Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach

Portugal, Liana; Schrouff, Jessica; Stiffler, R; Bertocci, M; Bebko, G; Chase, H; Lockovitch, J; Aslam, H; Graur, S; Greenberg, T; Pereira, M; Oliveira, L; Phillips, M; Mourao-Miranda, Janaina

doi:10.1016/j.nicl.2019.101813

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Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach

Portugal, Liana; Schrouff, Jessica; Stiffler, R et al.

2019 • In NeuroImage: Clinical, 23

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https://hdl.handle.net/2268/236352

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10.1016/j.nicl.2019.101813

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31082774

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Keywords :

RDoC; Anxiety; Depression; fMRI; Pattern recognition; Faces

Disciplines :

Psychiatry

Author, co-author :

Portugal, Liana

Schrouff, Jessica ; University College London - UCL

Stiffler, R

Bertocci, M

Bebko, G

Chase, H

Lockovitch, J

Aslam, H

Graur, S

Greenberg, T

More authors (4 more)

Language :

English

Title :

Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach

Publication date :

2019

Journal title :

NeuroImage: Clinical

eISSN :

2213-1582

Publisher :

Elsevier, Netherlands

Volume :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://discovery.ucl.ac.uk/10074679/

European Projects :

H2020 - 654038 - DecoMP_ECoG - Decoding memory processing from experimental and spontaneous human brain activity using intracranial electrophysiological recordings and machine learning based methods.

Funders :

CE - Commission Européenne

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since 05 June 2019

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