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Mindfulness is defined as paying attention in the present moment. We investigate the hypothesis that mindfulness training may alter or enhance specific aspects of attention. We examined three functionally and neuroanatomically distinct but overlapping attentional subsystems: alerting, orienting, and conflict monitoring. Functioning of each subsystem was indexed by performance on the Attention Network Test (ANT; Fan, McCandliss, Sommer, Raz, & Posner, 2002). Two types of mindfulness training (MT) programs were examined, and behavioral testing was conducted on participants before (Time 1) and after (Time 2) training. One training group consisted of individuals naive to mindfulness techniques who participated in an 8-week mindfulness-based stress reduction (MBSR) course that emphasized the development of concentrative meditation skills. The other training group consisted of individuals experienced in concentrative meditation techniques who participated in a 1-month intensive mindfulness retreat. Performance of these groups was compared with that of control participants who were meditation naive and received no MT. At Time 1, the participants in the retreat group demonstrated improved conflict monitoring performance relative to those in the MBSR and control groups. At Time 2, the participants in the MBSR course demonstrated significantly improved orienting in comparison with the control and retreat participants. In contrast, the participants in the retreat group demonstrated altered performance on the alerting component, with improvements in exogenous stimulus detection in comparison with the control and MBSR participants. The groups did not differ in conflict monitoring performance at Time 2. These results suggest that mindfulness training may improve attention-related behavioral responses by enhancing functioning of specific subcomponents of attention. Whereas participation in the MBSR course improved the ability to endogenously orient attention, retreat participation appeared to allow for the development and emergence of receptive attentional skills, which improved exogenous alerting-related process.

Studies have suggested that the default mode network is active during mind wandering, which is often experienced intermittently during sustained attention tasks. Conversely, an anticorrelated task-positive network is thought to subserve various forms of attentional processing. Understanding how these two systems work together is central for understanding many forms of optimal and sub-optimal task performance. Here we present a basic model of naturalistic cognitive fluctuations between mind wandering and attentional states derived from the practice of focused attention meditation. This model proposes four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. People who train in this style of meditation cultivate their abilities to monitor cognitive processes related to attention and distraction, making them well suited to report on these mental events. Fourteen meditation practitioners performed breath-focused meditation while undergoing fMRI scanning. When participants realized their mind had wandered, they pressed a button and returned their focus to the breath. The four intervals above were then constructed around these button presses. We hypothesized that periods of mind wandering would be associated with default mode activity, whereas cognitive processes engaged during awareness of mind wandering, shifting of attention and sustained attention would engage attentional subnetworks. Analyses revealed activity in brain regions associated with the default mode during mind wandering, and in salience network regions during awareness of mind wandering. Elements of the executive network were active during shifting and sustained attention. Furthermore, activations during these cognitive phases were modulated by lifetime meditation experience. These findings support and extend theories about cognitive correlates of distributed brain networks.
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The impact of using motion estimates as covariates of no interest was examined in general linear modeling (GLM) of both block design and rapid event-related functional magnetic resonance imaging (fMRI) data. The purpose of motion correction is to identify and eliminate artifacts caused by task-correlated motion while maximizing sensitivity to true activations. To optimize this process, a combination of motion correction approaches was applied to data from 33 subjects performing both a block-design and an event-related fMRI experiment, including analysis: (1) without motion correction; (2) with motion correction alone; (3) with motion-corrected data and motion covariates included in the GLM; and (4) with non-motion-corrected data and motion covariates included in the GLM. Inclusion of covariates was found to be generally useful for increasing the sensitivity of GLM results in the analysis of event-related data. When motion parameters were included in the GLM for event-related data, it made little difference if motion correction was actually applied to the data. For the block design, inclusion of motion covariates had a deleterious impact on GLM sensitivity when even moderate correlation existed between motion and the experimental design. Based on these results, we present a general strategy for block designs, event-related designs, and hybrid designs to identify and eliminate probable motion artifacts while maximizing sensitivity to true activations.
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OBJECTIVE: Positron emission tomography was used to investigate the neural substrates of normal human emotional and their dependence on the types of emotional stimulus. METHOD: Twelve healthy female subjects underwent 12 measurements of regional brain activity following the intravenous bolus administration of [15O]H2O as they alternated between emotion-generating and control film and recall tasks. Automated image analysis techniques were used to characterize and compare the increases in regional brain activity associated with the emotional response to complex visual (film) and cognitive (recall) stimuli. RESULTS: Film- and recall-generated emotion were each associated with significantly increased activity in the vicinity of the medial prefrontal cortex and thalamus, suggesting that these regions participate in aspects of emotion that do not depend on the nature of the emotional stimulus. Film-generated emotion was associated with significantly greater increases in activity bilaterally in the occipitotemporparietal cortex, lateral cerebellum, hypothalamus, and a region that includes the anterior temporal cortex, amygdala, and hippocampal formation, suggesting that these regions participate in the emotional response to certain exteroceptive sensory stimuli. Recall-generated sadness was associated with significantly greater increases in activity in the vicinity of the anterior insular cortex, suggesting that this region participates in the emotional response to potentially distressing cognitive or interoceptive sensory stimuli. CONCLUSIONS: While this study should be considered preliminary, it identified brain regions that participate in externally and internally generated human emotion.
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OBJECTIVE: Happiness, sadness, and disgust are three emotions that differ in their valence (positive or negative) and associated action tendencies (approach or withdrawal). This study was designed to investigate the neuroanatomical correlates of these discrete emotions. METHOD: Twelve healthy female subjects were studied. Positron emission tomography and [15O]H2O were used to measure regional brain activity. There were 12 conditions per subject: happiness, sadness, and disgust and three control conditions, each induced by film and recall. Emotion and control tasks were alternated throughout. Condition order was pseudo-randomized and counterbalanced across subjects. Analyses focused on brain activity patterns for each emotion when combining film and recall data. RESULTS: Happiness, sadness, and disgust were each associated with increases in activity in the thalamus and medial prefrontal cortex (Brodmann's area 9). These three emotions were also associated with activation of anterior and posterior temporal structures, primarily when induced by film. Recalled sadness was associated with increased activation in the anterior insula. Happiness was distinguished from sadness by greater activity in the vicinity of ventral mesial frontal cortex. CONCLUSIONS: While this study should be considered preliminary, it identifies regions of the brain that participate in happiness, sadness, and disgust, regions that distinguish between positive and negative emotions, and regions that depend on both the elicitor and valence of emotion or their interaction.
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Substantial evidence suggests that a key distinction in the classification of human emotion is that between an appetitive motivational system association with positive or pleasant emotion and an aversive motivational system associated with negative or unpleasant emotion. To explore the neural substrates of these two systems, 12 healthy women viewed sets of pictures previously demonstrated to elicit pleasant, unpleasant and neutral emotion, while positron emission tomographic (PET) measurements of regional cerebral blood flow were obtained. Pleasant and unpleasant emotions were each distinguished from neutral emotion conditions by significantly increased cerebral blood flow in the vicinity of the medial prefrontal cortex (Brodmann's area 9), thalamus, hypothalamus and midbrain (P < 0.005). Unpleasant was distinguished from neutral or pleasant emotion by activation of the bilateral occipito-temporal cortex and cerebellum, and left parahippocampal gyrus, hippocampus and amygdala (P < 0.005). Pleasant was also distinguished from neutral but not unpleasant emotion by activation of the head of the left caudate nucleus (P < 0.005). These findings are consistent with those from other recent PET studies of human emotion and demonstrate that there are both common and unique components of the neural networks mediating pleasant and unpleasant emotion in healthy women.
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Positive affect elicited in a mother toward her newborn infant may be one of the most powerful and evolutionarily preserved forms of positive affect in the emotional landscape of human behavior. This study examined the neurobiology of this form of positive emotion and in so doing, sought to overcome the difficulty of eliciting robust positive affect in response to visual stimuli in the physiological laboratory. Six primiparous human mothers with no indications of postpartum depression brought their infants into the laboratory for a photo shoot. Approximately 6 weeks later, they viewed photographs of their infant, another infant, and adult faces during acquisition of functional magnetic resonance images (fMRI). Mothers exhibited bilateral activation of the orbitofrontal cortex (OFC) while viewing pictures of their own versus unfamiliar infants. While in the scanner, mothers rated their mood more positively for pictures of their own infants than for unfamiliar infants, adults, or at baseline. The orbitofrontal activation correlated positively with pleasant mood ratings. In contrast, areas of visual cortex that also discriminated between own and unfamiliar infants were unrelated to mood ratings. These data implicate the orbitofrontal cortex in a mother's affective responses to her infant, a form of positive emotion that has received scant attention in prior human neurobiological studies. Furthermore, individual variations in orbitofrontal activation to infant stimuli may reflect an important dimension of maternal attachment.
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Neuroimage phenotyping for psychiatric and neurological disorders is performed using voxelwise analyses also known as voxel based analyses or morphometry (VBM). A typical voxelwise analysis treats measurements at each voxel (e.g., fractional anisotropy, gray matter probability) as outcome measures to study the effects of possible explanatory variables (e.g., age, group) in a linear regression setting. Furthermore, each voxel is treated independently until the stage of correction for multiple comparisons. Recently, multi-voxel pattern analyses (MVPA), such as classification, have arisen as an alternative to VBM. The main advantage of MVPA over VBM is that the former employ multivariate methods which can account for interactions among voxels in identifying significant patterns. They also provide ways for computer-aided diagnosis and prognosis at individual subject level. However, compared to VBM, the results of MVPA are often more difficult to interpret and prone to arbitrary conclusions. In this paper, first we use penalized likelihood modeling to provide a unified framework for understanding both VBM and MVPA. We then utilize statistical learning theory to provide practical methods for interpreting the results of MVPA beyond commonly used performance metrics, such as leave-one-out-cross validation accuracy and area under the receiver operating characteristic (ROC) curve. Additionally, we demonstrate that there are challenges in MVPA when trying to obtain image phenotyping information in the form of statistical parametric maps (SPMs), which are commonly obtained from VBM, and provide a bootstrap strategy as a potential solution for generating SPMs using MVPA. This technique also allows us to maximize the use of available training data. We illustrate the empirical performance of the proposed framework using two different neuroimaging studies that pose different levels of challenge for classification using MVPA.
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Increasing research indicates that concepts are represented as distributed circuits of property information across the brain's modality-specific areas. The current study examines the distributed representation of an important but under-explored category, foods. Participants viewed pictures of appetizing foods (along with pictures of locations for comparison) during event-related fMRI. Compared to location pictures, food pictures activated the right insula/operculum and the left orbitofrontal cortex, both gustatory processing areas. Food pictures also activated regions of visual cortex that represent object shape. Together these areas contribute to a distributed neural circuit that represents food knowledge. Not only does this circuit become active during the tasting of actual foods, it also becomes active while viewing food pictures. Via the process of pattern completion, food pictures activate gustatory regions of the circuit to produce conceptual inferences about taste. Consistent with theories that ground knowledge in the modalities, these inferences arise as reenactments of modality-specific processing.
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Individuals with fragile X syndrome (FXS) commonly display characteristics of social anxiety, including gaze aversion, increased time to initiate social interaction, and difficulty forming meaningful peer relationships. While neural correlates of face processing, an important component of social interaction, are altered in FXS, studies have not examined whether social anxiety in this population is related to higher cognitive processes, such as memory. This study aimed to determine whether the neural circuitry involved in face encoding was disrupted in individuals with FXS, and whether brain activity during face encoding was related to levels of social anxiety. A group of 11 individuals with FXS (5 M) and 11 age- and gender-matched control participants underwent fMRI scanning while performing a face encoding task with online eye-tracking. Results indicate that compared to the control group, individuals with FXS exhibited decreased activation of prefrontal regions associated with complex social cognition, including the medial and superior frontal cortex, during successful face encoding. Further, the FXS and control groups showed significantly different relationships between measures of social anxiety (including gaze-fixation) and brain activity during face encoding. These data indicate that social anxiety in FXS may be related to the inability to successfully recruit higher level social cognition regions during the initial phases of memory formation.
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BACKGROUND: Anhedonia, a reduced ability to experience pleasure, is a chief symptom of major depressive disorder and is related to reduced frontostriatal connectivity when attempting to upregulate positive emotion. The present study examined another facet of positive emotion regulation associated with anhedonia-namely, the downregulation of positive affect-and its relation to prefrontal cortex (PFC) activity. METHODS: Neuroimaging data were collected from 27 individuals meeting criteria for major depressive disorder as they attempted to suppress positive emotion during a positive emotion regulation task. Their PFC activation pattern was compared with the PFC activation pattern exhibited by 19 healthy control subjects during the same task. Anhedonia scores were collected at three time points: at baseline (time 1), 8 weeks after time 1 (i.e., time 2), and 6 months after time 1 (i.e., time 3). Prefrontal cortex activity at time 1 was used to predict change in anhedonia over time. Analyses were conducted utilizing hierarchical linear modeling software. RESULTS: Depressed individuals who could not inhibit positive emotion-evinced by reduced right ventrolateral prefrontal cortex activity during attempts to dampen their experience of positive emotion in response to positive visual stimuli-exhibited a steeper anhedonia reduction slope between baseline and 8 weeks of treatment with antidepressant medication (p < .05). Control subjects showed a similar trend between baseline and time 3. CONCLUSIONS: To reduce anhedonia, it may be necessary to teach individuals how to counteract the functioning of an overactive pleasure-dampening prefrontal inhibitory system.
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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.
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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.
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<p>The relaxation response (RR) is the counterpart of the stress response. Millennia-old practices evoking the RR include meditation, yoga and repetitive prayer. Although RR elicitation is an effective therapeutic intervention that counteracts the adverse clinical effects of stress in disorders including hypertension, anxiety, insomnia and aging, the underlying molecular mechanisms that explain these clinical benefits remain undetermined. To assess rapid time-dependent (temporal) genomic changes during one session of RR practice among healthy practitioners with years of RR practice and also in novices before and after 8 weeks of RR training, we measured the transcriptome in peripheral blood prior to, immediately after, and 15 minutes after listening to an RR-eliciting or a health education CD. Both short-term and long-term practitioners evoked significant temporal gene expression changes with greater significance in the latter as compared to novices. RR practice enhanced expression of genes associated with energy metabolism, mitochondrial function, insulin secretion and telomere maintenance, and reduced expression of genes linked to inflammatory response and stress-related pathways. Interactive network analyses of RR-affected pathways identified mitochondrial ATP synthase and insulin (INS) as top upregulated critical molecules (focus hubs) and NF-κB pathway genes as top downregulated focus hubs. Our results for the first time indicate that RR elicitation, particularly after long-term practice, may evoke its downstream health benefits by improving mitochondrial energy production and utilization and thus promoting mitochondrial resiliency through upregulation of ATPase and insulin function. Mitochondrial resiliency might also be promoted by RR-induced downregulation of NF-κB-associated upstream and downstream targets that mitigates stress.</p>
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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.
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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.
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<p>As Titchener pointed out more than one hundred years ago, attention is at the center of the psychological enterprise. Attention research investigates how voluntary control and subjective experience arise from and regulate our behavior. In recent years, attention has been one of the fastest growing of all fields within cognitive psychology and cognitive neuroscience. This review examines attention as characterized by linking common neural networks with individual differences in their efficient utilization. The development of attentional networks is partly specified by genes, but is also open to specific experiences through the actions of caregivers and the culture. We believe that the connection between neural networks, genes, and socialization provides a common approach to all aspects of human cognition and emotion. Pursuit of this approach can provide a basis for psychology that unifies social, cultural, differential, experimental, and physiological areas, and allows normal development to serve as a baseline for understanding various forms of pathology. D.O. Hebb proposed this approach 50 years ago in his volume Organization of Behavior and continued with introductory textbooks that dealt with all of the topics of psychology in a common framework. Use of a common network approach to psychological science may allow a foundation for predicting and understanding human behavior in its varied forms.</p>

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.
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<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>
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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.
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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.
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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.
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In recent years, three attentional networks have been defined in anatomical and functional terms. These functions involve alerting, orienting, and executive attention. Reaction time measures can be used to quantify the processing efficiency within each of these three networks. The Attention Network Test (ANT) is designed to evaluate alerting, orienting, and executive attention within a single 30-min testing session that can be easily performed by children, patients, and monkeys. A study with 40 normal adult subjects indicates that the ANT produces reliable single subject estimates of alerting, orienting, and executive function, and further suggests that the efficiencies of these three networks are uncorrelated. There are, however, some interactions in which alerting and orienting can modulate the degree of interference from flankers. This procedure may prove to be convenient and useful in evaluating attentional abnormalities associated with cases of brain injury, stroke, schizophrenia, and attention-deficit disorder. The ANT may also serve as an activation task for neuroimaging studies and as a phenotype for the study of the influence of genes on attentional networks.

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.
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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.
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