Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a Switch.
Journal
Neural computation
ISSN: 1530-888X
Titre abrégé: Neural Comput
Pays: United States
ID NLM: 9426182
Informations de publication
Date de publication:
17 02 2022
17 02 2022
Historique:
received:
06
01
2021
accepted:
21
09
2021
pubmed:
12
1
2022
medline:
4
3
2022
entrez:
11
1
2022
Statut:
ppublish
Résumé
As animals adapt to their environments, their brains are tasked with processing stimuli in different sensory contexts. Whether these computations are context dependent or independent, they are all implemented in the same neural tissue. A crucial question is what neural architectures can respond flexibly to a range of stimulus conditions and switch between them. This is a particular case of flexible architecture that permits multiple related computations within a single circuit. Here, we address this question in the specific case of the visual system circuitry, focusing on context integration, defined as the integration of feedforward and surround information across visual space. We show that a biologically inspired microcircuit with multiple inhibitory cell types can switch between visual processing of the static context and the moving context. In our model, the VIP population acts as the switch and modulates the visual circuit through a disinhibitory motif. Moreover, the VIP population is efficient, requiring only a relatively small number of neurons to switch contexts. This circuit eliminates noise in videos by using appropriate lateral connections for contextual spatiotemporal surround modulation, having superior denoising performance compared to circuits where only one context is learned. Our findings shed light on a minimally complex architecture that is capable of switching between two naturalistic contexts using few switching units.
Identifiants
pubmed: 35016220
pii: 109061
doi: 10.1162/neco_a_01472
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
541-594Subventions
Organisme : NIDA NIH HHS
ID : R90 DA033461
Pays : United States
Informations de copyright
© 2022 Massachusetts Institute of Technology.