900 resultados para Electroencephalography (eeg)


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OBJECTIVE To investigate pathological findings in the susceptibility weighted imaging (SWI) of patients experiencing convulsive (CSE) or non-convulsive status epilepticus (NCSE) with focal hyperperfusion in the acute setting. METHODS Twelve patients (six with NCSE confirmed by electroencephalogram (EEG) and six patients with CSE with seizure event clinically diagnosed) underwent MRI in this acute setting (mean time between onset of symptoms and MRI was 3 h 8 min), including SWI, dynamic susceptibility contrast MR imaging (DSC) and diffusion-weighted imaging (DWI). MRI sequences were retrospectively evaluated and compared with EEG findings (10/12 patients), and clinical symptoms. RESULTS Twelve out of 12 (100 %) patients showed a focal parenchymal area with pseudo-narrowed cortical veins on SWI, associated with focal hyperperfused areas (increased cerebral blood flow (CBF) and mean transit time (MTT) shortening), and cortical DWI restriction in 6/12 patients (50 %). Additionally, these areas were associated with ictal or postical EEG patterns in 8/10 patients (80 %). Most frequent acute clinical findings were aphasia and/or hemiparesis in eight patients, and all of them showed pseudo-narrowed veins in those parenchymal areas responsible for these symptoms. CONCLUSION In this study series with CSE and NCSE patients, SWI showed focally pseudo-narrowed cortical veins in hyperperfused and ictal parenchymal areas. Therefore, SWI might have the potential to identify an ictal region in CSE/NCSE. KEY POINTS • The focal ictal brain regions show hyperperfusion in DSC MR-perfusion imaging. • SWI shows focally diminished cortical veins in hyperperfused ictal regions. • SWI has the potential to identify a focal ictal region in CSE/NCSE.

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INTRODUCTION The orthographic depth hypothesis (Katz and Feldman, 1983) posits that different reading routes are engaged depending on the type of grapheme/phoneme correspondence of the language being read. Shallow orthographies with consistent grapheme/phoneme correspondences favor encoding via non-lexical pathways, where each grapheme is sequentially mapped to its corresponding phoneme. In contrast, deep orthographies with inconsistent grapheme/phoneme correspondences favor lexical pathways, where phonemes are retrieved from specialized memory structures. This hypothesis, however, lacks compelling empirical support. The aim of the present study was to investigate the impact of orthographic depth on reading route selection using a within-subject design. METHOD We presented the same pseudowords (PWs) to highly proficient bilinguals and manipulated the orthographic depth of PW reading by embedding them among two separated German or French language contexts, implicating respectively, shallow or deep orthography. High density electroencephalography was recorded during the task. RESULTS The topography of the ERPs to identical PWs differed 300-360 ms post-stimulus onset when the PWs were read in different orthographic depth context, indicating distinct brain networks engaged in reading during this time window. The brain sources underlying these topographic effects were located within left inferior frontal (German > French), parietal (French > German) and cingular areas (German > French). CONCLUSION Reading in a shallow context favors non-lexical pathways, reflected in a stronger engagement of frontal phonological areas in the shallow versus the deep orthographic context. In contrast, reading PW in a deep orthographic context recruits less routine non-lexical pathways, reflected in a stronger engagement of visuo-attentional parietal areas in the deep versus shallow orthographic context. These collective results support a modulation of reading route by orthographic depth.

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Humans engage in deceptive behavior that negatively affects others. The propensity to deceive is,however, characterized by vast inter-individual heterogeneity that is poorly understood. Attempts to investigate the origins of this heterogeneity have so far mainly relied on subjective measures and have shown little predictive power. Here, we used resting electroencephalography to measure objective and stable individual differences in neural baseline activation in combination with an ecologically valid deception paradigm. Results showed that task-independent baseline activation in the anterior insula, a brain area implicated in mapping internal bodily states and in representing emotional arousal and consciousfeelings, predicts individuals’ propensity for deceptive behavior. The higher the neural baseline activation in this area is, the lower individuals’ propensity to deceive. Moreover, results provide evidence that high baseline activation in the anterior insula is associated with negative affect and dispositional tendencies to avoid aversive emotional situations. These results provide converging neural and psychological evidence that individuals might avoid a deceptive act due to a highly active negative emotional system which would make a deceptive act too stressful and bothersome.

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Most previous neurophysiological studies evoked emotions by presenting visual stimuli. Models of the emotion circuits in the brain have for the most part ignored emotions arising from musical stimuli. To our knowledge, this is the first emotion brain study which examined the influence of visual and musical stimuli on brain processing. Highly arousing pictures of the International Affective Picture System and classical musical excerpts were chosen to evoke the three basic emotions of happiness, sadness and fear. The emotional stimuli modalities were presented for 70 s either alone or combined (congruent) in a counterbalanced and random order. Electroencephalogram (EEG) Alpha-Power-Density, which is inversely related to neural electrical activity, in 30 scalp electrodes from 24 right-handed healthy female subjects, was recorded. In addition, heart rate (HR), skin conductance responses (SCR), respiration, temperature and psychometrical ratings were collected. Results showed that the experienced quality of the presented emotions was most accurate in the combined conditions, intermediate in the picture conditions and lowest in the sound conditions. Furthermore, both the psychometrical ratings and the physiological involvement measurements (SCR, HR, Respiration) were significantly increased in the combined and sound conditions compared to the picture conditions. Finally, repeated measures ANOVA revealed the largest Alpha-Power-Density for the sound conditions, intermediate for the picture conditions, and lowest for the combined conditions, indicating the strongest activation in the combined conditions in a distributed emotion and arousal network comprising frontal, temporal, parietal and occipital neural structures. Summing up, these findings demonstrate that music can markedly enhance the emotional experience evoked by affective pictures.

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Human readiness to incur personal costs to punish norm violators is a key force in the maintenance of social norms. The willingness to punish is, however, characterized by vast individual heterogeneity that is poorly understood. In fact, this heterogeneity has so far defied explanations in terms of individual-level demographic or psychological variables. Here, we use resting electroencephalography, a stable measure of individual differences in cortical activity, to show that a highly specific neural marker--baseline cortical activity in the right prefrontal cortex--predicts individuals' punishment behavior. The analysis of task-independent individual variation in cortical baseline activity provides a new window into the neurobiology of decision making by bringing dispositional neural markers to the forefront of the analysis.

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Recent research demonstrates that response inhibition-a core executive function-may subserve self-regulation and self-control. However, it is unclear whether response inhibition also predicts self-control in the multifaceted, high-level phenomena of social decision-making. Here we examined whether electrophysiological indices of response inhibition would predict self-control in a social context. Electroencephalography was recorded as participants completed a widely used Go/NoGo task (the cued Continuous Performance Test). Participants then interacted with a partner in an economic exchange game that requires self-control. Results demonstrated that greater NoGo-Anteriorization and larger NoGo-P300 peak amplitudes-two established electrophysiological indices of response inhibition-both predicted more self-control in this social game. These findings support continued integration of executive function and self-regulation and help extend prior research into social decision-making processes.

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The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

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Prevention of psychoses has been intensively investigated within the past two decades, and particularly, prediction has been much advanced. Depending on the applied risk indicators, current criteria are associated with average, yet significantly heterogeneous transition rates of ≥30 % within 3 years, further increasing with longer follow-up periods. Risk stratification offers a promising approach to advance current prediction as it can help to reduce heterogeneity of transition rates and to identify subgroups with specific needs and response patterns, enabling a targeted intervention. It may also be suitable to improve risk enrichment. Current results suggest the future implementation of multi-step risk algorithms combining sensitive risk detection by cognitive basic symptoms (COGDIS) and ultra-high-risk (UHR) criteria with additional individual risk estimation by a prognostic index that relies on further predictors such as additional clinical indicators, functional impairment, neurocognitive deficits, and EEG and structural MRI abnormalities, but also considers resilience factors. Simply combining COGDIS and UHR criteria in a second step of risk stratification produced already a 4-year hazard rate of 0.66. With regard to prevention, two recent meta-analyses demonstrated that preventive measures enable a reduction in 12-month transition rates by 54-56 % with most favorable numbers needed to treat of 9-10. Unfortunately, psychosocial functioning, another important target of preventive efforts, did not improve. However, these results are based on a relatively small number of trials; and more methodologically sound studies and a stronger consideration of individual profiles of clinical needs by modular intervention programs are required

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There have been numerous attempts to reveal the neurobiological basis of schizophrenia spectrum disorders. Results however, remain as heterogeneous as the schizophrenia spectrum disorders itself. Therefore, one aim of this thesis was to divide patients affected by this disorder into subgroups in order to homogenize the results of future studies. In a first study it is suggested that psychopathological rating scales should focus on symptoms-clusters that may have a common neurophysiological background. The here presented Bern Psychopathology Scale (BPS) proposes that alterations in three wellknown brain systems (motor, language, and affective) are largely leading to the communication failures observable on a behavioral level, but also - as repeatedly hypothesized - to dysconnectivity within and between brain systems in schizophrenia spectrum disorders. The external validity of the motor domain in the BPS was tested against the objective measure of 24 hours wrist actigraphy, in a second study. The subjective, the quantitative, as well as the global rating of the degree of motor disorders in this patient group showed significant correlations to the acquired motor activity. This result confirmed in a first step the practicability of the motor domain of the BPS, but needs further validation regarding pathological brain alterations. Finally, in a third study (independent from the two other studies), two cerebral Resting State Networks frequently altered in schizophrenia were investigated for the first time using simultaneous EEG/fMRI: The well-known default mode network and the left working memory network. Besides the changes in these fMRI-based networks, there are well-documented findings that patients exhibit alterations in EEG spectra compared to healthy controls. However, only through the multimodal approach it was possible to discover that patients with schizophrenia spectrum disorders have a slower driving frequency of the Resting State Networks compared to the matched healthy controls. Such a dysfunctional coupling between neuronal frequency and functional brain organization could explain in a uni- or multifactorial way (dysfunctional cross-frequency coupling, maturational effects, vigilance fluctuations, task-related suppression), how the typical psychotic symptoms might occur. To conclude, the major contributions presented in this thesis were on one hand the development of a psychopathology rating scale that is based on the assumption of dysfunctional brain networks, as well as the new evidence of a dysfunctional triggering frequency of Resting State Networks from the simultaneous EEG/fMRI study in patients affected by a schizophrenia spectrum disorder.

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With the progressing course of Alzheimer's disease (AD), deficits in declarative memory increasingly restrict the patients' daily activities. Besides the more apparent episodic (biographical) memory impairments, the semantic (factual) memory is also affected by this neurodegenerative disorder. The episodic pathology is well explored; instead the underlying neurophysiological mechanisms of the semantic deficits remain unclear. For a profound understanding of semantic memory processes in general and in AD patients, the present study compares AD patients with healthy controls and Semantic Dementia (SD) patients, a dementia subgroup that shows isolated semantic memory impairments. We investigate the semantic memory retrieval during the recording of an electroencephalogram, while subjects perform a semantic priming task. Precisely, the task demands lexical (word/nonword) decisions on sequentially presented word pairs, consisting of semantically related or unrelated prime-target combinations. Our analysis focuses on group-dependent differences in the amplitude and topography of the event related potentials (ERP) evoked by related vs. unrelated target words. AD patients are expected to differ from healthy controls in semantic retrieval functions. The semantic storage system itself, however, is thought to remain preserved in AD, while SD patients presumably suffer from the actual loss of semantic representations.

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Individuals differ widely in how steeply they discount future rewards. The sources of these stable individual differences in delay discounting (DD) are largely unknown. One candidate is the COMT Val158Met polymorphism, known to modulate prefrontal dopamine levels and affect DD. To identify possible neural mechanisms by which this polymorphism may contribute to stable individual DD differences, we measured 73 participants' neural baseline activation using resting electroencephalogram (EEG). Such neural baseline activation measures are highly heritable and stable over time, thus an ideal endophenotype candidate to explain how genes may influence behavior via individual differences in neural function. After EEG-recording, participants made a series of incentive-compatible intertemporal choices to determine the steepness of their DD. We found that COMT significantly affected DD and that this effect was mediated by baseline activation level in the left dorsal prefrontal cortex (DPFC): (i) COMT had a significant effect on DD such that the number of Val alleles was positively correlated with steeper DD (higher numbers of Val alleles means greater COMT activity and thus lower dopamine levels). (ii) A whole-brain search identified a cluster in left DPFC where baseline activation was correlated with DD; lower activation was associated with steeper DD. (iii) COMT had a significant effect on the baseline activation level in this left DPFC cluster such that a higher number of Val alleles was associated with lower baseline activation. (iv) The effect of COMT on DD was explained by the mediating effect of neural baseline activation in the left DPFC cluster. Our study thus establishes baseline activation level in left DPFC as salient neural signature in the form of an endophenotype that mediates the link between COMT and DD.

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Human risk taking is characterized by a large amount of individual heterogeneity. In this study, we applied resting-state electroencephalography, which captures stable individual differences in neural activity, before subjects performed a risk-taking task. Using a source-localization technique, we found that the baseline cortical activity in the right prefrontal cortex predicts individual risk-taking behavior. Individuals with higher baseline cortical activity in this brain area display more risk aversion than do other individuals. This finding demonstrates that neural characteristics that are stable over time can predict a highly complex behavior such as risk-taking behavior and furthermore suggests that hypoactivity in the right prefrontal cortex might serve as a dispositional indicator of lower regulatory abilities, which is expressed in greater risk-taking behavior.

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OBJECTIVE To compare EEG power spectra and LORETA-computed intracortical activity between Alzheimer's disease (AD) patients and healthy controls, and to correlate the results with cognitive performance in the AD group. METHODS Nineteen channel resting EEG was recorded in 21 mild to moderate AD patients and in 23 controls. Power spectra and intracortical LORETA tomography were computed in seven frequency bands and compared between groups. In the AD patients, the EEG results were correlated with cognitive performance (Mini Mental State Examination, MMSE). RESULTS AD patients showed increased power in EEG delta and theta frequency bands, and decreased power in alpha2, beta1, beta2 and beta3. LORETA specified that increases and decreases of power affected different cortical areas while largely sparing prefrontal cortex. Delta power correlated negatively and alpha1 power positively with the AD patients' MMSE scores; LORETA tomography localized these correlations in left temporo-parietal cortex. CONCLUSIONS The non-invasive EEG method of LORETA localized pathological cortical activity in our mild to moderate AD patients in agreement with the literature, and yielded striking correlations between EEG delta and alpha1 activity and MMSE scores in left temporo-parietal cortex. SIGNIFICANCE The present data support the hypothesis of an asymmetrical progression of the Alzheimer's disease.

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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.