Stability through plasticity: Finding robust memories through representational drift.

ABSTRACT: Memories are believed to be stored in synapses and retrieved by reactivating neural ensembles. Learning alters synaptic weights, which can interfere with previously stored memories that share the same synapses, creating a trade-off between plasticity and stability. Interestingly, neural representations change even in stable environments, without apparent learning or forgetting-a phenomenon known as representational drift. Theoretical studies have suggested that multiple neural representations can correspond to a memory, with postlearning exploration of these representation solutions driving drift. However, it remains unclear whether representations explored through drift differ from those learned or offer unique advantages. Here, we show that representational drift uncovers noise-robust re

SUBMITTER: Natrajan M 

PROVIDER: S-EPMC12625983 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature