A new description of epileptic seizures based on dynamic analysis of a thalamocortical model

Abstract

Increasing evidence suggests that the brain dynamics can be interpreted from the viewpoint of nonlinear dynamical systems. The aim of this paper is to investigate the behavior of a thalamocortical model from this perspective. The model includes both cortical and sensory inputs that can affect the dynamic nature of the model. Driving response of the model subjected to various harmonic stimulations is considered to identify the effects of stimulus parameters on the cortical output. Detailed numerical studies including phase portraits, Poincare maps and bifurcation diagrams reveal a wide range of complex dynamics including period doubling and chaos in the output. Transition between different states can occur as the stimulation parameters are changed. In addition, the amplitude jump phenomena and hysteresis are shown to be possible as a result of the bending in the frequency response curve. These results suggest that the jump phenomenon due to the brain nonlinear resonance can be responsible for the transitions between ictal and interictal states.

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

“…2( A ) increasing coupling up to 1.25 causes more synchronization. At a coupling coefficient equal to 1.25, the network’s synchronization has increased sharply, which can confirm a disorder in network function [69–71]. Our results indicated that in the [1.25, 4.25] regime of coupling strength, the synchronization values are high.…”

“…3 the network shows the complete synchronization for 2 < 𝒦 < 4 which corresponding to coherent states. The nervous system in this condition is not in a healthy state and may lead to some brain disorder such as epileptic seizure activity [69, 73, 74]. Indeed, the system activity are coherent in space and time and shows the global synchronization.…”

Single-trial EEG analysis reveals burst structure during photic driving

“…Our results provide an explanation for the previously observed fluctuations in averaged photic driving data. Future applications include basic neuroscience research studies as well as clinical studies in epilepsy [15,16], autism spectrum disorders [17][18][19], schizophrenia [20,21], and migraine [22].…”

“…Despite the not fully understood mechanisms, in clinical applications, IPS is a widespread method and is typically used as an activation method. Especially in epilepsy diagnosis [15,16], it is a frequently used method. Moreover, IPS has been applied in autism spectrum disorders [17][18][19], schizophrenia [20,21], and migraine [22], among others.…”

Seizure evolution can be characterized as path through synaptic gain space of a neural mass model

“…The study of dynamics underlying epilepsy can be achieved in a purely theoretical way using bifurcation theory, which is a powerful tool for systematically studying the relationship between the output of the model and physiological based parameters (Breakspear et al., ; Geng et al., ; Marten, Rodrigues, Benjamin, Richardson, & Terry, ; Sohanian‐Haghighi & Markazi, ; Spiegler, Kiebel, Atay, & Knosche, ). It can also be achieved by fitting the model with recorded data (Freestone et al., ; Havlicek, Friston, Jan, Brazdil, & Calhoun, ; Lopez‐Cuevas, Castillo‐Toledo, Medina‐Ceja, & Ventura‐Mejia, ; Wendling et al., ), exploring this way the path through parameter space (Nevado‐Holgado et al., ).…”