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Multimodal Imaging Brain Markers in Early Adolescence Are Linked with a Physically Active Lifestyle.

Journal article

Salvan P. et al, (2021), J Neurosci, 41, 1092 - 1104

Detecting connectivity in EEG: A comparative study of data-driven effective connectivity measures.

Journal article

Bakhshayesh H. et al, (2019), Comput Biol Med, 111

Detecting synchrony in EEG: A comparative study of functional connectivity measures.

Journal article

Bakhshayesh H. et al, (2019), Comput Biol Med, 105, 1 - 15

Towards detecting connectivity in EEG: A comparative study of parameters of effective connectivity measures on simulated data

Conference paper

Bakhshayesh H. et al, (2019), 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings, 297 - 301

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

Journal article

Bastiani M. et al, (2019), Neuroimage, 185, 750 - 763

Improved artefact removal from EEG using Canonical Correlation Analysis and spectral slope.

Journal article

Janani AS. et al, (2018), J Neurosci Methods, 298, 1 - 15

Hand classification of fMRI ICA noise components.

Journal article

Griffanti L. et al, (2017), Neuroimage, 154, 188 - 205

Reducing training requirements through evolutionary based dimension reduction and subject transfer

Journal article

Atyabi A. et al, (2017), Neurocomputing, 224, 19 - 36

Electroencephalographic correlates of states of concentrative meditation.

Journal article

DeLosAngeles D. et al, (2016), Int J Psychophysiol, 110, 27 - 39

Construction of a neonatal cortical surface atlas using multimodal surface matching

Conference paper

Bozek J. et al, (2016), Proceedings - International Symposium on Biomedical Imaging, 2016-June, 775 - 778

Cross Subject Mental Work Load Classification from Electroencephalographic Signals with Automatic Artifact Rejection and Muscle Pruning

Conference paper

Kunjan S. et al, (2016), Brain Informatics and Health, 9919, 295 - 303

Cross subject mental work load classification from electroencephalographic signals with automatic artifact rejection and muscle pruning

Conference paper

Kunjan S. et al, (2016), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9919 LNAI, 295 - 303

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