Artifacts in Simultaneous hdEEG/fMRI Imaging: A Nonlinear Dimensionality Reduction Approach.

Simultaneous recordings of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) are at the forefront of technologies of interest to physicians and scientists because they combine the benefits of both modalities-better time resolution (hdEEG) and space resolution (fMRI). However, EEG measurements in the scanner contain an electromagnetic field that is induced in leads as a result of gradient switching slight head movements and vibrations, and it is corrupted by changes in the measured potential because of the Hall phenomenon. The aim of this study is to design and test a methodology for inspecting hidden EEG structures with respect to artifacts.

The effect of ((-)-2-oxa-4-aminobicyclo[3.1.0]hexane-2,6-dicarboxylic acid (LY379268), an mGlu2/3 receptor agonist, on EEG power spectra and coherence in ketamine model of psychosis.

In the present study we investigated the potential antipsychotic effects of the mGlu2/3 agonist LY379268 on changes in EEG power spectra and coherence in the ketamine model of psychosis. In order to use behaviorally active drug doses, experiments detecting changes in locomotor activity and sensorimotor gating were also conducted. In EEG experiments, adult male Wistar rats were injected with ketamine 30 mg/kg i.

Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions.

The goal of this paper is to describe a robust artifact removal (RAR) method, an automatic sequential procedure which is capable of removing short-duration, high-amplitude artifacts from long-term neonatal EEG recordings. Such artifacts are mainly caused by movement activity, and have an adverse effect on the automatic processing of long-term sleep recordings. The artifacts are removed sequentially in short-term signals using independent component analysis (ICA) transformation and wavelet denoising.

The change of QEEG prefrontal cordance as a response predictor to antidepressive intervention in bipolar depression. A pilot study.

Objectives: The aim of the study was to examine whether the change of quantitative EEG (QEEG) theta prefrontal cordance after one week of various antidepressive interventions predicts response to a 4-week treatment in patients with bipolar depression.

Methods: We investigated 20 inpatients who completed a 4-week treatment. EEG data were monitored at baseline and after 1 week of treatment.

Electroencephalographic spectral and coherence analysis of ketamine in rats: correlation with behavioral effects and pharmacokinetics.

Aims: This study was designed to evaluate the changes in EEG power spectra and EEG coherence in a ketamine model of psychosis in rats. Analyses of behavioral measurements--locomotion and sensorimotor gating--and the pharmacokinetics of ketamine and norketamine were also conducted.

Methods: Ketamine and norketamine levels in rat sera and brains were analyzed by gas chromatography-mass spectrometry after ketamine 30 mg/kg (i.

The change of prefrontal QEEG theta cordance as a predictor of response to bupropion treatment in patients who had failed to respond to previous antidepressant treatments.

Unlabelled: The aim of the study was to examine whether the reduction of theta prefrontal quantitative EEG (QEEG) cordance after one week of bupropion administration is a predictor of response to a 4-week treatment in patients that had failed to respond to previous antidepressant treatments.

Method: EEG data of 18 inpatients were monitored at baseline and after one week. QEEG cordance was computed at 3 frontal electrodes (Fp1, Fp2, Fz).

Multivariate analysis of full-term neonatal polysomnographic data.

Introduction: Polysomnography (PSG) is one of the most important noninvasive methods for studying maturation of the child brain. Sleep in infants is significantly different from sleep in adults. This paper addresses the problem of computer analysis of neonatal polygraphic signals.

Trazodone improves the results of cognitive behaviour therapy of primary insomnia in non-depressed patients.

Objectives: Cognitive behaviour therapy (CBT) of primary insomnia is frequently combined with various pharmacological treatments, including sedative antidepressants. The present study was undertaken to evaluate the clinical efficacy of CBT, singly and combined with trazodone pharmacotherapy, for primary insomnia.

Design And Setting: Randomised, comparative clinical trial, at a single academic medical centre.

LORETA functional imaging in antipsychotic-naive and olanzapine-, clozapine- and risperidone-treated patients with schizophrenia.

The aim of our study was to detect changes in the distribution of electrical brain activity in schizophrenic patients who were antipsychotic naive and those who received treatment with clozapine, olanzapine or risperidone. We included 41 subjects with schizophrenia (antipsychotic naive = 11; clozapine = 8; olanzapine = 10; risperidone = 12) and 20 healthy controls. Low-resolution brain electromagnetic tomography was computed from 19-channel electroencephalography for the frequency bands delta, theta, alpha-1, alpha-2, beta-1, beta-2 and beta-3.

QEEG changes during switch from depression to hypomania/mania: a case report.

Background: QEEG cordance and low-resolution electromagnetic tomography (LORETA) are relatively new applications of QEEG. Four small-scale studies have shown that decreases of QEEG prefrontal theta cordance after the first week on new antidepressants predict clinical response to treatment in patients with unipolar depression.

Methods: We calculated prefrontal theta cordance and changes in 3D distribution of brain electrical activity using LORETA in the case of a 54-year old man experiencing his third depressive episode.

Early reduction in prefrontal theta QEEG cordance value predicts response to venlafaxine treatment in patients with resistant depressive disorder.

Introduction: Previous studies of patients with unipolar depression have shown that early decrease of prefrontal EEG cordance in theta band can predict clinical response to various antidepressants. We have now examined whether decrease of prefrontal quantitative EEG (QEEG) cordance value after 1 week of venlafaxine treatment predicts clinical response to venlafaxine in resistant patients.

Method: We analyzed 25 inpatients who finished 4-week venlafaxine treatment.

Effect of low-frequency rTMS on electromagnetic tomography (LORETA) and regional brain metabolism (PET) in schizophrenia patients with auditory hallucinations.

Background: Auditory hallucinations are characteristic symptoms of schizophrenia with high clinical importance. It was repeatedly reported that low frequency ( View Article and Find Full Text PDF

Automatic detection of sleep stages in neonatal EEG using the structural time profiles.

The new method for automatic sleep stages detection in neonatal EEG was developed. The procedure is based on processing of time profiles computed by adaptive segmentation and subsequent classification of signal graphoelements. The time profiles, functions of the class membership in the course of time, reflect the dynamic EEG structure and may be used for indication of changes in the neonatal sleep stages.

Quantitative topographic differentiation of the neonatal EEG.

Objective: To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'.

Methods: 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG).

Comparison of quantitative EEG characteristics of quiet and active sleep in newborns.

Background And Purpose: The aim of the present study was to verify whether the proposed method of computer-supported EEG analysis is able to differentiate the EEG activity in quiet sleep (QS) from that in active sleep (AS) in newborns. A quantitative description of the neonatal EEG may contribute to a more exact evaluation of the functional state of the brain, as well as to a refinement of diagnostics of brain dysfunction manifesting itself frequently as 'dysrhythmia' or 'dysmaturity'.

Patients And Methods: Twenty-one healthy newborns (10 full-term and 11 pre-term) were examined polygraphically (EEG-eight channels, respiration, ECG, EOG and EMG) in the course of sleep.

Objective assessment of the degree of dementia by means of EEG.

The aim of the study was to elaborate a method to estimate the degree of cognitive impairment in Alzheimer's disease from the EEG quantitative indicators. We examined 38 unmedicated patients with a diagnosis of Alzheimer's disease, with various stages (mild, moderate, and severe) of dementia. The EEG recordings were evaluated both visually and by means of computer analysis.

EEG photic driving in workers exposed to mercury vapors.

Objective: To assess the potential of EEG photic driving (PD) as an indicator of an early neurotoxic effect of long-term, low-level exposure to mercury vapors.

Subjects And Methods: Twenty-four chloralkali workers exposed to mercury vapors; twenty-four age- and gender-matched control subjects. Level of exposure was determined by urinary mercury excreted both spontaneously and after administration of a chelating agent, sodium 2,3-dimercapto-1-propane sulfonate.

Extraction of principal components from biosignals by neural net.

This contribution gives the information on a useful application of principal component analysis (PCA) in the field of electroencephalogram (EEG) and laser-Doppler signal processing. The principal components are estimated by a neural network (NN) approach.

Application of optimized pattern recognition units in EEG analysis: common optimization of preprocessing and weights of neural networks as well as structure optimization.

The main goal of this study is to demonstrate the possibility of training the Neural Network (multilayer perceptron) classifier and preprocessing units simultaneously, i.e., that properties of preprocessing are chosen automatically during the training phase.

Structure optimization of neural networks with A* -algorithm application in EEG pattern analysis.

The A* - Algorithm for heuristic search is applied to construct a Neural Network structure (NS) that optimally fits the structure of data to be learned. In this way, the user of Neural Networks (NN) is able to avoid the empirical testing of different structures. The method given here is applied to the recognition of different patterns derived from the EEG of an epileptic patient.

Use of discrete Hilbert transformation for automatic spike mapping: a methodological investigation.

On the basis of discrete Hilbert transform (DHT) realised by fast Fourier transform (FFT), a new strategy for automatic spike mapping is introduced. The further computation of the EEG time series after DHT results in the time series of the momentary power and the momentary frequency. Both are used for the solution of the main requirements of automatic spike mapping.

Automatic identification of significant graphoelements in multichannel EEG recordings by adaptive segmentation and fuzzy clustering.

A new approach to visual evaluation of long-term EEG recordings is proposed. The method is based on multichannel adaptive segmentation, subsequent feature extraction, automatic classification of the acquired segments by fuzzy cluster analysis (fuzzy c-means algorithm), and on the distinguishing of thus identified EEG segments by colour directly in the EEG record. The black and white variant of the described automatic system is presented.

Automatic classification of EEG segments and extraction of representative ones by dynamic clusters method.

Use of the dynamic clusters method for automatic extraction of compressed information about recorded EEG signal is presented. The computer first divides the record into quasi-stationary segments by means of adaptive segmentation. Second, the extracted segments are classified by a method of dynamic clusters into homogeneous classes.