Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity.
PLoS Comput Biol
; 15(7): e1006446, 2019 07.
Article
em En
| MEDLINE
| ID: mdl-31299044
ABSTRACT
The dimensionality of a network's collective activity is of increasing interest in neuroscience. This is because dimensionality provides a compact measure of how coordinated network-wide activity is, in terms of the number of modes (or degrees of freedom) that it can independently explore. A low number of modes suggests a compressed low dimensional neural code and reveals interpretable dynamics [1], while findings of high dimension may suggest flexible computations [2, 3]. Here, we address the fundamental question of how dimensionality is related to connectivity, in both autonomous and stimulus-driven networks. Working with a simple spiking network model, we derive three main findings. First, the dimensionality of global activity patterns can be strongly, and systematically, regulated by local connectivity structures. Second, the dimensionality is a better indicator than average correlations in determining how constrained neural activity is. Third, stimulus evoked neural activity interacts systematically with neural connectivity patterns, leading to network responses of either greater or lesser dimensionality than the stimulus.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Potenciais de Ação
/
Rede Nervosa
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article