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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Synchronization structure of evolving epileptic networks using cross-entropy

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Rodrigues, Abner Cardoso [1] ; Sales Ferreira Caboclo, Luis Otavio [2] ; Cerdeira, Hilda Alicia [3, 4] ; Amaro, Jr., Edson [2] ; Machado, Birajara Soares [2]
Total Authors: 5
[1] Univ Sao Paulo, Inst Matemat & Estat, Sao Paulo - Brazil
[2] Hosp Israelita Albert Einstein, Sao Paulo - Brazil
[3] Sao Paulo State Univ, UNESP, Inst Fis Teor, Sao Paulo - Brazil
[4] Epistemic, Dept Res, Sao Paulo - Brazil
Total Affiliations: 4
Document type: Journal article
Source: European Physical Journal-Special Topics; v. 227, n. 7-9, p. 883-893, OCT 2018.
Web of Science Citations: 1

In this paper we present connectivity patterns of evolving large scale epileptic networks. We employed a cross-entropy measure in the frequency domain on EEG signals to infer the networks, before and during episodes of epileptic seizures. This measure allowed us to make a richer portrait about the node interactions on the graph and to identify emergent structures associated with the synchronization of brain activity. Our results points to a more complex scenario of network organization than the synchronized/unsynchronized dichotomy, with two main results: first, showing regions with unsynchronized (or independent) behavior, even during absence seizures, contradicting the concept of hypersynchrony. Furthermore, we explore the cross-entropy fluctuations along the seizure: a group of nodes became more similar over time while another group became more different, showing a complementary behaviour and different local brain activities. These results bring new questions about the spreading and the sustenance of the epileptic seizures and others synchronization phenomena in living systems. (AU)

FAPESP's process: 11/11973-4 - ICTP South American Institute for Fundamental Research: a regional center for theoretical physics
Grantee:Nathan Jacob Berkovits
Support type: Research Projects - Thematic Grants