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Elizabeth Thomas

profil-pics
  • Maître de conférences, HDR
  • Elizabeth.Thomas@u-bourgogne.fr
  • 03 80 39 67 84
  • 115
  • Institut Marey
    64 Rue de Sully
    21000 Dijon

PROFIL

Neurosciences computationnelles, Contrôle moteur

  • Habilitation à Diriger les Recherches, Université de Bourgogne, section 69 (Neurosciences).
    Titre : Computational Neuroscience : From Networks to Behavior
  • Doctorat en Chimie, University of Texas, Austin, U.S.A.
    Titre : Investigation of Dynamic and Static Aspects of a Thalamocortical Simulation
  • Licence en Chimie (summa cum laude), St. John’s University, New York

L’apprentissage machine appliqué aux études du contrôle moteur et les analyses des enregistrements électrophysiologiques du cortex moteur. L’interface entre cognition et la motricité.

Introduction aux Neurosciences, Neurosciences pour la rééducation, Statistiques, Matlab, Système visuel pour les ingénieurs

PUBLICATIONS

  • Tous
  • 2024
  • 2023
  • 2021
  • 2019
  • 2018
  • 2017
  • 2016

Article scientifiques dans des revues internationales ou nationales avec comité de lecture répertoriées

2024
Chambellant F, Falaki A, Moreau-Debord I, French R, Serrano E, Quessy S, Dancause N, Thomas E Variations in Clustering of Multielectrode Local Field Potentials in the Motor Cortex of Macaque Monkeys during a Reach-and-Grasp Task. eNeuro. 2024;11(9). doi: 10.1523/ENEURO.0047-24.2024. PMID: 39288997.
Chambellant F, Gaveau J, Papaxanthis C, Thomas E Deactivation and collective phasic muscular tuning for pointing direction: Insights from machine learning. Heliyon. 2024 Jun 28;10(13):e33461. doi: 10.1016/j.heliyon.2024.e33461. eCollection 2024 Jul 15. PMID: 39050418
Mathieu R, Chambellant F, Thomas E, Papaxanthis C, Hilt P, Manckoundia P, Mourey F, Gaveau J. Comparing arm to whole-body motor control disambiguates age-related deterioration from compensation Peer Community in Health and Movement Sciences 2024 10.24072/pci.healthmovsci.100077
2023
Thomas E, Ali FB, Tolambiya A, Chambellant F, Gaveau J Too much information is no information: how machine learning and feature selection could help in understanding the motor control of pointing. Front Big Data. 2023;6:921355. doi: 10.3389/fdata.2023.921355. PMID: 37546547.
2021
Labarrière F, Thomas E, Calistri L, Optasanu V, Gueugnon M, Ornetti P, Laroche D (2020) Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices-A Systematic Review. Sensors 6:20(21):6345. (IF :3.58)
2019
Thomas E, French R, Alizee G, Coull JT (2019) Having your cake and eating it: Faster responses with reduced muscular activation while learning a temporal interval. Neuroscience410:68–75. (IF : 3,1)
2018
Casteran M, Hilt P, Mourey F, Manckoundia P, French R, Thomas E (2018) Shifts in key time points and strategies for a multisegment motor task in healthy aging subjects. The Journals of gerontology. Series A, Biological sciences and medical sciences 73:1609-1617. (IF : 4,71)
2017
Addyman C, Rocha S, Fautrelle L, French RM, Thomas E, Marechal D(2017) Embodiment and the origin of interval timing kinematic and electromyographic data. Experimental Brain Research 235(3):923–930. (IF : 1.81)
Torlay L, Perrone-Bertolotti M, Thomas E, Baciu M (2017) Machine learning-XGBoost analysis of language networks to classify patients with epilepsy. Brain Informatics 4(3):159-169 (IF : 3.53)
2016
Addyman C, French RM, Thomas E (2016) Computational models of interval timing. Current opinion in Behavioral Sciences 8:140-146. (IF : 3.42)
Casteran M, Putot A, Pfitzenmeyer F, Thomas E, Manckoundia P (2016) Analysis of the impact of a cognitive task on the posture of elderly subjects with depression compared with healthy elderly subjects. Clinical Neurophysiology 127(11):3406-11. (IF : 3.87)
Thomas E, French RM (2016) Grandmother cells: much ado about nothing. Language, Cognition and Neuroscience 32:342-349. (IF :1.93)