Reduced hippocampal anisotropy related to anteriorization of alpha EEG in schizophrenia

Dysfunctions of the hippocampus have been suggested to be related to schizophrenia, and reduced connectivity with other brain regions may be a key for the pathophysiology. The aim of this study was to investigate the effect of white matter anomalies in the hippocampus, as a sign of altered connectivity, on the brain electrical activity. We investigated seven first episode schizophrenic patients and seven age, gender and education-matched controls with diffusion tensor imaging and resting EEG. Fractional anisotropy was computed based on diffusion tensor imaging data for the right and left hippocampus for both groups. No group differences were found in hippocampal fractional anisotropy, EEG spectral power and topography. However a significant correlation was found between more anterior alpha activity and lower fractional anisotropy of both hippocampi in schizophrenics, but not in controls. More anterior alpha activity has been described in schizophrenia. We conclude that this feature might depict a group of schizophrenic patients with reduced hippocampal connectivity.

An EEG approach to the neurodevelopmental hypothesis of schizophrenia studying schizophrenics, normal controls and adolescents

Based on an integrative brain model which focuses on memory-driven and EEG state-dependent information processing for the organisation of behaviour, we used the developmental changes of the awake EEG to further investigate the hypothesis that neurodevelopmental abnormalities (deviations in organisation and reorganisation of cortico-cortical connectivity during development) are involved in the pathogenesis of schizophrenia. First-episode, neuroleptic-naive schizophrenics and their matched controls and three age groups of normal adolescents were studied (total: 70 subjects). 19-channel EEG delta-theta, alpha and beta spectral band centroid frequencies during resting (baseline) and after verbal stimuli were used as measure of the level of attained complexity and momentary excitability of the neuronal network (working memory). Schizophrenics compared with all control groups showed lower delta-theta activity centroids and higher alpha and beta activity centroids. Reactivity centroids (centroid after stimulus minus centroid during resting) were used as measure of update of working memory. Schizophrenics showed partial similarities in delta-theta and beta reactivity centroids with the 11-year olds and in alpha reactivity centroids with the 13-year olds. Within the framework of our model, the results suggest multifactorially elicited imbalances in the level of excitability of neuronal networks in schizophrenia, resulting in network activation at dissociated complexity levels, partially regressed and partially prematurely developed. It is hypothesised that activation of age- and/or state-inadequate representations for coping with realities becomes manifest as productive schizophrenic symptoms. Thus, the results support some aspects of the neurodevelopmental hypothesis.

EEG signs of vigilance fluctuations preceding perceptual flips in multistable illusionary motion

This EEG study was performed to clarify the time course of brain electrical events and possible vigilance changes associated with perceptual flips during multistable perception. 13 healthy subjects (28.5 3.8 years) were recorded with a 21-channel digital EEG during a stroboscopic alternative motion paradigm implying illusionary motion with ambiguous direction. Perceptual flips were preceded by a significant decrease of EEG frequencies, and followed by a significant frequency increase with a trend to overshoot. EEG slowing is a reliable sign of vigilance decrease and can be related to thalamic deactivation. This is consistent with a recent fMRI study, which showed thalamic deactivation associated with perceptual flips. The study added important chronological information about this phenomenon and allows the conclusion that reduced vigilance facilitates perceptual discontinuities during multistable perception.

EEG reactivity and EEG activity in never-treated acute schizophrenics, measured with spectral parameters and dimensional complexity

Our approaches to the use of EEG studies for the understanding of the pathogenesis of schizophrenic symptoms are presented. The basic assumptions of a heuristic and multifactorial model of the psychobiological brain mechanisms underlying the organization of normal behavior is described and used in order to formulate and test hypotheses about the pathogenesis of schizophrenic behavior using EEG measures. Results from our studies on EEG activity and EEG reactivity (= EEG components of a memory-driven, adaptive, non-unitary orienting response) as analyzed with spectral parameters and "chaotic" dimensionality (correlation dimension) are summarized. Both analysis procedures showed a deviant brain functional organization in never-treated first-episode schizophrenia which, within the framework of the model, suggests as common denominator for the pathogenesis of the symptoms a deviation of working memory, the nature of which is functional and not structural.

Differences in the EEG profiles of early and late responders to antipsychotic treatment in first-episode, drug-naive psychotic patients

The aim of this study was to search for differences in the EEG of first-episode, drug-naive patients having a schizophrenic syndrome which presented different time courses in response to antipsychotic treatment. Thirteen patients who fulfilled DSM-IV diagnosis for schizophrenia or schizophreniform disorder participated in this study. Before beginning antipsychotic treatment, the EEG was recorded. On the same day psychopathological ratings were assessed using the ADMDP system, and again after 7 and 28 days of treatment. The resting EEG (19 leads) was subject to spectral analysis involving power values for six frequency bands. The score for the schizophrenic syndrome was used to divide the patients into two groups: those who displayed a clinically meaningful improvement of this syndrome (reduction of more than 30%) after 7 days of treatment (early responders, ER) and those who showed this improvement after 28 days (late responders. LR). Analysis of variance for repeated measures between ER, LR and their matched controls with the 19 EEG leads yielded highly significant differences for the factor group in the alpha2 and beta2 frequency band. No difference was found between the slow-wave frequency bands. Compared to controls the LR group showed significantly higher alpha2 and beta2 power and, in comparison to the ER group, significantly higher alpha2 power. There were no significant differences between the ER and the control group. These findings point to differences in brain physiology between ER and LR. The implications for diagnosis and treatment are discussed.

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

Decreased EEG synchronization in Alzheimer's disease and mild cognitive impairment

The hypothesis of a functional disconnection of neuro-cognitive networks in patients with mild cognitive impairment (MCI) and Alzheimer Dementia was investigated using baseline resting EEG data. EEG databases from New York (264 subjects) and Stockholm (155 subjects), including healthy controls and patients with varying degrees of cognitive decline or Alzheimer Dementia were analyzed using Global Field Synchronization (GFS), a novel measure of global EEG synchronization. GFS reflects the global amount of phase-locked activity at a given frequency by a single number; it is independent of the recording reference and of implicit source models. Patients showed decreased GFS values in Alpha, Beta, and Gamma frequency bands, and increased GFS values in the Delta band, confirming the hypothesized disconnection syndrome. The results are discussed within the framework of current knowledge about the functional significance of the affected frequency bands.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Visual and quantitative electroencephalographic analysis of healthy young and adult cats under medetomidine sedation

A study was designed to investigate the effect of medetomidine sedation on quantitative electroencephalography (q-EEG) in healthy young and adult cats to determine objective guidelines for diagnostic EEG recordings and interpretation. Preliminary visual examination of EEG recordings revealed high-voltage low-frequency background activity. Spindles, k-complexes and vertex sharp transients characteristic of sleep or sedation were superimposed on a low background activity. Neither paroxysmal activity nor EEG burst-suppression were observed. The spectral analysis of q-EEG included four parameters, namely, relative power (%), and mean, median and peak frequency (Hz) of all four frequency bands (delta, theta, alpha and beta). The findings showed a prevalence of slow delta and theta rhythms as opposed to fast alpha and beta rhythms in both young (group A) and adult (group B) cats. A posterior gradient was reported for the theta band and an anterior gradient for the alpha and beta bands in both groups, respectively. The relative power value in group B compared to group A was significantly higher for theta, alpha and beta bands, and lower for the delta band. The mean and median frequency values in group B was significantly higher for delta, theta and beta bands and lower for the alpha band. The study has shown that a medetomidine sedation protocol for feline EEG may offer a method for investigating bio-electrical cortical activity. The use of q-EEG analysis showed a decrease in high frequency bands and increased activity of the low frequency band in healthy cats under medetomidine sedation.

Theta burst transcranial magnetic stimulation is associated with increased EEG synchronization in the stimulated relative to unstimulated cerebral hemisphere

Theta burst transcranial magnetic stimulation (TBS) may induce behavioural changes that outlast the stimulation period. The neurophysiological basis of these behavioural changes are currently under investigation. Given the evidence that cortical information processing relies on transient synchronization and desynchronization of neuronal assemblies, we set out to test whether TBS is associated with changes of neuronal synchronization as assessed by surface EEG. In four healthy subjects one TBS train of 600 pulses (200 bursts, each burst consisting of 3 pulses at 30 Hz, repeated at intervals of 100 ms) was applied over the right frontal eye field and EEG synchronization was assessed in a time-resolved manner over 60 min by using a non-overlapping moving window. For each time step the linear cross-correlation matrix for six EEG channels of the right and for the six homotopic EEG channels of the left hemisphere were computed and their largest eigenvalues used to assess changes of synchronization. Synchronization was computed for broadband EEG and for the delta, theta, alpha, beta and gamma frequency bands. In all subjects EEG synchronization of the stimulated hemisphere was significantly and persistently increased relative to EEG synchronization of the unstimulated hemisphere. This effect occurred immediately after TBS for the theta, alpha, beta and gamma frequency bands and 10-20 min after TBS for broadband and delta frequency band EEG. Our results demonstrate that TBS is associated with increased neuronal synchronization of the cerebral hemisphere ipsilateral to the stimulation site relative to the unstimulated hemisphere. We speculate that enhanced synchronization interferes with cortical information processing and thus may be a neurophysiological correlate of the impaired behavioural performance detected previously.

Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.

Acute disseminated encephalomyelitis in adults: a reappraisal of clinical, CSF, EEG, and MRI findings

OBJECTIVES: To establish an adequate definition of acute disseminated encephalomyelitis (ADEM) in adults, based on our clinical observations of a case-series. METHODS: Over a period of three years 10 adult patients with a para- or postinfectious disseminated (diffuse or multifocal) syndrome of the CNS fulfilling predefined strict criteria for the diagnosis of ADEM were encountered and systematically followed. RESULTS: The age ranged from 21 to 62 years, two were men. MRI was normal in 5 patients and only mildly abnormal in the remaining patients. CSF was normal in 5 patients and mildly abnormal in the remainder, EEG was abnormal in 7/8 patients. All patients survived and were followed over a period of 30 months (range: 8 to 48 months). Nine patients were left with some residual defects, consisting most often of a mild cognitive impairment. CONCLUSIONS: The EEG as an investigation of brain function can be crucial in establishing the organic nature of disease. MRI is important to exclude other diffuse or multifocal encephalopathies. However, in contrast to previous reports in the literature abnormal MRI should not be considered mandatory in adult ADEM. Difficulties in the diagnosis of ADEM are discussed and the importance of clinical and paraclinical findings for establishing the diagnosis is outlined.

Evolution of sleep and sleep EEG after hemispheric stroke

The evolution of subjective sleep and sleep electroencephalogram (EEG) after hemispheric stroke have been rarely studied and the relationship of sleep variables to stroke outcome is essentially unknown. We studied 27 patients with first hemispheric ischaemic stroke and no sleep apnoea in the acute (1-8 days), subacute (9-35 days), and chronic phase (5-24 months) after stroke. Clinical assessment included estimated sleep time per 24 h (EST) and Epworth sleepiness score (ESS) before stroke, as well as EST, ESS and clinical outcome after stroke. Sleep EEG data from stroke patients were compared with data from 11 hospitalized controls and published norms. Changes in EST (>2 h, 38% of patients) and ESS (>3 points, 26%) were frequent but correlated poorly with sleep EEG changes. In the chronic phase no significant differences in sleep EEG between controls and patients were found. High sleep efficiency and low wakefulness after sleep onset in the acute phase were associated with a good long-term outcome. These two sleep EEG variables improved significantly from the acute to the subacute and chronic phase. In conclusion, hemispheric strokes can cause insomnia, hypersomnia or changes in sleep needs but only rarely persisting sleep EEG abnormalities. High sleep EEG continuity in the acute phase of stroke heralds a good clinical outcome.