115 resultados para Electroencephalographic


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Introduction. This is a pilot study of quantitative electro-encephalographic (QEEG) comodulation analysis, which is used to assist in identifying regional brain differences in those people suffering from chronic fatigue syndrome (CFS) compared to a normative database. The QEEG comodulation analysis examines spatial-temporal cross-correlation of spectral estimates in the resting dominant frequency band. A pattern shown by Sterman and Kaiser (2001) and referred to as the anterior posterior dissociation (APD) discloses a significant reduction in shared functional modulation between frontal and centro-parietal areas of the cortex. This research attempts to examine whether this pattern is evident in CFS. Method. Eleven adult participants, diagnosed by a physician as having CFS, were involved in QEEG data collection. Nineteen-channel cap recordings were made in five conditions: eyes-closed baseline, eyes-open, reading task one, math computations task two, and a second eyes-closed baseline. Results. Four of the 11 participants showed an anterior posterior dissociation pattern for the eyes-closed resting dominant frequency. However, seven of the 11 participants did not show this pattern. Examination of the mean 8-12 Hz amplitudes across three cortical regions (frontal, central and parietal) indicated a trend of higher overall alpha levels in the parietal region in CFS patients who showed the APD pattern compared to those who did not have this pattern. All patients showing the pattern were free of medication, while 71% of those absent of the pattern were using antidepressant medications. Conclusions. Although the sample is small, it is suggested that this method of evaluating the disorder holds promise. The fact that this pattern was not consistently represented in the CFS sample could be explained by the possibility of subtypes of CFS, or perhaps co-morbid conditions. Further, the use of antidepressant medications may mask the pattern by altering the temporal characteristics of the EEG. The results of this pilot study indicate that further research is warranted to verify that the pattern holds across the wider population of CFS sufferers.

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Pitch discrimination is a fundamental property of the human auditory system. Our understanding of pitch-discrimination mechanisms is important from both theoretical and clinical perspectives. The discrimination of spectrally complex sounds is crucial in the processing of music and speech. Current methods of cognitive neuroscience can track the brain processes underlying sound processing either with precise temporal (EEG and MEG) or spatial resolution (PET and fMRI). A combination of different techniques is therefore required in contemporary auditory research. One of the problems in comparing the EEG/MEG and fMRI methods, however, is the fMRI acoustic noise. In the present thesis, EEG and MEG in combination with behavioral techniques were used, first, to define the ERP correlates of automatic pitch discrimination across a wide frequency range in adults and neonates and, second, they were used to determine the effect of recorded acoustic fMRI noise on those adult ERP and ERF correlates during passive and active pitch discrimination. Pure tones and complex 3-harmonic sounds served as stimuli in the oddball and matching-to-sample paradigms. The results suggest that pitch discrimination in adults, as reflected by MMN latency, is most accurate in the 1000-2000 Hz frequency range, and that pitch discrimination is facilitated further by adding harmonics to the fundamental frequency. Newborn infants are able to discriminate a 20% frequency change in the 250-4000 Hz frequency range, whereas the discrimination of a 5% frequency change was unconfirmed. Furthermore, the effect of the fMRI gradient noise on the automatic processing of pitch change was more prominent for tones with frequencies exceeding 500 Hz, overlapping with the spectral maximum of the noise. When the fundamental frequency of the tones was lower than the spectral maximum of the noise, fMRI noise had no effect on MMN and P3a, whereas the noise delayed and suppressed N1 and exogenous N2. Noise also suppressed the N1 amplitude in a matching-to-sample working memory task. However, the task-related difference observed in the N1 component, suggesting a functional dissociation between the processing of spatial and non-spatial auditory information, was partially preserved in the noise condition. Noise hampered feature coding mechanisms more than it hampered the mechanisms of change detection, involuntary attention, and the segregation of the spatial and non-spatial domains of working-memory. The data presented in the thesis can be used to develop clinical ERP-based frequency-discrimination protocols and combined EEG and fMRI experimental paradigms.

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Objective: To document electroencephalogram (EEG) changes and their correlation with clinical parameters in a newly diagnosed pediatric cohort of type 1 diabetes mellitus (T1DM) patients with and without diabetic ketoacidosis (DKA) and to define their medium term utility and significance. Research design and methods: Prospective longitudinal study of children presenting with T1DM. EEGs were performed within 24 h of diagnosis, day 5, and at 6 months post-diagnosis and reviewed by a neurologist blinded to clinical status. Severity of encephalopathy was graded from 1 to 5 using the Aoki and Lombroso encephalopathy scale. Cognitive abilities were assessed using standardized tests of attention, memory, and intelligence. Results: Eighty eight children were recruited; 34 presented with DKA. Abnormal background slowing was more often observed in the first 24 h in children with DKA (p = 0.01). Encephalopathy scores on day 1 correlated with initial pH, CO2, HCO3, base excess, respiratory rate, heart rate, diastolic blood pressure, and IV fluid intake (all parameters p < 0.05). EEG scores at day 1 did not correlate with contemporaneous mental state or cognition in the medium term. Conclusions: DKA was associated with significant clinical and neurophysiologic signs of brain dysfunction at presentation. While EEG is sensitive to the detection of encephalopathy in newly diagnosed T1DM, it has limited use in identifying children at risk of later cognitive deficits.

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This work studies the effect of clozapine (CLO) on the electroencephalography (EEG) and reactive oxygen species (ROS) production by peripheral blood monocytes (MO) in patients with schizophrenia (SCH). The aim of the study was to investigate the mechanism of action of CLO, to clarify the effect of CLO on EEG absolute power spectrum and ROS production, and explore the relationship of these effects with clinical response. We also tried to clarify whether the EEG changes or ROS production would help to identify the patients who were most likely to respond to treatment with CLO. Our findings suggest that the amount of slow background activity, particularly the absolute power of the theta frequency band, in the EEG is markedly increased by CLO treatment and this finding correlates positively with clinical improvement in patients with SCH. CLO affected the production of ROS by blood MO with reduction or minimal increase of the ROS production being associated with clinical improvement, whereas marked increase of the ROS production did not. Also a positive correlation between theta absolute power increase in the EEG and suppression of the production of ROS by blood MO was found. The correlations between different symptom clusters of SCH and the EEG rhythms were investigated; the absolute power of beta activity in the EEG seemed to correlate positively to overall psychopathology in patients with SCH showing inadequate response. The results suggest that the EEG background activity and investigation of the production of ROS by MO seem to be an adjunctive method to objectively assess and possibly predict the therapeutic effect of CLO in patients with chronic SCH showing inadequate response to treatment with conventional antipsychotics.

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OBJECTIVES:: Preterm infants undergo frequent painful procedures in the neonatal intensive care unit. Electroencephalography (EEG) changes in reaction to invasive procedures have been reported in preterm and full-term neonates. Frontal EEG asymmetry as an index of emotion during tactile stimulation shows inconsistent findings in full-term infants, and has not been examined in the context of pain in preterm infants. Our aim was to examine whether heel lance for blood collection induces changes in right-left frontal asymmetry, suggesting negative emotional response, in preterm neonates at different gestational age (GA) at birth and different duration of stay in the neonatal intensive care unit. MATERIALS AND METHODS:: Three groups of preterm infants were compared: set 1: group 1 (n=24), born and tested at 28 weeks GA; group 2 (n=22), born at 28 weeks GA and tested at 33 weeks; set 2: group 3 (n=25), born and tested at 33 weeks GA. EEG power was calculated for 30-second artifact-free periods, in standard frequency bandwidths, in 3 phases (baseline, up to 5 min after heel lance, 10 min after heel lance). RESULTS:: No significant differences were found in right-left frontal asymmetry, or in ipsilateral or contralateral somatosensory response, across phases. In contrast, the Behavioral Indicators of Infant Pain scores changed across phase (P

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We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

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The aim of this study was to investigate the electroencephalographic (EEG) response of equidae to a castration stimulus. Study 1 included 11 mules (2 1/2-8 years; 230-315 kg) and 11 horses (1 1/2-3 1/2 years; 315-480 kg); study 2 included four ponies (15-17 months; 176-229 kg). They were castrated under halothane anesthesia after acepromazine premedication (IV [study 1] and intramuscular [study 2]) and thiopental anesthetic induction. Animals were castrated using a semiclosed technique (study 1) and a closed technique (study 2). Raw EEG data were analyzed and the EEG variables, median frequency (F50), total power (Ptot), and spectral edge frequency (F95), were derived using standard techniques at skin incision (skin) and emasculation (emasc) time points. Baseline values of F50, Ptot, and F95 for each animal were used to calculate percentage change from baseline at skin incision and emasculation. Differences were observed in Ptot and F50 data between hemispheres in horses but not mules (study 1) and in one pony (study 2). A response to castration (>10% change relative to baseline) was observed in eight horses (73% of animals) and four mules (36% of animals) for F50 and nine horses (82%) and four mules (36%) for Ptot. No changes in F95 data were observed in any animal in study 1. Responses to castration were observed in three ponies (75% of animals) for F50, one pony (25%) for F95, and all ponies for Ptot Alteration of acepromazine administration and castration technique produced a protocol that identified changes in EEG frequency and power in response to castration. (c) 2014 Elsevier Inc. All rights reserved.

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Objectives: The use of noninvasive cortical electrical stimulation with weak currents has significantly increased in basic and clinical human studies. Initial, preliminary studies with this technique have shown encouraging results; however, the safety and tolerability of this method of brain stimulation have not been sufficiently explored yet. The purpose of our study was to assess the effects of direct current (DC) and alternating current (AC) stimulation at different intensities in order to measure their effects on cognition, mood, and electroencephalogram. Methods: Eighty-two healthy, right-handed subjects received active and sham stimulation in a randomized order. We conducted 164 ninety-minute sessions of electrical stimulation in 4 different protocols to assess safety of (1) anodal DC of the dorsolateral prefrontal cortex (DLPFC); (2) cathodal DC of the DLPFC; (3) intermittent anodal DC of the DLPFC and; (4) AC on the zygomatic process. We used weak currents of 1 to 2 mA (for DC experiments) or 0.1 to 0.2 mA (for AC experiment). Results: We found no significant changes in electroencephalogram, cognition, mood, and pain between groups and a low prevalence of mild adverse effects (0.11% and 0.08% in the active and sham stimulation groups, respectively), mainly, sleepiness and mild headache that were equally distributed between groups. Conclusions: Here, we show no neurophysiological or behavioral signs that transcranial DC stimulation or AC stimulation with weak currents induce deleterious changes when comparing active and sham groups. This study provides therefore additional information for researchers and ethics committees, adding important results to the safety pool of studies assessing the effects of cortical stimulation using weak electrical currents. Further studies in patients with neuropsychiatric disorders are warranted.

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Economic theory distinguishes two concepts of utility: decision utility, objectively quantifiable by choices, and experienced utility, referring to the satisfaction by an obtainment. To date, experienced utility is typically measured with subjective ratings. This study intended to quantify experienced utility by global levels of neuronal activity. Neuronal activity was measured by means of electroencephalographic (EEG) responses to gain and omission of graded monetary rewards at the level of the EEG topography in human subjects. A novel analysis approach allowed approximating psychophysiological value functions for the experienced utility of monetary rewards. In addition, we identified the time windows of the event-related potentials (ERP) and the respective intracortical sources, in which variations in neuronal activity were significantly related to the value or valence of outcomes. Results indicate that value functions of experienced utility and regret disproportionally increase with monetary value, and thus contradict the compressing value functions of decision utility. The temporal pattern of outcome evaluation suggests an initial (∼250 ms) coarse evaluation regarding the valence, concurrent with a finer-grained evaluation of the value of gained rewards, whereas the evaluation of the value of omitted rewards emerges later. We hypothesize that this temporal double dissociation is explained by reward prediction errors. Finally, a late, yet unreported, reward-sensitive ERP topography (∼500 ms) was identified. The sources of these topographical covariations are estimated in the ventromedial prefrontal cortex, the medial frontal gyrus, the anterior and posterior cingulate cortex and the hippocampus/amygdala. The results provide important new evidence regarding “how,” “when,” and “where” the brain evaluates outcomes with different hedonic impact.

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To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.

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Neural correlates of electroencephalographic (EEG) alpha rhythm are poorly understood. Here, we related EEG alpha rhythm in awake humans to blood-oxygen-level-dependent (BOLD) signal change determined by functional magnetic resonance imaging (fMRI). Topographical EEG was recorded simultaneously with fMRI during an open versus closed eyes and an auditory stimulation versus silence condition. EEG was separated into spatial components of maximal temporal independence using independent component analysis. Alpha component amplitudes and stimulus conditions served as general linear model regressors of the fMRI signal time course. In both paradigms, EEG alpha component amplitudes were associated with BOLD signal decreases in occipital areas, but not in thalamus, when a standard BOLD response curve (maximum effect at approximately 6 s) was assumed. The part of the alpha regressor independent of the protocol condition, however, revealed significant positive thalamic and mesencephalic correlations with a mean time delay of approximately 2.5 s between EEG and BOLD signals. The inverse relationship between EEG alpha amplitude and BOLD signals in primary and secondary visual areas suggests that widespread thalamocortical synchronization is associated with decreased brain metabolism. While the temporal relationship of this association is consistent with metabolic changes occurring simultaneously with changes in the alpha rhythm, sites in the medial thalamus and in the anterior midbrain were found to correlate with short time lag. Assuming a canonical hemodynamic response function, this finding is indicative of activity preceding the actual EEG change by some seconds.