Dynamics of a random neural network with synaptic depression

Senn, Walter; Wyler, K.; Streit, J.; Larkum, M.; Lüscher, H.-R.; Mey, H.; Müller, L.; Stainhauser, D.; Vogt, K.; Wannier, Th. (1996). Dynamics of a random neural network with synaptic depression. Neural networks, 9(4), pp. 575-588. Elsevier 10.1016/0893-6080(95)00109-3

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We consider a randomly connected neural network with linear threshold elements which update in discrete time steps. The two main features of the network are: (1) equally distributed and purely excitatory connections and (2) synaptic depression after repetitive firing. We focus on the time evolution of the expected network activity. The four types of qualitative behavior are investigated: singular excitation, convergence to a constant activity, oscillation, and chaos. Their occurrence is discussed as a function of the average number of connections and the synaptic depression time. Our model relies on experiments with a slice culture of disinhibited embryonic rat spinal cord. The dynamics of these networks essentially depends on the following characteristics: the low non-structured connectivity, the high synaptic depression time and the large EPSP with respect to the threshold value.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Physiology

UniBE Contributor:

Senn, Walter, Streit, Jürg, Larkum, Matthew, Lüscher, Hans-Rudolf

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics
600 Technology > 610 Medicine & health

ISSN:

0893-6080

Publisher:

Elsevier

Language:

English

Submitter:

Virginie Sabado

Date Deposited:

20 Jan 2023 14:25

Last Modified:

30 Jan 2023 23:27

Publisher DOI:

10.1016/0893-6080(95)00109-3

BORIS DOI:

10.48350/177425

URI:

https://boris.unibe.ch/id/eprint/177425

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