The role of rebound spikes in the maintenance of self-sustained neural spiking activity
| Autor: | Rogério Gomes, Bruno Andre Santos, Phil Husbands |
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| Rok vydání: | 2021 |
| Předmět: |
Spiking neural network
0303 health sciences Computer science Applied Mathematics Mechanical Engineering Aerospace Engineering Ocean Engineering Stimulation Stimulus (physiology) Inhibitory postsynaptic potential 03 medical and health sciences Neural activity 0302 clinical medicine medicine.anatomical_structure Control and Systems Engineering medicine Neural system Spike (software development) Neuron Electrical and Electronic Engineering Neuroscience 030217 neurology & neurosurgery 030304 developmental biology |
| Zdroj: | Nonlinear Dynamics. 105:767-784 |
| ISSN: | 1573-269X 0924-090X |
| Popis: | In general, the mechanisms that maintain the activity of neural systems after a triggering stimulus has been removed are not well understood. Different mechanisms involving at the cellular and network levels have been proposed. In this work, based on analysis of a computational model of a spiking neural network, it is proposed that the spike that occurs after a neuron is inhibited (the rebound spike) can be used to sustain the activity in a recurrent inhibitory neural circuit after the stimulation has been removed. It is shown that, in order to sustain the activity, the neurons participating in the recurrent circuit should fire at low frequencies. It is also shown that the occurrence of a rebound spike depends on a combination of factors including synaptic weights, synaptic conductances and the neuron state. We point out that the model developed here is minimalist and does not aim at empirical accuracy. Its purpose is to raise and discuss theoretical issues that could contribute to the understanding of neural mechanisms underlying self-sustained neural activity. |
| Databáze: | OpenAIRE |
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