Work

A general decoding strategy explains the relationship between behavior and correlated variability

Year: 2022

Type: article

Abstract: ABSTRACT Improvements in perception are frequently accompanied by decreases in correlated variability in sensory cortex. This relationship is puzzling because overall changes in correlated variability should minimally affect optimal information coding. We hypothesize that this relationship arises because instead of using optimal strategies for decoding the specific stimuli at hand, observers prioritize generality : a single set of neuronal weights to decode any stimuli. We tested this using a combination of multineuron recordings in the visual cortex of behaving rhesus monkeys and a cortical circuit model. We found that general decoders optimized for broad rather than narrow sets of visual stimuli better matched the animals’ decoding strategy, and that their performance was more related to the magnitude of correlated variability. In conclusion, the inverse relationship between perceptual performance and correlated variability can be explained by observers using a general decoding strategy, capable of decoding neuronal responses to the variety of stimuli encountered in natural vision. IMPACT STATEMENT The frequently observed relationship between perceptual performance and correlated variability in sensory cortex can be explained by observers using a decoding strategy that prioritizes generality for many stimuli over precision.

Source: eLife

DOI: 10.7554/elife.67258

Authors: Amy M. Ni, Chengcheng Huang, Brent Doiron, Marlene R. Cohen

Institutions: University of Pittsburgh, Center for the Neural Basis of Cognition

Language: English

Topic: Visual perception and processing mechanisms

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,500