973 resultados para auditory EEG


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BACKGROUND: Analyses of brain responses to external stimuli are typically based on the means computed across conditions. However in many cognitive and clinical applications, taking into account their variability across trials has turned out to be statistically more sensitive than comparing their means. NEW METHOD: In this study we present a novel implementation of a single-trial topographic analysis (STTA) for discriminating auditory evoked potentials at predefined time-windows. This analysis has been previously introduced for extracting spatio-temporal features at the level of the whole neural response. Adapting the STTA on specific time windows is an essential step for comparing its performance to other time-window based algorithms. RESULTS: We analyzed responses to standard vs. deviant sounds and showed that the new implementation of the STTA gives above-chance decoding results in all subjects (in comparison to 7 out of 11 with the original method). In comatose patients, the improvement of the decoding performance was even more pronounced than in healthy controls and doubled the number of significant results. COMPARISON WITH EXISTING METHOD(S): We compared the results obtained with the new STTA to those based on a logistic regression in healthy controls and patients. We showed that the first of these two comparisons provided a better performance of the logistic regression; however only the new STTA provided significant results in comatose patients at group level. CONCLUSIONS: Our results provide quantitative evidence that a systematic investigation of the accuracy of established methods in normal and clinical population is an essential step for optimizing decoding performance.

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Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

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While humans can easily segregate and track a speaker's voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence.

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The mismatch negativity is an electrophysiological marker of auditory change detection in the event-related brain potential and has been proposed to reflect an automatic comparison process between an incoming stimulus and the representation of prior items in a sequence. There is evidence for two main functional subcomponents comprising the MMN, generated by temporal and frontal brain areas, respectively. Using data obtained in an MMN paradigm, we performed time-frequency analysis to reveal the changes in oscillatory neural activity in the theta band. The results suggest that the frontal component of the MMN is brought about by an increase in theta power for the deviant trials and, possibly, by an additional contribution of theta phase alignment. By contrast, the temporal component of the MMN, best seen in recordings from mastoid electrodes, is generated by phase resetting of theta rhythm with no concomitant power modulation. Thus, frontal and temporal MMN components do not only differ with regard to their functional significance but also appear to be generated by distinct neurophysiological mechanisms.

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The oscillation of neuronal circuits reflected in the EEG gamma frequency may be fundamental to the perceptual process referred to as binding (the integration of various thoughts and perceptions into a coherent picture). The aim of our study was to expand our knowledge of the developmental course ofEEG gamma in the auditory modality. 2 We investigated EEG 40 Hz gamma band responses (35.2 to 43.0 Hz) using an auditory novelty oddball paradigm alone and with a visual-number-series distracter task in 208 participants as a function of age (7 years to adult) at 9 sites across the sagital and lateral axes (F3, Fz, F4, C3, Cz, C4, P3, Pz, P4). Gamma responses were operationally defined as change in power or a change in phase synchrony level from baseline within two time windows. The evoked gamma response was defined as a significant change from baseline occurring between 0 to 150 ms after stimulus onset; the induced gamma response was measured from 250 to 750 ms after stimulus onset. A significant evoked gamma band response was found when measuring changes in both power and phase synchrony. The increase in both measures was maximal at frontal regions. Decreases in both measures were found when participants were distracted by a secondary task. For neither measure were developmental effects noted. However, evoked gamma power was significantly enhanced with the presentation of a novel stimulus, especially at the right frontal site (F4); frontal evoked gamma phase synchrony also showed enhancement for novel stimuli but only for our two oldest age groups (16-18 year olds and adults). Induced gamma band responses also varied with task-dependent cognitive stimulus properties. In the induced gamma power response in all age groups, target stimuli generated the highest power values at the parietal region, while the novel stimuli were always below baseline. Target stimuli increased induced synchrony in all regions for all participants, but the novel stimulus selectively affected participants dependent on their age and gender. Adult participants, for example, exhibited a reduction in gamma power, but an increase in synchrony to the novel stimulus within the same region. Induced gamma synchrony was more sensitive to the gender of the participant than was induced gamma power. While induced gamma power produced little effects of age, gamma synchrony did have age effects. These results confirm that the perceptual process which regulates gamma power is distinct from that which governs the synchronization for neuronal firing, and both gamma power and synchrony are important factors to be considered for the "binding" hypothesis. However, there is surprisingly little effect of age on the absolute levels of or distribution of EEG gamma in the age range investigated.

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Abnormal perceptions and cognitions in schizophrenia might be related to abnormal resting states of the brain. Previous research found that a specific class (class D) of sub-second electroencephalography (EEG) microstates was shortened in schizophrenia. This shortening correlated with positive symptoms. We questioned if this reflected positive psychotic traits or present psychopathology.

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Auditory verbal hallucinations (AVH) in schizophrenia patients assumingly result from a state inadequate activation of the primary auditory system. We tested brain responsiveness to auditory stimulation in healthy controls (n=26), and in schizophrenia patients that frequently (n=18) or never (n=11) experienced AVH. Responsiveness was assessed by driving the EEG with click-tones at 20, 30 and 40Hz. We compared stimulus induced EEG changes between groups using spectral amplitude maps and a global measure of phase-locking (GFS). As expected, the 40Hz stimulation elicited the strongest changes. However, while controls and non-hallucinators increased 40Hz EEG activity during stimulation, a left-lateralized decrease was observed in the hallucinators. These differences were significant (p=.02). As expected, GFS increased during stimulation in controls (p=.08) and non-hallucinating patients (p=.06), which was significant when combining the two groups (p=.01). In contrast, GFS decreased with stimulation in hallucinating patients (p=0.13), resulting in a significantly different GFS response when comparing subjects with and without AVH (p<.01). Our data suggests that normally, 40Hz stimulation leads to the activation of a synchronized network representing the sensory input, but in hallucinating patients, the same stimulation partly disrupts ongoing activity in this network.

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Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.

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Aim  We report three cases of Landau-Kleffner syndrome (LKS) in children (two females, one male) in whom diagnosis was delayed because the sleep electroencephalography (EEG) was initially normal. Method  Case histories including EEG, positron emission tomography findings, and long-term outcome were reviewed. Results  Auditory agnosia occurred between the age of 2 years and 3 years 6 months, after a period of normal language development. Initial awake and sleep EEG, recorded weeks to months after the onset of language regression, during a nap period in two cases and during a full night of sleep in the third case, was normal. Repeat EEG between 2 months and 2 years later showed epileptiform discharges during wakefulness and strongly activated by sleep, with a pattern of continuous spike-waves during slow-wave sleep in two patients. Patients were diagnosed with LKS and treated with various antiepileptic regimens, including corticosteroids. One patient in whom EEG became normal on hydrocortisone is making significant recovery. The other two patients did not exhibit a sustained response to treatment and remained severely impaired. Interpretation  Sleep EEG may be normal in the early phase of acquired auditory agnosia. EEG should be repeated frequently in individuals in whom a firm clinical diagnosis is made to facilitate early treatment.

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Background: Glutathione (GSH) dysregulation at the gene, protein and functional levels observed in schizophrenia patients, and schizophrenia-like anomalies in GSH deficit experimental models, suggest that genetic glutathione synthesis impairments represent one major risk factor for the disease (Do et al., 2009). In a randomized, double blind, placebo controlled, add-on clinical trial of 140 patients, the GSH precursor N-Acetyl-Cysteine (NAC, 2g/day, 6 months) significantly improved the negative symptoms and reduced sideeffects due to antipsychotics (Berk et al., 2008). In a subset of patients (n=7), NAC (2g/day, 2 months, cross-over design) also improved auditory evoked potentials, the NMDA-dependent mismatch negativity (Lavoie et al, 2008). Methods: To determine whether increased GSH levels would modulate the topography of functional brain connectivity, we applied a multivariate phase synchronization (MPS) estimator (Knyazeva et al, 2008) to dense-array EEGs recorded during rest with eyes closed at the protocol onset, the point of crossover, and at its end. Results: The whole-head imaging revealed a specific synchronization landscape in NAC compared to placebo condition. In particular, NAC increased MPS over frontal and left temporal regions in a frequency-specific manner. The topography and direction of MPS changes were similar and robust in all 7 patients. Moreover, these changes correlated with the changes in the Liddle's score of disorganization, thus linking EEG synchronization to the improvement of the clinical picture. Conclusions: The data suggest an important pathway towards new therapeutic strategies that target GSH dysregulation in schizophrenia. They also show the utility of MPS mapping as a marker of treatment efficacy.

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PURPOSE: EEG and somatosensory evoked potential are highly predictive of poor outcome after cardiac arrest; their accuracy for good recovery is however low. We evaluated whether addition of an automated mismatch negativity-based auditory discrimination paradigm (ADP) to EEG and somatosensory evoked potential improves prediction of awakening. METHODS: EEG and ADP were prospectively recorded in 30 adults during therapeutic hypothermia and in normothermia. We studied the progression of auditory discrimination on single-trial multivariate analyses from therapeutic hypothermia to normothermia, and its correlation to outcome at 3 months, assessed with cerebral performance categories. RESULTS: At 3 months, 18 of 30 patients (60%) survived; 5 had severe neurologic impairment (cerebral performance categories = 3) and 13 had good recovery (cerebral performance categories = 1-2). All 10 subjects showing improvements of auditory discrimination from therapeutic hypothermia to normothermia regained consciousness: ADP was 100% predictive for awakening. The addition of ADP significantly improved mortality prediction (area under the curve, 0.77 for standard model including clinical examination, EEG, somatosensory evoked potential, versus 0.86 after adding ADP, P = 0.02). CONCLUSIONS: This automated ADP significantly improves early coma prognostic accuracy after cardiac arrest and therapeutic hypothermia. The progression of auditory discrimination is strongly predictive of favorable recovery and appears complementary to existing prognosticators of poor outcome. Before routine implementation, validation on larger cohorts is warranted.

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We present a novel approach for analyzing single-trial electroencephalography (EEG) data, using topographic information. The method allows for visualizing event-related potentials using all the electrodes of recordings overcoming the problem of previous approaches that required electrode selection and waveforms filtering. We apply this method to EEG data from an auditory object recognition experiment that we have previously analyzed at an ERP level. Temporally structured periods were statistically identified wherein a given topography predominated without any prior information about the temporal behavior. In addition to providing novel methods for EEG analysis, the data indicate that ERPs are reliably observable at a single-trial level when examined topographically.

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Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

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Complex auditory hallucinations are often characterized by hearing voices and are then called auditory verbal hallucinations (AVHs). While AVHs have been extensively investigated in psychiatric patients suffering from schizophrenia, reports from neurological patients are rare and, in most cases, incomplete. Here, we characterize AVHs in 9 patients suffering from pharmacoresistant epilepsy by analyzing the phenomenology of AVHs and patients' neuropsychological and lesion profiles. From a cohort of 352 consecutively examined patients with epilepsy, 9 patients suffering AVHs were identified and studied by means of a semistructured interview, neuropsychological tests, and multimodal imaging, relying on a combination of functional and structural neuroimaging data and surface and intracranial EEG. We found that AVHs in patients with epilepsy were associated with prevalent language deficits and damage to posterior language areas and basal language areas in the left temporal cortex. Auditory verbal hallucinations, most of the times, consisted in hearing a single voice of the same gender and language as the patient and had specific spatial features, being, most of the times, perceived in the external space, contralateral to the lesion. We argue that the consistent location of AVHs in the contralesional external space, the prominence of associated language deficits, and the prevalence of lesions to the posterior temporal language areas characterize AVHs of neurological origin, distinguishing them from those of psychiatric origin.

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Background: Glutathione (GSH) dysregulation at the gene, protein and functional levels observed in schizophrenia patients, and schizophrenia-like anomalies in GSH deficit experimental models, suggest that genetic glutathione synthesis impairments represent one major risk factor for the disease (Do et al., 2009). In a randomized, double blind, placebo controlled, add-on clinical trial of 140 patients, the GSH precursor N-Acetyl-Cysteine (NAC, 2 g/day, 6 months) significantly improved the negative symptoms and reduced side-effects due to antipsychotics (Berk et al., 2008). In a subset of patients (n=7), NAC (2 g/day, 2 months, cross-over design) also improved auditory evoked potentials, the NMDAdependent mismatch negativity (Lavoie et al, 2008). Methods: To determine whether increased GSH levels would modulate the topography of functional brain connectivity, we applied a multivariate phase synchronization (MPS) estimator (Knyazeva et al, 2008) to dense-array EEGs recorded during rest with eyes closed at the protocol onset, the point of crossover, and at its end. Phase synchronization phenomena are appealing because they can be associated to synchronized phases while the amplitudes stay uncorrelated. MPS measures the degree of interactions among the recorded neuronal oscillators by quantifiying to what extent they behave like a macro-oscillator (i.e. the oscillators are phase synchronous). To assess the whole-head synchronization topography, we computed the MPS sensor-wise over the cluster of locations defined by the sensor itself and he surrounding ones belonging to its second-order neighborhood (Carmeli et al, 2005). Such a cluster spans about 12 cm on average. Abstracts 245 Results: The whole-head imaging revealed a specific synchronization landscape in NAC compared to placebo condition. In particular, NAC increased MPS over frontal and left temporal regions in a frequency-specific manner. Importantly, the topography and direction of MPS changes were similar and robust in all 7 patients. Moreover, these changes correlated with the changes in the Liddle's score of disorganization (Liddle, 1987) thus linking EEG synchronization to the improvement of clinical picture. Discussion: The data suggest an important pathway towards new therapeutic strategies that target GSH dysregulation in schizophrenia. They also show the utility of MPS mapping as a marker of treatment efficacy.