Brain network dynamics characterization in epileptic seizures

Rodrigues, Abner Cardoso; Machado, Birajara Soares; Florence, Gerson; Hamad, Ana Paula Andrade; Sakamoto, Américo Ceiki; Fujita, André; Baccalá, Luiz Antonio; Amaro, Edson; Sameshima, Koichi

doi:10.1140/epjst/e2014-02306-8

Cited by 11 publications

(7 citation statements)

References 30 publications

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“…Consequently, phase relationships between brain regions affect the relative timing of action potentials in those regions [20][21][22]. Moreover, studies using synchronization to analyse functional and effective connectivity [23][24][25], applied to neurophysiological data such as fMRI [26,27] and EEG [28,29] allowed a more accurate identification of specific anatomical areas activated during cognitive tasks and other brain states.…”

Section: Introductionmentioning

confidence: 99%

Phase-lag synchronization analysis in complex systems with directed inter-relations

Martins

Rodrigues

Cerdeira

et al. 2016

Eur. Phys. J. Spec. Top.

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In this work, we proposed a novel way to estimate phase-lag synchronization in coupled systems. This approach was applied into two systems: a directed-coupled Rössler-Lorenz system and a network of Izhikevich neurons. For the former case, the phase-lag synchronization revealed an increase in complexity for the Lorenz subsystem components, when the coupling is activated. The opposite behavior was observed when the Izhikevich network were organized in a hierarchical way. Our results point out to emergent synchronism related to causal interactions in coupled complex systems.

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Section: Introductionmentioning

confidence: 99%

Phase-lag synchronization analysis in complex systems with directed inter-relations

Martins

Rodrigues

Cerdeira

et al. 2016

Eur. Phys. J. Spec. Top.

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“…In order to investigate the role of the networks over the hypersynchronization feature of the seizure,we simulated a neuronal network with hubs, a topology that has been shown in [15] to appear during the ictal period. Some analytical and simulation studies point to a dependence between synchronizability of a network and the presence of highly connected nodes [16][17][18], while other works points towards the opposite direction [19].…”

Section: Introductionmentioning

confidence: 99%

The influence of hubs in the structure of a neuronal network during an epileptic seizure

Rodrigues

Cerdeira

Machado

2016

Eur. Phys. J. Spec. Top.

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In this work, we propose changes in the structure of a neuronal network with the intention to provoke strong synchronization to simulate episodes of epileptic seizure. Starting with a network of Izhikevich neurons we slowly increase the number of connections in selected nodes in a controlled way, to produce (or not) hubs. We study how these structures alter the synchronization on the spike firings interval, on individual neurons as well as on mean values, as a function of the concentration of connections for random and non-random (hubs) distribution. We also analyze how the post-ictal signal varies for the different distributions. We conclude that a network with hubs is more appropriate to represent an epileptic state. BSM thanks the UNIEMP for their support. HAC thanks the FAPESP (process 2011/ 11973-4) for their support.

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“…Os valores na tabela são as médias para cada medida com o desvio padrão entre parênteses. Adaptado de Rodrigues et al (2014). Durante a crise a sincronização é mais elevada.…”

Section: Resultsunclassified

“…Note que o Paciente 5 apresenta dois picos noR, mas que não foram em períodos de crise, provavelmente devido a curta duração do evento. Adaptado de Rodrigues et al (2014).…”

Section: Padrões De Conectividade Revelados Através De Entropia Cruzadaunclassified

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Caracterização e modelagem da atividade eletrofisiológica em pacientes com epilepsia

Neto¹,

Cardoso²

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Complex networks applyed to brain activity signals show the presence abnormal of connectivity patterns in patients suffering with diseases and others psychiatric disorders. From this, some authors began to question the influence of these structures in the cause of these problems and how it leads to the development of these abnormal patterns. From a theoretical point of view, several studies show how the topology of a network can change a process that maintains it, for example how a network influences the propagation of a system failure, synchronization or difussion processes. In this sense, the objective of this study is to characterize the functional networks of patients during episodes of seizures, making a parallel between the structure of these networks and the dynamic processes involved in the epilepsy, in particular the synchronization. For this, real data were analyzed and the inferred networks in a first step. And then, artificial simulations using the parameters obtained from the analysis were employed to show the impact of these networks in dynamic processes. The results indicate structures that can enhance the synchronization and the influence of the coupling mode on these systems.

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Brain network dynamics characterization in epileptic seizures

Cited by 11 publications

References 30 publications

Phase-lag synchronization analysis in complex systems with directed inter-relations

Phase-lag synchronization analysis in complex systems with directed inter-relations

The influence of hubs in the structure of a neuronal network during an epileptic seizure

Caracterização e modelagem da atividade eletrofisiológica em pacientes com epilepsia

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