Biology subjects

Rhoades, C. E.

Publications and source records attributed to Rhoades, C. E..

6 recordsLinked to original sources

bioRxiv2025

Cell-type specific repertoire of responses to natural scenes in primate retinal ganglion cells

At least 20 distinct retinal ganglion cells (RGC) types have been identified morphologically in the primate retina, but our understanding of the distinctive visual messages they send to various targets in the brain remains limited. Here, we use large-scale multi-electrode array recordings to examine how multiple functionally-distinct RGC types in the macaque retina respond to flashed natural images. Responses to white noise visual stimulation were used to functionally identify 936 RGCs of 12 types in three recordings. Each cell type was confirmed by the mosaic organization of receptive fields, and 7 cell types were cross-identified between recordings. The average kinetics of light response in each RGC type as well as the repertoire of distinct firing patterns that each type produces were examined across thousands of natural images. The kinetics of the average response across images were highly stereotyped among cells of each cell type and distinct for cells of different types. Moreover, the full repertoires of firing patterns produced by different cell types, assessed by their latency and duration, were generally quite distinct with only a few exceptions. Together these data provide an overview of the range of responses to natural images transmitted from the primate retina to the brain.

neuroscience↗

bioRxiv2024

Functional diversity in the output of the primate retina

The visual image transmitted by the retina to the brain has long been understood in terms of spatial filtering by the center-surround receptive fields of retinal ganglion cells (RGCs). Recently, this textbook view has been challenged by the stunning functional diversity and specificity observed in [~]40 distinct RGC types in the mouse retina. However, it is unclear whether the [~]20 morphologically and molecularly identified RGC types in primates exhibit similar functional diversity, or instead exhibit center-surround organization at different spatial scales. Here, we reveal striking and surprising functional diversity in macaque and human RGC types using large-scale multi-electrode recordings from isolated macaque and human retinas. In addition to the five well-known primate RGC types, 18-27 types were distinguished by their functional properties, likely revealing several previously unknown types. Surprisingly, many of these cell types exhibited striking non-classical receptive field structure, including irregular spatial and chromatic properties not previously reported in any species. Qualitatively similar results were observed in recordings from the human retina. The receptive fields of less-understood RGC types formed uniform mosaics covering visual space, confirming their classification, and the morphological counterparts of two types were established using single-cell recording. The striking receptive field diversity was paralleled by distinctive responses to natural movies and complexity of visual computation. These findings suggest that diverse RGC types, rather than merely filtering the scene at different spatial scales, instead play specialized roles in human vision.

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↗

bioRxiv2018

Unusual physiological properties of two ganglion cell types in primate retina

The visual functions of the diverse retinal ganglion cell types in the primate retina, and the parallel visual pathways they initiate, remain poorly understood. Here, the unusual physiological and computational properties of the ON and OFF smooth monostratified (SM) ganglion cells are explored. Large-scale multi-electrode recordings from 48 macaque retinas revealed that these cells exhibited strikingly irregular receptive field structure composed of spatially segregated hotspots, quite different from the receptive fields of previously described retinal ganglion cell types. The ON and OFF SM cells are paired cell types, but OFF SM cells exhibited stronger hotspot structure than ON cells. Targeted visual stimulation and computational inference demonstrate strong nonlinear subunit properties of each hotspot that contributed to the signaling properties of SM cells. Analysis of shared inputs to neighboring SM cells indicated that each hotspot could not be explained by an individual presynaptic input. Surprisingly, visual stimulation of different hotspots produced subtly different spatiotemporal spike waveforms in the same SM cell, consistent with a dendritic contribution to hotspot structure. These findings point to a previously unreported nonlinear mechanism in the output of the primate retina that contributes to signaling spatial information.

neuroscience↗

bioRxiv2018

Inference of Nonlinear Spatial Subunits by Spike-Triggered Clustering in Primate Retina

Integration of rectified synaptic inputs is a widespread nonlinear motif in sensory neuroscience. We present a novel method for maximum likelihood estimation of nonlinear subunits by soft-clustering spike-triggered stimuli. Subunits estimated from parasol ganglion cells recorded in macaque retina partitioned the receptive field into compact regions, likely representing bipolar cell inputs. Joint clustering with multiple RGCs revealed shared subunits in neighboring cells, producing a parsimonious population model. Closed-loop subunit validation was then performed by projecting white noise into the null space of the linear receptive field. Responses to these null stimuli were more accurately explained by a model with multiple subunits, and were stronger in OFF cells than ON cells. Presentation of natural stimuli containing jittering edges and textures also revealed greater response prediction accuracy with the subunit model. Finally, the generality of the approach was demonstrated by application to V1 data.

neuroscience↗