Transient destabilization of interhemispheric functional connectivity induced by spreading depolarization.

Cortical spreading depolarization (CSD), a slowly propagating wave of transient cellular depolarization, is a reliable cortical response to various brain insults (stroke, trauma, seizures) and underlying mechanism of migraine aura. Little is known about CSD effects on brain network activity. Using undirected (mutual information, MI) and directed (transfer entropy, TE) measures, we studied the dynamics of cross-hemispheric connectivity associated with the development of unilateral CSD in freely behaving rats and the involvement of inhibitory transmission in mechanisms of the coupling changes.

Intracortical functional connectivity dynamics induced by reflex seizures.

Functional connectivity analysis is gaining more interest due to its promising clinical applications. To study network mechanisms underlying seizure termination and postictal depression, we explore dynamics of interhemispheric functional connectivity near the offset of focal and bilateral seizures in the experimental model of reflex audiogenic epilepsy. In the model, seizures and spreading depression are induced by sound stimulation of genetically predisposed rodents.

Network analysis reveals a role of the hippocampus in absence seizures: The effects of a cannabinoid agonist.

The role of the hippocampus (Hp) in absence epileptic networks and the effect of endocannabinoid system on this network remain enigmatic. Here, using adapted nonlinear Granger causality, we compared the differences in network strength in four intervals (baseline or interictal, preictal, ictal and postictal) in two hours before (Epoch 1) and six hours (epochs 2, 3 and 4) after the administration of three different doses of the endocannabinoid agonist WIN55,212-2 (WIN) or solvent. Local field potentials were recorded for eight hours in 23 WAG/Rij rats in the Frontal (FC), Parietal PC), Occipital Cortex (OC) and in the hippocampus (Hp).

Thalamo-Cortical and Thalamo-Thalamic Coupling During Sleep and Wakefulness in Rats.

The thalamus, a heterogeneous brain structure, is involved in the generation of sleep-related thalamo-cortical oscillations. Higher order nuclei might possess a distinct function compared with first-order nuclei in brain communication. Here it is investigated whether this distinction can also be found during the process of falling asleep and deepening of slow-wave sleep.

Noise robust approach to reconstruction of van der Pol-like oscillators and its application to Granger causality.

Van der Pol oscillators and their generalizations are known to be a fundamental model in the theory of oscillations and their applications. Many objects of a different nature can be described using van der Pol-like equations under some circumstances; therefore, methods of reconstruction of such equations from experimental data can be of significant importance for tasks of model verification, indirect parameter estimation, coupling analysis, system classification, etc. The previously reported techniques were not applicable to time series with large measurement noise, which is usual in biological, climatological, and many other experiments.

Can absence seizures be predicted by vigilance states?: Advanced analysis of sleep-wake states and spike-wave discharges' occurrence in rats.

Spike-wave discharges (SWDs) are the main manifestation of absence epilepsy. Their occurrence is dependent on the behavioral state, and they preferentially occur during unstable vigilance periods. The present study investigated whether the occurrence of SWDs can be predicted by the preceding behavioral state and whether this relationship is different between the light and the dark phases of the 24-h day.

The Brain Network in a Model of Thalamocortical Dysrhythmia.

Sensory information processing and higher cognitive functions rely on the interactions between thalamus and cortex. Many types of neurological and psychiatric disorders are accompanied or driven by alterations in the brain connectivity. In this study, putative changes in functional and effective corticocortical (CC), thalamocortical (TC), and corticothalamic (CT) connectivity during wakefulness and slow-wave sleep (SWS) in a model of thalamocortical dysrhythmia, TRIP8b mice, and in control (wild-type or WT) mice are described.

Modeling spike-wave discharges by a complex network of neuronal oscillators.

Purpose: The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics of SWDs and dynamics of coupling between brain regions, relying mainly on properties of hierarchically organized networks of a large number of neuronal oscillators.

Model: We used a two level mesoscale model.

Changes in corticocortical and corticohippocampal network during absence seizures in WAG/Rij rats revealed with time varying Granger causality.

Purpose: Spike-and-wave discharges (SWDs) recorded in the cortical EEGs of WAG/Rij rats are the hallmark for absence epilepsy in this model. Although this type of epilepsy was long regarded as a form of primary generalized epilepsy, it is now recognized that there is an initiation zone - the perioral region of the somatosensory cortex. However, networks involved in spreading the seizure are not yet fully known.

Application of adaptive nonlinear Granger causality: disclosing network changes before and after absence seizure onset in a genetic rat model.

Background: Advanced methods of signal analysis of the preictal and ictal activity dynamics characterizing absence epilepsy in humans with absences and in genetic animal models have revealed new and unknown electroencephalographic characteristics, that has led to new insights and theories.

New Method: Taking into account that some network associations can be considered as nonlinear, an adaptive nonlinear Granger causality approach was developed and applied to analyze cortico-cortical, cortico-thalamic and intrathalamic network interactions from local field potentials (LFPs). The outcomes of adaptive nonlinear models, constructed based on the properties of electroencephalographic signal and on statistical criteria to optimize the number of coefficients in the models, were compared with the outcomes of linear Granger causality.