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The center-surround receptive field of retinal ganglion cells represents a fundamental concept for how the retina processes and encodes visual information. Yet, traditional approaches of using the receptive field as a linear filter to integrate light intensity over space often do not capture the responses of a ganglion cell to complex visual stimuli. Thus, models with local nonlinearities in subunits of the receptive field or with local temporal dynamics are emerging to better reflect relevant aspects of retinal circuitry and capture stimulus encoding. Here, we review recent efforts to identify such receptive-field substructure and evaluate its role in visual stimulus encoding. The concomitant development of new computational tools may pave the way toward a model-based, functional approach to retinal circuit analysis.

Bernstein Conference 2022 abstract. http://bernstein-conference.de

Bernstein Conference 2022 abstract. http://bernstein-conference.de

Waves of spontaneous activity sweep across the neonatal mouse retinal ganglion cell (RGC) layer, driven by directly interconnected cholinergic starburst amacrine cells (the only known retinal cholinergic cells) from postnatal day (P) 0-10, followed by waves driven by glutamatergic bipolar cells. We found transient clusters of cholinergic RGC-like cells around the optic disc during the period of cholinergic waves. They migrate towards the periphery between P2-9 and then they disappear. Pan-retinal multielectrode array recordings reveal that cholinergic wave origins follow a similar developmental center-to-periphery pattern. Electrical imaging unmasks hotspots of dipole electrical activity occurring in the vicinity of wave origins. We propose that these activity hotspots are sites for wave initiation and are related to the cholinergic cell clusters, reminiscent of activity in transient subplate neurons in the developing cortex, suggesting a universal hyper-excitability mechanism in developing CNS networks during the critical period for brain wiring.

Recent studies have pointed out that the neural code may use multiplexing to encode unique information at different temporal. Here we investigate in detail the information encoded in the spiking activity of a neuron by computing the unique contribution that each temporal scale makes to it. We do this by analytically inferring the derivative of the information with respect to the precision with which the neural response is measured. We propose the Information Jitter Derivative (IJD) method, which uses a jitter approach to modify the precision of the neural response. The IJD allows to infer the temporal scales playing a relevant role in the encoding of the information contained in the response of a neuron to a given set of stimuli. We validated the IJD on simulated data. We further demonstrated its usefulness on real neural responses recorded from the retinal ganglion cells (RGCs) of the axolotl salamander and show that these cells carry the information about fine and coarse features of a visual scene using different temporal scales., Presented at the Brains and Bits workshop, at the NIPS Conference, Barcelona, December, 2016. http://www.stat.ucla.edu/~akfletcher/brainsbits.html This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 699829 and under the Marie Sklodowska-Curie grant agreement No 659227.