SOURCE-LINKED INTELLIGENCE
A Gradient-based yet Spike-Timing-Dependent Solution to the Feedback Learning Problem in Neural Microcircuits
The brain uses discrete spikes for dynamic computation, yet, how neural microcircuits (NMCs) solve temporal credit assignment using local spike timing remains a fundamental open question. Dominant spiking neural network (SNN) approaches circumvent this by approximating backpropagation through surrogate gradients, decoupling learning from biological spike timing. Here, we reformulate temporal credit assignment as a state separation problem: extracting task-required components induced by historical perturbations directly from the current neural state. This enables an online feedback learning fra
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T00:27:18.000Z
First collected: 2026-09-20T20:22:01.598Z. This is not the publication date.