Author

Apolline Mellot

Institut national de recherche en sciences et technologies du numériqueORCID 0000-0002-7001-9749Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Alexandre GramfortiD· 2 shared Denis Alexander EngemanniD· 2 shared Antoine CollasiD· 1 shared David SabbaghiD· 1 shared Hubert J. BanvilleiD· 1 shared Lukas A. W. GemeiniD· 1 shared Pedro Luiz Coelho RodriguesiD· 1 shared Richard HöchenbergeriD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 26 mutual co-author links

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2 shared papersNeuroscience

Alexandre GramfortORCID

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2 papers

Recent·Most cited

NeuroscienceImaging NeurosciencePeer-reviewedNov 20, 2023

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling

Apolline Mellot, Antoine Collas, Pedro Luiz Coelho Rodrigues…·Alexandre Gramfort

This paper improves M/EEG-based regression models by applying covariance-based domain adaptation techniques to address dataset shifts across different recording contexts.

16 citations

electronic health recordsstatistical model

𝕏 PostBluesky

NeuroscienceNeuroImagePeer-reviewedJul 26, 2022

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

Denis Alexander Engemann, Apolline Mellot, Richard Höchenberger…·Alexandre Gramfort

This paper benchmarks machine learning approaches for brain age prediction using M/EEG signals across four international cohorts, finding that spatially aware models achieve the highest performance.

79 citationstop 1%

humanelectronic health records

𝕏 PostBluesky