Study of the frequency parameters of EEG influenced by zone-dependent local ELF-MF exposure on the human head

It has been reported that human subjects exposed to electromagnetic fields exhibit changes in human EEG signals at the frequency of stimulation. The aim of the present study was to expose different parts of the brain to extremely low-frequency magnetic fields locally and investigate EEG power spectrum alters at the frequency of stimulation. EEG relative power spectrum were evaluated at 3, 5, 10, 17, and 45 Hz frequencies at T4, T3, F3, Cz, and F4 points, respectively, when these points were exposed to magnetic fields with similar frequencies and 100 μT intensity. The paired t-test results showed that power value of EEG did not alter significantly at the frequency of stimulation (P < 0.05). Further, significant changes in different EEG bands caused by locally exposing to ELF-MF in different points of brain were observed. The changes in the EEG bands were not limited necessarily to the exposure point.     

Major vault protein (MVP) gene polymorphisms and drug resistance in mesial temporal lobe epilepsy with hippocampal sclerosis

The human major vault protein (MVP) has been implicated in the development of drug resistance in cancer cells. Over expression of MVP has also been reported in brain tissue samples from antiepileptic drug (AED)-resistant human focal epilepsies. To investigate the relationship between single nucleotide polymorphisms (SNPs) involving the MVP gene and AED-resistance, we compared the distribution of three SNPs in the MVP gene, rs4788187, rs3815824 and rs3815823, among 220 patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) (prototype of AED-resistant epilepsy syndrome), 201 patients with juvenile myoclonic epilepsy (JME) (prototype of AED-responsive epilepsy syndrome) and 213 ethnically matched non-epilepsy controls. All the patients and controls were residents of the South Indian state of Kerala for more than three generations. We did not find any significant difference in allele and genotypic frequencies of the studied SNPs between AED-resistant and AED-responsive cohorts, and between AED-resistant and AED-responsive cohorts independently and pooled together when compared with the controls. We conclude that rs4788187, rs3815824, rs3815823 variants of the MVP gene are associated neither with predisposition for epilepsy nor with AED-resistance in the population that we have studied. Our results suggest the need for further research into the link between MVP and AED-resistance.     

Identification of a novel IVD mutation in a consanguineous family with isovaleric acidemia

Isovaleric acidemia (IVA) is a rare autosomal recessive disorder caused by a deficiency of isovaleryl-CoA dehydrogenase encoded by IVD gene. In this case study we report the first Saudi IVA patients from a consanguineous family with a novel transversion (p.G362V) and briefly discuss likely phenotype–genotype correlation of the disease in the Saudi population. We explored the functional consequences of the mutation by using various bioinformatics prediction algorithms and discussed the likely mechanism of the disease caused by the mutation.     

Interstitial 2q24.3 deletion including SCN2A and SCN3A genes in a patient with autistic features,psychomotor delay,microcephaly and no history of seizures

Mutations in neuronal voltage-gated sodium channel genes SCN1A, SCN2A, and SCN3A may play an important role in the etiology of neurological diseases and psychiatric disorders, besides various types of epilepsy. Here we describe a 3-year-old boy with autistic features, language delay, microcephaly and no history of seizures. Array-CGH analysis revealed an interstitial deletion of ~ 291.9 kB at band 2q24.3 disrupting the entire SCN2A gene and part of SCN3A. We discuss the effects of haploinsufficiency of SCN2A and SCN3A on the genetic basis of neurodevelopmental and neurobehavioral disorders and we propose that this haploinsufficiency may be associated not only with epilepsy, but also with autistic features.     

Quantification of Sleepiness Through Principal Component Analysis of the Electroencephalographic Spectrum

Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 32–50?h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1–16?Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: putilov@ngs.ru)     

Using a dry electrode EEG device during balance tasks in healthy young-adult males: Test–retest reliability analysis

Abstract

Background: The analysis of brain activity during balance is an important topic in different fields of science. Given that all measurements involve an error that is caused by different agents, like the instrument, the researcher, or the natural human variability, a test–retest reliability evaluation of the electroencephalographic assessment is a needed starting point. However, there is a lack of information about the reliability of electroencephalographic measurements, especially in a new wireless device with dry electrodes.

Objective: The current study aims to analyze the reliability of electroencephalographic measurements from a wireless device using dry electrodes during two different balance tests.

Method: Seventeen healthy male volunteers performed two different static balance tasks on a Biodex Balance Platform: (a) with two feet on the platform and (b) with one foot on the platform. Electroencephalographic data was recorded using Enobio (Neuroelectrics). The mean power spectrum of the alpha band of the central and frontal channels was calculated. Relative and absolute indices of reliability were also calculated.

Results: In general terms, the intraclass correlation coefficient (ICC) values of all the assessed channels can be classified as excellent (>0.90). The percentage standard error of measurement oscillated from 0.54% to 1.02% and the percentage smallest real difference ranged from 1.50% to 2.82%.

Conclusion: Electroencephalographic assessment through an Enobio device during balance tasks has an excellent reliability. However, its utility was not demonstrated because responsiveness was not assessed.     

Discovery of 2,5-diarylnicotinamides as selective orexin-2 receptor antagonists (2-SORAs)

The orexin (or hypocretin) system has been identified as a novel target for the treatment of insomnia due to the wealth of biological and genetic data discovered over the past decade. Recently, clinical proof-of-concept was achieved for the treatment of primary insomnia using dual (OX₁R/OX₂R) orexin receptor antagonists. However, elucidation of the pharmacology associated with selective orexin-2 receptor antagonists (2-SORAs) has been hampered by the lack of orally bioavailable, highly selective small molecule probes. Herein, the discovery and optimization of a novel series of 2,5-diarylnicotinamides as potent and orally bioavailable orexin-2 receptor selective antagonists is described. A compound from this series demonstrated potent sleep promotion when dosed orally to EEG telemetrized rats.     

Bag-of-words representation for biomedical time series classification

Automatic analysis of biomedical time series such as electroencephalogram (EEG) and electrocardiographic (ECG) signals has attracted great interest in the community of biomedical engineering due to its important applications in medicine. In this work, a simple yet effective bag-of-words representation that is originally developed for text document analysis is extended for biomedical time series representation. In particular, similar to the bag-of-words model used in text document domain, the proposed method treats a time series as a text document and extracts local segments from the time series as words. The biomedical time series is then represented as a histogram of codewords, each entry of which is the count of a codeword appeared in the time series. Although the temporal order of the local segments is ignored, the bag-of-words representation is able to capture high-level structural information because both local and global structural information are well utilized. The performance of the bag-of-words model is validated on three datasets extracted from real EEG and ECG signals. The experimental results demonstrate that the proposed method is not only insensitive to parameters of the bag-of-words model such as local segment length and codebook size, but also robust to noise.     

Cannabinoid receptor 1 (CNR1) gene variant moderates neural index of cognitive disruption during nicotine withdrawal

Nicotine withdrawal‐related disruption of cognitive control may contribute to the reinforcement of tobacco use. Identification of gene variants that predict this withdrawal phenotype may lead to tailored pharmacotherapy for smoking cessation. Variation on the cannabinoid receptor 1 gene (CNR1) has been related to nicotine dependence, and CNR1 antagonists may increase attention and memory functioning. We targeted CNR1 variants as moderators of a validated neural marker of nicotine withdrawal‐related cognitive disruption. CNR1 polymorphisms comprising the ‘TAG’ haplotype (rs806379, rs1535255 and rs2023239) were tested independently, as no participants in this sample possessed this haplotype. Nicotine withdrawal‐related cognitive disruption was indexed as increased resting electroencephalogram (EEG) alpha‐1 power density across 17 electrodes. Seventy‐three Caucasian Non‐Hispanic smokers (≥15 cigarettes per day) visited the laboratory on two occasions following overnight smoking/nicotine deprivation. Either two nicotine or two placebo cigarettes were smoked prior to collecting EEG data at each session. Analyses showed that rs806379 moderated the effects of nicotine deprivation increasing slow wave EEG (P = 0.004). Smokers homozygous for the major allele exhibited greater nicotine withdrawal‐related cognitive disruption. The current findings suggest potential efficacy of cannabinoid receptor antagonism as a pharmacotherapy approach for smoking cessation among individuals who exhibit greater nicotine withdrawal‐related cognitive disruption.     

Spectral EEG indicator of pressure to enter into deep sleep: its responsiveness to closing the eyes for just a few minutes exhibits a pure exponential buildup during sleep deprivation

According to the two-process model of sleep–wake regulation, a homeostatic sleep pressure, i.e. a pressure to enter into deep non-rapid eyes movement (NREM) sleep, must exhibit a purely exponential buildup during prolonged wakefulness. However, this pressure is usually measured indirectly, i.e. during the following episode of actual deep NREM sleep. The purpose of this paper was to show that, despite a prominent circadian modulation of time course of any waking EEG index, the model-postulated purely exponential buildup of the homeostatic sleep pressure can be directly confirmed. During two days of sleep deprivation experiments, the EEG of healthy adults (N = 30) was recorded every other hour throughout 5-min eyes closed relaxation. Sixteen ln-transformed single-Hz power densities (from 1 to 16 Hz) were computed for each of 5 one-min intervals. Differences between these densities obtained for the first and the following intervals were calculated and averaged. The obtained 16 values were used as the frequency weighting curve for weighting densities of each set of 16 single-Hz power densities. Summing-up of these weighted densities provided a single measure that was found to co-vary with self-rated sleepiness throughout two-day interval of sleep deprivation, thus reflecting the joint influence of the circadian and homeostatic processes. However, two-day time course of responsiveness of this measure to closing the eyes for just a few minutes exhibited a purely exponential buildup. It was concluded that this result provided a direct experimental confirmation of the model-predicted exponential buildup of the homeostatic sleep pressure across prolonged episode of wakefulness.