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Self-sustained activity of low firing rate in balanced networks

Borges, FS and Protachevicz, PR and Pena, RFO and Lameu, EL and Higa, GSV and Kihara, AH and Matias, FS and Antonopoulos, CG and de Pasqual, R and Roque, AC and Iarosz, KC and Ji, P and Batista, AM (2019) 'Self-sustained activity of low firing rate in balanced networks.' Physica A: Statistical Mechanics and its Applications. ISSN 0378-4371

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Abstract

Self-sustained activity in the brain is observed in the absence of external stimuli and contributes to signal propagation, neural coding, and dynamic stability. It also plays an important role in cognitive processes. In this work, by means of studying intracellular recordings from CA1 neurons in rats and results from numerical simulations, we demonstrate that self-sustained activity presents high variability of patterns, such as low neural firing rates and activity in the form of small-bursts in distinct neurons. In our numerical simulations, we consider random networks composed of coupled, adaptive exponential integrate-and-fire neurons. The neural dynamics in the random networks simulates regular spiking (excitatory) and fast spiking (inhibitory) neurons. We show that both the connection probability and network size are fundamental properties that give rise to self-sustained activity in qualitative agreement with our experimental results. Finally, we provide a more detailed description of self-sustained activity in terms of lifetime distributions, synaptic conductances, and synaptic currents.

Item Type: Article
Uncontrolled Keywords: Spontaneous activity, Neural networks, Whole-cell recordings, Asynchronous irregular activity
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 20 Sep 2019 09:20
Last Modified: 20 Sep 2019 10:15
URI: http://repository.essex.ac.uk/id/eprint/25327

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