Solid State Neuroscience

Activité scientifique

We have discovered that a conventional electronic component know since the 50’s, the thyristor or silicon controlled rectifier (SCR), has memristive properties quite analog to a Mott material. We have succeeded in building an extremely simple and versatile artificial neuron, which we termed the UCN, for ultra-compact neuron. We have already published several papers, the first one in Scientific Reports, which was featured in Nature’s Research Device and Materials Engineering blog, and two others in Frontiers in Neuroscience, where we implement a spiking neural network circuit with a brain-like function, namely, the bi-aural detection of sound direction. This is a practical realization of a classic model of neurobiology, the Jeffress’ model. This work demonstrates that our UCN can be easily associated and interconnected to form networks. Therefore, it opens the way to practically explore fundamental and pressing questions of Neuroscience, such as emergent electrical behaviour and neural coding. A concrete example of this is the issue of how brain waves emerge in a seemingly randomly connected and activated neural environment.

Responsable de l’équipe : Marcelo ROZENBERG

Membres permanents :

  1. Marcelo ROZENBERG
  2. Kang WANG

Laboratoire :

Laboratoire de Physique des Solides (LPS), CNRS UMR 8502,
Université Paris Saclay
Faculté des Sciences, Bât. 510
F-91405 Orsay cedex