A dual-timescale Hebbian accumulator enables online SNN decoding for BMIs with constant memory, no BPTT, and reported correlations of R >= 0.81 and 0.63 on two primate datasets plus 63-86% memory savings.
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SAL is a spike-timing-based local learning rule that aligns feedback weights to forward weights in spiking networks by exploiting noise and Hebbian/anti-Hebbian plasticity to recover the true gradient.
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Dual-Timescale Hebbian Accumulators for Online Spiking Neural Network Decoding in Intracortical Brain Machine Interfaces
A dual-timescale Hebbian accumulator enables online SNN decoding for BMIs with constant memory, no BPTT, and reported correlations of R >= 0.81 and 0.63 on two primate datasets plus 63-86% memory savings.
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Spike-based alignment learning solves the weight transport problem
SAL is a spike-timing-based local learning rule that aligns feedback weights to forward weights in spiking networks by exploiting noise and Hebbian/anti-Hebbian plasticity to recover the true gradient.