Affordable Access

deepdyve-link
Publisher Website

Neuronal Adaptation Reveals a Suboptimal Decoding of Orientation Tuned Populations in the Mouse Visual Cortex.

Authors
  • Jin, Miaomiao1
  • Beck, Jeffrey M1
  • Glickfeld, Lindsey L2
  • 1 Department of Neurobiology, Duke University Medical Center, Durham, North Carolina 27710.
  • 2 Department of Neurobiology, Duke University Medical Center, Durham, North Carolina 27710 [email protected]
Type
Published Article
Journal
Journal of Neuroscience
Publisher
Society for Neuroscience
Publication Date
May 15, 2019
Volume
39
Issue
20
Pages
3867–3881
Identifiers
DOI: 10.1523/JNEUROSCI.3172-18.2019
PMID: 30833509
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Sensory information is encoded by populations of cortical neurons. Yet, it is unknown how this information is used for even simple perceptual choices such as discriminating orientation. To determine the computation underlying this perceptual choice, we took advantage of the robust visual adaptation in mouse primary visual cortex (V1). We first designed a stimulus paradigm in which we could vary the degree of neuronal adaptation measured in V1 during an orientation discrimination task. We then determined how adaptation affects task performance for mice of both sexes and tested which neuronal computations are most consistent with the behavioral results given the adapted population responses in V1. Despite increasing the reliability of the population representation of orientation among neurons, and improving the ability of a variety of optimal decoders to discriminate target from distractor orientations, adaptation increases animals' behavioral thresholds. Decoding the animals' choice from neuronal activity revealed that this unexpected effect on behavior could be explained by an overreliance of the perceptual choice circuit on target preferring neurons and a failure to appropriately discount the activity of neurons that prefer the distractor. Consistent with this all-positive computation, we find that animals' task performance is susceptible to subtle perturbations of distractor orientation and optogenetic suppression of neuronal activity in V1. This suggests that to solve this task the circuit has adopted a suboptimal and task-specific computation that discards important task-related information.SIGNIFICANCE STATEMENT A major goal in systems neuroscience is to understand how sensory signals are used to guide behavior. This requires determining what information in sensory cortical areas is used, and how it is combined, by downstream perceptual choice circuits. Here we demonstrate that when performing a go/no-go orientation discrimination task, mice suboptimally integrate signals from orientation tuned visual cortical neurons. While they appropriately positively weight target-preferring neurons, they fail to negatively weight distractor-preferring neurons. We propose that this all-positive computation may be adopted because of its simple learning rules and faster processing, and may be a common approach to perceptual decision-making when task conditions allow. Copyright © 2019 the authors.

Report this publication

Statistics

Seen <100 times