Topic: game-theoretical approach

How changes in synaptic connections underlie learning and memory is a central question in Neuroscience. Previous modeling efforts focused on biologically realistic learning rules and dynamics, but these rules usually produce bimodal weight distributions that are not aligned with experimentally observed lognormal distributions of synaptic weights. How biological learning rules preserve such unimodal distributions and at the same time retain information, i.e., learn, remains unknown. Here, we take a game-theoretical approach, asking whether learning is possible under the constraint of retaining