Mindful attention promotes control of brain network dynamics for self-regulation and discontinues the past from the present.

Mindful attention is characterized by acknowledging the present experience as a transient mental event. Early stages of mindfulness practice may require greater neural effort for later efficiency. Early effort may self-regulate behavior and focalize the present, but this understanding lacks a computational explanation. Here we used network control theory as a model of how external control inputs-operationalizing effort-distribute changes in neural activity evoked during mindful attention across the white matter network. We hypothesized that individuals with greater network controllability, thereby efficiently distributing control inputs, effectively self-regulate behavior. We further hypothesized that brain regions that utilize greater control input exhibit shorter intrinsic timescales of neural activity. Shorter timescales characterize quickly discontinuing past processing to focalize the present. We tested these hypotheses in a randomized controlled study that primed participants to either mindfully respond or naturally react to alcohol cues during fMRI and administered text reminders and measurements of alcohol consumption during 4 wk postscan. We found that participants with greater network controllability moderated alcohol consumption. Mindful regulation of alcohol cues, compared to one's own natural reactions, reduced craving, but craving did not differ from the baseline group. Mindful regulation of alcohol cues, compared to the natural reactions of the baseline group, involved more-effortful control of neural dynamics across cognitive control and attention subnetworks. This effort persisted in the natural reactions of the mindful group compared to the baseline group. More-effortful neural states had shorter timescales than less effortful states, offering an explanation for how mindful attention promotes being present.

Partisans process policy-based and identity-based messages using dissociable neural systems.

Political partisanship is often conceived as a lens through which people view politics. Behavioral research has distinguished two types of "partisan lenses"-policy-based and identity-based-that may influence peoples' perception of political events. Little is known, however, about the mechanisms through which partisan discourse appealing to policy beliefs or targeting partisan identities operate within individuals. We addressed this question by collecting neuroimaging data while participants watched videos of speakers expressing partisan views. A "partisan lens effect" was identified as the difference in neural synchrony between each participant's brain response and that of their partisan ingroup vs. outgroup. When processing policy-based messaging, a partisan lens effect was observed in socio-political reasoning and affective responding brain regions. When processing negative identity-based attacks, a partisan lens effect was observed in mentalizing and affective responding brain regions. These data suggest that the processing of political discourse that appeals to different forms of partisanship is supported by related but distinguishable neural-and therefore psychological-mechanisms, which may have implications for how we characterize partisanship and ameliorate its deleterious impacts.

Estradiol effects on an emotional interference task in adolescents with current and remitted depression.

Attentional biases to emotional stimuli are thought to reflect vulnerability for mood disorder onset and maintenance. This study examined the association between the endogenous sex hormone estradiol and emotional attentional biases in adolescent females with either current or remitted depression. Three groups of participants (mean age ± SD) completed the Emotional Interrupt Task: 1) 20 adolescent females (15.1 ± 1.83 years) currently diagnosed with Major Depressive Disorder (MDD), 2) 16 adolescent females (16.4 ± 1.31 years) who had experienced at least one episode of MDD in their lifetime but currently met criteria for MDD in remission, and 3) 30 adolescent female (15.4 ± 1.83 years) healthy controls. Attentional interference (AI) scores were calculated as differences in target response reaction time between trials with emotional facial expressions versus neutral facial expressions. Estradiol levels were assayed by Salimetrics LLC using saliva samples collected within 30 min of waking on assessment days. Robust multiple regression with product terms evaluated estradiol's main effect on AI scores, as well as hypothesized estradiol × diagnostic group interactions. Although neither mean estradiol levels nor mean AI scores in the current-MDD and remitted-MDD groups differed from controls, the relationship between estradiol and overall AI score differed between control adolescents and the remitted-MDD group. Specifically, the remitted-MDD adolescents performed worse (i.e., showed greater attentional interference) when they had higher estradiol; no significant relationship existed in the current-MDD group. Because this finding was driven by angry and not happy stimuli, it appears higher estradiol levels were associated with greater susceptibility to the attention-capturing effects of negatively-valenced emotional content in girls at risk for MDD from prior history.

Within-Person Temporal Associations Among Self-Reported Physical Activity, Sleep, and Well-Being in College Students.

OBJECTIVE: A holistic understanding of the naturalistic dynamics among physical activity, sleep, emotions, and purpose in life as part of a system reflecting wellness is key to promoting well-being. The main aim of this study was to examine the day-to-day dynamics within this wellness system. METHODS: Using self-reported emotions (happiness, sadness, anger, anxiousness) and physical activity periods collected twice per day, and daily reports of sleep and purpose in life via smartphone experience sampling, more than 28 days as college students ( n = 226 young adults; mean [standard deviation] = 20.2 [1.7] years) went about their daily lives, we examined day-to-day temporal and contemporaneous dynamics using multilevel vector autoregressive models that consider the network of wellness together. RESULTS: Network analyses revealed that higher physical activity on a given day predicted an increase of happiness the next day. Higher sleep quality on a given night predicted a decrease in negative emotions the next day, and higher purpose in life predicted decreased negative emotions up to 2 days later. Nodes with the highest centrality were sadness, anxiety, and happiness in the temporal network and purpose in life, anxiety, and anger in the contemporaneous network. CONCLUSIONS: Although the effects of sleep and physical activity on emotions and purpose in life may be shorter term, a sense of purpose in life is a critical component of wellness that can have slightly longer effects, bleeding into the next few days. High-arousal emotions and purpose in life are central to motivating people into action, which can lead to behavior change.

Large-scale network dynamics in neural response to emotionally negative stimuli linked to serotonin 1A binding in major depressive disorder.

Serotonergic dysfunction is implicated in major depressive disorder (MDD), but the mechanisms of this relationship remain elusive. Serotonin 1A (5-HT1A) autoreceptors regulate brain-wide serotonin neuron firing and are positioned to assert large-scale effects on negative emotion. Here we investigated the relationship between raphe 5-HT1A binding and brain-wide network dynamics of negative emotion. 22 healthy-volunteers (HV) and 27 medication-free participants with MDD underwent positron emission tomography (PET) using [11C]CUMI-101 (CUMI) to quantify 5-HT1A binding in midbrain raphe nuclei and functional magnetic resonance imaging (fMRI) scanning during emotionally negative picture viewing. Causal connectivity across regions responsive to negative emotion was estimated in the fMRI data using a multivariate dynamical systems model. During negative picture viewing, MDD subjects demonstrated significant hippocampal inhibition of amygdala, basal-ganglia, thalamus, orbital frontal cortex, inferior frontal gyrus and dorsomedial prefrontal cortex (IFG, dmPFC). MDD-related connectivity was not associated with raphe 5-HT1A binding. However, greater hippocampal inhibition of amygdala, thalamus, IFG and dmPFC correlated with hippocampal 5-HT1A binding. Correlation between hippocampal 5-HT1A binding and the hippocampal inhibition network was specific to MDD but not HV. MDD and HV groups also differed with respect to the correlation between raphe and hippocampal 5-HT1A binding which was more pronounced in HV. These findings suggest that increased hippocampal network inhibition in MDD is linked to hippocampal serotonergic dysfunction which may in turn arise from disrupted linkage in raphe to hippocampus serotonergic circuitry.

Failure to engage the temporoparietal junction/posterior superior temporal sulcus predicts impaired naturalistic social cognition in schizophrenia.

Schizophrenia is associated with marked impairments in social cognition. However, the neural correlates of these deficits remain unclear. Here we use naturalistic stimuli to examine the role of the right temporoparietal junction/posterior superior temporal sulcus (TPJ-pSTS)-an integrative hub for the cortical networks pertinent to the understanding complex social situations-in social inference, a key component of social cognition, in schizophrenia. Twenty-seven schizophrenia participants and 21 healthy control subjects watched a clip of the film The Good, the Bad and the Ugly while high resolution multiband functional MRI images were collected. We used inter-subject correlation to measure the evoked activity, which we then compared to social cognition as measured by The Awareness of Social Inference Test (TASIT). We also compared between groups the TPJ-pSTS blood oxygen level-dependent activity (i) relationship with the motion content in the film; (ii) synchronization with other cortical areas involved in the viewing of the movie; and (iii) relationship with the frequency of saccades made during the movie. Activation deficits were greatest in middle TPJ (TPJm) and correlated significantly with impaired TASIT performance across groups. Follow-up analyses of the TPJ-pSTS revealed decreased synchronization with other cortical areas, decreased correlation with the motion content of the movie, and decreased correlation with the saccades made during the movie. The functional impairment of the TPJm, a hub area in the middle of the TPJ-pSTS, predicts deficits in social inference in schizophrenia participants by disrupting the integration of visual motion processing into the TPJ. This disrupted integration then affects the use of the TPJ to guide saccades during the visual scanning of the movie clip. These findings suggest that the TPJ may be a treatment target for improving deficits in a key component of social cognition in schizophrenia participants.

Neural precursors of future liking and affective reciprocity.

Why do certain group members end up liking each other more than others? How does affective reciprocity arise in human groups? The prediction of interpersonal sentiment has been a long-standing pursuit in the social sciences. We combined fMRI and longitudinal social network data to test whether newly acquainted group members' reward-related neural responses to images of one another's faces predict their future interpersonal sentiment, even many months later. Specifically, we analyze associations between relationship-specific valuation activity and relationship-specific future liking. We found that one's own future (T2) liking of a particular group member is predicted jointly by actor's initial (T1) neural valuation of partner and by that partner's initial (T1) neural valuation of actor. These actor and partner effects exhibited equivalent predictive strength and were robust when statistically controlling for each other, both individuals' initial liking, and other potential drivers of liking. Behavioral findings indicated that liking was initially unreciprocated at T1 yet became strongly reciprocated by T2. The emergence of affective reciprocity was partly explained by the reciprocal pathways linking dyad members' T1 neural data both to their own and to each other's T2 liking outcomes. These findings elucidate interpersonal brain mechanisms that define how we ultimately end up liking particular interaction partners, how group members' initially idiosyncratic sentiments become reciprocated, and more broadly, how dyads evolve. This study advances a flexible framework for researching the neural foundations of interpersonal sentiments and social relations that-conceptually, methodologically, and statistically-emphasizes group members' neural interdependence.

Neural predictors and effects of cognitive behavioral therapy for depression: the role of emotional reactivity and regulation.

BACKGROUND: Cognitive behavioral therapy (CBT) is an effective treatment for many patients suffering from major depressive disorder (MDD), but predictors of treatment outcome are lacking, and little is known about its neural mechanisms. We recently identified longitudinal changes in neural correlates of conscious emotion regulation that scaled with clinical responses to CBT for MDD, using a negative autobiographical memory-based task. METHODS: We now examine the neural correlates of emotional reactivity and emotion regulation during viewing of emotionally salient images as predictors of treatment outcome with CBT for MDD, and the relationship between longitudinal change in functional magnetic resonance imaging (fMRI) responses and clinical outcomes. Thirty-two participants with current MDD underwent baseline MRI scanning followed by 14 sessions of CBT. The fMRI task measured emotional reactivity and emotion regulation on separate trials using standardized images from the International Affective Pictures System. Twenty-one participants completed post-treatment scanning. Last observation carried forward was used to estimate clinical outcome for non-completers. RESULTS: Pre-treatment emotional reactivity Blood Oxygen Level-Dependent (BOLD) signal within hippocampus including CA1 predicted worse treatment outcome. In contrast, better treatment outcome was associated with increased down-regulation of BOLD activity during emotion regulation from time 1 to time 2 in precuneus, occipital cortex, and middle frontal gyrus. CONCLUSIONS: CBT may modulate the neural circuitry of emotion regulation. The neural correlates of emotional reactivity may be more strongly predictive of CBT outcome. The finding that treatment outcome was predicted by BOLD signal in CA1 may suggest overgeneralized memory as a negative prognostic factor in CBT outcome.

Evidence That Default Network Connectivity During Rest Consolidates Social Information.

Brain regions engaged during social inference, medial prefrontal cortex (MPFC) and tempoparietal junction (TPJ), are also known to spontaneously engage during rest. While this overlap is well known, the social cognitive function of engaging these regions during rest remains unclear. Building on past research suggesting that new information is committed to memory during rest, we explored whether one function of MPFC and TPJ engagement during rest may be to consolidate new social information. MPFC and TPJ regions significantly increased connectivity during rest after encoding new social information (relative to baseline and post nonsocial encoding rest periods). Moreover, greater connectivity between rTPJ and MPFC, as well as other portions of the default network (vMPFC, anterior temporal lobe, and middle temporal gyrus) during post social encoding rest corresponded with superior social recognition and social associative memory. The tendency to engage MPFC and TPJ during rest may tune people towards social learning.

Self-regulation via neural simulation.

Can taking the perspective of other people modify our own affective responses to stimuli? To address this question, we examined the neurobiological mechanisms supporting the ability to take another person's perspective and thereby emotionally experience the world as they would. We measured participants' neural activity as they attempted to predict the emotional responses of two individuals that differed in terms of their proneness to experience negative affect. Results showed that behavioral and neural signatures of negative affect (amygdala activity and a distributed multivoxel pattern reflecting affective negativity) simulated the presumed affective state of the target person. Furthermore, the anterior medial prefrontal cortex (mPFC)-a region implicated in mental state inference-exhibited a perspective-dependent pattern of connectivity with the amygdala, and the multivoxel pattern of activity within the mPFC differentiated between the two targets. We discuss the implications of these findings for research on perspective-taking and self-regulation.

Neural Predictors of Decisions to Cognitively Control Emotion.

Deciding to control emotional responses is a fundamental means of responding to environmental challenges, but little is known about the neural mechanisms that predict the outcome of such decisions. We used fMRI to test whether human brain responses during initial viewing of negative images could be used to predict decisions to regulate affective responses to those images. Our results revealed the following: (1) decisions to regulate were more frequent in individuals exhibiting higher average levels of activity within the amygdala and regions of PFC known a priori to be involved in the cognitive control of emotion and (2) within-person expression of a distributed brain pattern associated with regulating emotion predicted choosing to regulate responses to particular stimuli beyond the predictive value of stimulus intensity or self-reports of emotion. These results demonstrate the behavioral relevance of variability in brain responses to aversive stimuli and provide a model that leverages this variability to predict behavior.SIGNIFICANCE STATEMENT Everyone experiences stressors, but how we respond to them can range from protracted disability to resilience and growth. One key process underlying this variability is the agentic decision to exert control over emotional responses. We present an fMRI-based model predicting decisions to control emotion, finding that activity in brain regions associated with the generation and regulation of emotion was predictive of which people choose to regulate frequently and a distributed brain pattern associated with regulating emotion was predictive of which stimuli regulation was chosen. These brain variables predicted future decisions to regulate emotion beyond what could be predicted from stimulus and self-report variables.

vlPFC-vmPFC-Amygdala Interactions Underlie Age-Related Differences in Cognitive Regulation of Emotion.

Emotion regulation is a critical life skill that develops throughout childhood and adolescence. Despite this development in emotional processes, little is known about how the underlying brain systems develop with age. This study examined emotion regulation in 112 individuals (aged 6-23 years) as they viewed aversive and neutral images using a reappraisal task. On "reappraisal" trials, participants were instructed to view the images as distant, a strategy that has been previously shown to reduce negative affect. On "reactivity" trials, participants were instructed to view the images without regulating emotions to assess baseline emotional responding. During reappraisal, age predicted less negative affect, reduced amygdala responses and inverse coupling between the ventromedial prefrontal cortex (vmPFC) and amygdala. Moreover, left ventrolateral prefrontal (vlPFC) recruitment mediated the relationship between increasing age and diminishing amygdala responses. This negative vlPFC-amygdala association was stronger for individuals with inverse coupling between the amygdala and vmPFC. These data provide evidence that vmPFC-amygdala connectivity facilitates vlPFC-related amygdala modulation across development.

Neural mechanisms tracking popularity in real-world social networks.

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.

Finding Positive Meaning in Negative Experiences Engages Ventral Striatal and Ventromedial Prefrontal Regions Associated with Reward Valuation.

Neuroimaging research has identified systems that facilitate minimizing negative emotion, but how the brain is able to transform the valence of an emotional response from negative to positive is unclear. Behavioral and psychophysiological studies suggest a distinction between minimizing reappraisal, which entails diminishing the arousal elicited by negative stimuli, and positive reappraisal, which instead changes the emotional valence of arousal from negative to positive. Here we show that successful minimizing reappraisal tracked with decreased activity in the amygdala, but successful positive reappraisal tracked with increased activity in regions involved in computing reward value, including the ventral striatum and ventromedial pFC (vmPFC). Moreover, positive reappraisal enhanced positive connectivity between vmPFC and amygdala, and individual differences in positive connectivity between vmPFC and amygdala, ventral striatum, dorsomedial pFC, and dorsolateral pFC predicted greater positive reappraisal success. These data broaden models of emotion regulation as quantitative dampening of negative emotion and identify activity in a network of brain valuation, arousal, and control regions as a neural basis for the ability to create positive meaning from negative experiences.

Emotion regulation deficits in regular marijuana users.

Effective regulation of negative affective states has been associated with mental health. Impaired regulation of negative affect represents a risk factor for dysfunctional coping mechanisms such as drug use and thus could contribute to the initiation and development of problematic substance use. This study investigated behavioral and neural indices of emotion regulation in regular marijuana users (n = 23) and demographically matched nonusing controls (n = 20) by means of an fMRI cognitive emotion regulation (reappraisal) paradigm. Relative to nonusing controls, marijuana users demonstrated increased neural activity in a bilateral frontal network comprising precentral, middle cingulate, and supplementary motor regions during reappraisal of negative affect (P < 0.05, FWE) and impaired emotion regulation success on the behavioral level (P < 0.05). Amygdala-focused analyses further revealed impaired amygdala downregulation in the context of decreased amygdala-dorsolateral prefrontal cortex functional connectivity (P < 0.05, FWE) during reappraisal in marijuana users relative to controls. Together, the present findings could reflect an unsuccessful attempt of compensatory recruitment of additional neural resources in the context of disrupted amygdala-prefrontal interaction during volitional emotion regulation in marijuana users. As such, impaired volitional regulation of negative affect might represent a consequence of, or risk factor for, regular marijuana use. Hum Brain Mapp 38:4270-4279, 2017. © 2017 Wiley Periodicals, Inc.

Social Cognition as Reinforcement Learning: Feedback Modulates Emotion Inference.

Neuroscientific studies of social cognition typically employ paradigms in which perceivers draw single-shot inferences about the internal states of strangers. Real-world social inference features much different parameters: People often encounter and learn about particular social targets (e.g., friends) over time and receive feedback about whether their inferences are correct or incorrect. Here, we examined this process and, more broadly, the intersection between social cognition and reinforcement learning. Perceivers were scanned using fMRI while repeatedly encountering three social targets who produced conflicting visual and verbal emotional cues. Perceivers guessed how targets felt and received feedback about whether they had guessed correctly. Visual cues reliably predicted one target's emotion, verbal cues predicted a second target's emotion, and neither reliably predicted the third target's emotion. Perceivers successfully used this information to update their judgments over time. Furthermore, trial-by-trial learning signals-estimated using two reinforcement learning models-tracked activity in ventral striatum and ventromedial pFC, structures associated with reinforcement learning, and regions associated with updating social impressions, including TPJ. These data suggest that learning about others' emotions, like other forms of feedback learning, relies on domain-general reinforcement mechanisms as well as domain-specific social information processing.

Vicarious Fear Learning Depends on Empathic Appraisals and Trait Empathy.

Empathy and vicarious learning of fear are increasingly understood as separate phenomena, but the interaction between the two remains poorly understood. We investigated how social (vicarious) fear learning is affected by empathic appraisals by asking participants to either enhance or decrease their empathic responses to another individual (the demonstrator), who received electric shocks paired with a predictive conditioned stimulus. A third group of participants received no appraisal instructions and responded naturally to the demonstrator. During a later test, participants who had enhanced their empathy evinced the strongest vicarious fear learning as measured by skin conductance responses to the conditioned stimulus in the absence of the demonstrator. Moreover, this effect was augmented in observers high in trait empathy. Our results suggest that a demonstrator's expression can serve as a "social" unconditioned stimulus (US), similar to a personally experienced US in Pavlovian fear conditioning, and that learning from a social US depends on both empathic appraisals and the observers' stable traits.

Emotions in "Black and White" or Shades of Gray? How We Think About Emotion Shapes Our Perception and Neural Representation of Emotion.

The demands of social life often require categorically judging whether someone's continuously varying facial movements express "calm" or "fear," or whether one's fluctuating internal states mean one feels "good" or "bad." In two studies, we asked whether this kind of categorical, "black and white," thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (a) across participants, judging emotions using a categorical, "black and white" scale relative to judging emotions using a continuous, "shades of gray," scale shifted subjective emotion perception thresholds; (b) these shifts corresponded with activity in brain regions previously associated with affective responding (i.e., the amygdala and ventral anterior insula); and (c) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotions may actively shape the perception and neural representation of the emotions in question.

Implicit Alcohol Approach and Avoidance Tendencies Predict Future Drinking in Problem Drinkers.

BACKGROUND: Addiction is characterized by compulsive drug seeking and substance use, yet many individuals break free of these patterns and change their behavior. Traditional candidate predictors of behavior change/persistence rely on self-reports of factors such as readiness to change. However, explicit measures only characterize top-down influences on behavior. The incentive sensitization model of addition suggests that more implicit, automatic processes, such as the tendency to approach substance cues, play a major role in behavior. METHODS: We examined implicit alcohol approach and avoidance tendencies using a reaction time (RT) task in a sample of problem drinkers with alcohol use disorder (AUD) seeking to reduce heavy drinking. We measured alcohol approach and avoidance tendencies at baseline and at outcome, 12 weeks later. We asked whether alcohol approach and avoidance tendencies (i) changed over time, (ii) related to current drinking, and (iii) predicted changes in drinking from baseline to outcome. RESULTS: Approach and avoidance tendencies did not significantly change over time, nor did they correlate with current drinking, but these tendencies at baseline did predict drinking weeks later. Faster alcohol approach was associated with greater overall drinking at outcome, and faster alcohol avoidance predicted fewer drinking days per week at outcome. Exploratory analyses examined the relationship between approach and avoidance and traditional explicit measures including appraisals of alcohol and motivation to change. Implicit approach tendencies were largely distinct from explicit measures, and approach and avoidance tendencies explained unique variance in outcome drinking. CONCLUSIONS: The current findings suggest that implicit alcohol approach and avoidance tendencies assessed via a simple reaction time task can predict relative changes in drinking weeks later. Given that many explicit measures typically used in treatment studies fail to predict who will change, approach and avoidance tendencies are promising candidates to understand individual differences in treatment responses.