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Keyword: credit assignment ×Clear all

2 claims from 1 paper

1. Neuroscience › Memory and Neural Mechanisms

   Credit Assignment via Behavioral Timescale Synaptic Plasticity: Theoretical Frameworks

   Cone, A and Costa · bioRxiv (Cold Spring Harbor Laboratory) · 2025

   The authors propose a generalised BTSP learning rule and test it in feedforward and recurrent network models on unsupervised and supervised tasks, finding it harder to use as networks get deeper or more recurrent.

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   1. UncheckedIn the authors' models, an unsupervised generalised BTSP rule behaves like competitive learning, forming place field maps or attractor memory networks.“Unsupervised gBTSP mirrors classical frameworks of competitive learning, learning place field maps (in the feed-forward case), and attractive memory networks (in the recurrent case).”
   2. UncheckedIn this modelling study, plateau events in a generalised BTSP rule can reduce task error, letting it solve trajectory matching and delayed non-match-to-sample.“For supervised learning, we show that plateau events can reduce task error, enabling gBTSP to solve tasks such as trajectory matching and delayed non-match-to-sample.”