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Obtaining lower gains than rejected alternatives during decision making evokes feelings of regret, whereas higher gains elicit gratification. Although decision-related emotions produce lingering effects on mental state, neuroscience research has generally focused on transient brain responses to positive or negative events, but ignored more sustained consequences of emotional episodes on subsequent brain states. We investigated how spontaneous brain activity and functional connectivity at rest are modulated by postdecision regret and gratification in 18 healthy human subjects using a gambling task in fMRI. Differences between obtained and unobtained outcomes were manipulated parametrically to evoke different levels of regret or gratification. We investigated how individual personality traits related to depression and rumination affected these responses. Medial and ventral prefrontal areas differentially responded to favorable and unfavorable outcomes during the gambling period. More critically, during subsequent rest, rostral anterior and posterior cingulate cortex, ventral striatum, and insula showed parametric response to the gratification level of preceding outcomes. Functional coupling of posterior cingulate with striatum and amygdala was also enhanced during rest after high gratification. Regret produced distinct changes in connectivity of subgenual cingulate with orbitofrontal cortex and thalamus. Interestingly, individual differences in depressive traits and ruminations correlated with activity of the striatum after gratification and orbitofrontal cortex after regret, respectively. By revealing lingering effects of decision-related emotions on key nodes of resting state networks, our findings illuminate how such emotions may influence self-reflective processing and subsequent behavioral adjustment, but also highlight the malleability of resting networks in emotional contexts. [ABSTRACT FROM AUTHOR]

Abstract: Functional connectivity analysis of fMRI data can reveal synchronised activity between anatomically distinct brain regions. Here, we extract the characteristic connectivity signatures of different brain states to perform classification, allowing us to decode the different states based on the functional connectivity patterns. Our approach is based on polythetic decision trees, which combine powerful discriminative ability with interpretability of results. We also propose to use ensemble of classifiers within specific frequency subbands, and show that they bring systematic improvement in classification accuracy. Exploiting multi-band classification of connectivity graphs is also proposed, and we explain theoretical reasons why the technique could bring further improvement in classification performance. The choice of decision trees as classifier is shown to provide a practical way to identify a subset of connections that distinguishes best between the conditions, permitting the extraction of very compact representations for differences between brain states, which we call discriminative graphs. Our experimental results based on strict train/test separation at all stages of processing show that the method is applicable to inter-subject brain decoding with relatively low error rates for the task considered. [Copyright &y& Elsevier]

Abstract: The functional properties of resting brain activity are poorly understood, but have generally been related to self-monitoring and introspective processes. Here we investigated how emotionally positive and negative information differentially influenced subsequent brain activity at rest. We acquired fMRI data in 15 participants during rest periods following fearful, joyful, and neutral movies. Several brain regions were more active during resting than during movie-watching, including posterior/anterior cingulate cortices (PCC, ACC), bilateral insula and inferior parietal lobules (IPL). Functional connectivity at different frequency bands was also assessed using a wavelet correlation approach and small-world network analysis. Resting activity in ACC and insula as well as their coupling were strongly enhanced by preceding emotions, while coupling between ventral-medial prefrontal cortex and amygdala was selectively reduced. These effects were more pronounced after fearful than joyful movies for higher frequency bands. Moreover, the initial suppression of resting activity in ACC and insula after emotional stimuli was followed by a gradual restoration over time. Emotions did not affect IPL average activity but increased its connectivity with other regions. These findings reveal specific neural circuits recruited during the recovery from emotional arousal and highlight the complex functional dynamics of default mode networks in emotionally salient contexts. [Copyright &y& Elsevier]

Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to characterize the interactions among cortical networks that are sensitive to working memory load since such interactions can also hint at the impaired dynamics in patients with poor working memory performance. Functional connectivity is a powerful tool used to investigate coordinated activity among local and distant brain regions. Here, we identified connectivity footprints that differentiate task states representing distinct working memory load levels. We employed linear support vector machines to decode working memory load from task-based functional connectivity matrices in 177 healthy adults. Using neighborhood component analysis, we also identified the most important connectivity pairs in classifying high and low working memory loads. We found that between-network coupling among frontoparietal, ventral attention and default mode networks, and within-network connectivity in ventral attention network are the most important factors in classifying low vs. high working memory load. Task-based within-network connectivity profiles at high working memory load in ventral attention and default mode networks were the most predictive of load-related increases in response times. Our findings reveal the large-scale impact of working memory load on the cerebral cortex and highlight the complex dynamics of intrinsic brain networks during active task states. • Working memory load can be reliably decoded from cortex-wide task functional connectivity matrices using machine learning. • Coupling among frontoparietal, ventral attention and default networks is the most discriminative of high vs. low load. • Coupling within ventral attention and default networks at high load best predicts load-related increases in response time. [ABSTRACT FROM AUTHOR]

Inertia, together with intensity and valence, is an important component of emotion. We tested whether positive and negative events generate lingering changes in subsequent brain responses to unrelated threat stimuli and investigated the impact of individual anxiety. We acquired fMRI data while participants watched positive or negative movie-clips and subsequently performed an unrelated task with fearful and neutral faces. We quantified changes in amygdala reactivity to fearful faces as a function of the valence of preceding movies and cumulative neural activity evoked during them. We demonstrate that amygdala responses to emotional movies spill over to subsequent processing of threat information in a valence-specific manner: negative movies enhance later amygdala activation whereas positive movies attenuate it. Critically, the magnitude of such changes is predicted by a measure of cumulative amygdala responses to the preceding positive or negative movies. These effects appear independent of overt attention, are regionally limited to amygdala, with no changes in functional connectivity. Finally, individuals with higher state anxiety displayed stronger modulation of amygdala reactivity by positive movies. These results suggest that intensity and valence of emotional events as well as anxiety levels promote local changes in amygdala sensitivity to threat, highlighting the importance of past experience in shaping future affective reactivity. [ABSTRACT FROM AUTHOR]

Objective: Numerous adverse prenatal exposures have been individually associated with risk for psychiatric illness in the offspring. However, such exposures frequently co-occur, raising questions about their cumulative impact. We evaluated effects of cumulative adverse prenatal exposure burden on psychopathology risk in school-aged children. Methods: Using baseline surveys from the U.S.-based Adolescent Brain and Cognitive Development (ABCD) Study (7,898 non-adopted, unrelated children from 21 sites, age 9–10, and their primary caregivers), we examined 8 retrospectively-reported adverse prenatal exposures in relation to caregiver-reported total and subscale Child Behavior Checklist (CBCL) scores. We also assessed cumulative effects of these factors on CBCL total as a continuous measure, as well as on odds of clinically significant psychopathology (CBCL total ≥60), in both the initial set and a separate ABCD sample comprising an additional 696 sibling pairs. Analyses were conducted before and after adjustment for 14 demographic and environmental covariates. Results: In minimally and fully adjusted models, 6 exposures (unplanned pregnancy; maternal alcohol, marijuana, and tobacco use early in pregnancy; pregnancy complications; and birth complications) independently associated with significant but small increases in CBCL total score. Among these 6, none increased the odds of crossing the threshold for clinically significant symptoms by itself. However, odds of exceeding this threshold became significant with 2 exposures (OR = 1.86, 95% CI 1.47–2.36), and increased linearly with each level of exposure (OR = 1.39, 95% CI 1.31–1.47), up to 3.53-fold for ≥4 exposures versus none. Similar effects were observed in confirmatory analysis among siblings. Within sibling pairs, greater discordance for exposure load associated with greater CBCL total differences, suggesting that results were not confounded by unmeasured family-level effects. Conclusion: Children exposed to multiple common, adverse prenatal events showed dose-dependent increases in broad, clinically significant psychopathology at age 9–10. Fully prospective studies are needed to confirm and elaborate upon this pattern. [ABSTRACT FROM AUTHOR]