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Parametric control of flexible timing through low-dimensional neural manifolds

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Title
Parametric control of flexible timing through low-dimensional neural manifolds
Author(s)
Beiran, Manuel; Meirhaeghe, Nicolas; Hansem Sohn; Jazayeri, Mehrdad; Ostojic, Srdjan
Publication Date
2023-03
Journal
NEURON, v.111, no.5, pp.739 - 753
Publisher
CELL PRESS
Abstract
Biological brains possess an unparalleled ability to adapt behavioral responses to changing stimuli and en-vironments. How neural processes enable this capacity is a fundamental open question. Previous works have identified two candidate mechanisms: a low-dimensional organization of neural activity and a modulation by contextual inputs. We hypothesized that combining the two might facilitate generalization and adaptation in complex tasks. We tested this hypothesis in flexible timing tasks where dynamics play a key role. Examining trained recurrent neural networks, we found that confining the dynamics to a low-dimensional subspace al-lowed tonic inputs to parametrically control the overall input-output transform, enabling generalization to novel inputs and adaptation to changing conditions. Reverse-engineering and theoretical analyses demon-strated that this parametric control relies on a mechanism where tonic inputs modulate the dynamics along non-linear manifolds while preserving their geometry. Comparisons with data from behaving monkeys confirmed the behavioral and neural signatures of this mechanism.
URI
https://pr.ibs.re.kr/handle/8788114/13321
DOI
10.1016/j.neuron.2022.12.016
ISSN
0896-6273
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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