PT  - JOURNAL ARTICLE
AU  - Shanglin Zhou
AU  - Michael Seay
AU  - Jiannis Taxidis
AU  - Peyman Golshani
AU  - Dean V. Buonomano
TI  - Multiplexing working memory and time: encoding retrospective and prospective information in neural trajectories
AID  - 10.1101/2022.07.08.499383
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.07.08.499383
4099  - http://biorxiv.org/content/early/2022/07/10/2022.07.08.499383.short
4100  - http://biorxiv.org/content/early/2022/07/10/2022.07.08.499383.full
AB  - Working memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components. In both cases the task-irrelevant component influenced performance. RNN simulations revealed that cue-specific neural sequences, which multiplexed WM and time, emerged as the dominant regime that captured the behavioral findings. Over the course of training RNN dynamics transitioned from low-dimensional ramps to high-dimensional neural sequences, and depending on task requirements, steady-state or ramping activity was also observed. Analysis of RNN structure revealed that neural sequences relied primarily on inhibitory connections, and could survive the deletion of all excitatory-to- excitatory connections. Our results suggest that in some instances WM is encoded in time-varying neural activity because of the importance of predicting when WM will be used.Competing Interest StatementThe authors have declared no competing interest.