E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.
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Publication Date
2018-06-12Journal Title
Sci Rep
ISSN
2045-2322
Publisher
Springer Science and Business Media LLC
Volume
8
Issue
1
Pages
8939
Language
eng
Type
Article
Physical Medium
Electronic
Metadata
Show full item recordCitation
Trapp, P., Echeveste, R., & Gros, C. (2018). E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.. Sci Rep, 8 (1), 8939. https://doi.org/10.1038/s41598-018-27099-5
Abstract
Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the E-I balanced state are substantially larger than the overall input. We show that such a state arises naturally in fully adapting networks which are deterministic, autonomously active and not subject to stochastic external or internal drivings. Temporary imbalances between excitatory and inhibitory inputs lead to large but short-lived activity bursts that stabilize irregular dynamics. We simulate autonomous networks of rate-encoding neurons for which all synaptic weights are plastic and subject to a Hebbian plasticity rule, the flux rule, that can be derived from the stationarity principle of statistical learning. Moreover, the average firing rate is regulated individually via a standard homeostatic adaption of the bias of each neuron's input-output non-linear function. Additionally, networks with and without short-term plasticity are considered. E-I balance may arise only when the mean excitatory and inhibitory weights are themselves balanced, modulo the overall activity level. We show that synaptic weight balance, which has been considered hitherto as given, naturally arises in autonomous neural networks when the here considered self-limiting Hebbian synaptic plasticity rule is continuously active.
Identifiers
External DOI: https://doi.org/10.1038/s41598-018-27099-5
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284675
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