Author

Jean‐Luc Schwartz

Institut polytechnique de GrenobleORCID 0000-0001-8969-9185Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Anne VilainiD· 1 shared E. TatulliiD· 1 shared Élise RogeriD· 1 shared Émilie Cousin· 1 shared Hélène LœvenbruckiD· 1 shared Laurent Girin BiD· 1 shared Lílian Rodrigues de AlmeidaiD· 1 shared Marcela Perrone‐BertolottiiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Anne VilainORCID

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2 papers

Recent·Most cited

NeuroscienceNeuroImagePeer-reviewedOct 6, 2022

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability.

Élise Roger, Lílian Rodrigues de Almeida, Hélène Lœvenbruck…·Monica V. Baciu

The paper constructs a task-related functional connectome of language using fMRI data from 150 adults, identifying crucial subnetworks, flexibility, and variability in language processing.

29 citations

humanimaging

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BioinformaticsbioRxivPreprintNov 18, 2018

How predictive can be predictions in the neurocognitive processing of auditory and audiovisual speech? A deep learning study.

Thomas Hueber, E. Tatulli, Laurent Girin B, Jean‐Luc Schwartz

The paper uses deep learning models to predict future audio observations from past auditory and audiovisual speech data, finding that predictions are most accurate within 50 ms and improve slightly with visual input.

DOI 10.1101/471581

deep learning

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