Persistent neuronal firing in the medial temporal lobe supports performance and workload of visual working memory in humans.
Entorhinal cortex
Hippocampus
Neural decoding
Spatial
Visual
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 07 2022
01 07 2022
Historique:
received:
14
11
2021
revised:
18
03
2022
accepted:
19
03
2022
pubmed:
25
3
2022
medline:
11
5
2022
entrez:
24
3
2022
Statut:
ppublish
Résumé
The involvement of the medial temporal lobe (MTL) in working memory is controversially discussed. Recent findings suggest that persistent neural firing in the hippocampus during maintenance in verbal working memory is associated with workload. Here, we recorded single neuron firing in 13 epilepsy patients (7 male) while they performed a visual working memory task. The number of colored squares in the stimulus set determined the workload of the trial. Performance was almost perfect for low workload (1 and 2 squares) and dropped at high workload (4 and 6 squares), suggesting that high workload exceeded working memory capacity. We identified maintenance neurons in MTL neurons that showed persistent firing during the maintenance period. More maintenance neurons were found in the hippocampus for trials with correct compared to incorrect performance. Maintenance neurons increased and decreased firing in the hippocampus and increased firing in the entorhinal cortex for high compared to low workload. Population firing predicted workload particularly during the maintenance period. Prediction accuracy of workload based on single-trial activity during maintenance was strongest for neurons in the entorhinal cortex and hippocampus. The data suggest that persistent neural firing in the MTL reflects a domain-general process of maintenance supporting performance and workload of multiple items in working memory below and beyond working memory capacity. Persistent neural firing during maintenance in the entorhinal cortex may be associated with its preference to process visual-spatial arrays.
Identifiants
pubmed: 35321857
pii: S1053-8119(22)00251-8
doi: 10.1016/j.neuroimage.2022.119123
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
119123Informations de copyright
Copyright © 2022. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare no conflict of interest.