Computing with Neural Ensembles
Professeur Miguel Nicolelis
Edmond & Lily SafraNeuroscience Institute, Natal, Brésil
Duke University, Durham, NC, États-Unis 
Professeur Visiteur, ESPCI ParisTech, Paris

Leçon de Clôture
Chaire Internationale Blaise Pascal 2008‐2011
financée par l'Etat et la Région d'Ile de France.

2 Novembre 2011 à 11h30
Amphithéâtre Langevin
ESPCI ParisTech10 rue Vauquelin 75005 Paris

 

Le professeur Miguel Nicolelis a été invité par le Professeur Jean Rossier pour développer le BMI (Brain Machine Interface) au sein du laboratoire de Neurobiologie de l'ESPCI. Il a donné une série de 4 conférences  en Octobre  2008 qui ont été enregistrées et sont disponibles sur le site web de l’ESPCI  http://radium.net.espci.fr/esp/MNicolelis/

Le 2 novembre le professeur Miguel Nicolelis détaillera ses derniers travaux sur le BMBI (Brain Machine Brain Interface) qui viennent d’être publiés le 5 octobre sur le web de la revue Nature doi:10.1038/nature10489 Nature october 5 2011 .

Brain–machine interfaces use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain–machine interfaces can be used to restore the normal sensori-motor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain–machine–brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signaling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.

 Pour toute information : Professeur Jean ROSSIER

 jean.rossier@espci.fr - 01 40 79 47 58