arXiv Machine Learning July 27, 2026 By Martin Andrews

Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation

Read the original on arXiv Machine Learning →

arXiv:2607. 21622v1 Announce Type: cross Abstract: We prove that two canonical local synaptic learning rules, the potentiation arm of spike-timing-dependent plasticity (STDP$^+$) and homeostatic plasticity (instantiated here via flashlight granule-cell-like neurons), together can implement the exact gradient of a SIGReg-like self-supervised learning objective.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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Dendritic In-Context Learning in a Single-Layer Spiking Neural Network

arXiv:2607. 02283v1 Announce Type: cross Abstract: In-context learning (ICL) operates via implicit gradient descent embedded in the forward pass of modern AI architectures -- Transformers, Mamba, state-space models, and MLPs.

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