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.
Highlights
Waves of neural activity in the brain play an essential role in recognition and learning [1]
Because the previously proposed reward-dependent synaptic plasticity rule requires coactivation of presynaptic and postsynaptic neurons, learning can fail if a subset of neurons along a distant network path is inactive at the beginning of learning
Our results show that this combination facilitates the learning and refinement of synaptic network paths
Summary
Waves of neural activity in the brain play an essential role in recognition and learning [1]. Jp/english/index.html The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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