Remission of benign epilepsy with rolandic spikes: an EEG-based connectivity study at the onset of the disease and at remission

Connectivity increases during spikes and spike-free periods in self-limited epilepsy with centrotemporal spikes

OBJECTIVE

To understand the impact of interictal spikes on brain connectivity in patients with Self-Limited Epilepsy with Centrotemporal Spikes (SeLECTS).

METHODS

Electroencephalograms from 56 consecutive SeLECTS patients were segmented into periods with and without spikes. Connectivity between electrodes was calculated using the weighted phase lag index. To determine if there are chronic alterations in connectivity in SeLECTS, we compared spike-free connectivity to connectivity in 65 matched controls. To understand the acute impact of spikes, we compared connectivity immediately before, during, and after spikes versus baseline, spike-free connectivity. We explored whether behavioral state, spike laterality, or antiseizure medications affected connectivity.

RESULTS

Children with SeLECTS had markedly higher connectivity than controls during sleep but not wakefulness, with greatest difference in the right hemisphere. During spikes, connectivity increased globally; before and after spikes, left frontal and bicentral connectivity increased. Right hemisphere connectivity increased more during right-sided than left-sided spikes; left hemisphere connectivity was equally affected by right and left spikes.

CONCLUSIONS

SeLECTS patient have persistent increased connectivity during sleep; connectivity is further elevated during the spike and perispike periods.

SIGNIFICANCE

Testing whether increased connectivity impacts cognition or seizure susceptibility in SeLECTS and more severe epilepsies could help determine if spikes should be treated.

Inter-ictal network of focal epilepsy and effects of clinical factors on network activity

OBJECTIVE

Aim of the study was to explore the inter-ictal, resting-state EEG network in patients with focal epilepsy (FE) and to specify clinical factors that influence network activity.

METHODS

Functional EEG connectivity (EEGfC) differences were computed between 232 FE patients (FE group) and 77 healthy controls. EEGfC was computed among 23 cortical regions within each hemisphere, for 25 very narrow bands from 1 to 25 Hz. We computed independent effects for six clinical factors on EEGfC in the FE group, by ANOVA and post-hoc t-statistics, corrected for multiple comparisons by false discovery rate method.

RESULTS

Robust, statistically significant EEGfC differences emerged between the FE and the healthy control groups. Etiology, seizure type, duration of the illness and antiepileptic treatment were independent factors that influenced EEGfC. Statistically significant results occurred selectively in one or a few very narrow bands and outlined networks. Most abnormal EEGfC findings occurred at frequencies that mediate integrative and motor activities.

CONCLUSIONS

FE patients have abnormal resting-state EEGfC network activity. Clinical factors significantly modify EEGfC.

SIGNIFICANCE

Delineation of the FE network and modifying factors can open the way for targeted investigations and introduction of EEGfC into epilepsy research and practice.

Atypical features of benign rolandic epilepsy in Chinese children: Retrospective study

BACKGROUND

Benign rolandic epilepsy (BRE) is one of the most common focal epilepsies in childhood, but less typical clinical presentations may lead to misdiagnosis and incorrect treatment. The focus of this study was therefore to retrospectively investigate the less typical features of BRE in Chinese children.

METHODS

Data on 316 Chinese children with BRE were collected and analyzed.

RESULTS

A total of 7.3% of children complained of tension, fear and terror at the onset of a seizure, and 5.4% had been misdiagnosed with mesial temporal lobe epilepsy. Approximately 12.3% had post-ictal Todd's paresis, with 6.6% having been misdiagnosed and given incorrect treatment. Nineteen children (6%) had neuroradiologic abnormalities, which could lead to a diagnosis of symptomatic epilepsy. Twenty-five patients (8.0%) had cognitive deficits.

CONCLUSIONS

Greater recognition of, and further investigation into, the spectrum of BRE are needed.

Children with well controlled epilepsy possess different spatio-temporal patterns of causal network connectivity during a visual working memory task

Using spectral Granger causality (GC) we identified distinct spatio-temporal causal connectivity (CC) patterns in groups of control and epileptic children during the execution of a one-back matching visual discrimination working memory task. Differences between control and epileptic groups were determined for both GO and NOGO conditions. The analysis was performed on a set of 19-channel EEG cortical activity signals. We show that for the GO task, the highest brain activity in terms of the density of the CC networks is observed in α band for the control group while for the epileptic group the CC network seems disrupted as reflected by the small number of connections. For the NOGO task, the denser CC network was observed in θ band for the control group while widespread differences between the control and the epileptic group were located bilaterally at the left temporal-midline and parietal areas. In order to test the discriminative power of our analysis, we performed a pattern analysis approach based on fuzzy classification techniques. The performance of the classification scheme was evaluated using permutation tests. The analysis demonstrated that, on average, 87.6 % of the subjects were correctly classified in control and epileptic. Thus, our findings may provide a helpful insight on the mechanisms pertaining to the cognitive response of children with well controlled epilepsy and could potentially serve as "functional" biomarkers for early diagnosis.

Increased resting-state EEG functional connectivity in benign childhood epilepsy with centro-temporal spikes

PURPOSE

To explore intrahemispheric, cortico-cortical EEG functional connectivity (EEGfC) in benign childhood epilepsy with rolandic spikes (BECTS).

METHODS

21-channel EEG was recorded in 17 non-medicated BECTS children and 19 healthy controls. 180s of spike- and artifact-free activity was selected for EEGfC analysis. Correlation of Low Resolution Electromagnetic Tomography- (LORETA-) defined current source density time series were computed between two cortical areas (region of interest, ROI). Analyses were based on broad-band EEGfC results. Groups were compared by statistical parametric network (SPN) method. Statistically significant differences between group EEGfC values were emphasized at p<0.05 corrected for multiple comparison by local false discovery rate (FDR).

RESULTS

(1) Bilaterally increased beta EEGfC occurred in the BECTS group as compared to the controls. Greatest beta abnormality emerged between frontal and frontal, as well as frontal and temporal ROIs. (2) Locally increased EEGfC emerged in all frequency bands in the right parietal area.

CONCLUSIONS

Areas of increased EEGfC topographically correspond to cortical areas that, based on relevant literature, are related to speech and attention deficit in BECTS children.

Resting-state oscillatory dynamics in sensorimotor cortex in benign epilepsy with centro-temporal spikes and typical brain development

Benign Epilepsy with Centro-Temporal Spikes (BECTS) is a common childhood epilepsy associated with deficits in several neurocognitive domains. Neurophysiological studies in BECTS often focus on centro-temporal spikes, but these correlate poorly with morphology and cognitive impairments. To better understand the neural profile of BECTS, we studied background brain oscillations, thought to be integrally involved in neural network communication, in sensorimotor areas. We used independent component analysis of temporally correlated sources on magnetoencephalography recordings to assess sensorimotor resting-state network activity in BECTS patients and typically developing controls. We also investigated the variability of oscillatory characteristics within focal primary motor cortex (M1), localized with a separate finger abduction task. We hypothesized that background oscillations would differ between patients and controls in the sensorimotor network but not elsewhere, especially in the beta band (13-30 Hz) because of its role in network communication and motor processing. The results support our hypothesis: in the sensorimotor network, patients had a greater variability in oscillatory amplitude compared to controls, whereas there was no difference in the visual network. Network measures did not correlate with age. The coefficient of variation of resting M1 peak frequency correlated negatively with age in the beta band only, and was greater than average for a number of patients. Our results point toward a "disorganized" functional sensorimotor network in BECTS, supporting a neurodevelopmental delay in sensorimotor cortex. Our findings further suggest that investigating the variability of oscillatory peak frequency may be a useful tool to investigate deficits of disorganization in neurodevelopmental disorders.