Affective brain patterns as multivariate neural correlates of cardiovascular disease risk

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.

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.

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.

Psychological stress and the longitudinal progression of subclinical atherosclerosis

OBJECTIVE

In a midlife sample of adults, the present study tested the extent to which changes in psychological stress relate to the progression of subclinical cardiovascular disease over multiple years and explored the potential moderating role of cardiometabolic risk.

METHOD

Participants were screened to exclude those with clinical cardiovascular, respiratory, metabolic, and other chronic illnesses, as well as those taking psychotropic, cardiovascular, lipid, and glucose control medications. At baseline (N = 331) and then again at follow-up an average of 3 years later (N = 260), participants completed the 10-item Perceived Stress Scale, underwent assessments of their cardiometabolic risk, and underwent ultrasonography to measure carotid artery intima-media thickness (IMT), which is a surrogate indicator of subclinical atherosclerosis.

RESULTS

Regression models showed that the change in psychological stress from baseline to follow-up was positively associated with the corresponding change in IMT, with covariate control for age at baseline, sex at birth, and variability in length of follow-up across participants. Cardiometabolic risk factors did not statistically moderate this longitudinal association. In exploratory analyses, cardiometabolic risk factors also did not statistically mediate this association.

CONCLUSION

These longitudinal findings suggest that increases in psychological stress in midlife relate to corresponding increases in subclinical atherosclerosis. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Reliability of task-based fMRI in the dorsal horn of the human spinal cord

The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across two consecutive days in 40 healthy volunteers. We assessed the test-retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat pain stimuli (1s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with good reliability across days. Taken together, these results demonstrate that heat pain stimuli as short as one second are able to evoke a robust and spatially specific BOLD response, which is however strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.

Beyond Neighborhood Disadvantage: Local Resources, Green Space, Pollution, and Crime as Residential Community Correlates of Cardiovascular Risk and Brain Morphology in Midlife Adults

OBJECTIVE

Residing in communities characterized by socioeconomic disadvantage confers risk of cardiometabolic diseases. Residing in disadvantaged communities may also confer the risk of neurodegenerative brain changes via cardiometabolic pathways. This study tested whether features of communities-apart from conventional socioeconomic characteristics-relate not only to cardiometabolic risk but also to relative tissue reductions in the cerebral cortex and hippocampus.

METHODS

Participants were 699 adults aged 30 to 54 years (340 women; 22.5% non-White) whose addresses were geocoded to compute community indicators of socioeconomic disadvantage, as well as air and toxic chemical pollutant exposures, homicide rates, concentration of employment opportunities, land use (green space), and availability of supermarkets and local resources. Participants also underwent assessments of cortical and hippocampal volumes and cardiometabolic risk factors (adiposity, blood pressure, fasting glucose, and lipids).

RESULTS

Multilevel structural equation modeling demonstrated that cardiometabolic risk was associated with community disadvantage ( β = 0.10, 95% confidence interval [CI] = 0.01 to 0.18), as well as chemical pollution ( β = 0.11, 95% CI = 0.02 to 0.19), homicide rates ( β = 0.10, 95% CI = 0.01 to 0.18), employment opportunities ( β = -0.16, 95% CI = -0.27 to -0.04), and green space ( β = -0.12, 95% CI = -0.20 to -0.04). Moreover, cardiometabolic risk indirectly mediated the associations of several of these community features and brain tissue volumes. Some associations were nonlinear, and none were explained by participants' individual-level socioeconomic characteristics.

CONCLUSIONS

Features of communities other than conventional indicators of socioeconomic disadvantage may represent nonredundant correlates of cardiometabolic risk and brain tissue morphology in midlife.

Limbic Responses to Aversive Visual Stimuli during the Acute and Recovery Phase of Takotsubo Syndrome

The role of the limbic system in the acute phase and during the recovery of takotsubo syndrome needs further clarification. In this longitudinal study, anatomical and task-based functional magnetic resonance imaging of the brain was performed during an emotional picture paradigm in 19 postmenopausal female takotsubo syndrome patients in the acute and recovery phases in comparison to sex- and aged-matched 15 healthy controls and 15 patients presenting with myocardial infarction. Statistical analyses were performed based on the general linear model where aversive and positive picture conditions were included in order to reveal group differences during encoding of aversive versus positive pictures and longitudinal changes. In the acute phase, takotsubo syndrome patients showed a lower response in regions involved in affective and cognitive emotional processes (e.g., insula, thalamus, frontal cortex, inferior frontal gyrus) while viewing aversive versus positive pictures compared to healthy controls and patients presenting with myocardial infarction. In the recovery phase, the response in these brain regions normalized in takotsubo syndrome patients to the level of healthy controls, whereas patients 8–12 weeks after myocardial infarction showed lower responses in the limbic regions (mainly in the insula, frontal regions, thalamus, and inferior frontal gyrus) compared to healthy controls and takotsubo syndrome patients. In conclusion, compared to healthy controls and patients suffering from acute myocardial infarction, limbic responses to aversive visual stimuli are attenuated during the acute phase of takotsubo syndrome, recovering within three months. Reduced functional brain responses in the recovery phase after a myocardial infarction need further investigation.

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.

Limits of decoding mental states with fMRI

A growing number of studies claim to decode mental states using multi-voxel decoders of brain activity. It has been proposed that the fixed, fine-grained, multi-voxel patterns in these decoders are necessary for discriminating between and identifying mental states. Here, we present evidence that the efficacy of these decoders might be overstated. Across various tasks, decoder patterns were spatially imprecise, as decoder performance was unaffected by spatial smoothing; 90% redundant, as selecting a random 10% of a decoder's constituent voxels recovered full decoder performance; and performed similarly to brain activity maps used as decoders. We distinguish decoder performance in discriminating between mental states from performance in identifying a given mental state, and show that even when discrimination performance is adequate, identification can be poor. Finally, we demonstrate that simple and intuitive similarity metrics explain 91% and 62% of discrimination performance within- and across-subjects, respectively. These findings indicate that currently used across-subject decoders of mental states are superfluous and inappropriate for decision-making.

Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults

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Brain measures from MRI do not improve Framingham Risk Score prediction of CA-IMT.

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Prediction stacking is a flexible approach to determine added predictive utility.

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Multimodal stacking can be applied to individual difference factors.

Background

Human neuroimaging evidence suggests that cardiovascular disease (CVD) risk may relate to functional and structural features of the brain. The present study tested whether combining functional and structural (multimodal) brain measures, derived from magnetic resonance imaging (MRI), would yield a multivariate brain biomarker that reliably predicts a subclinical marker of CVD risk, carotid-artery intima-media thickness (CA-IMT).

Methods

Neuroimaging, cardiovascular, and demographic data were assessed in 324 midlife and otherwise healthy adults who were free of (a) clinical CVD and (b) use of medications for chronic illnesses (aged 30–51 years, 49% female). We implemented a prediction stacking algorithm that combined multimodal brain imaging measures and Framingham Risk Scores (FRS) to predict CA-IMT. We included imaging measures that could be easily obtained in clinical settings: resting state functional connectivity and structural morphology measures from T1-weighted images.

Results

Our models reliably predicted CA-IMT using FRS, as well as for several individual MRI measures; however, none of the individual MRI measures outperformed FRS. Moreover, stacking functional and structural brain measures with FRS did not boost prediction accuracy above that of FRS alone.

Conclusions

Combining multimodal functional and structural brain measures through a stacking algorithm does not appear to yield a reliable brain biomarker of subclinical CVD, as reflected by CA-IMT.

Integrating across neuroimaging modalities boosts prediction accuracy of cognitive ability

Variation in cognitive ability arises from subtle differences in underlying neural architecture. Understanding and predicting individual variability in cognition from the differences in brain networks requires harnessing the unique variance captured by different neuroimaging modalities. Here we adopted a multi-level machine learning approach that combines diffusion, functional, and structural MRI data from the Human Connectome Project (N = 1050) to provide unitary prediction models of various cognitive abilities: global cognitive function, fluid intelligence, crystallized intelligence, impulsivity, spatial orientation, verbal episodic memory and sustained attention. Out-of-sample predictions of each cognitive score were first generated using a sparsity-constrained principal component regression on individual neuroimaging modalities. These individual predictions were then aggregated and submitted to a LASSO estimator that removed redundant variability across channels. This stacked prediction led to a significant improvement in accuracy, relative to the best single modality predictions (approximately 1% to more than 3% boost in variance explained), across a majority of the cognitive abilities tested. Further analysis found that diffusion and brain surface properties contribute the most to the predictive power. Our findings establish a lower bound to predict individual differences in cognition using multiple neuroimaging measures of brain architecture, both structural and functional, quantify the relative predictive power of the different imaging modalities, and reveal how each modality provides unique and complementary information about individual differences in cognitive function.

Internal reliability of blame-related functional MRI measures in major depressive disorder

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Self-blame-related fMRI measures were previously validated in depressive disorders.

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Reproducibility and internal consistency as a measure of reliability were examined.

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Whilst simple fMRI measures exhibited fair reliability, complex measures did not.

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Yet, complex measures showed reproducible clinical validity at the group level.

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Connectivity measures, that balance reliability and validity better, are needed.

Background

Methods

Results

Conclusions