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Due to the complexity of focal epilepsy and its risk for transiting to the generalized epilepsy, the development of reliable classification methods to accurately predict and classify focal and generalized seizures is critical for the clinical management of patients with epilepsy. In order to holistically understand the seizure propagation behavior of focal epilepsy, we propose a three-node motif reduced network by respectively simplifying the focal region, surrounding healthy region and their critical regions as the single node. Because three-node motif can richly characterize information evolutions, the motif analysis method could comprehensively investigate the seizure behavior of focal epilepsy. Firstly, we define a new seizure propagation marker value to capture the seizure onsets and intensity. Based on the three-node motif analysis, it is shown that the focal seizure and spreading can be categorized as inhibitory seizure, focal seizure, focal-critical seizure and generalized seizures, respectively. The four types of seizures correspond to specific modal types respectively, reflecting the strong correlation between seizure behavior and information flow evolution. In addition, it is found that the intensity difference of outflow and inflow information from the critical node (connection heterogeneity) and the excitability of the critical node significantly affected the distribution and transition of the four seizure types. In particular, the method of local linear stability analysis also verifies the effectiveness of four types of seizures classification. In sum, this paper computationally confirms the complex dynamic behavior of focal seizures, and the study of criticality is helpful to propose novel seizure control strategies., Competing Interests: Declaration of Competing Interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Temporal lobe epilepsy (TLE) is thought to be associated with neuronal hyperexcitability in the hippocampal-entorhinal cortical (EC) circuit. Due to the complexity of the hippocampal-EC network connections, the biophysical mechanisms of the different circuits in epilepsy generation and propagation are still not fully established. In this work, we propose a hippocampal-EC neuronal network model to explore the mechanism of epileptic generation. We demonstrate that enhanced excitability of pyramidal neurons in cornu ammonis 3 (CA3) can drive hippocampal-EC to produce a transition from background to seizure state and cause exaggerated phase-amplitude coupling (PAC) phenomenon of theta modulated high-frequency oscillations (HFO) in CA3, cornu ammonis 1 (CA1), dentate gyrus, and EC. Interestingly, PAC strength indirectly responds to the degree of CA3 pyramidal (PY) neuron hyperexcitability, suggesting that PAC can be used as a potential marker of seizures. Furthermore, we find that enhanced synaptic connectivity of mossy cells to granule cells and CA3 PY neurons drives the system to produce epileptic discharges. These two channels may play a key role in mossy fiber sprouting. In particular, the PAC phenomenon of delta-modulated HFO and theta-modulated HFO can be generated according to the different degrees of moss fiber sprouting. Finally, the results suggest that hyperexcitability of stellate cells in EC can lead to seizures, which supports the argument that EC can act as an independent source of seizures. Overall, these results highlight the key role of different circuits in seizures, providing a theoretical basis and new insights into the generation and propagation of TLE.

In presurgical monitoring, focal seizure onset is visually assessed from intracranial electroencephalogram (EEG), typically based on the selection of channels that show the strongest changes in amplitude and frequency. As epileptic seizure dynamics is increasingly considered to reflect changes in potentially distributed neural networks, it becomes important to also assess the interrelationships between channels. We propose a workflow to quantitatively extract the nodes and edges contributing to the seizure onset using an across-seizure scoring. We propose a quantification of the consistency of EEG channel contributions to seizure onset within a patient. The workflow is exemplified using recordings from patients with different degrees of seizure-onset consistency.

The concept of epileptogenic network was proposed with epilepsy increasingly understood as the result of network disorder. These alterations of networks proved to be associated with the increased seizure susceptibility in response to external stimulus or internal noise. However, the driving force behind its evolution is unclear. Substantial epilepsy research suggested that the epileptogenicity could be observed beyond clinically defined epileptogenic zone. Therefore, the mechanism of the epileptogenic network evolution may be related with the extension of epileptogenicity. In this paper, a small-world network with each node represented by a bistable computational model was established. Furthermore, part of the nodes connected with the primary epileptogenic zone would be transformed into secondary epileptogenic nodes during the evolution of networks, which represents the formation of secondary epileptogeniciy due to the kindling-like effect. Escape time was defined to quantify the likelihood of a node to develop into epileptic state. Meanwhile, phase synchronization was introduce to analyze the synchronization patterns in simulated multiunit systems. Results showed that the extension of epileptogenicity could increase the seizure likelihood of almost all nodes. Particularly, the synchronization patterns were significantly changed with the occurrence of the secondary epileptogenicity, which might imply the variation of functional connectivity between areas. Meanwhile, the reversal of nonspontaneous epileptogenicity could lead to running-down phenomenon. The extension of epileptogenicity seemed to provide novel insights into the diagnosis and treatment, indicating the possible minimum resection to reach excellent long-term surgical outcomes., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Given the complex temporal evolution of epileptic seizures, understanding their dynamic nature might be beneficial for clinical diagnosis and treatment. Yet, the mechanisms behind, for instance, the onset of seizures are still unknown. According to an existing classification, two basic types of dynamic onset patterns plus a number of more complex onset waveforms can be distinguished. Here, we introduce a basic three-variable model with two time scales to study potential mechanisms of spontaneous seizure onset. We expand the model to demonstrate how coupling of oscillators leads to more complex seizure onset waveforms. Finally, we test the response to pulse perturbation as a potential biomarker of interictal changes.

Epileptic absence seizure characterized by the typical 2-4 Hz spike-wave discharges (SWD) are known to arise due to the physiologically abnormal interactions within the thalamocortical network. By introducing a second inhibitory neuronal population in the cortical system, here we propose a modified thalamocortical field model to mathematically describe the occurrences and transitions of SWD under the mutual functions between cortex and thalamus, as well as the disinhibitory modulations of SWD mediated by the two different inhibitory interneuronal populations. We first show that stimulation can induce the recurrent seizures of SWD in the modified model. Also, we demonstrate the existence of various types of firing states including the SWD. Moreover, we can identify the bistable parametric regions where the SWD can be both induced and terminated by stimulation perturbations applied in the background resting state. Interestingly, in the absence of stimulation disinhibitory functions between the two different interneuronal populations can also both initiate and abate the SWD, which suggests that the mechanism of disinhibition is comparable to the effect of stimulation in initiating and terminating the epileptic SWD. Hopefully, the obtained results can provide theoretical evidences in exploring dynamical mechanism of epileptic seizures.

The transiting mechanism of abnormal brain functional activities, such as the epileptic seizures, has not been fully elucidated. In this study, we employ a probabilistic neural network model to investigate the impact of negative regulation, including negative connections and negative inputs, on the dynamical transition behavior of network dynamics. It is observed that negative connections significantly influence the transition behavior of the network, intensifying the oscillation of discharge probability, corresponding to uneven discharge and epileptic states. Negative inputs, within a certain range, exhibited a similar impact on the dynamic state of the network as negative connections, enhancing network oscillations and resulting in higher fragility. However, larger negative inputs can led to the disappearance of oscillations in the discharge probability, indicating a maintenance of lower fragility. We speculate that negative regulation may be an indispensable factor in the occurrence of epileptic seizures, and future research should give it due consideration. [ABSTRACT FROM AUTHOR]

Based on a neural field network model with impulsive and random disturbances, a preview control method that makes full use of known future information is proposed to reduce the static error of the target signal and the transient oscillatory behavior of the controlled system when it receives random disturbance inputs. The preview controller for epileptic seizures is constructed, and the feasibility and effectiveness of clinical single-target and multi-target stimulation in epilepsy regulation are explored from a computational perspective. In addition, a performance index function is proposed to evaluate the energy consumption of controller with and without preview under different input (target) strategies. Suggestions for different strategies are given in terms of the individualized disease environment of patients. From the perspective of seizure control effectiveness and performance consumption, the results show that the preview controller has a greater advantage. The theory of preview control is applied to the control of epileptic seizures for the first time, and the conclusions of the multifaceted study provide some references for clinical trials and controller applications. [ABSTRACT FROM AUTHOR]

In this paper, a reduced globus pallidus internal (GPI)-corticothalamic (GCT) model is developed, and a tri-phase delay stimulation (TPDS) with sequentially applying three pulses on the GPI representing the inputs from the striatal D1 neurons, subthalamic nucleus (STN), and globus pallidus external (GPE), respectively, is proposed. The GPI is evidenced to control absence seizures characterized by 2 Hz-4 Hz spike and wave discharge (SWD). Hence, based on the basal ganglia-thalamocortical (BGCT) model, we firstly explore the triple effects of Dl-GPI, GPE-GPI, and STN-GPI pathways on seizure patterns. Then, using the GCT model, we apply the TPDS on the GPI to potentially investigate the alternative and improved approach if these pathways to the GPI are blocked. The results show that the striatum D1, GPE, and STN can indeed jointly and significantly affect seizure patterns. In particular, the TPDS can effectively reproduce the seizure pattern if the D1-GPI, GPE-GPI, and STN-GPI pathways are cut off. In addition, the seizure abatement can be obtained by well tuning the TPDS stimulation parameters. This implies that the TPDS can play the surrogate role similar to the modulation of basal ganglia, which hopefully can be helpful for the development of the brain-computer interface in the clinical application of epilepsy. [ABSTRACT FROM AUTHOR]

Presently, we develop a simplified corticothalamic (SCT) model and propose a single-pulse alternately resetting stimulation (SARS) with sequentially applying anodic (A, "+") or cathodic (C, "−") phase pulses to the thalamic reticular (RE) nuclei, thalamus-cortex (TC) relay nuclei, and cortical excitatory (EX) neurons, respectively. Abatement effects of ACC-SARS of RE, TC, and EX for the 2Hz–4Hz spike and wave discharges (SWD) of absence seizures are then concerned. The m:n on-off ACC-SARS protocol is shown to effectively reduce the SWD with the least current consumption. In particular, when its frequency is out of the 2 Hz–4Hz SWD dominant rhythm, the desired seizure abatements can be obtained, which can be further improved by our proposed directional steering (DS) stimulation. The dynamical explanations for the SARS induced seizure abatements are lastly given by calculating the averaged mean firing rate (AMFR) of neurons and triggering averaged mean firing rates (TAMFRs) of 2Hz–4Hz SWD. [ABSTRACT FROM AUTHOR]

Much attention has been dedicated to clinical research of focal epilepsy, but the ability to derive a successful seizure control strategy based on unique dynamical features of the electroencephalogram is an unsolved problem. In this work, we introduce a basic model of spontaneous seizure dynamics and construct from it to a network model of focal-onset seizure dynamics. The full model is composed of coupled oscillators with scale-free network connectivity and a common slow variable. We find that global parameter changes and variation of the connectivity can drive the model from a quiescent state to recurrent seizures, and, eventually, to a permanent-seizure-state. Based on network synchronization features we design a stimulation scheme for the control of the fraction of nodes with strongest phase locking is proposed. Simulations lead to the identification of optimal stimuli for a given type of dynamics. Our results contribute to the development of a rational strategy for the non-surgical treatment of drug-resistant epilepsy. [ABSTRACT FROM AUTHOR]

Brain-derived neurotrophic factor (BDNF) has recently been implicated in the modulation of receptor activation leading to dynamic state transitions in temporal lobe epilepsy (TLE). In addition, the crucial role of neuronal noise in these transitions has been studied in electrophysiological experiments. However, the precise role of these factors during seizure generation in TLE is not known. Building on a previously proposed model of an epileptogenic hippocampal network, we included the actions of BDNF-regulated receptors and intrinsic noise. We found that the effects of both BDNF and noise can increase the activation of N-methyl-D-aspartate receptors leading to excessive C a 2 + flux, which induces abnormal fast spiking and bursting. Our results indicate that the combined effects have a strong influence on the seizure-generating network, resulting in higher firing frequency and amplitude. As correlations between firing increase, the synchronization of the entire network increases, a marker of the ictogenic transitions from normal to seizures-like dynamics. Our work on the effects of BDNF dynamics in a noisy environment might lead to an improved model-based understanding of the pathological mechanisms in TLE. [ABSTRACT FROM AUTHOR]

In this paper, based on the two-compartment unidirectionally coupled thalamocortical model network, we investigated the transition dynamics of epileptic seizures, by considering the inhibitory coupling strength from cortical inhibitory interneuronal (IN) population to excitatory pyramidal (PY) neuronal population as the key bifurcation parameter. The results show that in the single compartment thalamocortical model, inner-compartment inhibitory functions of IN can make the system transit from the absence seizures to the tonic oscillations. In the case of two-compartment coupled thalamocortical model network, the inter-compartment inhibitory coupling functions from the first compartment can drive the second compartment to more easily initiate the absence and tonic seizures at the lower inhibitory coupling strengths, respectively. Also, the driven functions can make the amplitudes of these seizures vary irregularly. Detailed investigations reveal that along with the various state transitions, the system consecutively undergoes Hopf bifurcations, fold of cycles bifurcations and torus bifurcations, respectively. In particular, the reinforcing inter-compartment inhibitory coupling function can induce the chaotic dynamics. We highlight the unidirectional coupling functions between two compartments which might give new insights into the propagation and evolution dynamics of epileptic seizures. [ABSTRACT FROM AUTHOR]

Electrophysiological experiments have long revealed the existence of two-way transitions between absence and tonic-clonic epileptic seizures in the cerebral cortex. Based on a modified spatially-extended Taylor &Baier neural field model, we here propose a computational framework to mathematically describe the transition dynamics between these epileptic seizures. We first demonstrate the existence of various transition types that are induced by disinhibitory functions between two inhibitory variables in an isolated Taylor &Baier model. Moreover, we show that these disinhibition-induced transitions can lead to stable tonic-clonic oscillations as well as periodic spike with slow-wave discharges, which are the hallmark of absence seizures. We also observe fascinating dynamical states, such as periodic 2-spike with slow-wave discharges, tonic death, bursting oscillations, as well as saturated firing. Most importantly, we identify paths that represent physiologically plausible transitions between absence and tonic-clonic seizures in the modified spatially-extended Taylor &Baier model. [ABSTRACT FROM AUTHOR]

The evolution of epilepsy is always accompanied with the transitions of dynamics. Characterizing these dynamical processes can be beneficial for understanding the mechanism of seizures. Meanwhile, there also exist dynamical differences between regions, especially in the epileptogenic and non-epileptogenic areas. Hence, in this study stereo-electroencephalograph (SEEG) recordings from 10 patients with refractory focal epilepsy were collected, and recurrence plot was used to investigate the dynamical differences between different epilepsy stages as well as regions. All dynamical characteristics were quantified by means of recurrence quantification analysis. Furthermore, synchronization between channels were also revealed through cross recurrence plot. Results suggested that almost all channels in the pre-ictal and ictal stages had higher recurrence rate than those in the inter-ictal. And epileptogenic channels were identified with longer diagonal structures, which indicated that recordings from epileptogenic regions were more deterministic and recurrent. When seizures occurred, the synchronizations between these epileptogenic channels were strengthened and dominated the dynamics of epileptic brain. This might provide additional insights into the dynamical nature of epileptic phenomena. • We investigate the dynamical differences between epileptic states as well as regions. • Epileptogenic channels are identified with longer diagonal structures. • Synchronizations between epileptogenic channels are strengthened when seizures occur. [ABSTRACT FROM AUTHOR]