973 resultados para auditory EEG
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BACKGROUND: Sedation protocols, including the use of sedation scales and regular sedation stops, help to reduce the length of mechanical ventilation and intensive care unit stay. Because clinical assessment of depth of sedation is labor-intensive, performed only intermittently, and interferes with sedation and sleep, processed electrophysiological signals from the brain have gained interest as surrogates. We hypothesized that auditory event-related potentials (ERPs), Bispectral Index (BIS), and Entropy can discriminate among clinically relevant sedation levels. METHODS: We studied 10 patients after elective thoracic or abdominal surgery with general anesthesia. Electroencephalogram, BIS, state entropy (SE), response entropy (RE), and ERPs were recorded immediately after surgery in the intensive care unit at Richmond Agitation-Sedation Scale (RASS) scores of -5 (very deep sedation), -4 (deep sedation), -3 to -1 (moderate sedation), and 0 (awake) during decreasing target-controlled sedation with propofol and remifentanil. Reference measurements for baseline levels were performed before or several days after the operation. RESULTS: At baseline, RASS -5, RASS -4, RASS -3 to -1, and RASS 0, BIS was 94 [4] (median, IQR), 47 [15], 68 [9], 75 [10], and 88 [6]; SE was 87 [3], 46 [10], 60 [22], 74 [21], and 87 [5]; and RE was 97 [4], 48 [9], 71 [25], 81 [18], and 96 [3], respectively (all P < 0.05, Friedman Test). Both BIS and Entropy had high variabilities. When ERP N100 amplitudes were considered alone, ERPs did not differ significantly among sedation levels. Nevertheless, discriminant ERP analysis including two parameters of principal component analysis revealed a prediction probability PK value of 0.89 for differentiating deep sedation, moderate sedation, and awake state. The corresponding PK for RE, SE, and BIS was 0.88, 0.89, and 0.85, respectively. CONCLUSIONS: Neither ERPs nor BIS or Entropy can replace clinical sedation assessment with standard scoring systems. Discrimination among very deep, deep to moderate, and no sedation after general anesthesia can be provided by ERPs and processed electroencephalograms, with similar P(K)s. The high inter- and intraindividual variability of Entropy and BIS precludes defining a target range of values to predict the sedation level in critically ill patients using these parameters. The variability of ERPs is unknown.
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Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.
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Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.
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In this article, it is shown that IWD incorporates topological perceptual characteristics of both spoken and written language, and it is argued that these characteristics should not be ignored or given up when synchronous textual CMC is technologically developed and upgraded.
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The integration of the auditory modality in virtual reality environments is known to promote the sensations of immersion and presence. However it is also known from psychophysics studies that auditory-visual interaction obey to complex rules and that multisensory conflicts may disrupt the adhesion of the participant to the presented virtual scene. It is thus important to measure the accuracy of the auditory spatial cues reproduced by the auditory display and their consistency with the spatial visual cues. This study evaluates auditory localization performances under various unimodal and auditory-visual bimodal conditions in a virtual reality (VR) setup using a stereoscopic display and binaural reproduction over headphones in static conditions. The auditory localization performances observed in the present study are in line with those reported in real conditions, suggesting that VR gives rise to consistent auditory and visual spatial cues. These results validate the use of VR for future psychophysics experiments with auditory and visual stimuli. They also emphasize the importance of a spatially accurate auditory and visual rendering for VR setups.
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This article describes a series of experiments which were carried out to measure the sense of presence in auditory virtual environments. Within the study a comparison of self-created signals to signals created by the surrounding environment is drawn. Furthermore, it is investigated if the room characteristics of the simulated environment have consequences on the perception of presence during vocalization or when listening to speech. Finally the experiments give information about the influence of background signals on the sense of presence. In the experiments subjects rated the degree of perceived presence in an auditory virtual environment on a perceptual scale. It is described which parameters have the most influence on the perception of presence and which ones are of minor influence. The results show that on the one hand an external speaker has more influence on the sense of presence than an adequate presentation of one’s own voice. On the other hand both room reflections and adequately presented background signals significantly increase the perceived presence in the virtual environment.
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The characteristics of moving sound sources have strong implications on the listener's distance perception and the estimation of velocity. Modifications of the typical sound emissions as they are currently occurring due to the tendency towards electromobility have an impact on the pedestrian's safety in road traffic. Thus, investigations of the relevant cues for velocity and distance perception of moving sound sources are not only of interest for the psychoacoustic community, but also for several applications, like e.g. virtual reality, noise pollution and safety aspects of road traffic. This article describes a series of psychoacoustic experiments in this field. Dichotic and diotic stimuli of a set of real-life recordings taken from a passing passenger car and a motorcycle were presented to test subjects who in turn were asked to determine the velocity of the object and its minimal distance from the listener. The results of these psychoacoustic experiments show that the estimated velocity is strongly linked to the object's distance. Furthermore, it could be shown that binaural cues contribute significantly to the perception of velocity. In a further experiment, it was shown that - independently of the type of the vehicle - the main parameter for distance determination is the maximum sound pressure level at the listener's position. The article suggests a system architecture for the adequate consideration of moving sound sources in virtual auditory environments. Virtual environments can thus be used to investigate the influence of new vehicle powertrain concepts and the related sound emissions of these vehicles on the pedestrians' ability to estimate the distance and velocity of moving objects.
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INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN). METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.
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BACKGROUND: The origin of auditory hallucinations, which are one of the core symptoms of schizophrenia, is still a matter of debate. It has been hypothesized that alterations in connectivity between frontal and parietotemporal speech-related areas might contribute to the pathogenesis of auditory hallucinations. These networks are assumed to become dysfunctional during the generation and monitoring of inner speech. Magnetic resonance diffusion tensor imaging is a relatively new in vivo method to investigate the directionality of cortical white matter tracts. OBJECTIVE: To investigate, using diffusion tensor imaging, whether previously described abnormal activation patterns observed during auditory hallucinations relate to changes in structural interconnections between the frontal and parietotemporal speech-related areas. METHODS: A 1.5 T magnetic resonance scanner was used to acquire twelve 5-mm slices covering the Sylvian fissure. Fractional anisotropy was assessed in 13 patients prone to auditory hallucinations, in 13 patients without auditory hallucinations, and in 13 healthy control subjects. Structural magnetic resonance imaging was conducted in the same session. Based on an analysis of variance, areas with significantly different fractional anisotropy values between groups were selected for a confirmatory region of interest analysis. Additionally, descriptive voxel-based t tests between the groups were computed. RESULTS: In patients with hallucinations, we found significantly higher white matter directionality in the lateral parts of the temporoparietal section of the arcuate fasciculus and in parts of the anterior corpus callosum compared with control subjects and patients without hallucinations. Comparing patients with hallucinations with patients without hallucinations, we found significant differences most pronounced in the left hemispheric fiber tracts, including the cingulate bundle. CONCLUSION: Our findings suggest that during inner speech, the alterations of white matter fiber tracts in patients with frequent hallucinations lead to abnormal coactivation in regions related to the acoustical processing of external stimuli. This abnormal activation may account for the patients' inability to distinguish self-generated thoughts from external stimulation.