Working memory in random neural networks
Gilles Wainrib (Ecole Normale Supérieure, Computer Science Department, FR)
April 03, 2015 — 10:30 — Location: None
Numerous experimental studies investigate how neural representations of a signal depend on its past context. Although synaptic plasticity and adaptation may play a crucial role to shape this dependence, we study here the hypothesis that this dependence upon past context may be also explained by dynamical network effects, in particular due to the recurrent nature of neural networks connectivity.
Gilles Wainrib is assistant professor in the Computer Science Department at Ecole Normale Supérieure and his research interests range from theoretical biology to applied mathematics and artificial intelligence.