967 resultados para Electroencephalogram (EEG)


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Event-related desynchronization (ERD) of the electroencephalogram (EEG) from the motor cortex is associated with execution, observation, and mental imagery of motor tasks. Generation of ERD by motor imagery (MI) has been widely used for brain-computer interfaces (BCIs) linked to neuroprosthetics and other motor assistance devices. Control of MI-based BCIs can be acquired by neurofeedback training to reliably induce MI-associated ERD. To develop more effective training conditions, we investigated the effect of static and dynamic visual representations of target movements (a picture of forearms or a video clip of hand grasping movements) during the BCI training. After 4 consecutive training days, the group that performed MI while viewing the video showed significant improvement in generating MI-associated ERD compared with the group that viewed the static image. This result suggests that passively observing the target movement during MI would improve the associated mental imagery and enhance MI-based BCIs skills.

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Background Event-related desynchronization/synchronization (ERD/ERS) is a relative power decrease/increase of electroencephalogram (EEG) in a specific frequency band during physical motor execution and mental motor imagery, thus it is widely used for the brain-computer interface (BCI) purpose. However what the ERD really reflects and its frequency band specific role have not been agreed and are under investigation. Understanding the underlying mechanism which causes a significant ERD would be crucial to improve the reliability of the ERD-based BCI. We systematically investigated the relationship between conditions of actual repetitive hand movements and resulting ERD. Methods Eleven healthy young participants were asked to close/open their right hand repetitively at three different speeds (Hold, 1/3 Hz, and 1 Hz) and four distinct motor loads (0, 2, 10, and 15 kgf). In each condition, participants repeated 20 experimental trials, each of which consisted of rest (8–10 s), preparation (1 s) and task (6 s) periods. Under the Hold condition, participants were instructed to keep clenching their hand (i.e., isometric contraction) during the task period. Throughout the experiment, EEG signals were recorded from left and right motor areas for offline data analysis. We obtained time courses of EEG power spectrum to discuss the modulation of mu and beta-ERD/ERS due to the task conditions. Results We confirmed salient mu-ERD (8–13 Hz) and slightly weak beta-ERD (14–30 Hz) on both hemispheres during repetitive hand grasping movements. According to a 3 × 4 ANOVA (speed × motor load), both mu and beta-ERD during the task period were significantly weakened under the Hold condition, whereas no significant difference in the kinetics levels and interaction effect was observed. Conclusions This study investigates the effect of changes in kinematics and kinetics on resulting ERD during repetitive hand grasping movements. The experimental results suggest that the strength of ERD may reflect the time differentiation of hand postures in motor planning process or the variation of proprioception resulting from hand movements, rather than the motor command generated in the down stream, which recruits a group of motor neurons.

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Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

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Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

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The neural mechanisms of music listening and appreciation are not yet completely understood. Based on the apparent relationship between the beats per minute (tempo) of music and the desire to move (for example feet tapping) induced while listening to that music it is hypothesised that musical tempo may evoke movement related activity in the brain. Participants are instructed to listen, without moving, to a large range of musical pieces spanning a range of styles and tempos during an electroencephalogram (EEG) experiment. Event-related desynchronisation (ERD) in the EEG is observed to correlate significantly with the variance of the tempo of the musical stimuli. This suggests that the dynamics of the beat of the music may induce movement related brain activity in the motor cortex. Furthermore, significant correlations are observed between EEG activity in the alpha band over the motor cortex and the bandpower of the music in the same frequency band over time. This relationship is observed to correlate with the strength of the ERD, suggesting entrainment of motor cortical activity relates to increased ERD strength

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A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

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TORRES, F ; FILHO, M.S. ; ANTUNES, C. ; KALININE, E. ; ANTONIOLLI, E. ; PORTELA, Luis Valmor ; SOUZA, Diogo Onofre ; TORT, A. B. L. . Electrophysiological effects of guanosine and MK-801 in a quinolinic acid-induced seizure model. Experimental Neurology , v. 221, p. 296-306, 2010

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Background: Many factors contribute to extend productive life in the modern world. Competition makes people worry about physical appearance, mosftly in respect to facial and skin aging. This has motivated new developments in cosmetic dermatology and the need of evaluating patient satisfaction with the new proposed treatments. Poll questionnaire has been used for such evaluation, and the analysis of the electroencephalogram (EEG) mapping obtained while the patient answers the satisfaction questionnaire may render the results less subjective. Objectives: The purpose of this paper is to study the satisfaction of a group of 33 women (mean age, 44.years) treated with hyaluronic acid filling of nasolabial folding or lips, combining the EEG brain mapping and questionnaire techniques. Methods: At the third month of evaluation, two networked personal computers were used for the EEG recording and for presenting the patient with a questionnaire about her well-being feeling; self-evaluation of her face; her satisfaction with the results of the aesthetic treatment; how the family, friends, and people at work evaluated the result of the treatment; and her decision to repeat the treatment and to recommend it to friends and family. Results: Poll results showed that patients were feeling well and were satisfied with the results of the aesthetic treatment. Furthermore, the regression EEG mappings showed patients to be satisfied with their appearance and with the treatment involving similar brain areas. Conclusion: Patients decided to undergo the treatment because they were already considering it (54%) or because they were dissatisfied with their lips or nasolabial folding (52%). The fact that the treatment was free of charge solidified the decision. Patients consider themselves as good-looking and they wanted to preserve such a condition. © 2008 Wiley Periodicals, Inc.

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Recent research has provided evidence of a link between behavioral measures of social cognition (SC) and neural and genetic correlates. Differences in face processing and variations in the oxytocin receptor (OXTR) gene have been associated with SC deficits and autism spectrum disorder (ASD) traits. Much work has examined the qualitative differences between those with ASD and typically developing (TD) individuals, but very little has been done to quantify the natural variation in ASD-like traits in the typical population. The present study examines this variation in TD children using a multidimensional perspective involving behavior assessment, neural electroencephalogram (EEG) testing, and OXTR genotyping. Children completed a series of neurocognitive assessments, provided saliva samples for sequencing, and completed a face processing task while connected to an EEG. No clear pattern emerged for EEG covariates or genotypes for individual OXTR single nucleotide polymorphisms (SNPs). However, SNPs rs2254298 and rs53576 consistently interacted such that the AG/GG allele combination of these SNPs was associated with poorer performance on neurocognitive measures. These results suggest that neither SNP in isolation is risk-conferring, but rather that the combination of rs2254298(A/G) and rs53576(G/G) confers a deleterious effect on SC across several neurocognitive measures. Copyright 2014. Published by Elsevier Ltd.

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STUDY OBJECTIVES: Periodic leg movements in sleep (PLMS) are frequently accompanied by arousals and autonomic activation, but the pathophysiologic significance of these manifestations is unclear. DESIGN: Changes in heart rate variability (HRV), HRV spectra, and electroencephalogram (EEG) spectra associated with idiopathic PLMS were compared with changes associated with isolated leg movements and respiratory-related leg movements during sleep. Furthermore, correlations between electromyographic activity, HRV changes, and EEG changes were assessed. SETTING: Sleep laboratory. PATIENTS: Whole-night polysomnographic studies of 24 subjects fulfilling the criteria of either periodic leg movements disorder (n = 8), obstructive sleep apnea syndrome (n = 7), or normal polysomnography (n = 9) were used. MEASUREMENTS AND RESULTS: Spectral HRV changes started before all EEG changes and up to 6 seconds before the onset of all types of leg movements. An initial weak autonomic activation was followed by a sympathetic activation, an increase of EEG delta activity, and finally a progression to increased higher-frequency EEG rhythms. After movement onset, HRV indicated a vagal activation, and, the EEG, a decrease in spindle activity. Sympathetic activation, as measured by HRV spectra, was greater for PLMS than for all other movement types. In EEG, gamma synchronization began 1 to 2 seconds earlier for isolated leg movements and respiratory-related leg movements than for PLMS. Significant correlations were found between autonomic activations and electromyographic activity, as well as between autonomic activations and EEG delta activity, but not between higher-frequency EEG rhythms and EMG activity or HRV changes. CONCLUSIONS: These results suggest a primary role of the sympathetic nervous system in the generation of PLMS.

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BACKGROUND: Although yawning is a ubiquitous and phylogenetically old phenomenon, its origin and purpose remain unclear. The study aimed at testing the widely held hypothesis that yawning is triggered by drowsiness and brings about a reversal or suspension of the process of falling asleep. METHODS: Subjects complaining of excessive sleepiness were spontaneously yawning while trying to stay awake in a quiet and darkened room. Changes in their electroencephalogram (EEG) and heart rate variability (HRV) associated with yawning were compared to changes associated with isolated voluntary body movements. Special care was taken to remove eye blink- and movement-artefacts from the recorded signals. RESULTS: Yawns were preceded and followed by a significantly greater delta activity in EEG than movements (p< or =0.008). After yawning, alpha rhythms were attenuated, decelerated, and shifted towards central brain regions (p< or =0.01), whereas after movements, they were attenuated and accelerated (p<0.02). A significant transient increase of HRV occurred after the onset of yawning and movements, which was followed by a significant slow decrease peaking 17s after onset (p<0.0001). No difference in HRV changes was found between yawns and movements. CONCLUSIONS: Yawning occurred during periods with increased drowsiness and sleep pressure, but was not followed by a measurable increase of the arousal level of the brain. It was neither triggered nor followed by a specific autonomic activation. Our results therefore confirm that yawns occur due to sleepiness, but do not provide evidence for an arousing effect of yawning.

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The present chapter gives a comprehensive introduction into the display and quantitative characterization of scalp field data. After introducing the construction of scalp field maps, different interpolation methods, the effect of the recording reference and the computation of spatial derivatives are discussed. The arguments raised in this first part have important implications for resolving a potential ambiguity in the interpretation of differences of scalp field data. In the second part of the chapter different approaches for comparing scalp field data are described. All of these comparisons can be interpreted in terms of differences of intracerebral sources either in strength, or in location and orientation in a nonambiguous way. In the present chapter we only refer to scalp field potentials, but mapping also can be used to display other features, such as power or statistical values. However, the rules for comparing and interpreting scalp field potentials might not apply to such data. Generic form of scalp field data Electroencephalogram (EEG) and event-related potential (ERP) recordings consist of one value for each sample in time and for each electrode. The recorded EEG and ERP data thus represent a two-dimensional array, with one dimension corresponding to the variable “time” and the other dimension corresponding to the variable “space” or electrode. Table 2.1 shows ERP measurements over a brief time period. The ERP data (averaged over a group of healthy subjects) were recorded with 19 electrodes during a visual paradigm. The parietal midline Pz electrode has been used as the reference electrode.

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INTRODUCTION: We studied intra-individual and inter-individual variability of two online sedation monitors, BIS and Entropy, in volunteers under sedation. METHODS: Ten healthy volunteers were sedated in a stepwise manner with doses of either midazolam and remifentanil or dexmedetomidine and remifentanil. One week later the procedure was repeated with the remaining drug combination. The doses were adjusted to achieve three different sedation levels (Ramsay Scores 2, 3 and 4) and controlled by a computer-driven drug-delivery system to maintain stable plasma concentrations of the drugs. At each level of sedation, BIS and Entropy (response entropy and state entropy) values were recorded for 20 minutes. Baseline recordings were obtained before the sedative medications were administered. RESULTS: Both inter-individual and intra-individual variability increased as the sedation level deepened. Entropy values showed greater variability than BIS(R) values, and the variability was greater during dexmedetomidine/remifentanil sedation than during midazolam/remifentanil sedation. CONCLUSIONS: The large intra-individual and inter-individual variability of BIS and Entropy values in sedated volunteers makes the determination of sedation levels by processed electroencephalogram (EEG) variables impossible. Reports in the literature which draw conclusions based on processed EEG variables obtained from sedated intensive care unit (ICU) patients may be inaccurate due to this variability. TRIAL REGISTRATION: clinicaltrials.gov Nr. NCT00641563.

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Syncope describes a sudden and brief transient loss of consciousness (TLOC) with postural failure due to cerebral global hypoperfusion. The term TLOC is used when the cause is either unrelated to cerebral hypoperfusion or is unknown. The most common causes of syncopal TLOC include: (1) cardiogenic syncope (cardiac arrhythmias, structural cardiac diseases, others); (2) orthostatic hypotension (due to drugs, hypovolemia, primary or secondary autonomic failure, others); (3) neurally mediated syncope (cardioinhibitory, vasodepressor, and mixed forms). Rarely neurologic disorders (such as epilepsy, transient ischemic attacks, and the subclavian steal syndrome) can lead to cerebal hypoperfusion and syncope. Nonsyncopal TLOC may be due to neurologic (epilepsy, sleep attacks, and other states with fluctuating vigilance), medical (hypoglycemia, drugs), psychiatric, or post-traumatic disorders. Basic diagnostic workup of TLOC includes a thorough history and physical examination, and a 12-lead electrocardiogram (ECG). Blood testing, electroencephalogram (EEG), magnetic resonance imaging (MRI) of the brain, echocardiography, head-up tilt test, carotid sinus massage, Holter monitoring, and loop recorders should be obtained only in specific contexts. Management strategies involve pharmacologic and nonpharmacologic interventions, and cardiac pacing.