An information-theoretic approach for studying synchronization phenomena in experimental bivariate time series is presented. "Coarse-grained" information rates are introduced and their ability to indicate generalized synchronization as well as to establish a "direction of information flow" between coupled systems, i.e., to discern the driving from the driven (response) system, is demonstrated using numerically generated time series from unidirectionally coupled chaotic systems. The method introduced is then applied in a case study of electroencephalogram recordings of an epileptic patient. Synchronization events leading to seizures have been found on two levels of organization of brain tissues and "directions of information flow" among brain areas have been identified. This allows localization of the primary epileptogenic areas, also confirmed by magnetic resonance imaging and pasitron emission tomography scans.

Dravet syndrome is a severe epilepsy syndrome characterized by infantile onset of therapy-resistant, fever-sensitive seizures followed by cognitive decline. Mutations in SCN1A explain about 75% of cases with Dravet syndrome; 90% of these mutations arise de novo. We studied a cohort of nine Dravet-syndrome-affected individuals without an SCN1A mutation (these included some atypical cases with onset at up to 2 years of age) by using whole-exome sequencing in proband-parent trios. In two individuals, we identified a de novo loss-of-function mutation in CHD2 (encoding chromodomain helicase DNA binding protein 2). A third CHD2 mutation was identified in an epileptic proband of a second (stage 2) cohort. All three individuals with a CHD2 mutation had intellectual disability and fever-sensitive generalized seizures, as well as prominent myoclonic seizures starting in the second year of life or later. To explore the functional relevance of CHD2 haploinsufficiency in an in vivo model system, we knocked down chd2 in zebrafish by using targeted morpholino antisense oligomers. chd2-knockdown larvae exhibited altered locomotor activity, and the epileptic nature of this seizure-like behavior was confirmed by field-potential recordings that revealed epileptiform discharges similar to seizures in affected persons. Both altered locomotor activity and epileptiform discharges were absent in appropriate control larvae. Our study provides evidence that de novo loss-of-function mutations in CHD2 are a cause of epileptic encephalopathy with generalized seizures.

The developmental and epileptic encephalopathies (DEEs) are heterogeneous disorders with a strong genetic contribution, but the underlying genetic etiology remains unknown in a significant proportion of individuals. To explore whether statistical support for genetic etiologies can be generated on the basis of phenotypic features, we analyzed whole-exome sequencing data and phenotypic similarities by using Human Phenotype Ontology (HPO) in 314 individuals with DEEs. We identified a de novo c.508C>T (p.Arg170Trp) variant in AP2M1 in two individuals with a phenotypic similarity that was higher than expected by chance (p ¼ 0.003) and a phenotype related to epilepsy with myoclonic-atonic seizures. We subsequently found the same de novo variant in two individuals with neurodevelopmental disorders and generalized epilepsy in a cohort of 2,310 individuals who underwent diagnostic whole-exome sequencing. AP2M1 encodes the m-subunit of the adaptor protein complex 2 (AP-2), which is involved in clathrin-mediated endocytosis (CME) and synaptic vesicle recycling. Modeling of protein dynamics indicated that the p.Arg170Trp variant impairs the conformational activation and thermodynamic entropy of the AP-2 complex. Functional complementation of both the m-subunit carrying the p.Arg170Trp variant in human cells and astrocytes derived from AP-2m conditional knockout mice revealed a significant impairment of CME of transferrin. In contrast, stability, expression levels, membrane recruitment, and localization were not impaired, suggesting a functional alteration of the AP-2 complex as the underlying disease mechanism. We establish a recurrent pathogenic variant in AP2M1 as a cause of DEEs with distinct phenotypic features, and we implicate dysfunction of the early steps of endocytosis as a disease mechanism in epilepsy.

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector's specificity and having important implications for future development of spike detectors in general.

The aim of the study was to investigate the potential association of epilepsy and EEG abnormalities with autistic regression and mental retardation. We examined a group of 77 autistic children (61 boys, 16 girls) with an average age of 9.1 +/- 5.3 years. Clinical interview, neurological examination focused on the evaluation of epilepsy, IQ testing, and 21-channel EEG (including night sleep EEG recording) were performed. Normal EEGs were observed in 44.4% of the patients, non-epileptiform abnormal EEGs in 17.5%, and abnormal EEGs with epileptiform discharges in 38.1% of the patients. Epilepsy was found in 22.1% of the subjects. A history of regression was reported in 25.8% of the patients, 54.8% of the sample had abnormal development during the first year of life, and 79.7% of the patients were mentally retarded. Autistic regression was significantly more frequent in patients with epilepsy than in non-epileptic patients (p = 0.003). Abnormal development during the first year of life was significantly associated with epileptiform EEG abnormalities (p = 0.014). Epilepsy correlated significantly with mental retardation (p = 0.001). Although the biological basis and possible causal relationships of these associations remain to be explained, they may point to different subgroups of patients with autistic spectrum disorders.