ePoster · Computational Neuroscience
The least-control principle for local learning at equilibrium
Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento · COSYNE 2023
Fri, Mar 10, 2023
A widely-accepted tenet of neuroscience is that learning relies on synaptic plasticity. Because plasticity is thought to be governed by local, activity-dependent rules, it is a longstanding mystery how synapses change in concert so that behavioral output improves. This problem is aggravated by the recurrent and multilayered architecture of the cortex, which makes it hard to determine the effects of a given synaptic modification. Here we present a novel principle for learning rooted in optimal control theory, which yields local plasticity rules for any neural dynamics which reaches an equilibri