[EEG abnormalities indicating the genetic determination of epilepsies]. / Az epilepsziák genetikus etiológiájára utaló EEG-eltérések.

Genetic and acquired factors contribute to epileptogenesis in all epilepsy syndromes and patients. A comprehensive evaluation of both components of etiology is essential in every patient. In this review, the authors enumerate the EEG abnormalities indicating the genetic determination of epilepsy. The authors briefly describe generalized spike-and-wave paroxysms, focal spikes and sharp waves, photosensitivity, 4-7 Hz theta rhythm, 2-4 Hz occipital intermittent rhythmic delta activity, phi rhythm, and generalized monomorphic alpha EEG background activity. For each abnormality, the authors review prior knowledge and add recent research results. The neurophysiological meaning of the abnormalities, age distribution, the relationship to epilepsy, the role of the EEG patterns in epileptogenesis, clinical presentation, and prognosis in the individual patient are the main aspects of description and discussion. These EEG abnormalities may shape the typical, syndrome-specific phenotype, forecast severity of the disease and difficulty of treatment or pharmacoresistance, and modify the syndrome-specific general prognosis of the syndrome. Relationship to epilepsy and heritability data of the EEG abnormalities can help to estimate the risk of epilepsy in the offspring. Epilepsy syndromes are taxonomic diagnostic categories that might be enriched with neurobiological meaning and heritability relations.

EEG-based connectivity in patients with partial seizures with and without generalization.

BACKGROUND AND PURPOSE: To investigate the neurophysiological basis of secondary generalization of partial epileptic seizures. METHODS: Inter-ictal, resting-state EEG functional connectivity (EEGfC) was evaluated and compared: patients with exclusively simple partial seizures (sp group) were compared to patients with simple partial and secondary generalized seizures (spsg group); patients with exclusively complex partial seizures (cp group) were compared to patients with cp and secondary generalized seizures (cpsg group); the collapsed sp+cp group (spcp) was compared to those who had exclusively secondary generalized seizures (sg group). EEGfC was computed from 21-channel waking EEG. 3 minutes of waking EEG background activity was analyzed by the LORETA Source Correlation (LSC) software. Current source density time series were computed for 23 pre-defined cortical regions (ROI) in each hemisphere, for the 1-25 Hz very narrow bands (1 Hz bandwidth). Thereafter Pearson correlation coefficients were calculated between all pairs of ROI time series in the same hemisphere. Z-scored correlation coefficients were compared at the group level (t-tests and correction for multiple comparisons by local false discovery rate, FDR). RESULTS: Statistically significant (corrected p<0.05) EEGfC differences emerged at specific frequencies (spsg > sg; cpsg > cp), and at many frequencies (sg > spcp). The findings indicated increased coupling between motor cortices and several non-motor areas in patients with partial and sg seizures as compared to patients with partial seizures and no sg seizures. Further findings suggested increased coupling between medial parietal-occipital areas (structural core of the cortex) and lateral hemispheric areas. CONCLUSION: Increased inter-ictal EEGfC is associated with habitual occurrence of secondary generalized seizures.

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.

Decrease of global current source density predicts successful treatment in absence and juvenile myoclonic epilepsies.

OBJECTIVE: To investigate relationship between treatment efficiency and EEG background activity changes in absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) patients. PATIENTS AND METHODS: EEGs of 31 patients were analysed before treatment and after six months of treatment. Three minutes of artifact-free waking EEG background activity (without epileptiform potentials) were analysed for each patient in both conditions. All the EEG samples were processed to LORETA (Low Resolution Electromagnetic Tomography). Average of all the voxel-wise current source density (CSD) values within the 0.5-8.0Hz frequency range was computed for each EEG. Fischer's exact test was used to investigate association between the global CSD changes and the therapeutic outcome. RESULTS: Tight connection was demonstrated between seizure freedom and decreased CSD, and between persisting seizures and increased CSD (p<0.001). SIGNIFICANCE: An EEG-based biomarker that predicts successful drug treatment was described.

[EEG-based cerebral networks in 14 neurological disorders]. / EEG-alapú agyi hálózatok 14 neurológiai betegségben.

Background - Brain networks have not been systematically investigated yet in most neurological disorders. Purpose - To investigate EEG functional connectivity (EEGfC) networks in 14 neurological disorders. Patients - Potentially eligible patients were collected from clinical and EEG databases. All the available clinical data and EEG records were critically revised. All the patients who suffered of a single neurological disorder (out of the 14) and had a good quality EEG recording entered the study. Confoundig factors as comorbidity and CNS-active drug effects were eliminated as far as possible. EEG analysis - Three minutes of resting-state, waking EEG activity were selected for analysis. Current source density (CSD) values were computed for 2394 cortical voxels by Low Resolution Electromagnetic Tomography (LORETA). Thereafter, Pearson correlation coefficients were computed between all pairs of 23 cortical regions of interest (ROI) in each hemisphere (LORETA Source Correlation, LSC software). Computation was carried out for conventional EEG broad bands and very narrow bands (1 Hz bandwidth) between 1 and 25 Hz as well. Correlation coefficients of each group were statistically compared to our normative EEG (LSC) database by two-talied t-tests. Bonferroni-corrected p<0.05 values were accepted as statistically significant, and were graphically displayed as topographical networks. Results and conclusion - Group-specific networks were demonstrated. However, non-specific networks, charasteristic for most groups, were detected as well. Common finding were: decreased connectivity in the alpha band and increased connectivity in the delta, theta bands and upper-beta band. Decreased alpha-band connectivity presumably reflected primary lesional effects and on the other hand, non-specific vulnerability of "rich club connections". Increased connectivity in the slow bands presumably indicated adaptive-compensatory activity of brain homeostasis.

[FOCAL MOTOR SEIZURES AND STATUS EPILEPTICUS PROVOKED BY MIRTAZAPINE]. / MIRTAZAPIN ÁLTAL PROVOKÁLT FOKÁLIS MOTOROS ROHAMOK ÉS STATUS EPILEPTICUS.

The seizure-provoking effect of the tetracyclic antidepressant mirtazapine is not a well-known adverse effect of the drug. The authors report on a 39-year-old non-epileptic patient who had been treated for depression with the usual daily dose of mirtazapine. Having increased the daily dose of the drug from 30 to 45 milligrams he experienced a few clonic seizures of the right lower limb. This symptom and insomnia erroneously intended the patient to further increase the daily dose of mirtazapine, which immediately resulted in the evolution of focal clonic status epilepticus in the same limb. After admission, this condition was recorded by video-EEG and abolished by intravenous administration of levetiracetam after the intravenous clonazepam had been ineffective. Discontinuation of mirtazapine and administration of carbamazepine resulted in completely seizure-free state that persisted even after carbamazepine treatment was terminated. The clinical and laboratory data indicate the seizure-provoking effect of mirtazapine in the reported case.