Interpreting the Retinal Neural Code for Natural Scenes: From Computations to Neurons

Overview

Journal Neuron

Publisher Cell Press

Specialty Neurology

Date 2023 Jul 14

PMID 37451264

Authors

Niru Maheswaranathan

Lane T McIntosh

Hidenori Tanaka

Satchel Grant

David B Kastner

Joshua B Melander

Aran Nayebi

Luke E Brezovec

Julia H Wang

Surya Ganguli

Stephen A Baccus

Affiliations

Soon will be listed here.

Abstract

Understanding the circuit mechanisms of the visual code for natural scenes is a central goal of sensory neuroscience. We show that a three-layer network model predicts retinal natural scene responses with an accuracy nearing experimental limits. The model's internal structure is interpretable, as interneurons recorded separately and not modeled directly are highly correlated with model interneurons. Models fitted only to natural scenes reproduce a diverse set of phenomena related to motion encoding, adaptation, and predictive coding, establishing their ethological relevance to natural visual computation. A new approach decomposes the computations of model ganglion cells into the contributions of model interneurons, allowing automatic generation of new hypotheses for how interneurons with different spatiotemporal responses are combined to generate retinal computations, including predictive phenomena currently lacking an explanation. Our results demonstrate a unified and general approach to study the circuit mechanisms of ethological retinal computations under natural visual scenes.

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