RT Journal Article
SR Electronic
T1 Drift of neural ensembles driven by slow fluctuations of intrinsic excitability
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.03.16.532958
DO 10.1101/2023.03.16.532958
A1 Geoffroy Delamare
A1 Yosif Zaki
A1 Denise J Cai
A1 Claudia Clopath
YR 2023
UL http://biorxiv.org/content/early/2023/03/17/2023.03.16.532958.abstract
AB Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not known. Since intrinsic neural excitability is suggested to play a key role in regulating memory allocation, fluctuations of excitability could bias the reactivation of previously stored memory ensembles and therefore act as a motor for drift. Here, we propose a rate-based plastic recurrent neural network with slow fluctuations of intrinsic excitability. We first show that subsequent reactivations of a neural ensemble can lead to drift of this ensemble. The model predicts that drift is induced by co-activation of previously active neurons along with neurons with high excitability which leads to remodelling of the recurrent weights. Consistent with previous experimental works, the drifting ensemble is informative about its temporal history. Crucially, we show that the gradual nature of the drift is necessary for decoding temporal information from the activity of the ensemble. Finally, we show that the memory is preserved and can be decoded by an output neuron having plastic synapses with the main region.Competing Interest StatementThe authors have declared no competing interest.