Article

Learning complex temporal dependencies via local synaptic plasticity

2026-07-10

Abstract excerpt

The ability to extract and exploit temporal structure across diverse tasks is central to human cognition. Neuroscientists have typically relied on recurrent neural networks (RNNs) trained with backpropagation through time (BPTT) when modelling neural and behavioural processes such as decision-making and motor control. However, this algorithm has limited biological plausibility, hence the computational principles u...

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Literature Corpus work: 852c6a1e-87c0-5d4d-909b-87c951d7c9b9
DOI: 10.64898/2026.07.09.737423

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