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. We characterize temporal evolution of seizure-associated coupling dynamics in the frontoparietal cortex during late ictal, immediate postictal and interictal resting states, using two measures applied to local field potentials recorded in awake epileptic rats. Signals were analyzed with mean phase coherence index in delta (1-4 Hz), theta (4-10 Hz) beta (10-25 Hz) and gamma (25-50 Hz) frequency bands and mutual information function. The study shows that reflex seizures elicit highly dynamic changes in interhemispheric functional coupling with seizure-, region- and frequency-specific patterns of increased and decreased connectivity during late ictal and immediate postictal periods. Also, secondary generalization of recurrent seizures (kindling) is associated with pronounced alterations in resting-state functional connectivity - an early wideband decrease and a subsequent beta-gamma increase. The findings show that intracortical functional connectivity is dynamically modified in response to seizures on short and long timescales, suggesting the existence of activity-dependent plastic network alterations that may promote or prevent seizure propagation within the cortex and underlie postictal behavioral impairments.

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). The four intervals were visually marked by an expert neurophysiologist and the strength of couplings between electrode pairs were calculated in both directions. Ictally, a strong decrease in coupling strength was found between Hp and FC, as well as a large increase bidirectionally between PC and FC and unidirectionally from FC and PC to OC, and from FC to Hp over all epochs. The highest dose of WIN increased the couplings strength from FC to Hp and from OC to PC during 4 and 2 hr respectively in all intervals, and decreased the FC to PC coupling strength postictally in epoch 2. A single rat showed generalized convulsive seizures after the highest dose: this rat shared not only coupling changes with the other rats in the same condition, but showed many more. WIN reduced SWD number in epoch 2 and 3, their mean duration increased in epochs 3 and 4. Conclusions:during SWDs FC and PC are strongly coupled and drive OC, while at the same time the influence of Hp to FC is diminished. The first is in agreement with the cortical focus theory, the latter demonstrates an involvement of the hippocampus in SWD occurrence and that ictally the hippocampal control of the cortico-thalamo-cortical system is lost. WIN causes dramatic network changes which have major consequences for the decrease of SWDs, the occurrence of convulsive seizures, and the normal cortico-cortical and cortico-hippocampal interactions.

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. Twenty-four-hour (12:12 light/dark phases) electroencephalographic (EEG) recordings of 12 Wistar Albino Glaxo, originally bred in Rijswijk (WAG/Rij) rats, a well-known genetic model of absence epilepsy, were analyzed and transformed into sequences of 2-s length intervals of the following 6 possible states: active wakefulness (AW), passive wakefulness (PW), deep slow-wave sleep (DSWS), light slow-wave sleep (LSWS), rapid eye movement (REM) sleep, and SWDs, given discrete series of categorical data. Probabilities of all transitions between states and Shannon entropy of transitions were calculated for the light and dark phases separately and statistically analyzed. Common differences between the light and the dark phases were found regarding the time spent in AW, LSWS, DSWS, and SWDs. The most probable transitions were that AW was preceded and followed by PW and vice versa regardless of the phase of the photoperiod. A similar relationship was found for light and deep slow-wave sleep. The most probable transitions to and from SWDs were AW and LSWS, respectively, with these transition likelihoods being consistent across both circadian phases. The second most probable transitions around SWDs appeared more variable between light and dark. During the light phase, SWDs occurred around PW and participated exclusively in sleep initiation; in the dark phase, SWDs were seen on both, ascending and descending steps towards and from sleep. Conditional Shannon entropy showed that AW and DSWS are the most predictable events, while the possible prediction horizon of SWDs is not larger than 4 s and despite the higher occurrence of SWDs in the dark phase, did not differ between phases. It can be concluded that although SWDs show a stable, strong circadian rhythm with a peak in number during the dark phase, their occurrence cannot be reliably predicted by the preceding behavioral state, except at a very short time base.

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. The first level consists of three structures: the nervus trigeminus serving as an input, the thalamus and the somatosensory cortex; the second level of a group of nearby situated neurons belonging to one of three modeled structures. RESULTS: The model reproduces the main features of the transition from normal to epileptiformic activity and its spontaneous abortion: an increase in the oscillation amplitude, the emergence of the main frequency and its higher harmonics, and the ability to generate trains of seizures. The model was stable with respect to variations in the structure of couplings and to scaling. The analyzes of the interactions between model structures from their time series using Granger causality method showed that the model reproduced the preictal coupling increase detected previously from experimental data. CONCLUSION: SWDs can be generated by changes in network organization. It is proposed that a specific pathological architecture of couplings in the brain is necessary to allow the transition from normal to epileptiformic activity, next to by others modeled and reported factors referring to complex, intrinsic, and synaptic mechanisms.

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. Previously, the dynamics of coupling between different layers of the perioral cortical region and between these zones and different thalamic nuclei was studied in time windows around the SWDs, using nonlinear Granger causality. The aim of the present study was to investigate, using the same method, the coupling dynamics between different regions of the cortex and between these regions and the hippocampus. METHODS: Local field potentials were recorded in the frontal, parietal, and occipital cortices and in the hippocampus of 19 WAG/Rij rats. To detect changes in coupling reliably in a short time window, in order to provide a good temporal resolution, the innovative adapted time varying nonlinear Granger causality method was used. Mutual information function was calculated in addition to validate outcomes. Results of both approaches were tested for significance. RESULTS: The SWD initiation process was revealed as an increase in intracortical interactions starting from 3.5s before the onset of electrographic seizure. The earliest preictal increase in coupling was directed from the frontal cortex to the parietal cortex. Then, the coupling became bidirectional, followed by the involvement of the occipital cortex (1.5s before SWD onset). There was no driving from any cortical region to hippocampus, but a slight increase in coupling from hippocampus to the frontoparietal cortex was observed just before SWD onset. After SWD onset, an abrupt drop in coupling in all studied pairs was observed. In most of the pairs, the decoupling rapidly disappeared, but driving force from hippocampus and occipital cortex to the frontoparietal cortex was reduced until the SWD termination. CONCLUSION: Involvement of multiple cortical regions in SWD initiation shows the fundamental role of corticocortical feedback loops, forming coupling architecture and triggering the generalized seizure. The results add to the ultimate aim to construct a complete picture of brain interactions preceding and accompanying absence seizures in rats.

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. RESULTS: The nonlinear adaptive method showed statistically significant preictal changes in Granger causality in almost all pairs of channels, as well as ictal changes in cortico-cortical, cortico-thalamic and intrathalamic networks. Current results suggest rearrangement of interactions in the thalamo-cortical network accompanied the transition from preictal to ictal phase. COMPARISON WITH EXISTING METHOD(S): The linear method revealed no preictal and less ictal changes in causality. CONCLUSIONS: Achieved results suggest that this proposed adaptive nonlinear method is more sensitive than the linear one to dynamics of network properties. Since changes in coupling were found before the seizure-related increase of LFP signal amplitude and also based on some additional tests it seems likely that they were not spurious and could not result from signal to noise ratio change.