Inflexibly sustained negative affect and rumination independently link default mode network efficiency to subclinical depressive symptoms

Reciprocal effects between negative affect and emotion regulation in daily life

The extended process model of emotion regulation provides a framework for understanding how emotional experiences and emotion regulation (ER) mutually influence each other over time. To investigate this reciprocal relationship, 202 adults completed a ten-day experience-sampling survey capturing levels of negative affect (NA) experience and use of ten ER strategies in daily life. Residual dynamic structural equation models (DSEMs) were used to examine within-person cross-lagged and autoregressive effects of NA and ER (strategy use and between-strategy variability). Results showed that NA predicted lower between-strategy variability, lower subsequent use of acceptance and problem-solving, but higher subsequent use of rumination and worry. Moreover, reappraisal and between-strategy variability predicted lower subsequent NA levels, while expressive suppression and worry predicted higher subsequent NA levels. Stable autoregressive effects were found for NA and for maladaptive ER strategies (e.g., rumination and worry). Exploratory correlation analyses revealed positive associations between NA inertia and maladaptive ER strategies. Together, these findings provide evidence of a dynamic interplay between NA and ER. This work deepens how we understand the challenges of applying ER strategies in daily life. Future clinical and translational research should consider these dynamic perspectives on ER and affect.

Brain network hierarchy reorganization in subthreshold depression

BACKGROUND

Hierarchy is the organizing principle of human brain network. How network hierarchy changes in subthreshold depression (StD) is unclear. The aim of this study was to investigate the altered brain network hierarchy and its clinical significance in patients with StD.

METHODS

A total of 43 patients with StD and 43 healthy controls matched for age, gender and years of education participated in this study. Alterations in the hierarchy of StD brain networks were depicted by connectome gradient analysis. We assessed changes in network hierarchy by comparing gradient scores in each network in patients with StD and healthy controls. The study compared different brain subdivisions if there was a different network. Finally, we analysed the relationship between the altered gradient scores and clinical characteristics.

RESULTS

Patients with StD had contracted network hierarchy and suppressed cortical range gradients. In the principal gradient, the gradient scores of default mode network were significantly reduced in patients with StD compared to controls. In the default network, the subdivisions of reduced gradient scores were mainly located in the precuneus, superior temporal gyrus, and anterior and posterior cingulate gyrus. Reduced gradient scores in the default mode network, the anterior and posterior cingulate gyrus were correlated with severity of depression.

CONCLUSIONS

The network hierarchy of the StD changed and was significantly correlated with depressive symptoms and severity. These results provided new insights into further understanding of the neural mechanisms of StD.

Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping

A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Aberrant degree centrality profiles during rumination in major depressive disorder

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self-reported rumination trait and the functional coupling among a network of brain regions using resting-state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher-order psychological processes such as rumination. During an MRI scan, individuals with MDD (N = 45) and healthy controls (HC, N = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex-wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network-wise seed-based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self-reported in-scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in-scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

Pain-free default mode network connectivity contributes to tonic experimental pain intensity beyond the role of negative mood and other pain-related factors

BACKGROUND

Alterations in the default mode network (DMN) connectivity across pain stages suggest a possible DMN involvement in the transition to persistent pain.

AIM

This study examined whether pain-free DMN connectivity at lower alpha oscillations (8-10 Hz) accounts for a unique variation in experimental peak pain intensity beyond the contribution of factors known to influence pain intensity.

METHODS

Pain-free DMN connectivity was measured with electroencephalography prior to 1 h of capsaicin-evoked pain using a topical capsaicin patch on the right forearm. Pain intensity was assessed on a (0-10) numerical rating scale and the association between peak pain intensity and baseline measurements was examined using hierarchical multiple regression in 52 healthy volunteers (26 women). The baseline measurements consisted of catastrophizing (helplessness, rumination, magnification), vigilance, depression, negative and positive affect, sex, age, sleep, fatigue, thermal and mechanical pain thresholds and DMN connectivity (medial prefrontal cortex [mPFC]-posterior cingulate cortex [PCC], mPFC-right angular gyrus [rAG], mPFC-left Angular gyrus [lAG], rAG-mPFC and rAG-PCC).

RESULTS

Pain-free DMN connectivity increased the explained variance in peak pain intensity beyond the contribution of other factors (ΔR2  = 0.10, p = 0.003), with the final model explaining 66% of the variation (R2  = 0.66, ANOVA: p < 0.001). In this model, negative affect (β = 0.51, p < 0.001), helplessness (β = 0.49, p = 0.007), pain-free mPFC-lAG connectivity (β = 0.36, p = 0.003) and depression (β = -0.39, p = 0.009) correlated significantly with peak pain intensity. Interestingly, negative affect and depression, albeit both being negative mood indices, showed opposing relationships with peak pain intensity.

CONCLUSIONS

This work suggests that pain-free mPFC-lAG connectivity (at lower alpha) may contribute to individual variations in pain-related vulnerability.

SIGNIFICANCE

These findings could potentially lead the way for investigations in which DMN connectivity is used in identifying individuals more likely to develop chronic pain.

Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones

Together, data from brain scanners and smartphones have sufficient coverage of biology, psychology, and environment to articulate between-person differences in the interplay within and across biological, psychological, and environmental systems thought to underlie psychopathology. An important next step is to develop frameworks that combine these two modalities in ways that leverage their coverage across layers of human experience to have maximum impact on our understanding and treatment of psychopathology. We review literature published in the last 3 years highlighting how scanners and smartphones have been combined to date, outline and discuss the strengths and weaknesses of existing approaches, and sketch a network science framework heretofore underrepresented in work combining scanners and smartphones that can push forward our understanding of health and disease.

Abnormal Reginal Homogeneity in Left Anterior Cingulum Cortex and Precentral Gyrus as a Potential Neuroimaging Biomarker for First-Episode Major Depressive Disorder

OBJECTIVE

There is no objective method to diagnose major depressive disorder (MDD). This study explored the neuroimaging biomarkers using the support vector machine (SVM) method for the diagnosis of MDD.

METHODS

52 MDD patients and 45 healthy controls (HCs) were involved in resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Imaging data were analyzed with the regional homogeneity (ReHo) and SVM methods.

RESULTS

Compared with HCs, MDD patients showed increased ReHo in the left anterior cingulum cortex (ACC) and decreased ReHo in the left precentral gyrus (PG). No correlations were detected between the ReHo values and the Hamilton Rating Scale for Depression (HRSD) scores. The SVM results showed a diagnostic accuracy of 98.96% (96/97). Increased ReHo in the left ACC, and decreased ReHo in the left PG were illustrated, along with a sensitivity of 98.07%(51/52) and a specificity of100% (45/45).

CONCLUSION

Our results suggest that abnormal regional neural activity in the left ACC and PG may play a key role in the pathophysiological process of first-episode MDD. Moreover, the combination of ReHo values in the left ACC and precentral gyrusmay serve as a neuroimaging biomarker for first-episode MDD.