This Frontiers in Neuroscience Research Topic explores the translation of biological learning mechanisms into neuromorphic engineering. It covers theoretical frameworks like predictive coding, analog VLSI implementations, emerging non-volatile devices (memristors), and on-chip architectures for spike-based computation. The resource explicitly excludes purely biological or device-physics studies lacking a clear computing component.
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Frontiers | From Synapses to Silicon: Theoretical Foundations and Neuromorphic Implementations of Biological Learning
A Frontiers Research Topic soliciting papers on translating synaptic plasticity theories into scalable neuromorphic hardware and algorithms, with an acceptance deadline of 2027-02-12.