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bioRxiv · 10.1101/2021.08.24.457446

Stochastic Consolidation of Lifelong Memory

Shaham, N.·Chandra, J.·Kreiman, G.·Sompolinsky, H.
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Abstract

Humans have the remarkable ability to continually store new memories, while maintaining old memories for a lifetime. How the brain avoids catastrophic forgetting of memories due to interference between encoded memories is an open problem in computational neuroscience. Here we present a model for continual learning in a recurrent neural network combining Hebbian learning, synaptic decay and a novel memory consolidation mechanism. Memories undergo stochastic rehearsals with rates proportional to the memorys basin of attraction, causing self-amplified consolidation, giving rise to memory lifetimes that extend much longer than synaptic decay time, and capacity proportional to a power of the number of neurons. Perturbations to the circuit model cause temporally-graded retrograde and anterograde deficits, mimicking observed memory impairments following neurological trauma.

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Shaham, N., Chandra, J., Kreiman, G., Sompolinsky, H.. 2021-08-25. Stochastic Consolidation of Lifelong Memory. https://doi.org/10.1101/2021.08.24.457446

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