158 resultados para Electroencephalogram (EEG)

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Avoidance of excessively deep sedation levels is problematic in intensive care patients. Electrophysiologic monitoring may offer an approach to solving this problem. Since electroencephalogram (EEG) responses to different sedation regimens vary, we assessed electrophysiologic responses to two sedative drug regimens in 10 healthy volunteers. Dexmedetomidine/remifentanil (dex/remi group) and midazolam/remifentanil (mida/remi group) were infused 7 days apart. Each combination of medications was given at stepwise intervals to reach Ramsay scores (RS) 2, 3, and 4. Resting EEG, bispectral index (BIS), and the N100 amplitudes of long-latency auditory-evoked potentials (ERP) were recorded at each level of sedation. During dex/remi, resting EEG was characterized by a recurrent high-power low-frequency pattern which became more pronounced at deeper levels of sedation. BIS Index decreased uniformly in only the dex/remi group (from 94 +/- 3 at baseline to 58 +/- 14 at RS 4) compared to the mida/remi group (from 94 +/- 2 to 76 +/- 10; P = 0.029 between groups). The ERP amplitudes decreased from 5.3 +/- 1.3 at baseline to 0.4 +/- 1.1 at RS 4 (P = 0.003) in only the mida/remi group. We conclude that ERPs in volunteers sedated with dex/remi, in contrast to mida/remi, indicate a cortical response to acoustic stimuli, even when sedation reaches deeper levels. Consequently, ERP can monitor sedation with midazolam but not with dexmedetomidine. The reverse is true for BIS.

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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.

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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.

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OBJECTIVE: In ictal scalp electroencephalogram (EEG) the presence of artefacts and the wide ranging patterns of discharges are hurdles to good diagnostic accuracy. Quantitative EEG aids the lateralization and/or localization process of epileptiform activity. METHODS: Twelve patients achieving Engel Class I/IIa outcome following temporal lobe surgery (1 year) were selected with approximately 1-3 ictal EEGs analyzed/patient. The EEG signals were denoised with discrete wavelet transform (DWT), followed by computing the normalized absolute slopes and spatial interpolation of scalp topography associated to detection of local maxima. For localization, the region with the highest normalized absolute slopes at the time when epileptiform activities were registered (>2.5 times standard deviation) was designated as the region of onset. For lateralization, the cerebral hemisphere registering the first appearance of normalized absolute slopes >2.5 times the standard deviation was designated as the side of onset. As comparison, all the EEG episodes were reviewed by two neurologists blinded to clinical information to determine the localization and lateralization of seizure onset by visual analysis. RESULTS: 16/25 seizures (64%) were correctly localized by the visual method and 21/25 seizures (84%) by the quantitative EEG method. 12/25 seizures (48%) were correctly lateralized by the visual method and 23/25 seizures (92%) by the quantitative EEG method. The McNemar test showed p=0.15 for localization and p=0.0026 for lateralization when comparing the two methods. CONCLUSIONS: The quantitative EEG method yielded significantly more seizure episodes that were correctly lateralized and there was a trend towards more correctly localized seizures. SIGNIFICANCE: Coupling DWT with the absolute slope method helps clinicians achieve a better EEG diagnostic accuracy.

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Global complexity of 47-channel resting electroencephalogram (EEG) of healthy young volunteers was studied after intake of a single dose of a nootropic drug (piracetam, Nootropil® UCB Pharma) in 12 healthy volunteers. Four treatment levels were used: 2.4, 4.8, 9.6 g piracetam and placebo. Brain electric activity was assessed through Global Dimensional Complexity and Global Omega-Complexity as quantitative measures of the complexity of the trajectory of multichannel EEG in state space. After oral ingestion (1–1.5 h), both measures showed significant decreases from placebo to 2.4 g piracetam. In addition, Global Dimensional Complexity showed a significant return to placebo values at 9.6 g piracetam. The results indicate that a single dose of piracetam dose-dependently affects the spontaneous EEG in normal volunteers, showing effects at the lowest treatment level. The decreased EEG complexity is interpreted as increased cooperativity of brain functional processes.

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An ascent to altitude has been shown to result in more central apneas and a shift towards lighter sleep in healthy individuals. This study employs spectral analysis to investigate the impact of respiratory disturbances (central/obstructive apnea and hypopnea or periodic breathing) at moderate altitude on the sleep electroencephalogram (EEG) and to compare EEG changes resulting from respiratory disturbances and arousals. Data were collected from 51 healthy male subjects who spent 1 night at moderate altitude (2590 m). Power density spectra of Stage 2 sleep were calculated in a subset (20) of these participants with sufficient artefact-free data for (a) epochs with respiratory events without an accompanying arousal, (b) epochs containing an arousal and (c) epochs of undisturbed Stage 2 sleep containing neither arousal nor respiratory events. Both arousals and respiratory disturbances resulted in reduced power in the delta, theta and spindle frequency range and increased beta power compared to undisturbed sleep. The similarity of the EEG changes resulting from altitude-induced respiratory disturbances and arousals indicates that central apneas are associated with micro-arousals, not apparent by visual inspection of the EEG. Our findings may have implications for sleep in patients and mountain tourists with central apneas and suggest that respiratory disturbances not accompanied by an arousal may, none the less, impact sleep quality and impair recuperative processes associated with sleep more than previously believed.

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BACKGROUND Disrupted sleep is a common complaint of individuals with alcohol use disorder and in abstinent alcoholics. Furthermore, among recovering alcoholics, poor sleep predicts relapse to drinking. Whether disrupted sleep in these populations results from prolonged alcohol use or precedes the onset of drinking is not known. The aim of this study was to examine the sleep electroencephalogram (EEG) in alcohol-naïve, parental history positive (PH+), and negative (PH-) boys and girls. METHODS All-night sleep EEG recordings in 2 longitudinal cohorts (child and teen) followed at 1.5 to 3 year intervals were analyzed. The child and teen participants were 9/10 and 15/16 years old at the initial assessment, respectively. Parental history status was classified by Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria applied to structured interviews (DIS-IV) resulting in 14 PH- and 10 PH+ children and 14 PH- and 10 PH+ teens. Sleep data were visually scored in 30-second epochs using standard criteria. Power spectra were calculated for EEG derivations C3/A2, C4/A1, O2/A1, O1/A2 for nonrapid eye movement (NREM) and rapid eye movement (REM) sleep. RESULTS We found no difference between PH+ and PH- individuals in either cohort for any visually scored sleep stage variable. Spectral power declined in both cohorts across assessments for NREM and REM sleep in all derivations and across frequencies independent of parental history status. With regard to parental history, NREM sleep EEG power was lower for the delta band in PH+ teens at both assessments for the central derivations. Furthermore, power in the sigma band for the right occipital derivation in both NREM and REM sleep was lower in PH+ children only at the initial assessment. CONCLUSIONS We found no gross signs of sleep disruption as a function of parental history. Modest differences in spectral EEG power between PH+ and PH- children and teens indicate that a marker of parental alcohol history may be detectable in teens at risk for problem drinking.

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BACKGROUND Gambling is a form of nonsubstance addiction classified as an impulse control disorder. Pathologic gamblers are considered healthy with respect to their cognitive status. Lesions of the frontolimbic systems, mostly of the right hemisphere, are associated with addictive behavior. Because gamblers are not regarded as "brain-lesioned" and gambling is nontoxic, gambling is a model to test whether addicted "healthy" people are relatively impaired in frontolimbic neuropsychological functions. METHODS Twenty-one nonsubstance dependent gamblers and nineteen healthy subjects underwent a behavioral neurologic interview centered on incidence, origin, and symptoms of possible brain damage, a neuropsychological examination, and an electroencephalogram. RESULTS Seventeen gamblers (81%) had a positive medical history for brain damage (mainly traumatic head injury, pre- or perinatal complications). The gamblers, compared with the controls, were significantly more impaired in concentration, memory, and executive functions, and evidenced a higher prevalence of non-right-handedness (43%) and, non-left-hemisphere language dominance (52%). Electroencephalogram (EEG) revealed dysfunctional activity in 65% of the gamblers, compared with 26% of controls. CONCLUSIONS This study shows that the "healthy" gamblers are indeed brain-damaged. Compared with a matched control population, pathologic gamblers evidenced more brain injuries, more fronto-temporo-limbic neuropsychological dysfunctions and more EEG abnormalities. The authors thus conjecture that addictive gambling may be a consequence of brain damage, especially of the frontolimbic systems, a finding that may well have medicolegal consequences.

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The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12 h time in bed (TIB)] following 12 h of wakefulness were interleaved with three nights of recovery sleep (12 h TIB) following 36 h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25 Hz frequency bins between 0.75 and 16.0 Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait.

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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.

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INTRODUCTION: Experience-based adaptation of emotional responses is an important faculty for cognitive and emotional functioning. Professional musicians represent an ideal model in which to elicit experience-driven changes in the emotional processing domain. The changes of the central representation of emotional arousal due to musical expertise are still largely unknown. The aim of the present study was to investigate the electroencephalogram (EEG) correlates of experience-driven changes in the domain of emotional arousal. Therefore, the differences in perceived (subjective arousal via ratings) and physiologically measured (EEG) arousal between amateur and professional musicians were examined. PROCEDURE: A total of 15 professional and 19 amateur musicians listened to the first movement of Ludwig van Beethoven's 5th symphony (duration=∼7.4min), during which a continuous 76-channel EEG was recorded. In a second session, the participants evaluated their emotional arousal during listening. In a tonic analysis, we examined the average EEG data over the time course of the music piece. For a phasic analysis, a fast Fourier transform was performed and covariance maps of spectral power were computed in association with the subjective arousal ratings. RESULTS: The subjective arousal ratings of the professional musicians were more consistent than those of the amateur musicians. In the tonic EEG analysis, a mid-frontal theta activity was observed in the professionals. In the phasic EEG, the professionals exhibited an increase of posterior alpha, central delta, and beta rhythm during high arousal. DISCUSSION: Professionals exhibited different and/or more intense patterns of emotional activation when they listened to the music. The results of the present study underscore the impact of music experience on emotional reactions.