Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming, or objects increasing in size. Various computatio...

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Bibliographic Details
Main Authors: Baohua Zhou, Zifan Li, Sunnie Kim, John Lafferty, Damon A Clark
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2022-01-01
Series:eLife
Subjects:
loom detection
visual circuits
inference
receptive fields
task optimization
machine learning
Online Access:https://elifesciences.org/articles/72067

Internet

https://elifesciences.org/articles/72067

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