Author

Manon Auffret

InsermORCID 0000-0002-7003-4084Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Mahmoud HassaniD· 2 shared Marc VériniD· 2 shared Fatima ChhadeiD· 1 shared Judie TabbaliD· 1 shared Peter FuhriD· 1 shared Sahar YassineiD· 1 shared Sourour Almarouk· 1 shared Ute GschwandtneriD· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

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2 shared papersNeuroscience

Mahmoud HassanORCID

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2 papers

Recent·Most cited

Electrophysiological signatures of anxiety in Parkinson's disease

Sahar Yassine, Sourour Almarouk, Ute Gschwandtner, Manon Auffret, Peter Fuhr, Marc Vérin, Mahmoud Hassan

This study identifies electrophysiological signatures of anxiety in Parkinson's disease using resting-state EEG, showing altered power and connectivity patterns associated with clinical anxiety scores.

Translational Psychiatry · Jan 27, 2024Peer-reviewedNeuroscience

Predicting real-life creativity using resting state electroencephalography

Fatima Chhade, Judie Tabbal, Véronique Paban, Manon Auffret, Mahmoud Hassan, Marc Vérin

This study uses HD-EEG and machine learning to identify resting-state brain networks predictive of real-life creativity, finding significant correlations in both internal and external validation.

bioRxiv · Jul 28, 2023 · PreprintNeuroscience