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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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A review of behavioral and neurobiological data on mood and mood regulation as they pertain to an understanding of mood disorders is presented. Four approaches are considered: 1) behavioral and cognitive; 2) neurobiological; 3) computational; and 4) developmental. Within each of these four sections, we summarize the current status of the field and present our vision for the future, including particular challenges and opportunities. We conclude with a series of specific recommendations for National Institute of Mental Health priorities. Recommendations are presented for the behavioral domain, the neural domain, the domain of behavioral-neural interaction, for training, and for dissemination. It is in the domain of behavioral-neural interaction, in particular, that new research is required that brings together traditions that have developed relatively independently. Training interdisciplinary clinical scientists who meaningfully draw upon both behavioral and neuroscientific literatures and methods is critically required for the realization of these goals.
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Children with an anxious temperament (AT) are at risk for developing psychiatric disorders along the internalizing spectrum, including anxiety and depression. Like these disorders, AT is a multidimensional phenotype and children with extreme anxiety show varying mixtures of physiological, behavioral, and other symptoms. Using a well-validated juvenile monkey model of AT, we addressed the degree to which this phenotypic heterogeneity reflects fundamental differences or similarities in the underlying neurobiology. The rhesus macaque is optimal for studying AT because children and young monkeys express the anxious phenotype in similar ways and have similar neurobiology. Fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET) in 238 freely behaving monkeys identified brain regions where metabolism predicted variation in three dimensions of the AT phenotype: hypothalamic-pituitary-adrenal (HPA) activity, freezing behavior, and expressive vocalizations. We distinguished brain regions that predicted all three dimensions of the phenotype from those that selectively predicted a single dimension. Elevated activity in the central nucleus of the amygdala and the anterior hippocampus was consistently found across individuals with different presentations of AT. In contrast, elevated activity in the lateral anterior hippocampus was selective to individuals with high levels of HPA activity, and decreased activity in the motor cortex (M1) was selective to those with high levels of freezing behavior. Furthermore, activity in these phenotype-selective regions mediated relations between amygdala metabolism and different expressions of anxiety. These findings provide a framework for understanding the mechanisms that lead to heterogeneity in the clinical presentation of internalizing disorders and set the stage for developing improved interventions.
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Recent theoretical and empirical work in cognitive science and neuroscience is brought into contact with the concept of the flow experience. After a brief exposition of brain function, the explicit-implicit distinction is applied to the effortless information processing that is so characteristic of the flow state. The explicit system is associated with the higher cognitive functions of the frontal lobe and medial temporal lobe structures and has evolved to increase cognitive flexibility. In contrast, the implicit system is associated with the skill-based knowledge supported primarily by the basal ganglia and has the advantage of being more efficient. From the analysis of this flexibility/efficiency trade-off emerges a thesis that identifies the flow state as a period during which a highly practiced skill that is represented in the implicit system's knowledge base is implemented without interference from the explicit system. It is proposed that a necessary prerequisite to the experience of flow is a state of transient hypofrontality that enables the temporary suppression of the analytical and meta-conscious capacities of the explicit system. Examining sensory-motor integration skills that seem to typify flow such as athletic performance, writing, and free-jazz improvisation, the new framework clarifies how this concept relates to creativity and opens new avenues of research.

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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Temperamentally anxious individuals can be identified in childhood and are at risk to develop anxiety and depressive disorders. In addition, these individuals tend to have extreme asymmetric right prefrontal brain activity. Although common and clinically important, little is known about the pathophysiology of anxious temperament. Regardless, indirect evidence from rodent studies and difficult to interpret primate studies is used to support the hypothesis that the amygdala plays a central role. In previous studies using rhesus monkeys, we characterized an anxious temperament endophenotype that is associated with excessive anxiety and fear-related responses and increased electrical activity in right frontal brain regions. To examine the role of the amygdala in mediating this endophenotype and other fearful responses, we prepared monkeys with selective fiber sparing ibotenic acid lesions of the amygdala. Unconditioned trait-like anxiety-fear responses remained intact in monkeys with >95% bilateral amygdala destruction. In addition, the lesions did not affect EEG frontal asymmetry. However, acute unconditioned fear responses, such as those elicited by exposure to a snake and to an unfamiliar threatening conspecific were blunted in monkeys with >70% lesions. These findings demonstrate that the primate amygdala is involved in mediating some acute unconditioned fear responses but challenge the notion that the amygdala is the key structure underlying the dispositional behavioral and physiological characteristics of anxious temperament.
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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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Theories of knowledge such as feature lists, semantic networks, and localist neural nets typically use a single global symbol to represent a property that occurs in multiple concepts. Thus, a global symbol represents mane across HORSE, PONY, and LION. Alternatively, perceptual theories of knowledge, as well as distributed representational systems, assume that properties take different local forms in different concepts. Thus, different local forms of mane exist for HORSE, PONY, and LION, each capturing the specific form that mane takes in its respective concept. Three experiments used the property verification task to assess whether properties are represented globally or locally (e.g., Does a PONY have mane?). If a single global form represents a property, then verifying it in any concept should increase its accessibility and speed its verification later in any other concept. Verifying mane for PONY should benefit as much from having verified mane for LION earlier as from verifying mane for HORSE. If properties are represented locally, however, verifying a property should only benefit from verifying a similar form earlier. Verifying mane for PONY should only benefit from verifying mane for HORSE, not from verifying mane for LION. Findings from three experiments strongly supported local property representation and ruled out the interpretation that object similarity was responsible (e.g., the greater overall similarity between HORSE and PONY than between LION and PONY). The findings further suggest that property representation and verification are complicated phenomena, grounded in sensory-motor simulations.
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The serotonin transporter (5-HTT) plays a critical role in regulating serotonergic neurotransmission and is implicated in the pathophysiology of anxiety and affective disorders. Positron emission tomography scans using [(11)C]DASB [(11)C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile] to measure 5-HTT availability (an index of receptor density and binding) were performed in 34 rhesus monkeys in which the relationship between regional brain glucose metabolism and anxious temperament was previously established. 5-HTT availability in the amygdalohippocampal area and bed nucleus of the stria terminalis correlated positively with individual differences in a behavioral and neuroendocrine composite of anxious temperament. 5-HTT availability also correlated positively with stress-induced metabolic activity within these regions. Collectively, these findings suggest that serotonergic modulation of neuronal excitability in the neural circuitry associated with anxiety mediates the developmental risk for affect-related psychopathology.
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A variant allele in the promoter region of the serotonin transporter gene, SLC6A4, the s allele, is associated with increased vulnerability to develop anxiety-related traits and depression. Furthermore, functional magnetic resonance imaging (fMRI) studies reveal that s carriers have increased amygdala reactivity in response to aversive stimuli, which is thought to be an intermediate phenotype mediating the influences of the s allele on emotionality. We used high-resolution microPET [18F]fluoro-2-deoxy-D-glucose (FDG) scanning to assess regional brain metabolic activity in rhesus monkeys to further explore s allele-related intermediate phenotypes. Rhesus monkeys provide an excellent model to understand mechanisms underlying human anxiety, and FDG microPET allows for the assessment of brain activity associated with naturalistic environments outside the scanner. During FDG uptake, monkeys were exposed to different ethologically relevant stressful situations (relocation and threat) as well as to the less stressful familiar environment of their home cage. The s carriers displayed increased orbitofrontal cortex activity in response to both relocation and threat. However, during relocation they displayed increased amygdala reactivity and in response to threat they displayed increased reactivity of the bed nucleus of the stria terminalis. No increase in the activity of any of these regions occurred when the animals were administered FDG in their home cages. These findings demonstrate context-dependent intermediate phenotypes in s carriers that provide a framework for understanding the mechanisms underlying the vulnerabilities of s-allele carriers exposed to different types of stressors.
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Social class is shaped by an individual's material resources as well as perceptions of rank vis-à-vis others in society, and in this article, we examine how class influences behavior. Diminished resources and lower rank create contexts that constrain social outcomes for lower-class individuals and enhance contextualist tendencies--that is, a focus on external, uncontrollable social forces and other individuals who influence one's life outcomes. In contrast, abundant resources and elevated rank create contexts that enhance the personal freedoms of upper-class individuals and give rise to solipsistic social cognitive tendencies--that is, an individualistic focus on one's own internal states, goals, motivations, and emotions. Guided by this framework, we detail 9 hypotheses and relevant empirical evidence concerning how class-based contextualist and solipsistic tendencies shape the self, perceptions of the social environment, and relationships to other individuals. Novel predictions and implications for research in other socio-political contexts are considered.
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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.
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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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BACKGROUND: Hypothalamic-pituitary-adrenal (HPA) system activation is adaptive in response to stress, and HPA dysregulation occurs in stress-related psychopathology. It is important to understand the mechanisms that modulate HPA output, yet few studies have addressed the neural circuitry associated with HPA regulation in primates and humans. Using high-resolution F-18-fluorodeoxyglucose positron emission tomography (FDG-PET) in rhesus monkeys, we assessed the relation between individual differences in brain activity and HPA function across multiple contexts that varied in stressfulness. METHODS: Using a logical AND conjunctions analysis, we assessed cortisol and brain metabolic activity with FDG-PET in 35 adolescent rhesus monkeys exposed to two threat and two home-cage conditions. To test the robustness of our findings, we used similar methods in an archival data set. In this data set, brain metabolic activity and cortisol were assessed in 17 adolescent male rhesus monkeys that were exposed to three stress-related contexts. RESULTS: Results from the two studies revealed that subgenual prefrontal cortex (PFC) metabolism (Brodmann's area 25/24) consistently predicted individual differences in plasma cortisol concentrations regardless of the context in which brain activity and cortisol were assessed. CONCLUSIONS: These findings suggest that activation in subgenual PFC may be related to HPA output across a variety of contexts (including familiar settings and novel or threatening situations). Individuals prone to elevated subgenual PFC activity across multiple contexts may be individuals who consistently show heightened cortisol and may be at risk for stress-related HPA dysregulation.
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This article completes the analysis of parental narratives of tantrums had by 335 children aged 18 to 60 months. Modal tantrum durations were 0.5 to 1 minute; 75% of the tantrums lasted 5 minutes or less. If the child stamped or dropped to the floor in the first 30 seconds, the tantrum was likely to be shorter and the likelihood of parental intervention less. A novel analysis of behavior probabilities that permitted grouping of tantrums of different durations converged with our previous statistically independent results to yield a model of tantrums as the expression of two independent but partially overlapping emotional and behavioral processes: Anger and Distress. Anger rises quickly, has its peak at or near the beginning of the tantrum, and declines thereafter. Crying and comfort-seeking, components of Distress, slowly increase in probability across the tantrum. This model indicates that tantrums can provide a window on the intense emotional processes of childhood.
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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.
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Who benefits most from making sacrifices for others? The current study provides one answer to this question by demonstrating the intrinsic benefits of sacrifice for people who are highly motivated to respond to a specific romantic partner's needs noncontingently, a phenomenon termed communal strength. In a 14-day daily-experience study of 69 romantic couples, communal strength was positively associated with positive emotions during the sacrifice itself, with feeling appreciated by the partner for the sacrifice, and with feelings of relationship satisfaction on the day of the sacrifice. Furthermore, feelings of authenticity for the sacrifice mediated these associations. Several alternative hypotheses were ruled out: The effects were not due to individuals higher in communal strength making qualitatively different kinds of sacrifices, being more positive in general, or being involved in happier relationships. Implications for research and theory on communal relationships and positive emotions are discussed.
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