical model

ObjectiveNeural interfaces are designed to evoke specific patterns of electrical activity in populations of neurons by stimulating with many electrodes. However, currents passed simultaneously through multiple electrodes often combine nonlinearly to drive neural responses, making evoked responses difficult to predict and control. This response nonlinearity could arise from the interaction of many excitable sites in each cell, any of which can produce a spike. However, this multi-site activation hypothesis is difficult to verify experimentally. ApproachWe developed a biophysical model to study retinal ganglion cell (RGC) responses to multi-electrode stimulation and validated it using data collected from ex vivo preparations of the macaque retina using a microelectrode array (512 electrodes; 30{micro}m pitch; 10{micro}m diameter). ResultsFirst, the model was validated by using it to reproduce essential empirical findings from single-electrode recording and stimulation, including recorded spike voltage waveforms at multiple locations and sigmoidal responses to injected current. Then, stimulation with two electrodes was modeled to test how the positioning of the electrodes relative to the cell affected the degree of response nonlinearity. Currents passed through pairs of electrodes positioned near the cell body or far from the axon (>40 {micro}m) exhibited approximately linear summation in evoking spikes. Currents passed through pairs of electrodes close to the axon summed linearly when their locations along the axon were similar, and nonlinearly otherwise. Over a range of electrode placements, several distinct, localized spike initiation sites were observed, and the number of these sites covaried with the degree of response nonlinearity. Similar trends were observed for three-electrode stimuli. All of these trends in the simulation were consistent with experimental observations. Significance. These findings support the multi-site activation hypothesis for nonlinear activation of neurons, providing a biophysical interpretation of previous experimental results and potentially enabling more efficient use of multi-electrode stimuli in future neural implants.

bioengineering↗

bioRxiv2024

Modeling responses of macaque and human retinal ganglion cells to natural images using a convolutional neural network

Linear-nonlinear (LN) cascade models provide a simple way to capture retinal ganglion cell (RGC) responses to artificial stimuli such as white noise, but their ability to model responses to natural images is limited. Recently, convolutional neural network (CNN) models have been shown to produce light response predictions that were substantially more accurate than those of a LN model. However, this modeling approach has not yet been applied to responses of macaque or human RGCs to natural images. Here, we train and test a CNN model on responses to natural images of the four numerically dominant RGC types in the macaque and human retina - ON parasol, OFF parasol, ON midget and OFF midget cells. Compared with the LN model, the CNN model provided substantially more accurate response predictions. Linear reconstructions of the visual stimulus were more accurate for CNN compared to LN model-generated responses, relative to reconstructions obtained from the recorded data. These findings demonstrate the effectiveness of a CNN model in capturing light responses of major RGC types in the macaque and human retinas in natural conditions.

neuroscience↗

bioRxiv2023

Decomposition of retinal ganglion cell electrical images for cell type and functional inference

ObjectiveIdentifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and for the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. ApproachThe electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. ResultsThe decomposition was evaluated using large-scale multi-electrode recordings from the macaque retina. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells) substantially more accurately than previous approaches. SignificanceThese findings contribute to more accurate inference of RGC types and their original light responses based purely on their electrical features, with potential implications for vision restoration technology.

neuroscience↗

bioRxiv2023

Fixational Eye Movements Enhance the Precision of Visual Information Transmitted by the Primate Retina

Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the retinal signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of retinal ganglion cells (RGCs) in the macaque retina (male), combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provides an interpretable framework for characterizing the retinal signal. Reconstructions were improved with artificial stimulus jitter that emulated fixational eye movements, even when the eye movement trajectory was assumed to be unknown and had to be inferred from retinal spikes. Reconstructions were degraded by small artificial perturbations of spike times, revealing more precise temporal encoding than suggested by previous studies. Finally, reconstructions were substantially degraded when derived from a model that ignored cell-to-cell interactions, indicating the importance of stimulusevoked correlations. Thus, fixational eye movements enhance the precision of the retinal representation.

neuroscience↗

bioRxiv2022

Inferring light responses of primate retinal ganglion cells using intrinsic electrical signatures

Reproducing high-acuity vision with an epiretinal implant will likely require inferring the natural light responses of diverse RGC types in the implanted retina, without measuring them directly. Here we demonstrate an approach that exploits intrinsic electrical features of primate RGCs. First, ON-parasol and OFF-parasol RGCs were identified with 95% accuracy using electrical features. Then, the somatic electrical footprint, predicted cell type, and average linear-nonlinear-Poisson model parameters of each cell type were used to infer a light response model for each cell. Across five retinas, these models achieved an average correlation with measured firing rates of 0.49 for white noise visual stimuli and 0.50 for natural scenes stimuli, compared to 0.65 and 0.58 respectively for models fitted to recorded light responses, an upper bound. This finding, and linear decoding of images from predicted RGC activity, suggested that the inference approach may be useful for high-fidelity sight restoration.

neuroscience↗

bioRxiv2022

High-fidelity restoration of visual signals by electrical stimulation in the central primate retina

Electrical stimulation of retinal ganglion cells (RGCs) with electronic implants provides rudimentary artificial vision to people blinded by retinal degeneration. However, current devices stimulate indiscriminately and therefore cannot reproduce the intricate neural code of the retina. Recent work has demonstrated more precise activation of RGCs using focal electrical stimulation with multi-electrode arrays in the peripheral macaque retina, but it is unclear how effective this can be in the central retina, which is required for high-resolution vision. This work probes the neural code and effectiveness of focal epiretinal stimulation in the central macaque retina, using large-scale electrical recording and stimulation ex vivo. The functional organization, light response properties, and electrical properties of the major RGC types in the central retina were mostly similar to the peripheral retina, with some notable differences in density, kinetics, linearity, spiking statistics and correlations. The major RGC types could be distinguished by their intrinsic electrical properties. Electrical stimulation targeting parasol cells revealed similar activation thresholds and reduced axon bundle activation in the central retina, but lower stimulation selectivity. Quantitative evaluation of the potential for image reconstruction from electrically-evoked parasol cell signals revealed higher overall expected image quality in the central retina. An exploration of inadvertent midget cell activation suggested that it could contribute high spatial frequency noise to the visual signal carried by parasol cells. These results support the possibility of reproducing high-acuity visual signals in the central retina with an epiretinal implant. Significance StatementArtificial restoration of vision with retinal implants is a major treatment for blindness. However, present-day implants do not provide high-resolution visual perception, in part because they do not reproduce the natural neural code of the retina. Here we demonstrate the level of visual signal reproduction that is possible with a future implant by examining how accurately responses to electrical stimulation of parasol retinal ganglion cells (RGCs) can convey visual signals. Although the precision of electrical stimulation in the central retina was diminished relative to the peripheral retina, the quality of expected visual signal reconstruction in parasol cells was greater. These findings suggest that visual signals could be restored with high fidelity in the central retina using a future retinal implant.

neuroscience↗

bioRxiv2022

Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors

Visual information arriving at the retina is transmitted to the brain by signals in the optic nerve, and the brain must rely solely on these signals to make inferences about the visual world. Previous work has probed the content of these signals by directly reconstructing images from retinal activity using linear regression or nonlinear regression with neural networks. Maximum a posteriori (MAP) reconstruction using retinal encoding models and separately-trained natural image priors offers a more general and principled approach. We develop a novel method for approximate MAP reconstruction that combines a generalized linear model for retinal responses to light, including their dependence on spike history and spikes of neighboring cells, with the image prior implicitly embedded in a deep convolutional neural network trained for image denoising. We use this method to reconstruct natural images from ex vivo simultaneously-recorded spikes of hundreds of retinal ganglion cells uniformly sampling a region of the retina. The method produces reconstructions that match or exceed the state-of-the-art in perceptual similarity and exhibit additional fine detail, while using substantially fewer model parameters than previous approaches. The use of more rudimentary encoding models (a linear-nonlinear-Poisson cascade) or image priors (a 1/f spectral model) significantly reduces reconstruction performance, indicating the essential role of both components in achieving high-quality reconstructed images from the retinal signal.

neuroscience↗

bioRxiv2021

Efficient Inference of Sensitivity to Electrical Stimulation from Intrinsic Electrical Properties of Primate Retinal Ganglion Cells

High-fidelity electronic implants can in principle restore the function of neural circuits by precisely activating neurons via extracellular stimulation. However, direct characterization of the individual electrical responses of a large population of target neurons, in order to precisely control their activity, is often difficult or impossible. A potential solution is to leverage biophysical principles to infer sensitivity to electrical stimulation from features of spontaneous electrical activity, which can be recorded relatively easily. Here, this approach is developed and its potential value for vision restoration is tested quantitatively using large-scale high-density stimulation and recording from primate retinal ganglion cells (RGCs) ex vivo. Electrodes recording larger spikes from a given cell exhibited lower stimulation thresholds, with distinct trends for somas and axons, across cell types, retinas, and eccentricities. Thresholds for somatic stimulation increased with distance from the axon initial segment. The dependence of spike probability on injected current was inversely related to threshold, and was substantially steeper for axonal than somatic compartments, which could be identified by recorded electrical signatures. Dendritic stimulation was largely ineffective for eliciting spikes. These findings were quantitatively reproduced with biophysical simulations, and confirmed in tests on human RGCs. The inference of stimulation sensitivity from recorded electrical features was tested in simulated visual reconstruction, and revealed that the approach could significantly improve the function of future high-fidelity retinal implants.

neuroscience↗

bioRxiv2021

High-frequency hearing is required for generating a topographic map of auditory space in the mouse superior colliculus

A topographic map of auditory space is a feature found in the superior colliculus (SC) of many species, including CBA/CaJ mice. In this genetic background, high-frequency monaural spectral cues and interaural level differences are used to generate spatial receptive fields (RFs) that form a topographic map along the azimuth. Unfortunately, C57BL/6 mice, a strain widely used for transgenic manipulation, display age-related hearing loss (AHL) due to an inbred mutation in the Cadherin 23 gene (Cdh23) that affects hair cell mechanotransduction. To overcome this problem, researchers have used young C57BL/6 mice in their studies, as they have been shown to have normal hearing thresholds. However, important details of the auditory response characteristics of the SC such as spectral responses and spatial localization, have not been characterized in young C57BL/6 mice. Here we show that 2-4-month C57BL/6 mice lack neurons with frontal auditory RFs and therefore lack a topographic representation of auditory space in the SC. Analysis of the spectrotemporal receptive fields (STRFs) of the SC auditory neurons shows that C57BL/6 mouse SC neurons lack the ability to detect the high-frequency (>40kHz) spectral cues that are needed to compute frontal RFs. We also show that crossing C57BL/6 mice with CBA/CaJ mice or introducing one copy of the wild-type Cdh23 to C57BL/6 mice rescues the high-frequency hearing deficit and improves the topographic map of auditory space. Taken together, these results demonstrate the importance of high-frequency hearing in computing a topographic map of auditory space. Significance StatementDespite the strains age-dependent hearing loss, C57BL/6 mice are widely used in auditory studies because of the development of transgenic reporter and Cre lines in this genetic background. Here we examined the topographic map of auditory space and spectrotemporal properties of neurons in the SC of C57BL/6 mice. We found an early-onset high-frequency hearing deficit that results in the loss of SC neurons with frontal RFs and, consequently, an absence of a topographic map of auditory space. These findings stress the importance of high-frequency hearing in generating spatially restricted receptive fields and serve as a caution to researchers that doing auditory-related research using the C57BL/6 genetic background may not be representative of true wild-type mice.

neuroscience↗

bioRxiv2021

Spatially Patterned Bi-electrode Epiretinal Stimulation for Axon Avoidance at Cellular Resolution

ObjectiveEpiretinal prostheses are designed to restore vision to people blinded by photoreceptor degenerative diseases by stimulating surviving retinal ganglion cells (RGCs), which carry visual signals to the brain. However, inadvertent stimulation of RGCs at their axons can result in non-focal visual percepts, limiting the quality of artificial vision. Theoretical work has suggested that axon activation can be avoided with current stimulation designed to minimize the second spatial derivative of the induced extracellular voltage along the axon. However, this approach has not been verified experimentally at the resolution of single cells. Approach. In this work, a custom multi-electrode array (512 electrodes, 10 m diameter, 60 m pitch) was used to stimulate and record RGCs in macaque retina ex vivo at single-cell, single-spike resolution. RGC activation thresholds resulting from bi-electrode stimulation, which consisted of bipolar currents simultaneously delivered through two electrodes straddling an axon, were compared to activation thresholds from traditional single-electrode stimulation. ResultsOn average, across three retinal preparations, the bi-electrode stimulation strategy reduced somatic activation thresholds ([~]21%) while increasing axonal activation thresholds ([~]14%), thus favoring selective somatic activation. Furthermore, individual examples revealed rescued selective activation of somas that was not possible with any individual electrode. Significance. This work suggests that a bi-electrode epiretinal stimulation strategy can reduce inadvertent axonal activation at cellular resolution, for high-fidelity artificial vision. Novelty & SignificanceThe effectiveness of bi-electrode stimulation for enhancing the electrical activation of retinal neurons was tested using high-density multi-electrode recording and stimulation in isolated macaque retina. The results suggest that spatially patterned bi-electrode stimuli reduce unwanted axon activation and thus improve the selectivity of stimulation at cellular resolution. Similar patterns could be implemented in a future high-resolution prosthesis to permit a more faithful replication of normal retinal activity, at the resolution of single-cells and single-spikes, for the treatment of incurable blindness.

bioengineering↗

bioRxiv2021

Live whole-eye, ex vivo imaging and laser-induced micro injury of the corneal basal epithelium and visualization of resident macrophage responses

PurposeIn this paper, we describe a novel live-imaging approach to visualize the short-term response of the mouse cornea to basal epithelial cell damage. Laser scanning confocal microscopy was used to induce precisely-defined, localized corneal basal epithelial cell damage and the live macrophage response to this damage was visualized and analyzed. MethodsLipophilic fluorescent dyes, SGC5 or FM 4-64, were injected into the anterior chamber of enucleated eyes and imaged live in whole-mount using confocal laser scanning microscopy. Laser-induced damage was performed by focusing onto a defined region of the corneal basal epithelium for a brief period using a high laser power setting and then returning to low laser power for imaging. Eyes from CX3CR1+/GFP mice were used to observe macrophage responses to laser damage in real-time. ResultsSGC5 or FM 4-64 dyes injected into the anterior chamber readily enter the cornea and are taken up by the stromal layer and labeled the outer membranes of corneal epithelial cells and remained stable when visualized using low laser power. Subjecting a defined region of the basal epithelium to high laser power for 1 minute or longer led to a rapid internalization of dye in the exposed basal epithelium cells and overall increase in cellular fluorescence. This change in fluorescence was also accompanied by cell swelling and contraction. Cellular internalization of the non-lipophilic, dye Alexa 647 hydrazide, indicated that membranes were compromised indicating that exposure to high power laser stimulation causes cellular damage to the basal epithelium. Visualization of corneal resident macrophages close to the site of laser-induced damage showed that within minutes, projecting macrophage filopodia extended towards the damaged region at a rate of 0.75{micro}m/min for roughly 40 minutes. ConclusionWe have developed a novel approach to image the live cornea and its response to damage. Laser-scanning confocal microscopy can be utilized to induce localized damage to mouse corneal basal epithelium and elicit a macrophage morphological response. This approach represents a useful tool for studying corneal wound healing and cellular responses to damage using live whole-mount imaging.

cell biology↗

bioRxiv2021

Automatic Identification and Avoidance of Axon Bundle Activation for Epiretinal Prosthesis

Retinal prostheses must be able to activate cells in a selective way in order to restore high-fidelity vision. However, inadvertent activation of far-away retinal ganglion cells (RGCs) through electrical stimulation of axon bundles can produce irregular and poorly controlled percepts, limiting artificial vision. Therefore, the problem of axon bundle activation can be defined as the axonal stimulation of RGCs with unknown soma and receptive field locations, typically outside the electrode array. Here, a new algorithm is presented that utilizes electrical recordings to determine the stimulation current amplitudes above which bundle activation occurs. The method exploits several spatiotemporal characteristics of electrically-evoked spikes to overcome the challenge of detecting small axonal spikes in extracellular recordings. The algorithm was validated using large-scale ex vivo stimulation and recording experiments in macaque retina, by comparing algorithmically and manually identified bundle activation thresholds. The algorithm could be used in a closed-loop manner by a future epiretinal prosthesis to reduce poorly controlled visual percepts associated with bundle activation. The method may also be applicable to other types of retinal implants and to cortical implants. ContributionsPT developed the algorithm and analyzed the data, with input from SMi and EJC. NB and NS helped with the analysis. SMa and LG performed dissections and collected the data. PT and VFH performed manual identification. PH, AS and AML developed and supported recording hardware and software. PT, EJC and SMi wrote the manuscript. NS and SMa edited it. EJC and SMi supervised the project.

bioengineering↗

bioRxiv2021

Nonlinear visuoauditory integration in the mouse superior colliculus

Sensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.

neuroscience↗

bioRxiv2020

Focal Electrical Stimulation of Human Retinal Ganglion Cells

Vision restoration with retinal implants that electrically stimulate retinal ganglion cells (RGCs), which transmit visual information to the brain, is limited by indiscriminate activation of many cells and cell types. Recent work in isolated macaque retina has demonstrated that direct electrical stimulation of RGCs can be performed with single-cell, single-spike resolution. However, the fidelity of epiretinal stimulation has not been examined in the human retina. Here, electrical activation of the major RGC types was examined using large-scale, multi-electrode recording and stimulation in the human retina ex vivo and compared directly to results from macaque. Targeted activation with single-cell, single-spike resolution was often possible without activating overlying axon bundles, at low stimulation current levels similar to those in macaque. Distinct cell types could be identified and targeted based on their distinct electrical signatures. Simulation based on these measurements revealed that a novel, dynamic stimulation approach would produce a nearly optimal evoked visual signal. These results indicate that high-fidelity control of spiking in human RGCs is achievable with extracellular stimulation and that the macaque retina is an accurate model for vision restoration with epiretinal implants.

neuroscience↗

bioRxiv2020

Reconstruction of natural images from responses of primate retinal ganglion cells

The visual message conveyed by a retinal ganglion cell (RGC) is often summarized by its spatial receptive field, but in principle also depends on the responses of other RGCs and natural image statistics. This possibility was explored by linear reconstruction of natural images from responses of the four numerically-dominant macaque RGC types. Reconstructions were highly consistent across retinas. The optimal reconstruction filter for each RGC - its visual message - reflected natural image statistics, and resembled the receptive field only when nearby, same-type cells were included. ON and OFF cells conveyed largely independent, complementary representations, and parasol and midget cells conveyed distinct and expected features. Correlated activity and nonlinearities had statistically significant but minor effects on reconstruction. Simulated reconstructions, using linear-nonlinear cascade models of RGC light responses that incorporated measured spatial properties and nonlinearities, produced similar results. Spatiotemporal reconstructions exhibited similar spatial properties, suggesting that the results are relevant for natural vision.

neuroscience↗