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Adaptation without Plasticity

delete2016-09-01
delete27
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OA
AI
M
Maria del Mar Quiroga
A
Adam P. Morris
B
Bart Krekelberg *
DOI:10.1016/j.celrep.2016.08.089delete
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Abstract

Abstract

En 中文
Sensory adaptation is a phenomenon in which neurons are affected not only by their immediate input but also by the sequence of preceding inputs. In visual cortex, for example, neurons shift their preferred orientation after exposure to an oriented stimulus. This adaptation is traditionally attributed to plasticity. We show that a recurrent network generates tuning curve shifts observed in cat and macaque visual cortex, even when all synaptic weights and intrinsic properties in the model are fixed. This demonstrates that, in a recurrent network, adaptation on timescales of hundreds of milliseconds does not require plasticity. Given the ubiquity of recurrent connections, this phenomenon likely contributes to responses observed across cortex and shows that plasticity cannot be inferred solely from changes in tuning on these timescales. More broadly, our findings show that recurrent connections can endow a network with a powerful mechanism to store and integrate recent contextual information.
Keywords:
PRIMARY VISUAL-CORTEX
CLASSICAL RECEPTIVE-FIELD
ORIENTATION SELECTIVITY
RECURRENT NETWORKS
SIMPLE CELLS
AREA MT
STRIATE CORTEX
GAIN-CONTROL
MODEL
NEURONS
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Cell Reports cover
Cell Reports
IF:
6.9
Papers:
1.7W
Citations:
10.2W

Organization

R
rutgers university system
Scholars:
4.1W
Papers: 3.7W
Citations: 53