Learning poly-synaptic paths with traveling waves

TL;DR

This paper investigates how traveling waves in the brain influence learning by facilitating synaptic plasticity, enabling efficient learning of complex network paths and nonlinear functions through computational modeling.

Contribution

It introduces a computational framework showing that traveling waves enhance poly-synaptic learning and pathfinding, advancing understanding of their role in neural plasticity.

Findings

Traveling waves promote learning of poly-synaptic network paths.

They expedite the discovery of shortest paths in neural networks.

Traveling waves improve learning of nonlinear functions like XOR.

Abstract

Traveling waves are commonly observed across the brain. While previous studies have suggested the role of traveling waves in learning, the mechanism is still 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.