Learning top-down gain control of feature selectivity in a recurrent network model of a visual cortical area

doi:10.1016/j.visres.2005.05.028

Paper

Learning top-down gain control of feature selectivity in a recurrent network model of a visual cortical area

Published Nov 1, 2005 · L. Schwabe, K. Obermayer

Vision Research

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6

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Abstract

Abstract removed due to Elsevier request; this does not indicate any issues with the research. Click the full text link above to read the abstract and view the original source.

Study Snapshot

Key takeawayTop-down modulations in the visual cortex strengthen task-relevant pathways, reflecting a simple strategy to strengthen relevant pathways in a task-dependent manner.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Learning top-down gain control of feature selectivity in a recurrent network model of a visual cortical area

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