Default mode network shows distinct emotional and contextual responses yet common effects of retrieval demands across tasks.

The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from the sensory-motor cortex. It supports memory-based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of association to be retrieved, or both. In a picture association task, participants retrieved semantic associations that were either contextual or emotional in nature. Participants were asked to avoid generating episodic associations. In the generate phase, these associations were retrieved from a novel picture, while in the switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of association being accessed. The frontotemporal and medial temporal DMN showed a preference for emotional and semantic contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient-a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands.

Decreased emotional reactivity after 3-month socio-affective but not attention- or meta-cognitive-based mental training: A randomized, controlled, longitudinal fMRI study.

Meditation-based mental training interventions show physical and mental health benefits. However, it remains unclear how different types of mental practice affect emotion processing at both the neuronal and the behavioural level. In the context of the ReSource project, 332 participants underwent an fMRI scan while performing an emotion anticipation task before and after three 3-month training modules cultivating 1) attention and interoceptive awareness (Presence); 2) socio-affective skills, such as compassion (Affect); 3) socio-cognitive skills, such as theory of mind (Perspective). Only the Affect module led to a significant reduction of experienced negative affect when processing images depicting human suffering. In addition, after the Affect module, participants showed significant increased activation in the right supramarginal gyrus when confronted with negative stimuli. We conclude that socio-affective, but not attention- or meta-cognitive based mental training is specifically effective to improve emotion regulation capabilities when facing adversity.

Differential impact of emotional task relevance on three indices of prioritised processing for fearful and angry facial expressions.

It is commonly assumed that threatening expressions are perceptually prioritised, possessing the ability to automatically capture and hold attention. Recent evidence suggests that this prioritisation depends on the task relevance of emotion in the case of attention holding and for fearful expressions. Using a hybrid attentional blink (AB) and repetition blindness (RB) paradigm we investigated whether task relevance also impacts on prioritisation through attention capture and perceptual salience, and if these effects generalise to angry expressions. Participants judged either the emotion (relevant condition) or gender (irrelevant condition) of two target facial stimuli (fearful, angry or neutral) imbedded in a stream of distractors. Attention holding and capturing was operationalised as modulation of AB deficits by first target (T1) and second target (T2) expression. Perceptual salience was operationalised as RB modulation. When emotion was task-relevant (Experiment 1; N = 29) fearful expressions captured and held attention, and were more perceptually salient than neutral expressions. Angry expressions captured attention, but were less perceptually salient and capable of holding attention than fearful and neutral expressions. When emotion was task-irrelevant (Experiment 2; N = 30), only fearful attention capture and perceptual salience effects remained significant. Our findings highlight the importance for threat-prioritisation research to heed both the type of threat and prioritisation investigated.

Medial prefrontal and anterior cingulate cortical thickness predicts shared individual differences in self-generated thought and temporal discounting.

When deprived of compelling perceptual input, the mind is often occupied with thoughts unrelated to the immediate environment. Previous behavioral research has shown that this self-generated task-unrelated thought (TUT), especially under non-demanding conditions, relates to cognitive capacities such as creativity, planning, and reduced temporal discounting. Despite the frequency and importance of this type of cognition, little is known about its structural brain basis. Using MRI-based cortical thickness measures in 37 participants, we were able to show that individuals with a higher tendency to engage in TUT under low-demanding conditions (but not under high-demanding conditions) show an increased thickness of medial prefrontal cortex (mPFC) and anterior/midcingulate cortex. Thickness of these regions also related to less temporal discounting (TD) of monetary rewards in an economic task, indicative of more patient decision-making. The findings of a shared structural substrate in mPFC and anterior/midcingulate cortex underlying both TUT and TD suggest an important role of these brain regions in supporting the self-generation of information that is unrelated to the immediate environment and which may be adaptive in nature.

Self-report assessment of Positive Appraisal Style (PAS): Development of a process-focused and a content-focused questionnaire for use in mental health and resilience research.

Positive Appraisal Style Theory of Resilience posits that a person's general style of evaluating stressors plays a central role in mental health and resilience. Specifically, a tendency to appraise stressors positively (positive appraisal style; PAS) is theorized to be protective of mental health and thus a key resilience factor. To this date no measures of PAS exist. Here, we present two scales that measure perceived positive appraisal style, one focusing on cognitive processes that lead to positive appraisals in stressful situations (PASS-process), and the other focusing on the appraisal contents (PASS-content). For PASS-process, the items of the existing questionnaires Brief COPE and CERQ-short were analyzed in exploratory and confirmatory factor analyses (EFA, CFA) in independent samples (N = 1157 and N = 1704). The resulting 10-item questionnaire was internally consistent (α = .78, 95% CI [.86, .87]) and showed good convergent and discriminant validity in comparisons with self-report measures of trait optimism, neuroticism, urgency, and spontaneity. For PASS-content, a newly generated item pool of 29 items across stressor appraisal content dimensions (probability, magnitude, and coping potential) were subjected to EFA and CFA in two independent samples (N = 1174 and N = 1611). The resulting 14-item scale showed good internal consistency (α = .87, 95% CI [.86, .87]), as well as good convergent and discriminant validity within the nomological network. The two scales are a new and reliable way to assess self-perceived positive appraisal style in large-scale studies, which could offer key insights into mechanisms of resilience.

Escaping the here and now: evidence for a role of the default mode network in perceptually decoupled thought.

Cognition that is not based on perception can lead to at least two different outcomes. In some situations, cognition that is independent of perception can allow actions to be selected other than those prescribed by immediate perceptual input. In others, cognition can be independent of perception and unrelated to the current behavioral goal allowing thoughts to develop that are largely independent of the actions involved in an external task. The default mode network (DMN) has been implicated in both of these kinds of perceptually decoupled thought. The current experiment used functional magnetic resonance imaging to explore whether a common region of this network was co-activated by both of these states. Both the medial pre-frontal cortex and the posterior cingulate - two major hubs of the DMN - showed greater activity when (i) actions that did not depend upon immediate perceptual input were faster and (ii) when actions based on perceptual input were slower. Together these data suggest that the DMN is important in cognition that is independent from perceptual input regardless of whether such thoughts result in action, or, instead compete with the behavioral goals of the moment.

Individualizing deep dynamic models for psychological resilience data.

Deep learning approaches can uncover complex patterns in data. In particular, variational autoencoders achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project, which features intermittent longitudinal measurements of stressors and mental health, we propose an approach for individualized, dynamic modeling in this latent space. Specifically, we utilize ordinary differential equations (ODEs) and develop a novel technique for obtaining person-specific ODE parameters even in settings with a rather small number of individuals and observations, incomplete data, and a differing number of observations per individual. This technique allows us to subsequently investigate individual reactions to stimuli, such as the mental health impact of stressors. A potentially large number of baseline characteristics can then be linked to this individual response by regularized regression, e.g., for identifying resilience factors. Thus, our new method provides a way of connecting different kinds of complex longitudinal and baseline measures via individualized, dynamic models. The promising results obtained in the exemplary resilience application indicate that our proposal for dynamic deep learning might also be more generally useful for other application domains.

The Frequent Stressor and Mental Health Monitoring-Paradigm: A Proposal for the Operationalization and Measurement of Resilience and the Identification of Resilience Processes in Longitudinal Observational Studies.

Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E-P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure ("stressor reactivity," SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.

Psycho-social factors associated with mental resilience in the Corona lockdown.

The SARS-CoV-2 pandemic is not only a threat to physical health but is also having severe impacts on mental health. Although increases in stress-related symptomatology and other adverse psycho-social outcomes, as well as their most important risk factors have been described, hardly anything is known about potential protective factors. Resilience refers to the maintenance of mental health despite adversity. To gain mechanistic insights about the relationship between described psycho-social resilience factors and resilience specifically in the current crisis, we assessed resilience factors, exposure to Corona crisis-specific and general stressors, as well as internalizing symptoms in a cross-sectional online survey conducted in 24 languages during the most intense phase of the lockdown in Europe (22 March to 19 April) in a convenience sample of N = 15,970 adults. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p < 0.0001). The resilience factor PAS also partly mediated the positive association between perceived social support and resilience, and its association with resilience was in turn partly mediated by the ability to easily recover from stress (both p < 0.0001). In comparison with other resilience factors, good stress response recovery and positive appraisal specifically of the consequences of the Corona crisis were the strongest factors. Preregistered exploratory subgroup analyses (osf.io/thka9) showed that all tested resilience factors generalize across major socio-demographic categories. This research identifies modifiable protective factors that can be targeted by public mental health efforts in this and in future pandemics.

A functional connectome phenotyping dataset including cognitive state and personality measures.

The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits, and cognitive abilities. Specifically, 194 healthy participants (between 20 and 75 years of age) filled out 31 questionnaires, performed 7 tasks, and reported 4 probes of in-scanner mind-wandering. The scanning session included four 15.5-min resting-state functional MRI runs using a multiband EPI sequence and a hig h-resolution structural scan using a 3D MP2RAGE sequence. This dataset constitutes one part of the MPI-Leipzig Mind-Brain-Body database.

Memory Control: A Fundamental Mechanism of Emotion Regulation.

Memories play a ubiquitous role in our emotional lives, both causing vivid emotional experiences in their own right and imbuing perception of the external world with emotional significance. Controlling the emotional impact of memories therefore poses a major emotion-regulation challenge, suggesting that there might be a hitherto unexplored link between the neurocognitive mechanisms underlying memory control (MC) and emotion regulation. We present here a theoretical account of how the mechanisms of MC constitute core component processes of cognitive emotion regulation (CER), and how this observation may help to understand its basic mechanisms and their disruption in psychiatric disorders.

Endogenous emotion generation ability is associated with the capacity to form multimodal internal representations.

Training the capacity to self-generate emotions can be a potent "vaccine" against negative stressors and be an effective intervention for affective psychopathology. However, due to a lack of knowledge about sources of individual differences in generation abilities, it is unclear how to optimally design such interventions. We investigated one potential source of variation, namely preference for using different information modalities (Visual Imagery, Auditory Imagery, Bodily Interoception, and Semantic Analysis). A representative sample of 293 participants self-induced positive and negative emotional states, freely choosing to use these modalities singly or in combination. No evidence was found for modality usage being associated with differential efficacy at generating of positive or negative emotion. Rather, usage of all modalities (except Auditory Imagery) predicted success at generation of both positive and negative emotional states. Increasing age predicted capacity to generate, especially negative, emotions. While no specific combinations of modalities were superior, the overall degree to which participants adopted multimodal implementations did predict generation efficacy. These findings inform interventions aimed at improving emotional self-generation, suggesting these must be mindful of individual differences in generation abilities and implementation tendencies, and that they should focus on enhancing the capacity to use multiple modalities.

Structural changes in socio-affective networks: Multi-modal MRI findings in long-term meditation practitioners.

Our goal was to assess the effects of long-term mental training in socio-affective skills on structural brain networks. We studied a group of long-term meditation practitioners (LTMs) who have focused on cultivating socio-affective skills using loving-kindness and compassion meditation for an average of 40k h, comparing these to meditation-naïve controls. To maximize homogeneity of prior practice, LTMs were included only if they had undergone extensive full-time meditation retreats in the same center. MRI-based cortical thickness analysis revealed increased thickness in the LTM cohort relative to meditation-native controls in fronto-insular cortices. To identify functional networks relevant for the generation of socio-affective states, structural imaging analysis were complemented by fMRI analysis in LTMs, showing amplitude increases during a loving-kindness meditation session relative to non-meditative rest in multiple prefrontal and insular regions bilaterally. Importantly, functional findings partially overlapped with regions of cortical thickness increases in the left ventrolateral prefrontal cortex and anterior insula, suggesting that these regions may play a central role in the generation of emotional states relevant for the meditative practice. Our multi-modal MRI approach revealed structural changes in LTMs who have cultivated loving-kindness and compassion for a significant period of their life in functional networks activated by these practices. These preliminary cross-sectional findings motivate future longitudinal work studying brain plasticity following the regular practice of skills aiming at enhancing human altruism and prosocial motivation.

The neural component-process architecture of endogenously generated emotion.

Despite the ubiquity of endogenous emotions and their role in both resilience and pathology, the processes supporting their generation are largely unknown. We propose a neural component process model of endogenous generation of emotion (EGE) and test it in two functional magnetic resonance imaging (fMRI) experiments (N = 32/293) where participants generated and regulated positive and negative emotions based on internal representations, usin self-chosen generation methods. EGE activated nodes of salience (SN), default mode (DMN) and frontoparietal control (FPCN) networks. Component processes implemented by these networks were established by investigating their functional associations, activation dynamics and integration. SN activation correlated with subjective affect, with midbrain nodes exclusively distinguishing between positive and negative affect intensity, showing dynamics consistent generation of core affect. Dorsomedial DMN, together with ventral anterior insula, formed a pathway supporting multiple generation methods, with activation dynamics suggesting it is involved in the generation of elaborated experiential representations. SN and DMN both coupled to left frontal FPCN which in turn was associated with both subjective affect and representation formation, consistent with FPCN supporting the executive coordination of the generation process. These results provide a foundation for research into endogenous emotion in normal, pathological and optimal function.

Cognitive flexibility, heart rate variability, and resilience predict fine-grained regulation of arousal during prolonged threat.

Emotion regulation in the ongoing presence of a threat is essential for adaptive behavior. Threatening situations change over time and, as a consequence, require a fine-tuned, dynamic regulation of arousal to match the current state of the environment. Constructs such as cognitive flexibility, heart rate variability, and resilience have been proposed as resources for adaptive emotion regulation, especially in a moment-to-moment fashion. Nevertheless, none of these constructs has been empirically related to the dynamic regulation of arousal as it unfolds over the course of a prolonged threatening episode. Here, we do so by placing participants in a threatening and evolving immersive virtual environment called Room 101, while recording their skin conductance. Subsequently, participants rated their subjective arousal continuously over the course of the experience. Participants who had shown greater cognitive flexibility in a separate task (i.e., fewer task-switching costs when switching to evaluating the valence of positive stimuli) showed better regulation of physiological arousal (skin conductance level), during less-threatening phases of Room 101. Individuals with higher trait resilience and individuals with higher resting heart rate variability showed more regulation in terms of their subjective arousal experience. The results indicate that emotional, cognitive, and physiological flexibility support nuanced adaptive regulation of objective and experienced arousal in the ongoing presence of threats. Furthermore, the results indicate that these forms of flexibility differentially affect automatic and objective versus reflective and subjective processes.

Compassion-based emotion regulation up-regulates experienced positive affect and associated neural networks.

Emotion regulation research has primarily focused on techniques that attenuate or modulate the impact of emotional stimuli. Recent evidence suggests that this mode regulation can be problematic in the context of regulation of emotion elicited by the suffering of others, resulting in reduced emotional connectedness. Here, we investigated the effects of an alternative emotion regulation technique based on the up-regulation of positive affect via Compassion-meditation on experiential and neural affective responses to depictions of individuals in distress, and compared these with the established emotion regulation strategy of Reappraisal. Using fMRI, we scanned 15 expert practitioners of Compassion-meditation either passively viewing, or using Compassion-meditation or Reappraisal to modulate their emotional reactions to film clips depicting people in distress. Both strategies effectively, but differentially regulated experienced affect, with Compassion primarily increasing positive and Reappraisal primarily decreasing negative affect. Imaging results showed that Compassion, relative to both passive-viewing and Reappraisal increased activation in regions involved in affiliation, positive affect and reward processing including ventral striatum and medial orbitfrontal cortex. This network was shown to be active prior to stimulus presentation, suggesting that the regulatory mechanism of Compassion is the stimulus-independent endogenous generation of positive affect.

Shaped by the Past: The Default Mode Network Supports Cognition that Is Independent of Immediate Perceptual Input.

Although many different accounts of the functions of the default mode network (DMN) have been proposed, few can adequately account for the spectrum of different cognitive functions that utilize this network. The current study used functional magnetic resonance imaging (fMRI) to explore the hypothesis that the role of the DMN in higher order cognition is to allow cognition to be shaped by information from stored representations rather than information in the immediate environment. Using a novel task paradigm, we observed increased BOLD activity in regions of the medial prefrontal cortex and posterior cingulate cortex when individuals made decisions on the location of shapes from the prior trial and decreased BOLD activity when individuals made decisions on the location of shapes on the current trial. These data are inconsistent with views of the DMN as a task-negative system or one that is sensitive only to stimuli with strong personal or emotional ties. Instead the involvement of the DMN when people make decisions about where a shape was, rather than where it is now, supports the hypothesis that the core hubs of the DMN allow cognition to be guided by information other than the immediate perceptual input. We propose that a variety of different forms of higher order thought (such as imagining the future or considering the perspective of another person) engage the DMN because these more complex introspective forms of higher order thought all depend on the capacity for cognition to be shaped by representations that are not present in the external environment.

Empathy circuits.

The social neuroscientific investigation of empathy has revealed that the same neural networks engaged during first-hand experience of affect subserve empathic responses. Recent meta-analyses focusing on empathy for pain for example reliably identified a network comprising anterior insula and anterior midcingulate cortex. Moreover, recent studies suggest that the generation of empathy is flexibly supported by networks involved in action simulation and mentalizing depending on the information available in the environment. Further, empathic responses are modulated by many factors including the context they occur in. Recent work shows how this modulation can be afforded by the engagement of antagonistic motivational systems or by cognitive control circuits, and these modulatory systems can also be employed in efforts to regulate one's empathic responses.

How self-generated thought shapes mood--the relation between mind-wandering and mood depends on the socio-temporal content of thoughts.

Recent work has highlighted that the generation of thoughts unrelated to the current environment may be both a cause and a consequence of unhappiness. The current study used lag analysis to examine whether the relationship between self-generated thought and negative affect depends on the content of the thoughts themselves. We found that the emotional content could strongly predict subsequent mood (e.g. negative thoughts were associated with subsequent negative mood). However, this direct relationship was modulated by the socio-temporal content of the thoughts: thoughts that were past- and other-related were associated with subsequent negative mood, even if current thought content was positive. By contrast, future- and self-related thoughts preceded improvements of mood, even when current thought content was negative. These results highlight the important link between self-generated thought and mood and suggest that the socio-temporal content plays an important role in determining whether an individual's future affective state will be happy or sad.