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Florian Chambellant

profil-pics
  • PhD Student
  • florian.chambellant@etu.u-bourgogne.fr
  • +33 3 80 39 67 77
  • R18
  • Laboratoire INSERM U1093
    Université de Bourgogne
    Institut Marey, Maison de la Métallurgie
    BP 27877
    21078 Dijon

PROFILE

Neurosciences, Engineering

Master in Biotechnology and Life Sciences, à l’EPFL (Lausanne)

  • The Use of Machine Learning to Investigate the Neural Control of Arm and Hand Movement
  • Elizabeth Thomas
  • Motor control, Machine learning

PUBLICATIONS

Scientific articles in international or national peer-reviewed journals

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.