Analysis of the EEG Dynamics of Epileptic Activity in Gelastic Seizures Using Decomposition in Independent Components

Objective: Gelastic seizures are a frequent and well established manifestation of the epilepsy associated with hypothalamic hamartomas. The scalp EEG recordings very seldom demonstrate clear spike activity and the information about the ictal epilepsy dynamics is limited. In this work, we try to isolate epileptic rhythms in gelastic seizures and study their generators. Methods: We extracted rhythmic activity from EEG scalp recordings of gelastic seizures using decomposition in independent components (ICA) in three patients, two with hypothalamic hamartomas and one with no hypothalamic lesion. Time analysis of these rhythms and inverse source analysis was done to recover their foci of origin and temporal dynamics. Results: In the two patients with hypothalamic hamartomas consistent ictal delta (2–3 Hz) rhythms were present, with subcortical generators in both and a superficial one in a single patient. The latter pattern was observed in the patient with no hypothalamic hamartoma visible in MRI. The deep generators activated earlier than the superficial ones, suggesting a consistent sub-cortical origin of the rhythmical activity. Conclusions: Our data is compatible with early and brief epileptic generators in deep sub-cortical regions and more superficial ones activating later. Significance: Gelastic seizures express rhythms on scalp EEG compatible with epileptic activity originating in sub-cortical generators and secondarily involving cortical ones.

N170 Asymmetry as an Index of Inferior Occipital Dysfunction in Patients With Symptomatic Occipital Lobe Epilepsy

Objective: Localizing epileptic foci in posterior brain epilepsy remains a difficult exercise in surgery for epilepsy evaluation. Neither clinical manifestations, neurological, EEG nor neuropsychological evaluations provide strong information about the area of onset, and fast spread of paroxysms often produces mixed features of occipital, temporal and parietal symptoms. We investigated the usefulness of the N170 event-related potential to map epileptic activity in these patients. Methods: A group of seven patients with symptomatic posterior cortex epilepsy were submitted to a high-resolution EEG (78 electrodes), with recordings of interictal spikes and face-evoked N170. Generators of spikes and N170 were localized by source analysis. Range of normal N170 asymmetry was determined in 30 healthy volunteers. Results: In 3 out of 7 patients the N170 inter-hemispheric asymmetry was outside control values. Those were the patients whose spike sources were nearest (within 3 cm) to the fusiform gyrus, while foci further away did not affect the N170 ratio. Conclusions: N170 event-related potential provides useful information about focal cortical dysfunction produced by epileptic foci located in the close neighborhood of the fusiform gyrus, but are unaffected by foci further away. Significance: The N170 evoked by faces can improve the epileptic foci localization in posterior brain epilepsy.

Analysis of the Generators of Epileptic Activity in Early-Onset Childhood Benign Occipital Lobe Epilepsy

Objective: The Panayiotopoulos type of idiopathic occipital epilepsy has peculiar and easily recognizable ictal symptoms, which are associated with complex and variable spike activity over the posterior scalp areas. These characteristics of spikes have prevented localization of the particular brain regions originating clinical manifestations. We studied spike activity in this epilepsy to determine their brain generators. Methods: The EEG of 5 patients (ages 7–9) was recorded, spikes were submitted to blind decomposition in independent components (ICs) and those to source analysis (sLORETA), revealing the spike generators. Coherence analysis evaluated the dynamics of the components. Results: Several ICs were recovered for posterior spikes in contrast to central spikes which originated a single one. Coherence analysis supports a model with epileptic activity originating near lateral occipital area and spreading to cortical temporal or parietal areas. Conclusions: Posterior spikes demonstrate rapid spread of epileptic activity to nearby lobes, starting in the lateral occipital area. In contrast, central spikes remain localized in the rolandic fissure. Significance: Rapid spread of posterior epileptic activity in the Panayitopoulos type of occipital lobe epilepsy is responsible for the variable and poorly localized spike EEG. The lateral occipital cortex is the primary generator of the epileptic activity.

Optimal Cut-Off Value for Homeostasis Model Assessment (HOMA) Index of Insulin-Resistance in a Population of Patients Admitted Electively in a Portuguese Cardiology Ward

INTRODUCTION: Insulin resistance is the pathophysiological key to explain metabolic syndrome. Although clearly useful, the Homeostasis Model Assessment index (an insulin resistance measurement) hasn't been systematically applied in clinical practice. One of the main reasons is the discrepancy in cut-off values reported in different populations. We sought to evaluate in a Portuguese population the ideal cut-off for Homeostasis Model Assessment index and assess its relationship with metabolic syndrome. MATERIAL AND METHODS: We selected a cohort of individuals admitted electively in a Cardiology ward with a BMI < 25 Kg/m2 and no abnormalities in glucose metabolism (fasting plasma glucose < 100 mg/dL and no diabetes). The 90th percentile of the Homeostasis Model Assessment index distribution was used to obtain the ideal cut-off for insulin resistance. We also selected a validation cohort of 300 individuals (no exclusion criteria applied). RESULTS: From 7 000 individuals, and after the exclusion criteria, there were left 1 784 individuals. The 90th percentile for Homeostasis Model Assessment index was 2.33. In the validation cohort, applying that cut-off, we have 49.3% of individuals with insulin resistance. However, only 69.9% of the metabolic syndrome patients had insulin resistance according to that cut-off. By ROC curve analysis, the ideal cut-off for metabolic syndrome is 2.41. Homeostasis Model Assessment index correlated with BMI (r = 0.371, p < 0.001) and is an independent predictor of the presence of metabolic syndrome (OR 19.4, 95% CI 6.6 - 57.2, p < 0.001). DISCUSSION: Our study showed that in a Portuguese population of patients admitted electively in a Cardiology ward, 2.33 is the Homeostasis Model Assessment index cut-off for insulin resistance and 2.41 for metabolic syndrome. CONCLUSION: Homeostasis Model Assessment index is directly correlated with BMI and is an independent predictor of metabolic syndrome.

Ocular Pulse Amplitude and Doppler Waveform Analysis in Glaucoma Patients

PURPOSE: To determine the correlation between ocular blood flow velocities and ocular pulse amplitude (OPA) in glaucoma patients using colour Doppler imaging (CDI) waveform analysis. METHOD: A prospective, observer-masked, case-control study was performed. OPA and blood flow variables from central retinal artery and vein (CRA, CRV), nasal and temporal short posterior ciliary arteries (NPCA, TPCA) and ophthalmic artery (OA) were obtained through dynamic contour tonometry and CDI, respectively. Univariate and multiple regression analyses were performed to explore the correlations between OPA and retrobulbar CDI waveform and systemic cardiovascular parameters (blood pressure, blood pressure amplitude, mean ocular perfusion pressure and peripheral pulse). RESULTS: One hundred and ninety-two patients were included [healthy controls: 55; primary open-angle glaucoma (POAG): 74; normal-tension glaucoma (NTG): 63]. OPA was statistically different between groups (Healthy: 3.17 ± 1.2 mmHg; NTG: 2.58 ± 1.2 mmHg; POAG: 2.60 ± 1.1 mmHg; p < 0.01), but not between the glaucoma groups (p = 0.60). Multiple regression models to explain OPA variance were made for each cohort (healthy: p < 0.001, r = 0.605; NTG: p = 0.003, r = 0.372; POAG: p < 0.001, r = 0.412). OPA was independently associated with retrobulbar CDI parameters in the healthy subjects and POAG patients (healthy CRV resistance index: β = 3.37, CI: 0.16-6.59; healthy NPCA mean systolic/diastolic velocity ratio: β = 1.34, CI: 0.52-2.15; POAG TPCA mean systolic velocity: β = 0.14, CI 0.05-0.23). OPA in the NTG group was associated with diastolic blood pressure and pulse rate (β = -0.04, CI: -0.06 to -0.01; β = -0.04, CI: -0.06 to -0.001, respectively). CONCLUSIONS: Vascular-related models provide a better explanation to OPA variance in healthy individuals than in glaucoma patients. The variables that influence OPA seem to be different in healthy, POAG and NTG patients.