Presentation of the project

Neurobot is a french ANR research project, featuring 4 academic partners:

  • ETIS (UMR CNRS 8051, Equipes Traitement de l’Information et Systèmes, ENSEA Cergy et Université de Cergy-Pontoise);
  • LPPA (UMR CNRS 7152, Laboratoire de Physiologie et de Perception de l’Action, Collège de France) ;
  • LNC (UMR CNRS 7291, Laboratoire de Neurosciences Cognitives, Université de Provence) ;
  • GNT (unité INSERM 960, Groupe de Neurosciences Théoriques, ENS Paris).

Coding of information on different time scales for spatial decision

Tracking, memorizing and recalling real world events and episodes poses a formidable problem for artificial as well as biological computational processors. A major issue is time: the underlying mechanisms are much too rapid – nanoseconds and milliseconds for in silico and in vivo systems respectively. Thus efficient solutions must be found to scale up to the timescale of typical experiences which for autonomous robots and animals are on the order of seconds, minutes and hours. Furthermore, optimal operation at these different timescales requires hierarchies of nested systems in order to permit expression of adaptive behaviour at the highest level. The nature of this nesting and the control systems for optimal communication between these levels remains a critical issue to be resolved.

Biologically-inspired control systems for robots provide robustness, flexibility and adaptiveness with the aim of approaching performance levels of the mammalian brain. However typically firing rate models are employed because they are faster to implement than spiking neuron models, thus excluding important boosts in computational capacities provided by the latter. Here functioning firing rate models will be extended with recent streamlined spiking neuron models and will be applied at a system level, rather than in single structures.