Modeling spike-wave discharges by a complex network of neuronal oscillators
Publication year
2018Number of pages
12 p.
Source
Neural Networks, 98, (2018), pp. 271-282ISSN
Publication type
Article / Letter to editor
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Organization
SW OZ DCC SMN
Journal title
Neural Networks
Volume
vol. 98
Languages used
English (eng)
Page start
p. 271
Page end
p. 282
Subject
Biological psychology; DI-BCB_DCC_Theme 3: Plasticity and Memory; Biologische psychologieAbstract
Purpose: The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics of SWDs and dynamics of coupling between brain regions, relying mainly on properties of hierarchically organized networks of a large number of neuronal oscillators. Model: We used a two level mesoscale model. The first level consists of three structures: the nervus trigeminus serving as an input, the thalamus and the somatosensory cortex; the second level of a group of nearby situated neurons belonging to one of three modeled structures. Results: The model reproduces the main features of the transition from normal to epileptiformic activity and its spontaneous abortion: an increase in the oscillation amplitude, the emergence of the main frequency and its higher harmonics, and the ability to generate trains of seizures. The model was stable with respect to variations in the structure of couplings and to scaling. The analyzes of the interactions between model structures from their time series using Granger causality method showed that the model reproduced the preictal coupling increase detected previously from experimental data. Conclusion: SWDs can be generated by changes in network organization. It is proposed that a specific pathological architecture of couplings in the brain is necessary to allow the transition from normal to epileptiformic activity, next to by others modeled and reported factors referring to complex, intrinsic, and synaptic mechanisms.
This item appears in the following Collection(s)
- Academic publications [246860]
- Electronic publications [134256]
- Faculty of Social Sciences [30549]
- Open Access publications [107776]
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