Learning poly-synaptic paths with traveling waves.

Affiliation

Ito Y(1), Toyoizumi T(2)(3).
Author information:
(1)Graduate School of Information and Technology, the Department of Mechano-Informatics, the University of Tokyo, Tokyo, Japan.
(2)Lab for Neural Computation and Adaptation, RIKEN Center for Brain Science, Saitama, Japan.
(3)Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan.

Abstract

Traveling waves are commonly observed across the brain. While previous studies have suggested the role of traveling waves in learning, the mechanism remains unclear. We adopted a computational approach to investigate the effect of traveling waves on synaptic plasticity. Our results indicate that traveling waves facilitate the learning of poly-synaptic network paths when combined with a reward-dependent local synaptic plasticity rule. We also demonstrate that traveling waves expedite finding the shortest paths and learning nonlinear input/output mapping, such as exclusive or (XOR) function.