A Generalized Linear Model of a Navigation Network.
entorinal cortex
generalized linear model
grid cell
head direction cells
navigation
speed cells
theta oscillation
Journal
Frontiers in neural circuits
ISSN: 1662-5110
Titre abrégé: Front Neural Circuits
Pays: Switzerland
ID NLM: 101477940
Informations de publication
Date de publication:
2020
2020
Historique:
received:
03
06
2020
accepted:
28
07
2020
entrez:
5
10
2020
pubmed:
6
10
2020
medline:
5
10
2021
Statut:
epublish
Résumé
Navigation by mammals is believed to rely on a network of neurons in the hippocampal formation, which includes the hippocampus, the medial entorhinal cortex (MEC), and additional nearby regions. Neurons in these regions represent spatial information by tuning to the position, orientation, and speed of the animal in the form of head direction cells, speed cells, grid cells, border cells, and unclassified spatially modulated cells. While the properties of single cells are well studied, little is known about the functional structure of the network in the MEC. Here, we use a generalized linear model to study the network of spatially modulated cells in the MEC. We found connectivity patterns between all spatially encoding cells and not only grid cells. In addition, the neurons' past activity contributed to the overall activity patterns. Finally, position-modulated cells and head direction cells differed in the dependence of the activity on the history. Our results indicate that MEC neurons form a local interacting network to support spatial information representations and suggest an explanation for their complex temporal properties.
Identifiants
pubmed: 33013326
doi: 10.3389/fncir.2020.00056
pmc: PMC7509173
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
56Informations de copyright
Copyright © 2020 Vinepinsky, Perchik and Segev.
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