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

Shah, Nikhil D.; Brackbill, Nora; Rhoades, Colleen; Kling, Alexandra; Goetz, Georges; Litke, A. M.; Sher, Alexander; Ep, Simoncelli; Chichilnisky, E. J.

doi:10.1101/496422

Cited by 6 publications

(6 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Attempts of modelling a neural system of interest are ubiquitous in neuroscience in general and in neural prosthetics in particular. An appropriate encoding model allows to predict the system's response to an input, and to draw inferences about the elements of the system [52][53][54] . Furthermore, it can be used to find optimal stimuli that maximally activate a target neuron 55 .…”

Section: Discussionmentioning

confidence: 99%

Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina

Hoefling

Berens

Zeck

2019

Preprint

View full text Add to dashboard Cite

Retinal implants are used to replace lost photoreceptors in blind patients suffering from retinopathies such as retinitis pigmentosa. Patients wearing implants regain some rudimentary visual function. However, it is severely limited compared to normal vision because non-physiological stimulation strategies fail to selectively activate different retinal pathways at sufficient spatial and temporal resolution. The development of improved stimulation strategies is rendered difficult by the large space of potential stimuli. Here we systematically explore a subspace of potential stimuli by electrically stimulating healthy and blind mouse retina in epiretinal configuration using smooth Gaussian white noise delivered by a high-density CMOS-based microelectrode array. We identify linear filters of retinal ganglion cells (RGCs) by fitting a linear-nonlinear-Poisson (LNP) model. Our stimulus evokes fast, reliable, and spatially confined spiking responses in RGC which are accurately predicted by the LNP model. Furthermore, we find diverse shapes of linear filters in the linear stage of the model, suggesting diverse preferred electrical stimuli of RGCs. Our smooth electrical stimulus could provide a starting point of a model-guided search for improved stimuli for retinal prosthetics.

show abstract

Section: Discussionmentioning

confidence: 99%

Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina

Hoefling

Berens

Zeck

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Given that the observed hotspots combine nonlinearly, a computational procedure that identifies the nonlinear subunits in the RF should also identify the RF hotspots (Liu et al, 2017). To test this prediction, a computational model designed to extract the spatial structure of nonlinear subunits was used (Shah et al, 2018).…”

Section: Subunit Estimation Through Spike-triggered Stimulus Clusteringmentioning

confidence: 99%

“…The subunit model construction and fitting approach were described in Shah et al, 2018. Briefly, the model was fit using an alternating cascade of two linear-nonlinear stages with a Poisson firing rate.…”

Section: Spiking Response Model Fittingmentioning

confidence: 99%

Unusual physiological properties of two ganglion cell types in primate retina

Rhoades

Shah

Manookin

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

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. Receptive field properties of simultaneously recorded retinal ganglion cell typesTo explore the properties of poorly understood RGC types, large-scale multi-electrode recordings were used to simultaneously record the light responses of hundreds of RGCs

show abstract

“…Furthermore, even within a single species, visual input statistics and behavioural demands can be very different across the visual field, and studies have shown that retinal circuits also strongly vary across the retinal surface 1,2, 10,11 . These considerations have sparked a new wave of studies probing retinal circuit organization in the context of its function, assessed using natural rather than artificial inputs 4, 13,14 .…”

mentioning

confidence: 99%