Significant progress has been made in our understanding of the neural substrates of emotion and its disorders. Neuroimaging methods have been used to characterize the circuitry underlying disorders of emotion. Particular emphasis has been placed on the prefrontal cortex, anterior cingulate, parietal cortex, and the amygdala as critical components of the circuitry that may be dysfunctional in both depression and anxiety.
Electroencephalogram (EEG) alpha power has been demonstrated to be inversely related to mental activity and has subsequently been used as an indirect measure of brain activation. The thalamus has been proposed as an important site for modulation of rhythmic alpha activity. Studies in animals have suggested that cortical alpha rhythms are correlated with alpha rhythms in the thalamus. However, little empirical evidence exists for this relation in humans. In the current study, resting EEG and a fluorodeoxyglucose positron emission tomography scan were measured during the same experimental session. Over a 30-min period, average EEG alpha power across 28 electrodes from 27 participants was robustly inversely correlated with glucose metabolic activity in the thalamus. These data provide the first evidence for a relation between alpha EEG power and thalamic activity in humans.
Given the central role of the amygdala in fear perception and expression and its likely abnormality in affective disorders and autism, there is great demand for a technique to measure differences in neurochemistry of the human amygdala. Unfortunately, it is also a technically complex target for magnetic resonance spectroscopy (MRS) due to a small volume, high field inhomogeneity and a shared boundary with hippocampus, which can undergo opposite changes in response to stress. We attempted to achieve reliable PRESS-localized single-voxel MRS at 3T of the isolated human amygdala by using anatomy to guide voxel size and location. We present data from 106 amygdala-MRS sessions from 58 volunteers aged 10 to 52 years, including two tests of one-week stability and a feasibility study in an adolescent sample. Our main outcomes were indices of spectral quality, repeated measurement variability (within- and between-subject standard deviations), and sensitivity to stable individual differences measured by intra-class correlation (ICC). We present metrics of amygdala-MRS reliability for n-acetyl-aspartate, creatine, choline, myo-Inositol, and glutamate+glutamine (Glx). We found that scan quality suffers an age-related difference in field homogeneity and modified our protocol to compensate. We further identified an effect of anatomical inclusion near the endorhinal sulcus, a region of high synaptic density, that contributes up to 29% of within-subject variability across 4 sessions (n=14). Remaining variability in line width but not signal-to-noise also detracts from reliability. Statistical correction for partial inclusion of these strong neurochemical gradients decreases n-acetyl-aspartate reliability from an intraclass correlation of 0.84 to 0.56 for 7-minute acquisitions. This suggests that systematic differences in anatomical inclusion can contribute greatly to apparent neurochemical concentrations and could produce false group differences in experimental studies. Precise, anatomically-based prescriptions that avoid age-related sources of inhomogeneity and use longer scan times may permit study of individual differences in neurochemistry throughout development in this late-maturing structure.
Four U.S. sites formed a consortium to conduct a multisite study of fMRI methods. The primary purpose of this consortium was to examine the reliability and reproducibility of fMRI results. FMRI data were collected on healthy adults during performance of a spatial working memory task at four different institutions. Two sets of data from each institution were made available. First, data from two subjects were made available from each site and were processed and analyzed as a pooled data set. Second, statistical maps from five to eight subjects per site were made available. These images were aligned in stereotactic space and common regions of activation were examined to address the reproducibility of fMRI results when both image acquisition and analysis vary as a function of site. Our grouped and individual data analyses showed reliable patterns of activation in dorsolateral prefrontal cortex and posterior parietal cortex during performance of the working memory task across all four sites. This multisite study, the first of its kind using fMRI data, demonstrates highly consistent findings across sites.
Four theories of the human conceptual system--semantic memory, exemplar models, feed-forward connectionist nets, and situated simulation theory--are characterized and contrasted on five dimensions. Empirical evidence is then reviewed for the situated simulation theory and conclusions are discussed. (Author/VWL)
Test-retest reliability of resting regional cerebral metabolic rate of glucose (rCMR) was examined in selected subcortical structures: the amygdala, hippocampus, thalamus, and anterior caudate nucleus. Findings from previous studies examining reliability of rCMR suggest that rCMR in small subcortical structures may be more variable than in larger cortical regions. We chose to study these subcortical regions because of their particular interest to our laboratory in its investigations of the neurocircuitry of emotion and depression. Twelve normal subjects (seven female, mean age = 32.42 years, range 21-48 years) underwent two FDG-PET scans separated by approximately 6 months (mean = 25 weeks, range 17-35 weeks). A region-of-interest approach with PET-MRI coregistration was used for analysis of rCMR reliability. Good test-retest reliability was found in the left amygdala, right and left hippocampus, right and left thalamus, and right and left anterior caudate nucleus. However, rCMR in the right amygdala did not show good test-retest reliability. The implications of these data and their import for studies that include a repeat-test design are considered.
We present a new sparse shape modeling framework on the Laplace-Beltrami (LB) eigenfunctions. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes by forming a Fourier series expansion. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we propose to filter out only the significant eigenfunctions by imposing l1-penalty. The new sparse framework can further avoid additional surface-based smoothing often used in the field. The proposed approach is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shapes in the normal population. In addition, we show how the emotional response is related to the anatomy of the subcortical structures.
Previous research has shown that na_ve participants display a high level of agreement when asked to choose or drawschematic representations, or image schemas, of concrete and abstract verbs [Proceedings of the 23rd Annual Meeting of the Cognitive Science Society, 2001, Erlbaum, Mawhah, NJ, p. 873]. For example, participants tended to ascribe a horizontal image schema to push, and a vertical image schema to respect. This consistency in offline data is preliminary evidence that language invokes spatial forms of representation. It also provided norms that were used in the present research to investigate the activation of spatial image schemas during online language comprehension. We predicted that if comprehending a verb activates a spatial representation that is extended along a particular horizontal or vertical axis, it will affect other forms of spatial processing along that axis. Participants listened to short sentences while engaged in a visual discrimination task (Experiment 1) and a picture memory task (Experiment 2). In both cases, reaction times showed an interaction between the horizontal/vertical nature of the verb's image schema, and the horizontal/vertical position of the visual stimuli. We argue that such spatial effects of verb comprehension provide evidence for the perceptual–motor character of linguistic representations.
<p>Social cognition, including complex social judgments and attitudes, is shaped by individual learning experiences, where affect often plays a critical role. Aversive classical conditioning-a form of associative learning involving a relationship between a neutral event (conditioned stimulus, CS) and an aversive event (unconditioned stimulus, US)-represents a well-controlled paradigm to study how the acquisition of socially relevant knowledge influences behavior and the brain. Unraveling the temporal unfolding of brain mechanisms involved appears critical for an initial understanding about how social cognition operates. Here, 128-channel ERPs were recorded in 50 subjects during the acquisition phase of a differential aversive classical conditioning paradigm. The CS+ (two fearful faces) were paired 50% of the time with an aversive noise (CS upward arrow + /Paired), whereas in the remaining 50% they were not (CS upward arrow + /Unpaired); the CS- (two different fearful faces) were never paired with the noise. Scalp ERP analyses revealed differences between CS upward arrow + /Unpaired and CS- as early as approximately 120 ms post-stimulus. Tomographic source localization analyses revealed early activation modulated by the CS+ in the ventral visual pathway (e.g. fusiform gyrus, approximately 120 ms), right middle frontal gyrus (approximately 176 ms), and precuneus (approximately 240 ms). At approximately 120 ms, the CS- elicited increased activation in the left insula and left middle frontal gyrus. These findings not only confirm a critical role of prefrontal, insular, and precuneus regions in aversive conditioning, but they also suggest that biologically and socially salient information modulates activation at early stages of the information processing flow, and thus furnish initial insight about how affect and social judgments operate.</p>
<p>Illustrates parallels between global descriptions of internal states in clinical and personality psychology and notions of global arousal in autonomic and central psychophysiology. Such assumptions about the undifferentiated nature of internal states are questioned on the basis of recent psychophysiological research. Data are reviewed on cortical specificity and its implications for conceptualizing clinically relevant cognitive and affective processes. Principles of psychophysiological specificity are applied to the understanding and self-regulation of anxiety. General implications of this approach for the rationally based construction of therapeutic interventions are discussed. (41 ref)</p>
We used fMRI to examine amygdala activation in response to fearful facial expressions, measured over multiple scanning sessions. 15 human subjects underwent three scanning sessions, at 0, 2 and 8 weeks. During each session, functional brain images centered about the amygdala were acquired continuously while participants were shown alternating blocks of fearful, neutral and happy facial expressions. Intraclass correlation coefficients calculated across the sessions indicated stability of response in left amygdala to fearful faces (as a change from baseline), but considerably less left amygdala stability in responses to neutral expressions and for fear versus neutral contrasts. The results demonstrate that the measurement of fMRI BOLD responses in amygdala to fearful facial expressions might be usefully employed as an index of amygdala reactivity over extended periods. While signal change to fearful facial expressions appears robust, the experimental design employed here has yielded variable responsivity within baseline or comparison conditions. Future studies might manipulate the experimental design to either amplify or attenuate this variability, according to the goals of the research.
The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the e-neighbor method that does not need any predetermined parcellation. The proposed pipeline is applied in detecting the topological alteration of the white matter connectivity in maltreated children.
<p>Studied the different effects of yoga and psychomotor activity on a coding task, with 34 children referred to a learning center as Ss. They received a baseline period, a control period involving a fine motor task, an experimental treatment, another control period, a treatment reversal, and a control period. The results indicate that order of treatment had no effect on the results. Furthermore, coding scores in the 2nd half of the experiment were higher than those in the 1st half. There was no difference in the effect on performance of yoga and gross motor activities. Irrespective of which treatment was given, scores after treatment were significantly higher than those during the control periods. There are implications for physical education programming in elementary schools.</p>
We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.
BACKGROUND: EEG alpha power has been demonstrated to be inversely related to mental activity and has subsequently been used as an indirect measure of brain activation. The hypothesis that the thalamus serves as a neuronal oscillator of alpha rhythms has been supported by studies in animals, but only minimally by studies in humans. METHODS: In the current study, PET-derived measures of regional glucose metabolism, EEG, and structural MRI were obtained from each participant to assess the relation between thalamic metabolic activity and alpha power in depressed patients and healthy controls. The thalamus was identified and drawn on each subject's MRI. The MRI was then co-registered to the corresponding PET scan and metabolic activity from the thalamus extracted. Thalamic activity was then correlated with a 30-min aggregated average of alpha EEG power. RESULTS: Robust inverse correlations were observed in the control data, indicating that greater thalamic metabolism is correlated with decreased alpha power. No relation was found in the depressed patient data. CONCLUSIONS: The results are discussed in the context of a possible abnormality in thalamocortical circuitry associated with depression.
Muscle electrical activity, or "electromyogenic" (EMG) artifact, poses a serious threat to the validity of electroencephalography (EEG) investigations in the frequency domain. EMG is sensitive to a variety of psychological processes and can mask genuine effects or masquerade as legitimate neurogenic effects across the scalp in frequencies at least as low as the alpha band (8-13 Hz). Although several techniques for correcting myogenic activity have been described, most are subjected to only limited validation attempts. Attempts to gauge the impact of EMG correction on intracerebral source models (source "localization" analyses) are rarer still. Accordingly, we assessed the sensitivity and specificity of one prominent correction tool, independent component analysis (ICA), on the scalp and in the source-space using high-resolution EEG. Data were collected from 17 participants while neurogenic and myogenic activity was independently varied. Several protocols for classifying and discarding components classified as myogenic and non-myogenic artifact (e.g., ocular) were systematically assessed, leading to the exclusion of one-third to as much as three-quarters of the variance in the EEG. Some, but not all, of these protocols showed adequate performance on the scalp. Indeed, performance was superior to previously validated regression-based techniques. Nevertheless, ICA-based EMG correction exhibited low validity in the intracerebral source-space, likely owing to incomplete separation of neurogenic from myogenic sources. Taken with prior work, this indicates that EMG artifact can substantially distort estimates of intracerebral spectral activity. Neither regression- nor ICA-based EMG correction techniques provide complete safeguards against such distortions. In light of these results, several practical suggestions and recommendations are made for intelligently using ICA to minimize EMG and other common artifacts.
Recent neuroimaging and neuropsychological work has begun to shed light on how the brain responds to the viewing of facial expressions of emotion. However, one important category of facial expression that has not been studied on this level is the facial expression of pain. We investigated the neural response to pain expressions by performing functional magnetic resonance imaging (fMRI) as subjects viewed short video sequences showing faces expressing either moderate pain or, for comparison, no pain. In alternate blocks, the same subjects received both painful and non-painful thermal stimulation. Facial expressions of pain were found to engage cortical areas also engaged by the first-hand experience of pain, including anterior cingulate cortex and insula. The reported findings corroborate other work in which the neural response to witnessed pain has been examined from other perspectives. In addition, they lend support to the idea that common neural substrates are involved in representing one's own and others' affective states.
Reputation systems promote cooperation and deter antisocial behavior in groups. Little is known, however, about how and why people share reputational information. Here, we seek to establish the existence and dynamics of prosocial gossip, the sharing of negative evaluative information about a target in a way that protects others from antisocial or exploitative behavior. We present a model of prosocial gossip and the results of 4 studies testing the model's claims. Results of Studies 1 through 3 demonstrate that (a) individuals who observe an antisocial act experience negative affect and are compelled to share information about the antisocial actor with a potentially vulnerable person, (b) sharing such information reduces negative affect created by observing the antisocial behavior, and (c) individuals possessing more prosocial orientations are the most motivated to engage in such gossip, even at a personal cost, and exhibit the greatest reduction in negative affect as a result. Study 4 demonstrates that prosocial gossip can effectively deter selfishness and promote cooperation. Taken together these results highlight the roles of prosocial motivations and negative affective reactions to injustice in maintaining reputational information sharing in groups. We conclude by discussing implications for reputational theories of the maintenance of cooperation in human groups.
We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination of basis functions. The basic properties of the representation are investigated in connection with a self-adjoint partial differential equation and the traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, a new iterative residual fitting (IRF) algorithm is developed. Its computational and numerical implementation issues are discussed in detail. The computer codes are also available at http://www.stat.wisc.edu/-mchung/softwares/weighted.SPHARM/weighted-SPHARM.html. As an illustration, the WFS is applied i n quantifying the amount ofgray matter in a group of high functioning autistic subjects. Within the WFS framework, cortical thickness and gray matter density are computed and compared.
One of the most important goals and outcomes of social life is to attain status in the groups to which we belong. Such face-to-face status is defined by the amount of respect, influence, and prominence each member enjoys in the eyes of the others. Three studies investigated personological determinants of status in social groups (fraternity, sorority, and dormitory), relating the Big Five personality traits and physical attractiveness to peer ratings of status. High Extraversion substantially predicted elevated status for both sexes. High Neuroticism, incompatible with male gender norms, predicted lower status in men. None of the other Big Five traits predicted status. These effects were independent of attractiveness, which predicted higher status only in men. Contrary to previous claims, women's status ordering was just as stable as men's but emerged later. Discussion focuses on personological pathways to attaining status and on potential mediators.