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Elisabetta Chicca

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Open access Aug 2026

Learning in spiking neural networks with a calcium-based Hebbian rule for spike timing-dependent plasticity

This work presents a Hebbian local learning rule that models synaptic modification as a function of calcium traces tracking neuronal activity and demonstrates how spike timing and rate can be complementary in their role of shaping the connectivity of spiking neural networks.

Willian Soares Girāo, Nicoletta Risi, Caroline Geisler et al. · 0 citations