Vladimir Krajca

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

INTRODUCTIONnPrevious 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.nnnMETHODnWe analyzed 25 inpatients who finished 4-week venlafaxine treatment. EEG data were monitored at baseline and after 1 week of treatment. QEEG cordance was computed at three frontal electrodes in theta frequency band. Depressive symptoms and clinical status were assessed using Montgomery-Asberg Depression Rating Scale (MADRS), Beck Depression Inventory-Short Form (BDI-S) and Clinical Global Impression (CGI).nnnRESULTSnEleven of 12 responders (reduction of MADRS >or=50%) and only 5 of 13 non-responders had decreased prefrontal QEEG cordance value after the first week of treatment (p=0.01). The decrease of prefrontal cordance after week 1 in responders was significant (p=0.03) and there was no significant change in non-responders. Positive and negative predictive values of cordance reduction for response were 0.7 and 0.9, respectively.nnnCONCLUSIONnThe reduction of prefrontal theta QEEG cordance value after first week of treatment might be helpful in the prediction of response to venlafaxine.

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. The EEG spectra and coherences in 6 frequency bands were calculated in 16 EEG derivations. Among various EEG indicators, a decrease in the alpha coherence and an increase in the delta coherence was found to be most significantly correlated to the degree of dementia. Combining 6 variables from the spectrum and coherence analysis by means of the multiple regression model, a high correlation (r = 0.87) between a set of EEG variables and the Mini-Mental State Examination score could be obtained. The results suggest that the EEG can supplement the clinical examination by providing an independent assessment of the degree of dementia. The results also suggest that the EEG coherences are of particular interest in dementia, being an indicator of the signal transfer between various parts of the brain cortex.

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

UNLABELLEDnThe 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.nnnMETHODnEEG data of 18 inpatients were monitored at baseline and after one week. QEEG cordance was computed at 3 frontal electrodes (Fp1, Fp2, Fz). Response to treatment was defined as a >/=50% reduction of MADRS score.nnnRESULTSnNine of the eleven responders and one of the seven non-responders showed decreased prefrontal cordance value after the first week of treatment (p=0.01). Positive and negative predictive values of cordance reduction for the prediction of response to the treatment were 0.9 and 0.75, respectively.nnnCONCLUSIONnSimilar to other antidepressants, the reduction of prefrontal QEEG cordance might be helpful in the prediction of the acute outcome of bupropion treatment.

Standardized low-resolution brain electromagnetic tomography (sLORETA) in the prediction of response to cholinesterase inhibitors in patients with Alzheimer's disease

Materials and methods Resting EEG was recorded in 20 mild to moderate AD patients (mean age= 75.04 years; 13 women and 7 men; MMSE 15-24) before and after 6 months and 2 years on ChEI (donepezil, rivastigmine, galantamine) treatment. Based on changes of MMSE scores after 2 years follow-up, 11 patients were classified as Non-responders (decrease of MMSE > 2) and 9 patients as Responders (decrease of MMSE < 2). The localization of the differences in activity between two groups (at baseline) and within groups (baseline vs. 6 months) was assessed by voxel-by-voxel ttests of the sLORETA images of the log-transformed computed current density power in seven frequency bands.

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

OBJECTIVESnThe 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.nnnMETHODSnWe investigated 20 inpatients who completed a 4-week treatment. EEG data were monitored at baseline and after 1 week of treatment. QEEG cordance was computed at 3 frontal electrodes (Fp1, Fp2, Fz) in theta frequency band. Depressive symptoms and clinical status were assessed using Montgomery-Åsberg Depression Rating Scale (MADRS), Clinical Global Impression (CGI) and Young Mania Rating Scale (YMRS).nnnRESULTSnSeven of 8 responders (reduction of MADRS ≥50%) and only 2 of 12 non-responders had decreased prefrontal theta cordance value after the first week of treatment (pxa0=xa00.02). The positive and negative predictive values of cordance reduction for response were 0.78 and 0.91, respectively. We also found significant differences in cordance value reductions between responders and non-responders after week 1 and higher baseline cordance in responders.nnnCONCLUSIONnThe change in prefrontal theta cordance was associated with subsequent change in depressive symptoms and potentially might be a useful tool in the early detection of acute response to antidepressive interventions in bipolar depressed patients.

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. We compared antipsychotic-naive subjects with healthy controls and medicated patients. (1) Comparing antipsychotic-naive subjects and controls we found a general increase in the slow delta and theta frequencies over the fronto-temporo-occipital cortex, particularly in the temporolimbic structures, an increase in alpha-1 and alpha-2 in the temporal cortex and an increase in beta-1 and beta-2 in the temporo-occipital and posterior limbic structures. (2) Comparing patients who received clozapine and those who were antipsychotic naive, we found an increase in delta and theta frequencies in the anterior cingulate and medial frontal cortex, and a decrease in alpha-1 and beta-2 in the occipital structures. (3) Comparing patients taking olanzapine with those who were antipsychotic naive, there was an increase in theta frequencies in the anterior cingulum, a decrease in alpha-1, beta-2 and beta-3 in the occipital cortex and posterior limbic structures, and a decrease in beta-3 in the frontotemporal cortex and anterior cingulum. (4) In patients taking risperidone, we found no significant changes from those who were antipsychotic naive. Our results in antipsychotic-naive patients are in agreement with existing functional findings. Changes in those taking clozapine and olanzapine versus those who were antipsychotic naive suggest a compensatory mechanism in the neurobiological substrate for schizophrenia. The lack of difference in risperidone patients versus antipsychotic-naive subjects may relate to risperidone’s different pharmacodynamic mechanism.

Application of Artificial Neural Networks for Analyses of EEG Record with Semi-Automated Etalons Extraction: A Pilot Study

Application of artificial neural network (ANN) classification – multilayer perceptron (MLP) with simulated annealing for initialization and genetic algorithm for weight optimization on multi-channel EEG record is presented here. The novelty of the approach lies in the semi-automated etalon extraction. The etalons are suggested by the k-means algorithm and verified/edited by an expert. The whole process of EEG record consists of multichannel adaptive segmentation, feature extraction from segments, semi-automatic process of etalons extraction by the k-means cluster analysis leading to color segment identification and continuing with manual choice of segments for etalons by the expert and feature extraction of chosen etalons. Subsequent classification by ANN leads to unique color identification of segments in the EEG record and additionally in temporal profile. Our goal is to help the physician by mimetic software because the examination of long multichannel EEG is a tedious work.

Fuzzy c-Means Algorithm in Automatic Classification of EEG

The electroencephalogram (EEG) provides markers of brain disturbances in the field of epilepsy. In short duration EEG data recordings, the epileptic graphoelements may not manifest. The visual analysis of lengthy signals is a tedious task. It is necessary to track the activity on the computer screen and to detect the epileptiform graphoelements and the other pathological activity. The automation of the process is suggested. The procedure is based on processing temporal profiles computed by means of multichannel adaptive segmentation and subsequent classification of detected signal graphoelements. The temporal profiles, function of the class membership in the course of time, reflect the dynamic EEG microstructure and may be used for visual indication of abnormal changes in the EEG using different colors. We will show that Fuzzy c-means (FCM) algorithm can be used for correct classification of epileptic pattern, creating homogeneous compact classes of significant EEG segments.