Interpreting wide-band neural activity using convolutional neural networks.
calcium imaging
decoding
deep learning
electrophysiology
neuroscience
rat
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
02 08 2021
02 08 2021
Historique:
received:
15
01
2021
accepted:
13
07
2021
entrez:
2
8
2021
pubmed:
3
8
2021
medline:
13
10
2021
Statut:
epublish
Résumé
Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires considerable knowledge about the nature of the representation and often depends on manual operations. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of the encoding scheme. Here, we developed a deep-learning framework able to decode sensory and behavioral variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviors, brain regions, and recording techniques. Once trained, it can be analyzed to determine elements of the neural code that are informative about a given variable. We validated this approach using electrophysiological and calcium-imaging data from rodent auditory cortex and hippocampus as well as human electrocorticography (ECoG) data. We show successful decoding of finger movement, auditory stimuli, and spatial behaviors - including a novel representation of head direction - from raw neural activity.
Identifiants
pubmed: 34338632
doi: 10.7554/eLife.66551
pii: 66551
pmc: PMC8328518
doi:
pii:
Banques de données
figshare
['10.6084/m9.figshare.c.5486703.v1']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 110238/Z/15/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 212281/Z/18/Z
Pays : United Kingdom
Informations de copyright
© 2021, Frey et al.
Déclaration de conflit d'intérêts
MF, ST, CP, AO, MN, JK, AB, DB, JL, CD, CB No competing interests declared
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