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EEG Data (eeg + data)
Selected AbstractsToward a better understanding of the pathophysiology of OCD SSRI responders: QEEG source localizationACTA PSYCHIATRICA SCANDINAVICA, Issue 3 2007T. G. Bolwig Objective:, To demonstrate the utility of three-dimensional source localization of the scalp-recorded electroencephalogram (EEG) for the identification of the most probable underlying brain dysfunction in patients with obsessive,compulsive disorder (OCD). Method:, Eyes-closed resting EEG data was recorded from the scalp locations of the International 10/20 System. Variable resolution electromagnetic tomography (VARETA) was applied to artifact-free EEG data. This mathematical algorithm estimates the source generators of EEG recorded from the scalp. Results:, An excess in the alpha range was found with sources in the corpus striatum, in the orbito-frontal and temporo-frontal regions in untreated OCD patients. This abnormality was seen to decrease following successful treatment with paroxetine. Conclusion:, The VARETA findings of an activation/deactivation pattern in cortical and subcortical structures in paroxetine-responsive patients are in good accordance with data obtained in previously published positron emission tomography studies related to current hypotheses of a thalamo-striatal-frontal feedback loop being relevant for understanding the pathophysiology of OCD. [source] Removing Eye-movement Artifacts from the EEG during the Intracarotid Amobarbital ProcedureEPILEPSIA, Issue 3 2005Weidong Zhou Summary:,Purpose: The EEG is often recorded during the intracarotid amobarbital procedure (IAP) to help in the assessment of the spatial extent and the duration of the effect of the drug. In scalp recordings, the EEG is always heavily contaminated with eye movement artifacts as the patient actively performs visual tasks. Methods: Independent component analysis (ICA) is a new technique for blind source separation. In this study, we separated the EEG data recorded during the IAP into independent components using ICA. The EEG signal was reconstructed by excluding the components related to eye movement and eye blinks. Results: EEGs from 10 IAP tests were analyzed. The experimental results indicate that ICA is very efficient at subtracting eye-movement artifacts, while retaining the EEG slow waves and making their interpretation easier. Conclusions: ICA appears to be a generally applicable and effective method for removing ocular artifacts from EEG recordings during IAP, although slow waves and ocular artifacts share similar frequency distributions. [source] Ictal Spitting: Clinical and Electroencephalographic FeaturesEPILEPSIA, Issue 8 2003Christoph Kellinghaus Summary: Purpose: To identify clinical and EEG correlates of ictal spitting automatisms and to assess their reliability in indicating the hemisphere of seizure onset. Methods: The epilepsy-monitoring database (1994,2002) of the Cleveland Clinic Foundation (CCF) was searched for patients with a definite history of ictal spitting. All available documents of the patients, particularly their original video and EEG data, were reviewed. Results: Twelve (0.3%) of the ,4,000 patients had a documented history of ictal spitting. In seven of them, 15 seizures with spitting automatisms were recorded. All of them started with an aura or arousal out of sleep. In six of the seven patients (12 of 15 seizures), EEG onset was clearly lateralized to the right, nondominant hemisphere. Spitting occurred at a median time of 21 s after EEG seizure onset. At that time, predominantly fast, high-amplitude theta (5,7 Hz) was seen in the hemisphere of seizure onset, maximum temporal. In all but one of the total 12 patients, the epileptogenic zone was in the temporal lobe. In nine of the 12 patients, seizure onset was in the non,language-dominant hemisphere. Two patients had seizures arising from the language-dominant hemisphere; in another patient, the side of the seizure onset could not be determined. Conclusions: Ictal spitting is an uncommon feature of epileptic seizures. Although the symptomatogenic area is probably outside the temporal lobe, it is most frequently seen in temporal lobe epilepsy of the right, nondominant hemisphere. [source] Dynamic links between theta executive functions and alpha storage buffers in auditory and visual working memoryEUROPEAN JOURNAL OF NEUROSCIENCE, Issue 9 2010Masahiro Kawasaki Abstract Working memory (WM) tasks require not only distinct functions such as a storage buffer and central executive functions, but also coordination among these functions. Neuroimaging studies have revealed the contributions of different brain regions to different functional roles in WM tasks; however, little is known about the neural mechanism governing their coordination. Electroencephalographic (EEG) rhythms, especially theta and alpha, are known to appear over distributed brain regions during WM tasks, but the rhythms associated with task-relevant regional coupling have not been obtained thus far. In this study, we conducted time,frequency analyses for EEG data in WM tasks that include manipulation periods and memory storage buffer periods. We used both auditory WM tasks and visual WM tasks. The results successfully demonstrated function-specific EEG activities. The frontal theta amplitudes increased during the manipulation periods of both tasks. The alpha amplitudes increased during not only the manipulation but also the maintenance periods in the temporal area for the auditory WM and the parietal area for the visual WM. The phase synchronization analyses indicated that, under the relevant task conditions, the temporal and parietal regions show enhanced phase synchronization in the theta bands with the frontal region, whereas phase synchronization between theta and alpha is significantly enhanced only within the individual areas. Our results suggest that WM task-relevant brain regions are coordinated by distant theta synchronization for central executive functions, by local alpha synchronization for the memory storage buffer, and by theta,alpha coupling for inter-functional integration. [source] Independent component analysis of erroneous and correct responses suggests online response controlHUMAN BRAIN MAPPING, Issue 9 2010Sven Hoffmann Abstract After errors in reaction tasks, a sharp negative wave emerges in the event-related potential (ERP), the error (related) negativity (Ne or ERN). However, also after correct trials, an Ne-like wave is seen, called CRN or Nc, which is much smaller than the Ne. This study tested the hypothesis whether Ne and Nc reflect the same functional process, and whether this process is linked to online response control. For this purpose, independent component analysis (ICA) was utilized with the EEG data of two types of reaction tasks: a flanker task and a mental rotation task. To control for speed-accuracy effects, speed and accuracy instructions were balanced in a between subjects design. For both tasks ICA and dipole analysis revealed one component (Ne-IC) explaining most of the variance for the difference between correct and erroneous trials. The Ne-IC showed virtually the same features as the raw postresponse ERP, being larger for erroneous compared to correct trials and for the flanker than for the rotation task. In addition, it peaked earlier for corrected than for uncorrected errors. The results favor the hypothesis that Ne and Nc reflect the same process, which is modulated by response correctness and type of task. On the basis of the literature and the present results, we assume that this process induces online response control, which is much stronger in error than correct trials and with direct rather than indirect stimulus response mapping. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc. [source] Noninvasive dynamic imaging of seizures in epileptic patientsHUMAN BRAIN MAPPING, Issue 12 2009Louise Tyvaert Abstract Epileptic seizures are due to abnormal synchronized neuronal discharges. Techniques measuring electrical changes are commonly used to analyze seizures. Neuronal activity can be also defined by concomitant hemodynamic and metabolic changes. Simultaneous electroencephalogram (EEG)-functional MRI (fMRI) measures noninvasively with a high-spatial resolution BOLD changes during seizures in the whole brain. Until now, only a static image representing the whole seizure was provided. We report in 10 focal epilepsy patients a new approach to dynamic imaging of seizures including the BOLD time course of seizures and the identification of brain structures involved in seizure onset and discharge propagation. The first activation was observed in agreement with the expected location of the focus based on clinical and EEG data (three intracranial recordings), thus providing validity to this approach. The BOLD signal preceded ictal EEG changes in two cases. EEG-fMRI may detect changes in smaller and deeper structures than scalp EEG, which can only record activity form superficial cortical areas. This method allowed us to demonstrate that seizure onset zone was limited to one structure, thus supporting the concept of epileptic focus, but that a complex neuronal network was involved during propagation. Deactivations were also found during seizures, usually appearing after the first activation in areas close or distant to the activated regions. Deactivations may correspond to actively inhibited regions or to functional disconnection from normally active regions. This new noninvasive approach should open the study of seizure generation and propagation mechanisms in the whole brain to groups of patients with focal epilepsies. Hum Brain Mapp, 2009. © 2009 Wiley-Liss, Inc. [source] Improved EEG source analysis using low-resolution conductivity estimation in a four-compartment finite element head modelHUMAN BRAIN MAPPING, Issue 9 2009Seok Lew Abstract Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to geometry and conductivity properties of the different head tissues. We propose a low-resolution conductivity estimation (LRCE) method using simulated annealing optimization on high-resolution finite element models that individually optimizes a realistically shaped four-layer volume conductor with regard to the brain and skull compartment conductivities. As input data, the method needs T1- and PD-weighted magnetic resonance images for an improved modeling of the skull and the cerebrospinal fluid compartment and evoked potential data with high signal-to-noise ratio (SNR). Our simulation studies showed that for EEG data with realistic SNR, the LRCE method was able to simultaneously reconstruct both the brain and the skull conductivity together with the underlying dipole source and provided an improved source analysis result. We have also demonstrated the feasibility and applicability of the new method to simultaneously estimate brain and skull conductivity and a somatosensory source from measured tactile somatosensory-evoked potentials of a human subject. Our results show the viability of an approach that computes its own conductivity values and thus reduces the dependence on assigning values from the literature and likely produces a more robust estimate of current sources. Using the LRCE method, the individually optimized four-compartment volume conductor model can, in a second step, be used for the analysis of clinical or cognitive data acquired from the same subject. Hum Brain Mapp, 2009. © 2008 Wiley-Liss, Inc. [source] White-matter lesions along the cholinergic tracts are related to cortical sources of EEG rhythms in amnesic mild cognitive impairmentHUMAN BRAIN MAPPING, Issue 5 2009Claudio Babiloni Abstract Does impairment of cholinergic systems represent an important factor in the development of amnesic mild cognitive impairment (aMCI), as a preclinical stage of Alzheimer's disease (AD)? Here we tested the hypothesis that electroencephalographic (EEG) rhythms, known to be modulated by the cholinergic system, may be particularly affected in aMCI patients with lesions along the cholinergic white-matter tracts. Eyes-closed resting EEG data were recorded in 28 healthy elderly (Nold) and 57 aMCI patients. Lesions along the cholinergic white-matter tracts were detected with fluid-attenuated inversion recovery sequences on magnetic resonance imaging. The estimation of the cholinergic lesion was performed with a validated semi-automatic algorithm pipeline after registration to a stereotactic template, image integration with stereotactic masks of the cholinergic tracts, and normalization to intracranial volume. The aMCI patients were divided into two groups of high (MCI Ch+; N = 29; MMSE = 26.2) and low cholinergic damage (MCI Ch,; N = 28; MMSE = 26.6). EEG rhythms of interest were delta (2,4 Hz), theta (4,8 Hz), alpha 1 (8,10.5 Hz), alpha 2 (10.5,13 Hz), beta 1 (13,20 Hz), and beta 2 (20,30 Hz). Cortical EEG generators were estimated by LORETA software. As main results, (i) power of occipital, parietal, temporal, and limbic alpha 1 sources was maximum in Nold, intermediate in MCI Ch,, and low in MCI Ch+ patients; (ii) the same trend was true in theta sources. These results are consistent with the hypothesis that damage to the cholinergic system is associated with alterations of EEG sources in aMCI subjects. Hum Brain Mapp 2009. © 2008 Wiley-Liss, Inc. [source] EEG-fMRI of focal epileptic spikes: Analysis with multiple haemodynamic functions and comparison with gadolinium-enhanced MR angiogramsHUMAN BRAIN MAPPING, Issue 3 2004Andrew P. Bagshaw Abstract Combined EEG-fMRI has recently been used to explore the BOLD responses to interictal epileptiform discharges. This study examines whether misspecification of the form of the haemodynamic response function (HRF) results in significant fMRI responses being missed in the statistical analysis. EEG-fMRI data from 31 patients with focal epilepsy were analysed with four HRFs peaking from 3 to 9 sec after each interictal event, in addition to a standard HRF that peaked after 5.4 sec. In four patients, fMRI responses were correlated with gadolinium-enhanced MR angiograms and with EEG data from intracranial electrodes. In an attempt to understand the absence of BOLD responses in a significant group of patients, the degree of signal loss occurring as a result of magnetic field inhomogeneities was compared with the detected fMRI responses in ten patients with temporal lobe spikes. Using multiple HRFs resulted in an increased percentage of data sets with significant fMRI activations, from 45% when using the standard HRF alone, to 62.5%. The standard HRF was good at detecting positive BOLD responses, but less appropriate for negative BOLD responses, the majority of which were more accurately modelled by an HRF that peaked later than the standard. Co-registration of statistical maps with gadolinium-enhanced MRIs suggested that the detected fMRI responses were not in general related to large veins. Signal loss in the temporal lobes seemed to be an important factor in 7 of 12 patients who did not show fMRI activations with any of the HRFs. Hum. Brain Mapp. 22:179,192, 2004. © 2004 Wiley-Liss, Inc. [source] Recursive penalized least squares solution for dynamical inverse problems of EEG generationHUMAN BRAIN MAPPING, Issue 4 2004Okito Yamashita Abstract In the dynamical inverse problem of electroencephalogram (EEG) generation where a specific dynamics for the electrical current distribution is assumed, we can impose general spatiotemporal constraints onto the solution by casting the problem into a state space representation and assuming a specific class of parametric models for the dynamics. The Akaike Bayesian Information Criterion (ABIC), which is based on the Type II likelihood, was used to estimate the parameters and evaluate the model. In addition, dynamic low-resolution brain electromagnetic tomography (LORETA), a new approach for estimating the current distribution is introduced. A recursive penalized least squares (RPLS) step forms the main element of our implementation. To obtain improved inverse solutions, dynamic LORETA exploits both spatial and temporal information, whereas LORETA uses only spatial information. A considerable improvement in performance compared to LORETA was found when dynamic LORETA was applied to simulated EEG data, and the new method was applied also to clinical EEG data. Hum. Brain Mapp. 21:221,235, 2004. © 2004 Wiley-Liss, Inc. [source] Improved GMM with parameter initialization for unsupervised adaptation of Brain,Computer interfaceINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 6 2010Guangquan Liu Abstract An important property of brain signals is their nonstationarity. How to adapt a brain,computer interface (BCI) to the changing brain states is one of the challenges faced by BCI researchers, especially in real application where the subject's real intent is unknown to the system. Gaussian mixture model (GMM) has been used for the unsupervised adaptation of the classifier in BCI. In this paper, a method of initializing the model parameters is proposed for expectation maximization-based GMM parameter estimation. This improved GMM method and other two existing unsupervised adaptation methods are applied to groups of constructed artificial data with different data properties. Performances of these methods in different situations are analyzed. Compared with the other two unsupervised adaptation methods, this method shows a better ability of adapting to changes and discovering class information from unlabelled data. The methods are also applied to real EEG data recorded in 19 experiments. For real data, the proposed method achieves an error rate significantly lower than the other two unsupervised methods. Results of the real data agree with the analysis based on the artificial data, which confirms not only the effectiveness of our method but also the validity of the constructed data. Copyright © 2009 John Wiley & Sons, Ltd. [source] Improved artifact correction for combined electroencephalography/functional MRI by means of synchronization and use of vectorcardiogram recordingsJOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 3 2008Karen J. Mullinger BSc Abstract Purpose To demonstrate that two methodological developments (synchronization of the MR scanner and electroencephalography [EEG] clocks and use of the scanner's vectorcardiogram [VCG]) improve the quality of EEG data recorded in combined EEG/functional MRI experiments in vivo. Materials and Methods EEG data were recorded using a 32-channel system, during simultaneous multislice EPI acquisition carried out on a 3 Tesla scanner. Recordings were made on three subjects in the resting state and on five subjects using a block paradigm involving visual stimulation with a 10-Hz flashing checkerboard. Results Gradient artifacts were significantly reduced in the EEG data recorded in vivo when synchronization and a TR equal to a multiple of the EEG clock period were used. This was evident from the greater attenuation of the signal at multiples of the slice acquisition frequency. Pulse artifact correction based on R-peak markers derived from the VCG was shown to offer a robust alternative to the conventionally used ECG-based method. Driven EEG responses at frequencies of up to 60 Hz due to the visual stimulus could be more readily detected in data recorded with EEG and MR scanner clock synchronization. Conclusion Synchronization of the scanner and EEG clocks, along with VCG-based R-peak detection is advantageous in removing gradient and pulse artifacts in combined EEG/fMRI recordings. This approach is shown to allow the robust detection of high frequency driven activity in the EEG data. J. Magn. Reson. Imaging 2008;27:607,616. © 2008 Wiley-Liss, Inc. [source] Coupling of theta activity and glucose metabolism in the human rostral anterior cingulate cortex: An EEG/PET study of normal and depressed subjectsPSYCHOPHYSIOLOGY, Issue 6 2003Diego A. Pizzagalli Abstract In rodents, theta rhythm has been linked to the hippocampal formation, as well as other regions, including the anterior cingulate cortex (ACC). To test the role of the ACC in theta rhythm, concurrent measurements of brain electrical activity (EEG) and glucose metabolism (PET) were performed in 29 subjects at baseline. EEG data were analyzed with a source localization technique that enabled voxelwise correlations of EEG and PET data. For theta, but not other bands, the rostral ACC (Brodmann areas 24/32) was the largest cluster with positive correlations between current density and glucose metabolism. Positive correlations were also found in right fronto-temporal regions. In control but not depressed subjects, theta within ACC and prefrontal/orbitofrontal regions was positively correlated. The results reveal a link between theta and cerebral metabolism in the ACC as well as disruption of functional connectivity within frontocingulate pathways in depression. [source] Effectiveness of the ketogenic diet in a broad range of seizure types and EEG features for severe childhood epilepsiesACTA NEUROLOGICA SCANDINAVICA, Issue 1 2010S. Beniczky Background,,, Ketogenic diet (KD) is an effective treatment for pharmacoresistant epilepsy: more than half of the patients show a greater than 50% reduction in seizures. Objective,,, To identify clinical or electroencephalogram (EEG) variables predicting the response to KD. Methods,,, Clinical and EEG data were retrospectively analysed from 50 consecutive patients treated by KD for severe, pharmacoresistant epilepsy. Most of the patients (70%) had retarded mental and motor development. Results,,, Three months after the start of the KD two-thirds (33) of the patients were responders (had a more than 50% reduction in seizure frequency). The presence of epileptiform EEG discharges in the temporal region correlated with an unfavourable response (P = 0.03). The presence of bilateral synchronous epileptiform discharges, and the presence of complex partial seizures approached significance but all other variables did not. Conclusions,,, Our results further support that KD is efficient in a wide variety of epileptic patients with a broad range of EEG features. However, patients with epileptiform discharges in the temporal region are less likely to achieve therapeutic response. [source] Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG dataACTA NEUROPSYCHIATRICA, Issue 3 2010Vince D. Calhoun Calhoun VD, Wu L, Kiehl KA, Eichele T, Pearlson GD. Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG data. Background: Aberrant electrophysiological and haemodynamic processing of auditory oddball stimuli is among the most robustly documented findings in patients with schizophrenia. However, no study to date has directly examined linked patterns of electrical and haemodynamic differences in patients and controls. Methods: In a recent paper we demonstrated a data-driven approach, joint independent component analysis (jICA) to fuse together functional magnetic resonance imaging (fMRI) and event-related potential (ERP) data and elucidated the chronometry of auditory oddball target detection in healthy control subjects. In this paper we extend our fusion method to identify specific differences in the neuronal chronometry of target detection for chronic schizophrenia patients compared to healthy controls. Results: We found one linked source, consistent with the N2 response, known to be related to cognitive processing of deviant stimuli, spatially localized to bilateral fronto-temporal regions. This source showed significant between-group differences both in amplitude response and in the fMRI/ERP distribution pattern. These findings are consistent with previous work showing N2 amplitude and latency abnormalities in schizophrenia, and provide new information about the linkage between the two. Conclusions: In summary, we use a novel approach to isolate and identify a linked fMRI/ERP component which shows marked differences in chronic schizophrenia patients. We also show that jointly using both fMRI and ERP measures provides a fully picture of the underlying haemodynamic and electrical changes which are present in patients. Our approach also has broad applicability to other diseases such as autism, Alzheimer's disease, or bipolar disorder. [source] A review of EEG and ERP studies in bipolar disorderACTA NEUROPSYCHIATRICA, Issue 2 2009Racheal Degabriele Objective:, The electroencephalogram (EEG) can be a useful tool in determining differences in general neural activity and specific waveforms in individuals with a number of psychiatric disorders. This paper aims to outline and discuss significant findings in EEG and event-related potential (ERP) research into bipolar disorder (BD). Methods:, A literature review was performed through searches of MedLine, EMBASE, CINAHL and PsycInfo medical research databases for papers published from 1985 onwards. References of selected articles were also examined for other relevant studies. Results:, Differences in general EEG data were found in subjects with BD, namely increased theta and delta and decreased alpha wave bands. Changes in EEG were also found in euthymic BD subjects and those undergoing medication programmes. ERP studies commonly report prolonged latencies and reduced amplitudes in the P300 component. Hyperfunctioning of the right hemisphere in BD was also reported in some studies, although further confirmation of this finding is required. Finally, the effects of medication and the role that genetics plays in EEG still remain unclear. Conclusions:, The literature reviewed demonstrates supporting evidence for the presence of significant differences in EEG and ERP data in subjects with BD. However, methodological considerations such as varying mood states and medication status of the patients need to be followed more stringently for future research to bring about a robust model of the cognitive deficits of BD. [source] The prognostic value of early aEEG in asphyxiated infants undergoing systemic hypothermia treatmentACTA PAEDIATRICA, Issue 4 2010B Hallberg Abstract Background:, Induced moderate hypothermia (HT) for 72 h has been shown to reduce the combined outcome of death or severe neurodevelopmental disabilities in asphyxiated full-term infants. A pathological amplitude integrated EEG background as early as 3,6 h after birth, has been shown to correlate to poor prognosis. Aim:, The aim of this study was to investigate the correlation between amplitude integrated EEG during HT treatment and short-term outcome in asphyxiated full-term infants with moderate/severe hypoxic-ischaemic encephalopathy. Methods:, Between December 2006 and December 2007, 24 infants were treated with moderate HT (33.5°C for 72 h) using a cooling mattress. Motor functions were assessed at 4 and 12 months of age. Results:, Of the total birth cohort of 28,837 infants, 26 infants fulfilled the criteria for HT treatment (0.9/1000) of whom 23 was treated with HT and all of these infants had available amplitude integrated EEG data. Normal 1-year outcome was found in 10/15 infants with severely abnormal burst-suppression pattern or worse at 6 h of age. Severe abnormalities were found to be significantly predictive for abnormal outcome after 36 h. Conclusion:, Among asphyxiated infants treated with HT, only those who had aEEG abnormalities persisting at and beyond 24 h after birth showed poor neurological outcome at 1 year. [source] Disruptions in Sleep Time and Sleep Architecture in a Mouse Model of Repeated Ethanol WithdrawalALCOHOLISM, Issue 7 2006Lynn M. Veatch Background: Insomnia and other sleep difficulties are perhaps the most common and enduring symptoms reported by alcoholics undergoing detoxification, especially those alcoholics with a history of multiple detoxifications. While some studies have reported sleep disruptions in animal models after chronic ethanol exposure, the reports are inconsistent and few address sleep architecture across repeated ethanol exposures and withdrawals. The present study evaluated sleep time and architecture in a well-characterized mouse model of repeated chronic ethanol exposure and withdrawal. Methods: C57BL6/J mice were fitted with electrodes in frontal cortex, hippocampus, and nuchal muscle for collection of continuous electroencephalogram (EEG)/electromyogram (EMG) data. Baseline data were collected, after which mice received 4 cycles of 16-hour exposure to alcohol (ethanol: EtOH) vapor separated by 8-hour periods of withdrawal or similar handling in the absence of EtOH vapor. Ethanol-exposed mice attained a blood ethanol concentration of 165 mg%. Upon completion of vapor exposure, EEG/EMG data were again collected across 4 days of acute withdrawal. Data were subjected to automated analyses classifying 10-second epochs into wake, non,rapid eye movement (REM) sleep, or REM sleep states. Results: Mice in withdrawal after chronic EtOH exposure showed profound disruptions in the total time asleep, across the acute withdrawal period. Sleep architecture, the composition of sleep, was also disrupted with a reduction in non-REM sleep concomitant with a profound increase in REM sleep. While altered sleep time and non-REM sleep loss resolved by the fourth day of withdrawal, the increase in REM sleep ("REM rebound") persisted. Conclusions: These results mirror those reported for the human alcoholic and demonstrate that EtOH withdrawal,induced sleep disruptions are evident in this mouse model of alcohol withdrawal,induced sensitization. This mouse model may provide mechanisms to investigate fully the high correlation between unremitting sleep problems and increased risk of relapse documented clinically. [source] | ||||||||||||||||||||||||||||