Global, regional, and local measures of complexity of multichannel electroencephalography in acute, neuroleptic-naive, first-break schizophrenics

Background: Schizophrenic symptoms commonly are felt to indicate a loosened coordination, i.e. a decreased connectivity of brain processes. Methods: To address this hypothesis directly, global and regional multichannel electroencephalographic (EEG) complexities (omega complexity and dimensional complexity) and single channel EEG dimensional complexities were calculated from 19-channel EEG data from 9 neuroleptic-naive, first-break, acute schizophrenics and 9 age- and sex-matched controls. Twenty artifact-free 2 second EEG epochs during resting with closed eyes were analyzed (2–30 Hz bandpass, average reference for global and regional complexities, local EEG gradient time series for single channels). Results: Anterior regional Omega-Complexity was significantly increased in schizophrenics compared with controls (p < 0.001) and anterior regional Dimensional Complexity showed a trend for increase. Single channel Dimensional Complexity of local gradient waveshapes was prominently increased in the schizophrenics at the right precentral location (p = 0.003). Conclusions: The results indicate a loosened cooperativity or coordination (vice versa: an increased independence) of the active brain processes in the anterior brain regions of the schizophrenics.

On the comparison of a novel serious game and electroencephalography biomarkers for early dementia screening

Patients with amnestic mild cognitive impairment are at high risk for developing Alzheimer's disease. Besides episodic memory dysfunction they show deficits in accessing contextual knowledge that further specifies a general spatial navigation task or an executive function (EF) virtual action planning. Virtual reality (VR) environments have already been successfully used in cognitive rehabilitation and show increased potential for use in neuropsychological evaluation allowing for greater ecological validity while being more engaging and user friendly. In our study we employed the in-house platform of virtual action planning museum (VAP-M) and a sample of 25 MCI and 25 controls, in order to investigate deficits in spatial navigation, prospective memory, and executive function. In addition, we used the morphology of late components in event-related potential (ERP) responses, as a marker for cognitive dysfunction. The related measurements were fed to a common classification scheme facilitating the direct comparison of both approaches. Our results indicate that both the VAP-M and ERP averages were able to differentiate between healthy elders and patients with amnestic mild cognitive impairment and agree with the findings of the virtual action planning supermarket (VAP-S). The sensitivity (specificity) was 100% (98%) for the VAP-M data and 87% (90%) for the ERP responses. Considering that ERPs have proven to advance the early detection and diagnosis of "presymptomatic AD," the suggested VAP-M platform appears as an appealing alternative.

TETRA mobile radios interfere with electroencephalography recording equipment

We observed an anomaly in the human electroencephalogram (EEG) associated with exposure to terrestrial trunked radio (TETRA) Radiofrequency Fields (RF). Here, we characterize the time and frequency components of the anomaly and demonstrate that it is an artefact caused by TETRA RF interfering with the EEG recording equipment and not by any direct or indirect effect on the brain.

Using electroencephalography signals to control acoustical processing

Current hearing-assistive technology performs poorly in noisy multi-talker conditions. The goal of this thesis was to establish the feasibility of using EEG to guide acoustic processing in such conditions. To attain this goal, this research developed a model via the constructive research method, relying on literature review. Several approaches have revealed improvements in the performance of hearing-assistive devices under multi-talker conditions, namely beamforming spatial filtering, model-based sparse coding shrinkage, and onset enhancement of the speech signal. Prior research has shown that electroencephalography (EEG) signals contain information that concerns whether the person is actively listening, what the listener is listening to, and where the attended sound source is. This thesis constructed a model for using EEG information to control beamforming, model-based sparse coding shrinkage, and onset enhancement of the speech signal. The purpose of this model is to propose a framework for using EEG signals to control sound processing to select a single talker in a noisy environment containing multiple talkers speaking simultaneously. On a theoretical level, the model showed that EEG can control acoustical processing. An analysis of the model identified a requirement for real-time processing and that the model inherits the computationally intensive properties of acoustical processing, although the model itself is low complexity placing a relatively small load on computational resources. A research priority is to develop a prototype that controls hearing-assistive devices with EEG. This thesis concludes highlighting challenges for future research.

Longitudinal Analysis Of Hippocampal T2 Relaxometry In Fmtle.

To investigate the degree of T2 relaxometry changes over time in groups of patients with familial mesial temporal lobe epilepsy (FMTLE) and asymptomatic relatives. We conducted both cross-sectional and longitudinal analyses of T2 relaxometry with Aftervoxel, an in-house software for medical image visualization. The cross-sectional study included 35 subjects (26 with FMTLE and 9 asymptomatic relatives) and 40 controls; the longitudinal study was composed of 30 subjects (21 with FMTLE and 9 asymptomatic relatives; the mean time interval of MRIs was 4.4 ± 1.5 years) and 16 controls. To increase the size of our groups of patients and relatives, we combined data acquired in 2 scanners (2T and 3T) and obtained z-scores using their respective controls. General linear model on SPSS21® was used for statistical analysis. In the cross-sectional analysis, elevated T2 relaxometry was identified for subjects with seizures and intermediate values for asymptomatic relatives compared to controls. Subjects with MRI signs of hippocampal sclerosis presented elevated T2 relaxometry in the ipsilateral hippocampus, while patients and asymptomatic relatives with normal MRI presented elevated T2 values in the right hippocampus. The longitudinal analysis revealed a significant increase in T2 relaxometry for the ipsilateral hippocampus exclusively in patients with seizures. The longitudinal increase of T2 signal in patients with seizures suggests the existence of an interaction between ongoing seizures and the underlying pathology, causing progressive damage to the hippocampus. The identification of elevated T2 relaxometry in asymptomatic relatives and in patients with normal MRI suggests that genetic factors may be involved in the development of some mild hippocampal abnormalities in FMTLE.

Rolandic Epilepsy And Dyslexia.

Although benign epilepsy with centrotemporal spikes (BECTS) is an idiopathic, age-related epilepsy syndrome with favorable outcome, recent studies have shown impairment in specific neuropsychological tests. The objective of this study was to analyze the comorbidity between dyslexia and BECTS. Thirty-one patients with clinical and electroencephalographic diagnosis of BECTS (group A) and 31 paired children (group B) underwent a language and neuropsychological assessment performed with several standardized protocols. Our findings were categorized as: a) dyslexia; b) other difficulties; c) without difficulties. Our results were compared and statistically analyzed. Our data showed that dyslexia occurred in 19.4% and other difficulties in 74.2% of our patients. This was highly significant when compared with the control group (p<0.001). Phonological awareness, writing, reading, arithmetic, and memory tests showed a statistically significant difference when comparing both groups. Our findings show significant evidence of the occurrence of dyslexia in patients with BECTS.

Hemispheric Lateralization in Benign Focal Epilepsy in Childhood With Centrotemporal Spikes (BECTS)

Benign focal epilepsy in childhood with centrotemporal spikes (BECTS) is one of the most common forms of epilepsy. In adults there is a higher percentage of lateralized epileptic discharges in the left cerebral hemisphere; however, in children this pattern does not seem to have the same distribution. The objective of this study was to evaluate the lateralization of interictal spikes in children with BECTS in relation to the sex of the child and the age of onset of epilepsy. We studied the electroencephalograms (EEGs) of 114 children with a clinical diagnosis of BECTS according to ILAE. The results obtained from two EEGs, performed at intervals of 6 and 12 months, were correlated with the age of onset of the epileptic seizures and the sex of the child. There was no association between the onset of epileptic seizures and the age of the child (p=0.461). When we analyzed the relationship between laterality and sex we did not observe any difference in the first EEG (p = 0.767) results; however, in the results of the second EEG there was a difference (p = 0.002). In males, left and bilateral interictal spikes were predominant, and in females the right hemisphere showed predominant spikes and there were continuous spike-and-wave discharges during slow sleep (CSWSS). The analysis between laterality and a child`s age did not show predominant interictal spikes in the hemispheres, except in males where there were predominant multifocal and generalized spikes, but not lateralization (p=0.011). The conclusion was that in BECTS the lateralization of interictal spikes was not consistent as described in adult patients, but there was a slight left hemispheric predominance in boys and right hemispheric predominance in girls.

Prevalence of Epilepsy in Children From a Brazilian Area of High Deprivation

This study assessed the prevalence rate of epilepsy and its causes in children and adolescents in one area of high deprivation in Sao Paulo, Sao Paulo, in Southeast Brazil. Between July 2005 and June 2006, 4947 families from a population of 22,013 inhabitants (including 10,405 children and adolescents between the ages of 0 and 16 years) living in the shantytown of Paraisopolis, were interviewed. In the first phase, a validated questionnaire was administered, to identify the occurrence of seizures. In the second phase, clinical history, neurologic examination, electroencephalography, and structural neuroimaging were performed. The diagnosis of epilepsy, including etiology, seizure types, and epileptic syndrome classification, was according to criteria of the International League Against Epilepsy. The screening phase identified 353 presumptive cases. In the second phase, 101 of these cases (33.8%) received the diagnosis of epilepsy. Crude prevalence of epilepsy was 9.7/1000 and prevalence of active epilepsy was 8.7/1000. Partial seizures were the most frequent seizure type (62/101). Symptomatic focal epilepsy was the most common form, and hypoxic-ischemic encephalopathy the most common etiology, reflecting the socioeconomic conditions of this specific population. Adequate public policies regarding perinatal assistance could help reduce the prevalence of epilepsy. (C) 2010 by Elsevier Inc. All rights reserved.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Emotional trauma and abuse in patients with psychogenic nonepileptic seizures

A history of childhood trauma and the presence of dissociative phenomena are considered to be the most important risk factors for psychogenic nonepileptic seizure disorder (PNESD). This case-control study investigated 20 patients with PNESD and 20 with temporal lobe epilepsy (TLE) diagnosed by video/EEG monitoring who were matched for gender and age. Patients with both conditions were not included in the study. Groups were evaluated for age at onset and at diagnosis, worst lifetime weekly seizure frequency, trauma history, and presence of dissociative phenomena. Age at onset (P = 0.007) and age at diagnosis (P < 0.001) were significantly higher in the PNESD group than the control group, as were the scores on the Dissociative Experiences Scale (P < 0.001) and Childhood Trauma Questionnaire (P = 0.014). Only the differences in scores on the Childhood Trauma Questionnaire subscales Emotional Neglect (P = 0.013) and Emotional Abuse (P = 0.014) reached statistical significance. Dissociative phenomena and a reported history of childhood trauma are more common in patients with PNESD than in those with TLE. However, only emotional neglect and abuse were associated with PNESD in this study. (C) 2010 Elsevier Inc. All rights reserved.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

Gamma band oscillations under influence of bromazepam during a sensorimotor integration task: An EEG coherence study

The goal of the present study was to explore the dynamics of the gamma band using the coherence of the quantitative electroencephalography (qEEG) in a sensorimotor integration task and the influence of the neuromodulator bromazepam on the band behavior. Our hypothesis is that the needs of the typewriting task will demand the coupling of different brain areas, and that the gamma band will promote the binding of information. It is also expected that the neuromodulator will modify this coupling. The sample was composed of 39 healthy subjects. We used a randomized double-blind design and divided subjects into three groups: placebo (n = 13), bromazepam 3 mg (n = 13) and bromazepam 6 mg (n = 13). The two-way ANOVA analysis demonstrated a main effect for the factors condition (i.e., C4-CZ electrode pair) and moment (i.e., C3-CZ, C3-C4 and C4-CZ pairs of electrodes). We propose that the gamma band plays an important role in the binding among several brain areas in complex motor tasks and that each hemisphere is influenced in a different manner by the neuromodulator. (C) 2009 Elsevier Ireland Ltd. All rights reserved.