Work

Neural Learning as a Game Induced by Spike-Timing-Dependent Plasticity

Year: 2026
Type: preprint
Abstract: A general framework for inferring the computational role of spike-timing-dependent plasticity (STDP) does not currently exist. Here, we develop a game-theoretic description for a canonical, convergent neural circuit with general STDP and postsynaptic-potential (PSP) kernels. Parity-matched STDP-PSP interactions induce a potential game among presynaptic neurons, whereas parity-mismatched interactions induce a zero-sum game. These components, respectively, implement contrastive PCA and flow selection; their weighted interplay determines learning dynamics and computation for arbitrary STDP rules.
Language: English
Open Access status: green
OpenAlex ID: W7213942961
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