Similarity in evoked responses does not imply similarity in macroscopic network states.

It is commonplace in neuroscience to assume that if two tasks activate the same brain areas in the same way, then they are recruiting the same underlying networks. Yet computational theory has shown that the same pattern of activity can emerge from many different underlying network representations. Here we evaluated whether similarity in activation necessarily implies similarity in network architecture by comparing region-wise activation patterns and functional correlation profiles from a large sample of healthy subjects (N = 242). Participants performed two executive control tasks known to recruit nearly identical brain areas, the color-word Stroop task and the Multi-Source Interference Task (MSIT). Using a measure of instantaneous functional correlations, based on edge time series, we estimated the task-related networks that differed between incongruent and congruent conditions. We found that the two tasks were much more different in their network profiles than in their evoked activity patterns at different analytical levels, as well as for a wide range of methodological pipelines. Our results reject the notion that having the same activation patterns means two tasks engage the same underlying representations, suggesting that task representations should be independently evaluated at both node and edge (connectivity) levels.

As a dynamical system, the brain can encode information at the module (e.g., brain regions) or the network level (e.g., connections between brain regions). This means that two tasks can produce the same pattern of activation, but differ in their network profile. Here we tested this using two tasks with largely similar cognitive requirements. Despite producing nearly identical macroscopic activation patterns, the two tasks produced different functional network profiles. These findings confirm prior theoretical work that similarity in task activation does not imply the same similarity in underlying network states.

A systems identification approach using Bayes factors to deconstruct the brain bases of emotion regulation.

Cognitive reappraisal is fundamental to cognitive therapies and everyday emotion regulation. Analyses using Bayes factors and an axiomatic systems identification approach identified four reappraisal-related components encompassing distributed neural activity patterns across two independent functional magnetic resonance imaging (fMRI) studies (n = 182 and n = 176): (1) an anterior prefrontal system selectively involved in cognitive reappraisal; (2) a fronto-parietal-insular system engaged by both reappraisal and emotion generation, demonstrating a general role in appraisal; (3) a largely subcortical system activated during negative emotion generation but unaffected by reappraisal, including amygdala, hypothalamus and periaqueductal gray; and (4) a posterior cortical system of negative emotion-related regions downregulated by reappraisal. These systems covaried with individual differences in reappraisal success and were differentially related to neurotransmitter binding maps, implicating cannabinoid and serotonin systems in reappraisal. These findings challenge 'limbic'-centric models of reappraisal and provide new systems-level targets for assessing and enhancing emotion regulation.

Stressor-evoked brain activity, cardiovascular reactivity, and subclinical atherosclerosis in midlife adults.

Background: Cardiovascular responses to psychological stressors have been separately associated with preclinical atherosclerosis and hemodynamic brain activity patterns across different studies and cohorts; however, what has not been established is whether cardiovascular stress responses reliably link indicators of stressor-evoked brain activity and preclinical atherosclerosis that have been measured in the same individuals. Accordingly, the present study used cross-validation and predictive modeling to test for the first time whether stressor-evoked systolic blood pressure (SBP) responses statistically mediated the association between concurrently measured brain activity and a vascular marker of preclinical atherosclerosis in the carotid arteries. Methods: 624 midlife adults (aged 28-56 years, 54.97% female) from two different cohorts underwent two information-conflict fMRI tasks, with concurrent SBP measures collected. Carotid artery intima-media thickness (CA-IMT) was measured by ultrasonography. A mediation framework that included harmonization, cross-validation, and penalized principal component regression was then employed, while significant areas in possible direct and indirect effects were identified through bootstrapping. Sensitivity analysis further tested the robustness of findings after accounting for prevailing levels of cardiovascular disease risk and brain imaging data quality control. Results: Task-averaged patterns of hemodynamic brain responses exhibited a generalizable association with CA-IMT, which was mediated by an area-under-the-curve measure of aggregate SBP reactivity. Importantly, this effect held in sensitivity analyses. Implicated brain areas in this mediation included the ventromedial prefrontal cortex, anterior cingulate cortex, insula and amygdala. Conclusions: These novel findings support a link between stressor-evoked brain activity and preclinical atherosclerosis accounted for by individual differences in corresponding levels of stressor-evoked cardiovascular reactivity.

Subjective Social Status and Longitudinal Changes in Systemic Inflammation.

BACKGROUND: Subjective social status (SSS) refers to a person's perception of their social rank relative to others and is cross-sectionally linked to systemic inflammation independently of objective socioeconomic status. PURPOSE: We test the extent to which SSS relates to multiyear changes in inflammation, or if associations differ by race or sex. METHODS: Healthy adults (N = 331; 30-51 years) completed a baseline visit and 278 participants returned for a second visit 2.85 years later. At both visits, participants underwent a fasting blood draw and completed community (SSSC) and US (SSSUS) versions of the MacArthur Scale. Multiple linear regression analyses examined change in interleukin-6 (IL-6) and C-reactive protein (CRP) predicted by each type of SSS, adjusting for time between visits, sex, race, age, body mass index, smoking, baseline inflammation, and objective socioeconomic status. Additional analyses further adjusted for hopelessness and depressive symptoms. Interactions examined moderations by sex and race. RESULTS: Lower SSSC was longitudinally associated with greater IL-6 independently of all covariates, including education and income (ß = -0.06), hopelessness (ß = -0.06), and depressive symptoms (ß = -0.06). Lower SSSUS was longitudinally associated with greater IL-6 independently of demographic covariates including education and income (ß = -0.06), but was slightly attenuated after adjusting for hopelessness (ß = -0.06) and depressive symptoms (ß = -0.06). There were no associations for CRP or moderation by race or sex. CONCLUSIONS: Lower SSS may be associated with greater circulating markers of inflammation over time as suggested by increases in IL-6.

Subjective social status (SSS) refers to how people perceive their social rank compared with others and has been linked to meaningful differences in physical health. Increases in inflammation may contribute to associations between lower SSS and poorer physical health. In a sample of healthy adults, we examined whether SSS was associated with prospective, multiyear changes in markers of systemic inflammation and if this differed by sex or race. We found that adults who perceived their social status as lower than peers in their community exhibited an accelerated increase in interleukin-6, a marker of systemic inflammation, over a 3-year period. When participants were asked to compare themselves to people in the broader USA, the pattern was similar but less robust. Results were independent of individual differences in sociodemographic characteristics including family-adjusted income and education. Findings did not differ by sex or race and were not explained by differences in adiposity and symptoms of depression and hopelessness. Effects for C-reactive protein, a second marker of inflammation, were generally nonsignificant. Although preliminary, findings suggest an immune pathway by which perceived social status may relate to chronic diseases of aging.

Multivariate Brain Activity while Viewing and Reappraising Affective Scenes Does Not Predict the Multiyear Progression of Preclinical Atherosclerosis in Otherwise Healthy Midlife Adults.

Cognitive reappraisal is an emotion regulation strategy that is postulated to reduce risk for atherosclerotic cardiovascular disease (CVD), particularly the risk due to negative affect. At present, however, the brain systems and vascular pathways that may link reappraisal to CVD risk remain unclear. This study thus tested whether brain activity evoked by using reappraisal to reduce negative affect would predict the multiyear progression of a vascular marker of preclinical atherosclerosis and CVD risk: carotid artery intima-media thickness (CA-IMT). Participants were 176 otherwise healthy adults (50.6% women; aged 30-51 years) who completed a functional magnetic resonance imaging task involving the reappraisal of unpleasant scenes from the International Affective Picture System. Ultrasonography was used to compute CA-IMT at baseline and a median of 2.78 (interquartile range, 2.67 to 2.98) years later among 146 participants. As expected, reappraisal engaged brain systems implicated in emotion regulation. Reappraisal also reduced self-reported negative affect. On average, CA-IMT progressed over the follow-up period. However, multivariate and cross-validated machine-learning models demonstrated that brain activity during reappraisal failed to predict CA-IMT progression. Contrary to hypotheses, brain activity during cognitive reappraisal to reduce negative affect does not appear to forecast the progression of a vascular marker of CVD risk. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-021-00098-y.

Affective brain patterns as multivariate neural correlates of cardiovascular disease risk.

This study tested whether brain activity patterns evoked by affective stimuli relate to individual differences in an indicator of pre-clinical atherosclerosis: carotid artery intima-media thickness (CA-IMT). Adults (aged 30-54 years) completed functional magnetic resonance imaging (fMRI) tasks that involved viewing three sets of affective stimuli. Two sets included facial expressions of emotion, and one set included neutral and unpleasant images from the International Affective Picture System (IAPS). Cross-validated, multivariate and machine learning models showed that individual differences in CA-IMT were partially predicted by brain activity patterns evoked by unpleasant IAPS images, even after accounting for age, sex and known cardiovascular disease risk factors. CA-IMT was also predicted by brain activity patterns evoked by angry and fearful faces from one of the two stimulus sets of facial expressions, but this predictive association did not persist after accounting for known cardiovascular risk factors. The reliability (internal consistency) of brain activity patterns evoked by affective stimuli may have constrained their prediction of CA-IMT. Distributed brain activity patterns could comprise affective neural correlates of pre-clinical atherosclerosis; however, the interpretation of such correlates may depend on their psychometric properties, as well as the influence of other cardiovascular risk factors and specific affective cues.

Retrospectively reported childhood physical abuse, systemic inflammation, and resting corticolimbic connectivity in midlife adults.

Childhood abuse confers risk for psychopathology and pathophysiology in midlife through intermediate pathways that remain unclear. Systemic inflammation was tested in the present study as one pathway that may link physical abuse in childhood to the adult functioning of corticolimbic brain circuits broadly implicated in risk for poor mental and physical health. Midlife adults (N = 303; 30-51 years of age; 149 women) without psychiatric, immune, or cardiovascular diagnoses provided retrospective reports of childhood physical abuse. Functional connectivity between corticolimbic brain areas (amygdala, hippocampus, ventromedial prefrontal cortex [vmPFC], anterior cingulate cortex [ACC]) was measured at rest using functional magnetic resonance imaging. Circulating levels of interleukin(IL)-6, a pro-inflammatory cytokine previously linked to childhood abuse and corticolimbic functionality, were measured via blood draw. Consistent with prior studies, retrospectively reported childhood physical abuse was associated positively with circulating IL-6, and negatively with connectivity between the amygdala and vmPFC. IL-6 was also associated negatively with several corticolimbic functional connections, including amygdala-vmPFC connectivity. Moreover, path analyses revealed an indirect effect of IL-6 that partially explained the association between childhood physical abuse and adult amygdala-vmPFC connectivity. Consistent with recent neurobiological models of early life influences on disease risk across the lifespan, associations between childhood physical abuse and adulthood corticolimbic circuit functionality may be partially explained by inflammatory processes.

Ventromedial prefrontal cortex connectivity during and after psychological stress in women.

The ventromedial prefrontal cortex (vmPFC) integrates sensory, affective, memory-related, and social information from diverse brain systems to coordinate behavioral and peripheral physiological responses according to contextual demands that are appraised as stressful. However, the functionality of the vmPFC during stressful experiences is not fully understood. Among 40 female participants, the present study evaluated (a) functional connectivity of the vmPFC during exposure to and recovery following an acute psychological stressor, (b) associations among vmPFC functional connectivity, heart rate, and subjective reports of stress across individuals, and (c) whether patterns of vmPFC functional connectivity were associated with distributed brain networks. Results showed that psychological stress increased vmPFC functional connectivity with individual brain areas implicated in stressor processing (e.g., insula, amygdala, anterior cingulate cortex) and decreased connectivity with the posterior cingulate cortex and thalamus. There were no statistical differences in vmPFC connectivity to individual brain areas during recovery, as compared with baseline. Spatial similarity analyses revealed stressor-evoked increased connectivity of the vmPFC with the so-called dorsal attention, ventral attention, and frontoparietal networks, as well as decreased connectivity with the default mode network. During recovery, vmPFC connectivity increased with the frontoparietal network. Finally, individual differences in heart rate and perceived stress were associated with vmPFC connectivity to the ventral attention, frontoparietal, and default mode networks. Psychological stress appears to alter network-level functional connectivity of the vmPFC in a manner that further relates to individual differences in stressor-evoked cardiovascular and affective reactivity.

Neural Mechanisms Linking Emotion with Cardiovascular Disease.

PURPOSE OF REVIEW: The present review discusses brain circuits that are engaged by negative emotions and possibly linked to cardiovascular disease risk. It describes recent human brain imaging studies that relate activity in these brain circuits to emotional processes, peripheral physiology, preclinical pathophysiology, as well as clinical outcomes. RECENT FINDINGS: Negative emotions and the regulation of negative emotions reliably engage several brain regions that cross-sectional and longitudinal brain imaging studies have associated with CVD risk markers and outcomes. These brain regions include the amygdala, anterior cingulate cortex, medial prefrontal cortex, and insula. Other studies have applied advanced statistical techniques to characterize multivariate patterns of brain activity and brain connectivity that associate with negative emotion and CVD-relevant peripheral physiology. Brain imaging studies on emotion and cardiovascular disease risk are expanding our understanding of the brain-body bases of psychosocial and behavioral risk for cardiovascular disease.

Functional neuroanatomy of peripheral inflammatory physiology: A meta-analysis of human neuroimaging studies.

Communication between the brain and peripheral mediators of systemic inflammation is implicated in numerous psychological, behavioral, and physiological processes. Functional neuroimaging studies have identified brain regions that associate with peripheral inflammation in humans, yet there are open questions about the consistency, specificity, and network characteristics of these findings. The present systematic review provides a meta-analysis to address these questions. Multilevel kernel density analysis of 24 studies (37 statistical maps; 264 coordinates; 457 participants) revealed consistent effects in the amygdala, hippocampus, hypothalamus, striatum, insula, midbrain, and brainstem, as well as prefrontal and temporal cortices. Effects in some regions were specific to particular study designs and tasks. Spatial pattern analysis revealed significant overlap of reported effects with limbic, default mode, ventral attention, and corticostriatal networks, and co-activation analyses revealed functional ensembles encompassing the prefrontal cortex, insula, and midbrain/brainstem. Together, these results characterize brain regions and networks associated with peripheral inflammation in humans, and they provide a functional neuroanatomical reference point for future neuroimaging studies on brain-body interactions.

Data-Driven Subgroups in Depression Derived from Directed Functional Connectivity Paths at Rest.

Depressed patients show abnormalities in brain connectivity at rest, including hyperconnectivity within the default mode network (DMN). However, there is well-known heterogeneity in the clinical presentation of depression that is overlooked when averaging connectivity data. We used data-driven parsing of neural connectivity to reveal subgroups among 80 depressed patients completing resting state fMRI. Directed functional connectivity paths (eg, region A influences region B) within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation, a method shown to accurately recover the direction and presence of connectivity paths in individual participants. Individuals were clustered using community detection on neural connectivity estimates. Subgroups were compared on network features and on clinical and biological/demographic characteristics that influence depression prognosis. Two subgroups emerged. Subgroup A, containing 71% of the patients, showed a typical pattern of connectivity across DMN nodes, as previously reported in depressed patients on average. Subgroup B exhibited an atypical connectivity profile lacking DMN connectivity, with increased dorsal anterior cingulate-driven connectivity paths. Subgroup B members had an over-representation of females (87% of Subgroup B vs 65% of Subgroup A; χ2=3.89, p=0.049), comorbid anxiety diagnoses (42.9% of Subgroup B vs 17.5% of Subgroup A; χ2=5.34, p=.02), and highly recurrent depression (63.2% of Subgroup B vs 31.8% of Subgroup A; χ2=5.38, p=.02). Neural connectivity-based categorization revealed an atypical pattern of connectivity in a depressed patient subset that would be overlooked in group comparisons of depressed and healthy participants, and tracks with clinically relevant phenotypes including anxious depression and episodic recurrence. Data-driven parsing suggests heterogeneous substrates of depression; ideally, future work building on these findings will inform personalized treatment.

Cardiovascular and autonomic reactivity to psychological stress: Neurophysiological substrates and links to cardiovascular disease.

Psychologically stressful experiences evoke changes in cardiovascular physiology that may influence risk for cardiovascular disease (CVD). But what are the neural circuits and intermediate physiological pathways that link stressful experiences to cardiovascular changes that might in turn confer disease risk? This question is important because it has broader implications for our understanding of the neurophysiological pathways that link stressful and other psychological experiences to physical health. This review highlights selected findings from brain imaging studies of stressor-evoked cardiovascular reactivity and CVD risk. Converging evidence across these studies complements animal models and patient lesion studies to suggest that a network of cortical, limbic, and brainstem areas for central autonomic and physiological control are important for generating and regulating stressor-evoked cardiovascular reactivity via visceromotor and viscerosensory mechanisms. Emerging evidence further suggests that these brain areas may play a role in stress-related CVD risk, specifically by their involvement in mediating metabolically-dysregulated or extreme stressor-evoked cardiovascular reactions. Contextually, the research reviewed here offers an example of how brain imaging and health neuroscience methods can be integrated to address open and mechanistic questions about the neurophysiological pathways linking psychological stress and physical health.

Systemic inflammation and resting state connectivity of the default mode network.

The default mode network (DMN) encompasses brain systems that exhibit coherent neural activity at rest. DMN brain systems have been implicated in diverse social, cognitive, and affective processes, as well as risk for forms of dementia and psychiatric disorders that associate with systemic inflammation. Areas of the anterior cingulate cortex (ACC) and surrounding medial prefrontal cortex (mPFC) within the DMN have been implicated specifically in regulating autonomic and neuroendocrine processes that relate to systemic inflammation via bidirectional signaling mechanisms. However, it is still unclear whether indicators of inflammation relate directly to coherent resting state activity of the ACC, mPFC, or other areas within the DMN. Accordingly, we tested whether plasma interleukin (IL)-6, an indicator of systemic inflammation, covaried with resting-state functional connectivity of the DMN among 98 adults aged 30-54 (39% male; 81% Caucasian). Independent component analyses were applied to resting state fMRI data to generate DMN connectivity maps. Voxel-wise regression analyses were then used to test for associations between IL-6 and DMN connectivity across individuals, controlling for age, sex, body mass index, and fMRI signal motion. Within the DMN, IL-6 covaried positively with connectivity of the sub-genual ACC and negatively with a region of the dorsal medial PFC at corrected statistical thresholds. These novel findings offer evidence for a unique association between a marker of systemic inflammation (IL-6) and ACC and mPFC functional connectivity within the DMN, a network that may be important for linking aspects of immune function to psychological and behavioral states in health and disease.

Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood.

BACKGROUND: There is well-known heterogeneity in affective mechanisms in depression that may extend to positive affect. We used data-driven parsing of neural connectivity to reveal subgroups present across depressed and healthy individuals during positive processing, informing targets for mechanistic intervention. METHODS: Ninety-two individuals (68 depressed patients, 24 never-depressed control subjects) completed a sustained positive mood induction during functional magnetic resonance imaging. Directed functional connectivity paths within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation (GIMME), a method shown to accurately recover the direction and presence of connectivity paths in individual participants. During model selection, individuals were clustered using community detection on neural connectivity estimates. Subgroups were externally tested across multiple levels of analysis. RESULTS: Two connectivity-based subgroups emerged: subgroup A, characterized by weaker connectivity overall, and subgroup B, exhibiting hyperconnectivity (relative to subgroup A), particularly among ventral affective regions. Subgroup predicted diagnostic status (subgroup B contained 81% of patients; 50% of control subjects; χ2 = 8.6, p = .003) and default mode network connectivity during a separate resting-state task. Among patients, subgroup B members had higher self-reported symptoms, lower sustained positive mood during the induction, and higher negative bias on a reaction-time task. Symptom-based depression subgroups did not predict these external variables. CONCLUSIONS: Neural connectivity-based categorization travels with diagnostic category and is clinically predictive, but not clinically deterministic. Both patients and control subjects showed heterogeneous, and overlapping, profiles. The larger and more severely affected patient subgroup was characterized by ventrally driven hyperconnectivity during positive processing. Data-driven parsing suggests heterogeneous substrates of depression and possible resilience in control subjects in spite of biological overlap.