57 resultados para Neuroimage


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The moral force of impartiality (i.e. the equal treatment of all human beings) is imperative for providing justice and fairness. Yet, in reality many people become partial during intergroup interactions; they demonstrate a preferential treatment of ingroup members and a discriminatory treatment of outgroup members. Some people, however, do not show this intergroup bias. The underlying sources of these inter-individual differences are poorly understood. Here we demonstrate that the larger the gray matter volume and thickness of the dorsomedial prefrontal cortex (DMPFC), the more individuals in the role of an uninvolved third-party impartially punish outgroup and ingroup perpetrators. Moreover, we show evidence for a possible mechanism that explains the impact of DMPFC's gray matter volume on impartiality, namely perspective-taking. Large gray matter volume of DMPFC seems to facilitate equal perspective-taking of all sides, which in turn leads to impartial behavior. This is the first evidence demonstrating that brain structure of the DMPFC constitutes an important source underlying an individual's propensity for impartiality.

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Strategies of cognitive control are helpful in reducing anxiety experienced during anticipation of unpleasant or potentially unpleasant events. We investigated the associated cerebral information processing underlying the use of a specific cognitive control strategy during the anticipation of affect-laden events. Using functional magnetic resonance imaging, we examined differential brain activity during anticipation of events of unknown and negative emotional valence in a group of eighteen healthy subjects that used a cognitive control strategy, similar to "reality checking" as used in psychotherapy, compared with a group of sixteen subjects that did not exert cognitive control. While expecting unpleasant stimuli, the "cognitive control" group showed higher activity in left medial and dorsolateral prefrontal cortex areas but reduced activity in the left extended amygdala, pulvinar/lateral geniculate nucleus and fusiform gyrus. Cognitive control during the "unknown" expectation was associated with reduced amygdalar activity as well and further with reduced insular and thalamic activity. The amygdala activations associated with cognitive control correlated negatively with the reappraisal scores of an emotion regulation questionnaire. The results indicate that cognitive control of particularly unpleasant emotions is associated with elevated prefrontal cortex activity that may serve to attenuate emotion processing in for instance amygdala, and, notably, in perception related brain areas.

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Since we do not know what future holds for us, we prepare for expected emotional events in order to deal with a pleasant or threatening environment. From an evolutionary perspective, it makes sense to be particularly prepared for the worst-case scenario. We were interested to evaluate whether this assumption is reflected in the central nervous information processing associated with expecting visual stimuli of unknown emotional valence. While being scanned with functional magnetic resonance imaging, healthy subjects were cued to expect and then perceive visual stimuli with a known emotional valence as pleasant, unpleasant, and neutral, as well as stimuli of unknown valence that could have been either pleasant or unpleasant. While anticipating pictures of unknown valence, the activity of emotion processing brain areas was similar to activity associated with expecting unpleasant pictures, but there were no areas in which the activity was similar to the activity when expecting pleasant pictures. The activity of the revealed regions, including bilateral insula, right inferior frontal gyrus, medial thalamus, and red nucleus, further correlated with the individual ratings of mood: the worse the mood, the higher the activity. These areas are supposedly involved in a network for internal adaptation and preparation processes in order to act according to potential or certain unpleasant events. Their activity appears to reflect a 'pessimistic' bias by anticipating the events of unknown valence to be unpleasant.

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The study assessed the brain electric mechanisms of light and deep hypnotic conditions in the framework of EEG temporal microstates. Multichannel EEG of healthy volunteers during initial resting, light hypnosis, deep hypnosis, and eventual recovery was analyzed into temporal EEG microstates of four classes. Microstates are defined by the spatial configuration of their potential distribution maps ([Symbol: see text]potential landscapes') on the head surface. Because different potential landscapes must have been generated by different active neural assemblies, it is reasonable to assume that they also incorporate different brain functions. The observed four microstate classes were very similar to the four standard microstate classes A, B, C, D [Koenig, T. et al. Neuroimage, 2002;16: 41-8] and were labeled correspondingly. We expected a progression of microstate characteristics from initial resting to light to deep hypnosis. But, all three microstate parameters (duration, occurrence/second and %time coverage) yielded values for initial resting and final recovery that were between those of the two hypnotic conditions of light and deep hypnosis. Microstates of the classes B and D showed decreased duration, occurrence/second and %time coverage in deep hypnosis compared to light hypnosis; this was contrary to microstates of classes A and C which showed increased values of all three parameters. Reviewing the available information about microstates in other conditions, the changes from resting to light hypnosis in certain respects are reminiscent of changes to meditation states, and changes to deep hypnosis of those in schizophrenic states.

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Low-frequency "off-line" repetitive transcranial magnetic stimulation (rTMS) over the course of several minutes has attained considerable attention as a research tool in cognitive neuroscience due to its ability to induce functional disruptions of brain areas. This disruptive rTMS effect is highly valuable for revealing a causal relationship between brain and behavior. However, its influence on remote interconnected areas and, more importantly, the duration of the induced neurophysiological effects, remain unknown. These aspects are critical for a study design in the context of cognitive neuroscience. In order to investigate these issues, 12 healthy male subjects underwent 8 H(2)(15)O positron emission tomography (PET) scans after application of long-train low-frequency rTMS to the right dorsolateral prefrontal cortex (DLPFC). Immediately after the stimulation train, regional cerebral blood flow (rCBF) increases were present under the stimulation site as well as in other prefrontal cortical areas, including the ventrolateral prefrontal cortex (VLPFC) ipsilateral to the stimulation site. The mean increases in rCBF returned to baseline within 9 min. The duration of this unilateral prefrontal rTMS effect on rCBF is of particular interest to those who aim to influence behavior in cognitive paradigms that use an "off-line" approach.

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Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

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Neural correlates have been described for emotions evoked by states of homeostatic imbalance (e.g. thirst, hunger, and breathlessness) and for emotions induced by external sensory stimulation (such as fear and disgust). However, the neurobiological mechanisms of their interaction, when they are experienced simultaneously, are still unknown. We investigated the interaction on the neurobiological and the perceptional level using subjective ratings, serum parameters, and functional magnetic resonance imaging (fMRI) in a situation of emotional rivalry, when both a homeostatic and a sensory-evoked emotion were experienced at the same time. Twenty highly dehydrated male subjects rated a disgusting odor as significantly less repulsive when they were thirsty. On the neurobiological level, we found that this reduction in subjective disgust during thirst was accompanied by a significantly reduced neural activity in the insular cortex, a brain area known to be considerably involved in processing of disgust. Furthermore, during the experience of disgust in the satiated condition, we observed a significant functional connectivity between brain areas responding to the disgusting odor, which was absent during the stimulation in the thirsty condition. These results suggest interference of conflicting emotions: An acute homeostatic imbalance can attenuate the experience of another emotion evoked by the sensory perception of a potentially harmful external agent. This finding offers novel insights with regard to the behavioral relevance of biologically different types of emotions, indicating that some types of emotions are more imperative for behavior than others. As a general principle, this modulatory effect during the conflict of homeostatic and sensory-evoked emotions may function to safeguard survival.

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The momentary, global functional state of the brain is reflected by its electric field configuration. Cluster analytical approaches consistently extracted four head-surface brain electric field configurations that optimally explain the variance of their changes across time in spontaneous EEG recordings. These four configurations are referred to as EEG microstate classes A, B, C, and D and have been associated with verbal/phonological, visual, attention reorientation, and subjective interoceptive-autonomic processing, respectively. The present study tested these associations via an intra-individual and inter-individual analysis approach. The intra-individual approach tested the effect of task-induced increased modality-specific processing on EEG microstate parameters. The inter-individual approach tested the effect of personal modality-specific parameters on EEG microstate parameters. We obtained multichannel EEG from 61 healthy, right-handed, male students during four eyes-closed conditions: object-visualization, spatial-visualization, verbalization (6 runs each), and resting (7 runs). After each run, we assessed participants' degrees of object-visual, spatial-visual, and verbal thinking using subjective reports. Before and after the recording, we assessed modality-specific cognitive abilities and styles using nine cognitive tests and two questionnaires. The EEG of all participants, conditions, and runs was clustered into four classes of EEG microstates (A, B, C, and D). RMANOVAs, ANOVAs and post-hoc paired t-tests compared microstate parameters between conditions. TANOVAs compared microstate class topographies between conditions. Differences were localized using eLORETA. Pearson correlations assessed interrelationships between personal modality-specific parameters and EEG microstate parameters during no-task resting. As hypothesized, verbal as opposed to visual conditions consistently affected the duration, occurrence, and coverage of microstate classes A and B. Contrary to associations suggested by previous reports, parameters were increased for class A during visualization, and class B during verbalization. In line with previous reports, microstate D parameters were increased during no-task resting compared to the three internal, goal-directed tasks. Topographic differences between conditions concerned particular sub-regions of components of the metabolic default mode network. Modality-specific personal parameters did not consistently correlate with microstate parameters except verbal cognitive style which correlated negatively with microstate class A duration and positively with class C occurrence. This is the first study that aimed to induce EEG microstate class parameter changes based on their hypothesized functional significance. Beyond, the associations of microstate classes A and B with visual and verbal processing, respectively and microstate class D with interoceptive-autonomic processing, our results suggest that a finely-tuned interplay between all four EEG microstate classes is necessary for the continuous formation of visual and verbal thoughts, as well as interoceptive-autonomic processing. Our results point to the possibility that the EEG microstate classes may represent the head-surface measured activity of intra-cortical sources primarily exhibiting inhibitory functions. However, additional studies are needed to verify and elaborate on this hypothesis.

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Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

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Intergroup bias - the tendency to behave more positively towards an ingroup member than an outgroup member - is a powerful social force, for good and ill. And though it is widely demonstrated, intergroup bias is not universal, as it is characterized by significant individual differences. Recently, attention has begun to turn to whether neuroanatomy might explain these individual differences in intergroup bias. However, no research to date has examined whether white matter microstructure could help determine differences in behavior towards ingroup and outgroup members. In the current research, we examine intergroup bias with the third-party punishment paradigm and white matter integrity and connectivity strength as determined by diffusion tensor imaging (DTI). We found that both increased white matter integrity at the right temporal-parietal junction (TPJ) and connectivity strength between the right TPJ and the dorsomedial prefrontal cortex (DMPFC) were associated with increased impartiality in the third-party punishment paradigm, i.e., reduced intergroup bias. Further, consistent with the role that these brain regions play in the mentalizing network, we found that these effects were mediated by mentalizing processes. Participants with greater white matter integrity at the right TPJ and connectivity strength between the right TPJ and the DMPFC employed mentalizing processes more equally for ingroup and outgroup members, and this non-biased use of mentalizing was associated with increased impartiality. The current results help shed light on the mechanisms of bias and, potentially, on interventions that promote impartiality over intergroup bias.