Personality profile of patients with juvenile myoclonic epilepsy

Epilepsy in Children: From Diagnosis to Treatment with Focus on Emergency

Seizures are defined as a transient occurrence of signs and symptoms due to the abnormal, excessive, or synchronous neuronal activity in the brain characterized by abrupt and involuntary skeletal muscle activity. An early diagnosis, treatment, and specific medical support must be performed to prevent Status Epilepticus (SE). Seizure onset, especially in the child population, is related to specific risk factors like positive family history, fever, infections, neurological comorbidity, premature birth, mother’s alcohol abuse, and smoking in pregnancy. Early death risk in children without neurological comorbidity is similar to the general population. Diagnosis is generally based on the identification of continuous or recurrent seizures but Electroencephalogram (EEG) evaluation could be useful if SE condition is suspected. The main goal of therapy is to counteract the pathological mechanism which occurs in SE before neural cells are irreversibly damaged. According to the latest International Guidelines and Recommendations of seizure related diseases, a schematic and multi-stage pharmacological and diagnostic approach is proposed especially in the management of SE and its related causes in children. First measures should focus on early and appropriate drugs administration at adequate dosage, airway management, monitoring vital signs, Pediatric Intensive Care Unit (PICU) admission, and management of parent anxiety.

What graph theory actually tells us about resting state interictal MEG epileptic activity

Graph theory provides a useful framework to study functional brain networks from neuroimaging data. In epilepsy research, recent findings suggest that it offers unique insight into the fingerprints of this pathology on brain dynamics. Most studies hitherto have focused on seizure activity during focal epilepsy, but less is known about functional epileptic brain networks during interictal activity in frontal focal and generalized epilepsy. Besides, it is not clear yet which measures are most suitable to characterize these networks. To address these issues, we recorded magnetoencephalographic (MEG) data using two orthogonal planar gradiometers from 45 subjects from three groups (15 healthy controls (7 males, 24 ± 6 years), 15 frontal focal (8 male, 32 ± 16 years) and 15 generalized epileptic (6 male, 27 ± 7 years) patients) during interictal resting state with closed eyes. Then, we estimated the total and relative spectral power of the largest principal component of the gradiometers, and the degree of phase synchronization between each sensor site in the frequency range [0.5–40 Hz]. We further calculated a comprehensive battery of 15 graph-theoretic measures and used the affinity propagation clustering algorithm to elucidate the minimum set of them that fully describe these functional brain networks. The results show that differences in spectral power between the control and the other two groups have a distinctive pattern: generalized epilepsy presents higher total power for all frequencies except the alpha band over a widespread set of sensors; frontal focal epilepsy shows higher relative power in the beta band bilaterally in the fronto-central sensors. Moreover, all network indices can be clustered into three groups, whose exemplars are the global network efficiency, the eccentricity and the synchronizability. Again, the patterns of differences were clear: the brain network of the generalized epilepsy patients presented greater efficiency and lower eccentricity than the control subjects for the high frequency bands, without a clear topography. Besides, the frontal focal epileptic patients showed only reduced eccentricity for the theta band over fronto-temporal and central sensors. These outcomes indicate that functional epileptic brain networks are different to those of healthy subjects during interictal stage at rest, with a unique pattern of dissimilarities for each type of epilepsy. Further, when properly selected, three network indices suffice to provide a comprehensive description of these differences. Yet, since such uniqueness in the pattern of differences is also evident in the power spectrum, we conclude that the added value of the graph theory approach in this context should not be overestimated.

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We study MEG activity during interictal resting state with closed eyes.

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Generalized epilepsy presents higher total power over a widespread set of sensors.

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Frontal epilepsy shows higher relative power in beta band on fronto-central sensors.

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We also found altered functional brain networks in epilepsy using graph theory.

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The pattern of differences from control subjects is unique for each type of epilepsy.

Juvenile myoclonic epilepsy: psychiatric comorbidity and impact on outcome

Juvenile myoclonic epilepsy (JME) is a well-defined age-related idiopathic epilepsy syndrome. Past studies have emphasized the difficulties in the treatment of patients with JME, which have been attributed to some specific psychiatric, psychological, and psychosocial characteristics. These aspects have aroused a significant amount of interest in the last two decades. In this article, the available studies that investigated the prevalence of psychiatric disorders (PDs) in JME and its impact on seizure outcome were reviewed in order to provide an update to clinicians about these two important aspects associated with this common epilepsy syndrome. The review disclosed a high prevalence of PDs in patients with JME, particularly mood, anxiety, and personality disorders. In addition, most recent studies have also observed that overall prevalence of PDs in JME has not shown statistically significant differences when compared with TLE, an epilepsy syndrome where the psychiatric aspects are most frequently studied. Taken together, data regarding the prevalence of PDs and their possible consequences on seizure outcome on JME indicate that special attention should be directed to psychological disturbances and psychiatric symptoms in this epilepsy syndrome. The early recognition and treatment of psychiatric symptoms, as well as psychological disturbances and psychosocial difficulties, should be considered fundamental to JME prognosis.