Stochastic fluctuations of permittivity coupling regulate seizure dynamics in partial epilepsy

Guo, Daqing; Xia, Chuan; Wu, Shengdun; Zhang, Tianjiao; Zhang, Yangsong; Yang, Xiaobo; Yao, Dezhong

doi:10.1007/s11431-017-9030-4

Cited by 14 publications

(6 citation statements)

References 46 publications

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“…Blood oxygenation level-dependent (BOLD) fMRI has been recognized as an effective noninvasive technique to investigate epilepsy (Luo et al, 2014 ; Cao et al, 2017 ; Ji et al, 2017 ). Seizure dynamics of epilepsy have been studied using the epileptor model (Guo et al, 2017 ). Simultaneous EEG and functional MRI (EEG-fMRI) has been used to study the brain activity in patients with IGE (Gotman et al, 2005 ; Li et al, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

Jiang

Peng

et al. 2017

Front. Comput. Neurosci.

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The purpose of this study was to evaluate the spatiotemporal Consistency of spontaneous activities in local brain regions in patients with generalized tonic-clonic seizures (GTCS). The resting-state fMRI data were acquired from nineteen patients with GTCS and twenty-two matched healthy subjects. FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) metric was used to analyze the spontaneous activity in whole brain. The FOCA difference between two groups were detected using a two sample t-test analysis. Correlations between the FOCA values and features of seizures were analyzed. The findings of this study showed that patients had significantly increased FOCA in motor-related cortex regions, including bilateral supplementary motor area, paracentral lobule, precentral gyrus and left basal ganglia, as well as a substantial reduction of FOCA in regions of default mode network (DMN) and parietal lobe. In addition, several brain regions in DMN demonstrated more reduction with longer duration of epilepsy and later onset age, and the motor-related regions showed higher FOCA value in accompany with later onset age. These findings implicated the abnormality of motor-related cortical network in GTCS which were associated with the genesis and propagation of epileptiform activity. And the decreased FOCA in DMN might reflect the intrinsic disturbance of brain activity. Moreover, our study supported that the FOCA might be potential tool to investigate local brain spontaneous activity related with the epileptic activity, and to provide important insights into understanding the underlying pathophysiological mechanisms of GTCS.

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Section: Introductionmentioning

confidence: 99%

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

Jiang

Peng

et al. 2017

Front. Comput. Neurosci.

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“…This result has a biological importance due to the fact that the seizure state is a relatively small probability event compared with the normal state. DaQing et al (2017) showed that noise can regulate seizure dynamics in partial epilepsy. Figure 2F displays falsemml-overlineR¯×gexc for Gaussian noise with mean 0 and standard deviation σ noise equal to 25 pA and 250 pA. We verify that the bistable region decreases when the noise level increases.…”

Section: Resultsmentioning

confidence: 99%

Bistable Firing Pattern in a Neural Network Model

Protachevicz

Borges

Lameu

et al. 2019

Front. Comput. Neurosci.

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Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.

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“…In addition to the interaction between the fast and slow nervous system in the model, it is also coupled through the permittivity variable

, as shown in Figure 1A ( 28 ). The dielectric coefficients are considered to be correlated with excitability and control the onset state of the model.…”

Section: Models and Methodsmentioning

confidence: 99%

“…The dielectric coefficients are considered to be correlated with excitability and control the onset state of the model. Figure 1B ( 28 ) gives a bifurcation diagram of the fast variable

with regards to the variable z . When the dielectric coefficient goes from large to small through the SNIC (Saddle-node on invariant circle), the model transitions from the interictal to the ictal state.…”

Section: Models and Methodsmentioning

confidence: 99%

The distribution and heterogeneity of excitability in focal epileptic network potentially contribute to the seizure propagation

Fan

Wu²,

Luan³

et al. 2023

Front. Psychiatry

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IntroductionExisting dynamical models can explain the transmigration mechanisms involved in seizures but are limited to a single modality. Combining models with networks can reproduce scaled epileptic dynamics. And the structure and coupling interactions of the network, as well as the heterogeneity of both the node and network activities, may influence the final state of the network model.MethodsWe built a fully connected network with focal nodes prominently interacting and established a timescale separated epileptic network model. The factors affecting epileptic network seizure were explored by varying the connectivity patterns of focal network nodes and modulating the distribution of network excitability.ResultsThe whole brain network topology as the brain activity foundation affects the consistent delayed clustering seizure propagation. In addition, the network size and distribution heterogeneity of the focal excitatory nodes can influence seizure frequency. With the increasing of the network size and averaged excitability level of focal network, the seizure period decreases. In contrast, the larger heterogeneity of excitability for focal network nodes can lower the functional activity level (average degree) of focal network. There are also subtle effects of focal network topologies (connection patterns of excitatory nodes) that cannot be ignored along with non-focal nodes.DiscussionUnraveling the role of excitatory factors in seizure onset and propagation can be used to understand the dynamic mechanisms and neuromodulation of epilepsy, with profound implications for the treatment of epilepsy and even for the understanding of the brain.

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Stochastic fluctuations of permittivity coupling regulate seizure dynamics in partial epilepsy

Cited by 14 publications

References 46 publications

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

Altered Local Spatiotemporal Consistency of Resting-State BOLD Signals in Patients with Generalized Tonic-Clonic Seizures

Bistable Firing Pattern in a Neural Network Model

The distribution and heterogeneity of excitability in focal epileptic network potentially contribute to the seizure propagation

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