PT  - JOURNAL ARTICLE
AU  - Nicolas Y. Masse
AU  - Guangyu R. Yang
AU  - H. Francis Song
AU  - Xiao-Jing Wang
AU  - David J. Freedman
TI  - Circuit mechanisms for the maintenance and manipulation of information in working memory
AID  - 10.1101/305714
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 305714
4099  - http://biorxiv.org/content/early/2018/04/22/305714.short
4100  - http://biorxiv.org/content/early/2018/04/22/305714.full
AB  - Recently it has been proposed that information in short-term memory may not always be stored in persistent neuronal activity, but can be maintained in “activity-silent” hidden states such as synaptic efficacies endowed with short-term plasticity (STP). However, working memory involves manipulation as well as maintenance of information in the absence of external stimuli. In this work, we investigated working memory representation using recurrent neural network (RNN) models trained to perform several working memory dependent tasks. We found that STP can support the short-term maintenance of information provided that the memory delay period is sufficiently short. However, in tasks that require actively manipulating information, persistent neuronal activity naturally emerges from learning, and the amount of persistent neuronal activity scales with the degree of manipulation required. These results shed insight into the current debate on working memory encoding, and suggest that persistent neural activity can vary markedly between tasks used in different experiments.