The default mode network and rumination in individuals at risk for depression

Deconstructive meditations and psychotherapy: Transforming the perception of the self

Selfishness, understood as excessive focus on the self, appears to be a predominant feature of contemporary culture. While the degree of self-focus is adaptive for survival and decision-making, self-rigidity has been associated with significant psychological, interpersonal, and social costs. Throughout history, philosophers, religious leaders, and social activists have promoted a “hypo-egoic” way of being, characterized by reduced self-fixation and greater openness to others. However, a key question arises: How can one cultivate a more flexible and interdependent perspective on the self? Deconstructive meditations are a group of contemplative practices that aim to dismantle self-rigidity by exploring perception, cognition, and emotion. Their central mechanism is self-inquiry, an experiential process that involves directly observing patterns of the self, questioning the solidity of identity, and developing new ways to relate to experience. From the perspective of contemplative neuroscience, these practices have been shown to reduce self-narrative identification and promote psychological flexibility. Despite their potential, empirical research on deconstructive meditations remains limited and requires further investigation. This article reviews the essential findings on practices, their connection to psychotherapy, and their potential therapeutic applications. Finally, their clinical implications are discussed along with future research directions to validate their impact on mental health.

Neural correlates of insomnia with depression and anxiety from a neuroimaging perspective: A systematic review

Insomnia affects a substantial proportion of the population and frequently co-occurs with mental illnesses including depression and anxiety. However, the neurobiological correlates of these disorders remain unclear. Here we review magnetic resonance imaging (MRI) studies assessing structural and functional brain associations with depressive and anxiety symptoms in insomnia disorder (ID; n = 38), insomnia symptoms in depressive and anxiety disorders (n = 14), and these symptoms in the general populations (n = 3). The studies on insomnia disorder consistently showed overlapping (salience network: insula and anterior cingulate cortex) and differential MRI correlation patterns between depressive (thalamus, orbitofrontal cortex and its associated functional connectivity) and anxiety (functional connectivity associated with default mode network) symptoms. The insula was also consistently identified as indicating the severity of insomnia symptoms in depressive disorder. In contrast, findings for other regions related to insomnia symptoms in both depressive and anxiety disorders were generally inconsistent across studies, partly due to variations in methods and patient cohorts. In the general population, brain regions in the default mode network provided a functional link between insomnia and depressive symptoms. These findings underscore both the shared and distinct neural correlates among depression, anxiety, and insomnia, providing potential avenues for the clinical management of these conditions.

Local connections enhancement as a neuroprotective strategy against depression recurrence: Insights from structural brain network analysis

BACKGROUND

Depression recurrence significantly impacts patients' well-being and presents a major clinical challenge. Identifying the risk of recurrence during remission could enable early intervention and prevent disease progression.

METHODS

This study included 115 patients in remission from their first depressive episode and 47 healthy controls (HCs). Participants underwent diffusion tensor imaging (DTI), neuropsychological assessments, and follow-up evaluations every three months over a two-year period. Structural brain networks were constructed using deterministic fiber tracking and graph theory analysis.

RESULTS

Non-recurrence patients exhibited significantly higher baseline local connections compared to the recurrence group (t = 8.148; P < 0.001), which emerged as a robust negative predictor of recurrence (AUC = 0.853 [95 % CI: 0.774-0.912]; OR = 0.594 [95 % CI: 0.489-0.722]; P < 0.001). Rich-club connections were inversely correlated with depression severity (r = -0.510; P < 0.001) and duration (r = -0.221; P = 0.018). Additionally, increases in local connections during remission correlated positively with subsequent rich-club connections (r = 0.540; P < 0.05).

CONCLUSION

Elevated local connections during remission after the first depressive episode significantly reduce the risk of recurrence. This suggests a compensatory neuroprotective mechanism, where enhanced local connections stabilize rich-club connections, thereby maintaining the integrity of the whole-brain network. These findings highlight local connections as a critical factor in preventing depression recurrence and as a potential target for early clinical intervention.

Catalyst for change: Psilocybin's antidepressant mechanisms-A systematic review

BACKGROUND

Recent clinical trials suggest promising antidepressant effects of psilocybin, despite methodological challenges. While various studies have investigated distinct mechanisms and proposed theoretical opinions, a comprehensive understanding of psilocybin's neurobiological and psychological antidepressant mechanisms is lacking.

AIMS

Systematically review potential antidepressant neurobiological and psychological mechanisms of psilocybin.

METHODS

Search terms were generated based on existing evidence of psilocybin's effects related to antidepressant mechanisms. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, 15 studies were systematically reviewed, exploring various therapeutic change principles such as brain dynamics, emotion regulation, cognition, self-referential processing, connectedness, and interpersonal functioning.

RESULTS

Within a supportive setting, psilocybin promoted openness, cognitive and neural flexibility, and greater ability and acceptance of emotional experiences. A renewed sense of connectedness to the self, others, and the world emerged as a key experience. Imaging studies consistently found altered brain dynamics, characterized by reduced global and within default mode network connectivity, alongside increased between-network connectivity.

CONCLUSIONS

Together, these changes may create a fertile yet vulnerable window for change, emphasizing the importance of a supportive set, setting, and therapeutic guidance. The results suggest that psilocybin, within a supportive context, may induce antidepressant effects by leveraging the interplay between neurobiological mechanisms and common psychotherapeutic factors. This complements the view of purely pharmacological effects, supporting a multileveled approach that reflects various relevant dimensions of therapeutic change, including neurobiological, psychological, and environmental factors.

Translating Molecular Psychiatry: From Biomarkers to Personalized Therapies-A Narrative Review

In this review, we explore the biomarkers of different psychiatric disorders, such as major depressive disorder, generalized anxiety disorder, schizophrenia, and bipolar disorder. Moreover, we show the interplay between genetic and environmental factors. Novel techniques such as genome-wide association studies (GWASs) have identified numerous risk loci and single-nucleotide polymorphisms (SNPs) implicated in these conditions, contributing to a better understanding of their mechanisms. Moreover, the impact of genetic variations on drug metabolisms, particularly through cytochrome P450 (CYP450) enzymes, highlights the importance of pharmacogenomics in optimizing psychiatric treatment. This review also explores the role of neurotransmitter regulation, immune system interactions, and metabolic pathways in psychiatric disorders. As the technology advances, integrating genetic markers into clinical practice will be crucial in advancing precision psychiatry, improving diagnostic accuracy and therapeutic interventions for individual patients.

Sleep disturbances in generalized anxiety Disorder: The central role of insomnia

Generalized anxiety disorder (GAD) is a chronic and disabling mental health condition characterized by excessive, uncontrollable worry and persistent psychological and somatic tension. Affecting approximately 3-6 % of the global population, GAD significantly impairs daily functioning and often coexists with other psychiatric conditions. Among its many symptoms, sleep disturbances-particularly insomnia-are among the most frequently reported and debilitating. Individuals with GAD commonly experience difficulties with sleep initiation, maintenance, and restorative rest, making insomnia one of the most pervasive features of the disorder. Emerging research highlights a bidirectional relationship between GAD and insomnia: while anxiety contributes to cognitive and physiological arousal that interferes with sleep, insomnia in turn exacerbates emotional dysregulation, amplifies worry, and may even precede the development of anxiety disorders. Neurobiological and neuroimaging studies support this reciprocal link, showing shared dysfunctions such as heightened hypothalamic-pituitary-adrenal (HPA) axis activity, increased amygdala reactivity, reduced prefrontal cortical control, and GABAergic deficits. These overlapping mechanisms underscore a common pathophysiological substrate that reinforces both conditions. Recognizing and addressing this interplay is critical, as untreated insomnia may perpetuate or intensify GAD symptoms. Notably, cognitive behavioral therapy for insomnia (CBT-I) has been effective in improving sleep and reducing anxiety severity-even without directly targeting anxiety-supporting a shift toward integrating sleep-focused interventions in the treatment of GAD. This review aimed to elucidate clinical and neurobiological evidence on the bidirectional link between insomnia and GAD, emphasizing shared mechanisms and treatment implications.

The Journey of the Default Mode Network: Development, Function, and Impact on Mental Health

The Default Mode Network has been extensively studied in recent decades due to its central role in higher cognitive processes and its relevance for understanding mental disorders. This neural network, characterized by synchronized and coherent activity at rest, is intrinsically linked to self-reflection, mental exploration, social interaction, and emotional processing. Our understanding of the DMN extends beyond humans to non-human animals, where it has been observed in various species, highlighting its evolutionary basis and adaptive significance throughout phylogenetic history. Additionally, the DMN plays a crucial role in brain development during childhood and adolescence, influencing fundamental cognitive and emotional processes. This literature review aims to provide a comprehensive overview of the DMN, addressing its structural, functional, and evolutionary aspects, as well as its impact from infancy to adulthood. By gaining a deeper understanding of the organization and function of the DMN, we can advance our knowledge of the neural mechanisms that underlie cognition, behavior, and mental health. This, in turn, can lead to more effective therapeutic strategies for a range of neuropsychiatric conditions.

Diagnosis of Major Depressive Disorder Based on Individualized Brain Functional and Structural Connectivity

BACKGROUND

Traditional neuroimaging studies have primarily emphasized analysis at the group level, often neglecting the specificity at the individual level. Recently, there has been a growing interest in individual differences in brain connectivity. Investigating individual-specific connectivity is important for understanding the mechanisms of major depressive disorder (MDD) and the variations among individuals.

PURPOSE

To integrate individualized functional connectivity and structural connectivity with machine learning techniques to distinguish people with MDD and healthy controls (HCs).

STUDY TYPE

Prospective.

SUBJECTS

A total of 182 patients with MDD and 157 HCs and a verification cohort including 54 patients and 46 HCs.

FIELD STRENGTH/SEQUENCE

3.0 T/T1-weighted imaging, resting-state functional MRI with echo-planar sequence, and diffusion tensor imaging with single-shot spin echo.

ASSESSMENT

Functional and structural brain networks from rs-fMRI and DTI data were constructed, respectively. Based on these networks, individualized functional connectivity (IFC) and individualized structural connectivity (ISC) were extracted using common orthogonal basis extraction (COBE). Subsequently, multimodal canonical correlation analysis combined with joint independent component analysis (mCCA + jICA) was conducted to fusion analysis to identify the joint and unique independent components (ICs) across multiple modes. These ICs were utilized to generate features, and a support vector machine (SVM) model was implemented for the classification of MDD.

STATISTICAL TESTS

The differences in individualized connectivity between patients and controls were compared using two-sample t test, with a significance threshold set at P < 0.05. The established model was tested and evaluated using the receiver operating characteristic (ROC) curve.

RESULTS

The classification performance of the constructed individualized connectivity feature model after multisequence fusion increased from 72.2% to 90.3%. Furthermore, the prediction model showed significant predictive power for assessing the severity of depression in patients with MDD (r = 0.544).

DATA CONCLUSION

The integration of IFC and ISC through multisequence fusion enhances our capacity to identify MDD, highlighting the advantages of the individualized approach and underscoring its significance in MDD research.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Increased functional connectivity between brainstem substructures and cortex in treatment resistant depression

Previous functional magnetic resonance imaging (fMRI) studies showed an abnormal brainstem-to-cortex functional connectivity (FC) in major depressive disorder. However, only few studies analyzed brainstem substructures in treatment-resistant depression (TRD). In this study, we analyzed resting-state seed-based FC between midbrain, pons, medulla oblongata and cortical/subcortical brain regions in patients with TRD (n = 24) and age- and sex-matched healthy controls (n = 24). FC was analyzed in each group and compared between groups. Correlation analyses assessed the relationship between FC strength and depressive symptom severity in regions showing significant group differences in seed-based connectivity. Our findings reveal an increased FC in the midbrain and pons to the precentral gyrus, postcentral gyrus, and temporal gyrus in patients with TRD compared to healthy controls. Interestingly, in TRD patients, FC between midbrain and cortex was negatively correlated with BDI-II scores, indicating a relationship between altered connectivity and self-reported depression severity. It is essential to note that our naturalistic, cross-sectional approach precludes causal conclusions regarding the relationship between FC and pathophysiology of TRD. The small sample size necessitates confirmation in a larger cohort. Midbrain/pons-to-cortex FC was increased in patients with TRD compared to healthy controls. Future studies should explore the relationship between abnormal brainstem-to-cortex FC and depressive symptomatology in more detail.

Multivariate Neural Markers of Individual Differences in Thought Control Difficulties

Difficulties in controlling thought, including pathological rumination, worry, and intrusive thoughts, occur in a range of mental health disorders. Here we identify specific patterns of brain activity distributed within and across canonical brain networks that are associated with self-reported difficulties in controlling one's thoughts. These activity patterns were derived using multivariate pattern analysis on fMRI data recorded while participants engaged in one of four operations on an item in working memory: maintaining it, replacing it with another, specifically suppressing it, or clearing the mind of all thought. Individuals who reported greater difficulties exhibited brain activation patterns that were more variable and less differentiated across the four operations in frontoparietal and default mode networks, and showed less distinct patterns of connectivity within the default mode network. These activity profiles were absent during rest but serve as promising task-based neural markers, explaining over 30% of the variance in thought control difficulties.

Reliable Multimodal Brain Signatures Predict Mental Health Outcomes in Children

BACKGROUND

Interindividual brain differences likely precede the emergence of mood and anxiety disorders; however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health.

METHODS

In a large population-based cohort of children from the ABCD (Adolescent Brain Cognitive Development) Study (N > 10,000), we applied data-driven linked independent component analysis to identify linked variations in cortical structure and white matter microstructure that together predict longitudinal behavioral and mental health symptoms. Brain differences were examined in a subsample of twins depending on the presence of at-risk behaviors.

RESULTS

Two multimodal brain signatures at ages 9 to 10 years predicted longitudinal mental health symptoms from 9 to 12 years, with small effect sizes. Cortical variations in association, limbic, and default mode regions linked with peripheral white matter microstructure together predicted higher depression and anxiety symptoms across 2 independent split-halves. The brain signature differed between depression and anxiety symptom trajectories and related to emotion regulation network functional connectivity. Linked variations of subcortical structures and projection tract microstructure variably predicted behavioral inhibition, sensation seeking, and psychosis symptom severity over time in male participants. These brain patterns were significantly different between pairs of twins discordant for self-injurious behavior.

CONCLUSIONS

Our results demonstrate reliable, multimodal brain patterns in childhood, before mood and anxiety disorders tend to emerge, that lay the foundation for long-term mental health outcomes and offer targets for early identification of children at risk.

Mapping the Neural Basis of Wake Onset Regularity and Its Effects on Sleep Quality and Positive Affect

The regularity of sleep-wake cycles is a defining characteristic of normative sleep patterns that are typically associated with proper circadian rhythmicity. The previous literature indicates that consistent patterns of sleep and wake are associated with improved sleep quality and cognitive functioning. Conversely, sleep irregularity has been associated with reduced well-being and inefficiency in resting-state neural networks. This study investigated the relationship between specific sleep regularity measures and outcomes, including emotional affect, sleep quality, and resting-state functional connectivity. We found that variability in wake onset predicted poorer sleep quality and reduced positive affect. Furthermore, sleep regularity measures were associated with altered functional connectivity between the posterior cingulate cortex and regions involved in emotional processing. We propose that alterations in default mode network (DMN) connectivity linked to sleep irregularity reflect disruptions in emotional processing and sleep quality.

Negative rumination in depression subtypes with melancholic features and anxious distress

Background

Aberrant cognition is one of the crucial symptoms of depression. However, whether the negative rumination participates in depression with melancholic features or anxious distress remains unclear.

Methods

In this study, we addressed this issue by compiling a questionnaire that can comprehensively measure the negative cognitive processing bias in depression. We also conducted an exhaustive analysis of its influencing factors, including the subtype of depression, age, gender, age of onset, family history of mental disorder, and education year.

Results

We found that depression increased negative attention bias, negative memory bias, negative interpretation bias, and negative rumination bias. Importantly, among the several dimensions of negative cognitive bias, negative rumination bias was more serious in the melancholic than anxious subgroup. Furthermore, Spearman rank correlation analysis showed that negative rumination bias correlates with family history and age of onset of depression.

Limitations

We mainly explored melancholic and anxiety subgroups and did not include other subtypes. Due to time constraints, we did not conduct long-term follow-ups or explore the neural mechanisms of the differences between depressive and anxious rumination.

Conclusion

Our results contribute to the existing literature on the psychological mechanisms underlying aberrant cognition in depression. These findings could provide guidance for clinical practice and individualized precision treatment of cognitive biases in major depressive disorder. Therefore, rumination-focused therapies would be tailored differently for melancholic versus anxious subgroups.

Multivariate Neural Markers of Individual Differences in Thought Control Difficulties

Difficulties in controlling thought, including pathological rumination, worry, and intrusive thoughts, occur in a range of mental health disorders. Here we identify specific patterns of brain activity distributed within and across canonical brain networks that are associated with self-reported difficulties in controlling one's thoughts. These activity patterns were derived using multivariate pattern analysis on fMRI data recorded while participants engaged in one of four operations on an item in working memory: maintaining it, replacing it with another, specifically suppressing it, or clearing the mind of all thought. Individuals who reported greater difficulties exhibited brain activation patterns that were more variable and less differentiated across the four operations in frontoparietal and default mode networks, and showed less distinct patterns of connectivity within the default mode network. These activity profiles were absent during rest but serve as promising task-based neural markers, explaining over 30% of the variance in thought control difficulties.

Vagus nerve stimulation and gut microbiota interactions: A novel therapeutic avenue for neuropsychiatric disorders

The rising prevalence of treatment-resistant neuropsychiatric disorders underscores the need for innovative and effective treatment strategies. The gut microbiota (GM) plays a pivotal role in the progression of these diseases, influencing the brain and mental health through the gut-brain axis (GBA). The vagus nerve plays a significant role in the GBA, making it a key area of focus for potential novel therapeutic interventions. Vagus nerve stimulation (VNS) was introduced and approved as a treatment for refractory forms of some neuropsychological disorders, such as depression and epilepsy. Considering its impact on several brain regions that play a vital part in mood, motivation, affection, and cognitive function, the VNS has shown significant therapeutic potential for treating a variety of neuropsychiatric disorders. Using VNS to target the bidirectional communication pathways linking the GM and the VN could present an exciting and novel approach to treating neuropsychological disorders. Imbalances in the GM, such as dysbiosis, can impair the communication pathways between the gut and the brain, contributing to the development of neuropsychological disorders. VNS shows potential for modulating these interconnected systems, helping to restore balance. Interestingly, the composition of the GM may also influence the effectiveness of VNS, as it has the potential to modify the brain's response to this therapeutic approach. This study provides a comprehensive analysis of a relatively unexplored but noteworthy interaction between VNS and GM in the treatment of neuropsychiatric disorders. In addition, we discussed the mechanisms, therapeutic potential, and clinical implications of VNS on the GBA across neuropsychiatric disorders.

Brooding, reflection, and anger rumination in late life suicidal behavior

BACKGROUND

Current literature on age-specific risk factors for suicide in older adulthood is lacking. One risk factor for younger-life suicide, rumination, has not been extensively studied in older adults, but from prior research, may be more relevant to late-life vs. early life suicide. The current study investigated how multiple subtypes of rumination (i.e., brooding, reflection, and anger rumination) relate to suicidal ideation and recent suicidal behavior in late life.

METHODS

378 participants aged 50-90 (mean age 63.4, SD 7.5) were recruited into a case-control study examining suicide in older adults. Participants were recruited into three groups: 1) depressed adults who had made a recent (past two years) suicide attempt, 2) those with depression but no suicide attempt, and 3) a healthy comparison group. Among depressed groups, we examined relationships between rumination types, trait anger, depression, and suicidal ideation. Then, we conducted logistic regression to test which variables were related to having made a suicide attempt in the past two years among those with current suicidal ideation.

RESULTS

All forms of rumination were related to depression. Brooding was related to ideation severity, but only depression severity related to presence of ideation. Anger rumination and ideation severity each contributed unique variance in their prediction of recent suicide attempts.

LIMITATIONS

Our cross-section design does not allow for causal claims; future studies should consider using ecological momentary assessment approaches.

CONCLUSIONS

Treatments to decrease rumination without an intense cognitive component should be considered for late-life patients.

Polygenic risk for depression and resting-state functional connectivity of subgenual anterior cingulate cortex in young adults

BACKGROUND

Genetic variants may confer risk for depression by modulating brain structure and function; evidence has underscored the key role of the subgenual anterior cingulate cortex (sgACC) in depression. We sought to examine how the resting-state functional connectivity (rsFC) of the sgACC was associated with polygenic risk for depression in a subclinical population.

METHODS

Following published protocols, we computed seed-based whole-brain sgACC rsFC and calculated polygenic risk scores (PRS) using data from healthy young adults from the Human Connectome Project. We performed whole-brain regression against PRS and severity of depression symptoms in a single model for all participants and by sex, controlling for age, sex, race or ethnicity, alcohol use severity, and household income. We evaluated the results at a corrected threshold.

RESULTS

We included data for 717 healthy young adults. We found lower rsFC between the sgACC and the default mode network and frontal regions in association with PRS and lower sgACC-cerebellar rsFC in association with depression severity. We also noted differences by sex in the connectivity correlates of PRS and depression severity. In an additional set of analyses, we observed a significant correlation between PRS and somatic complaints, as well as altered sgACC-somatosensory cortical connectivity in association with the severity of somatic complaints.

LIMITATIONS

The current findings should be considered specific to subclinical depression and may not generalize to patients with depressive disorders.

CONCLUSION

Our findings highlight the pivotal role of distinct sgACC-based networks in the genetic predisposition for depression and the manifestation of depression among young adults with subclinical depression. Distinguishing the risk from severity markers of depression may have implications in developing early and effective treatments for people at risk for depression.

Longitudinal neurofunctional alterations following nonpharmacological treatments and the mediating role of regional homogeneity in subclinical depression comorbid with sleep disorders among college students

BACKGROUND

Clinical guidelines recommend nonpharmacological treatment (nPHT) as the primary intervention for subthreshold depression management. Counseling (CS) and electroacupuncture (EA) are two promising nonpharmacological approaches for improving both depression and sleep disturbance. However, the intrinsic neuroimaging mechanisms underlying the antidepressant effects of these nPHTs are not yet fully understood.

METHODS

We analyzed longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) data from a randomized, single-blind clinical trial involving 96 first-episode, drug-naïve college students with subclinical depression and sleep disorders (sDSD; mean age 20.43 ± 2.72 years; 66.7% female) and 90 healthy controls (HCs; mean age 21.02 ± 2.68 years; 61.1% female). Participants with sDSD were randomly assigned to receive either scalp EA (n = 47) or CS (n = 49) for six weeks. The regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) before and after nPHT were calculated. Correlation and mediation analyses were performed to investigate the complex relationships between fMRI indicators and clinical symptoms.

RESULTS

The ALFF in the left paracentral lobule in sDSD patients presented an interaction effect between group and time following six weeks of nPHT. In the CS group, the ALFF in the left paracentral lobule decreased (p < 0.001), and in the EA group, it increased (p < 0.05). Compared with HCs, the baseline sDSD has many abnormal brain regions in terms of ALFF and ReHo. The whole-brain average ReHo was negatively correlated with depression scores (r = -0.26, p < 0.001) and sleep quality scores (r = -0.25, p < 0.001) and mediated the association between depression and sleep disorders [β = 0.2857, p < 0.001, 95% CI (0.23, 0.35)].

CONCLUSIONS

Nonpharmacological therapies provide different therapeutic outcomes in terms of the same rs-fMRI indicator. ALFF in the left paracentral lobule could be used as an imaging biomarker in nPHT selection. Rs-fMRI indicators are promising for understanding the neural basis of the complex relationship between subclinical depression and insomnia comorbidities in young adults.

Neural Modulation Alteration to Positive and Negative Emotions in Depressed Patients: Insights from fMRI Using Positive/Negative Emotion Atlas

BACKGROUND

Although it has been noticed that depressed patients show differences in processing emotions, the precise neural modulation mechanisms of positive and negative emotions remain elusive. FMRI is a cutting-edge medical imaging technology renowned for its high spatial resolution and dynamic temporal information, making it particularly suitable for the neural dynamics of depression research.

METHODS

To address this gap, our study firstly leveraged fMRI to delineate activated regions associated with positive and negative emotions in healthy individuals, resulting in the creation of the positive emotion atlas (PEA) and the negative emotion atlas (NEA). Subsequently, we examined neuroimaging changes in depression patients using these atlases and evaluated their diagnostic performance based on machine learning.

RESULTS

Our findings demonstrate that the classification accuracy of depressed patients based on PEA and NEA exceeded 0.70, a notable improvement compared to the whole-brain atlases. Furthermore, ALFF analysis unveiled significant differences between depressed patients and healthy controls in eight functional clusters during the NEA, focusing on the left cuneus, cingulate gyrus, and superior parietal lobule. In contrast, the PEA revealed more pronounced differences across fifteen clusters, involving the right fusiform gyrus, parahippocampal gyrus, and inferior parietal lobule.

CONCLUSIONS

These findings emphasize the complex interplay between emotion modulation and depression, showcasing significant alterations in both PEA and NEA among depression patients. This research enhances our understanding of emotion modulation in depression, with implications for diagnosis and treatment evaluation.

Integration patterns of functional brain networks can predict the response to abdominal acupuncture in patients with major depressive disorder

Abdominal acupuncture has definite efficacy for major depressive disorder (MDD). Our study examined how abdominal acupuncture regulates the integration within and between brain networks of MDD patients by neuroimaging and whether this functional integration can predict the efficacy. Forty-six female MDD patients were randomly divided into a fluoxetine + real acupuncture group (n = 22) and a fluoxetine + sham acupuncture group (n = 24). The differences in functional magnetic resonance imaging data in the intra- and inter-network functional connectivity (FC) of the default mode network (DMN), affective network (AN), salience network (SN), and cognitive control network (CCN) between the two groups were analyzed. The FCs in brain regions with the inter-group differences and support vector regression were used to predict the efficacy of abdominal acupuncture. Our results showed: that the intra- and inter-network FCs of DMN, AN, SN, and CCN could be changed by abdominal acupuncture. Using the baseline FCs within AN and DMN or AN-DMN as characteristics, combined with support vector regression, could better predict the efficacy of acupuncture. Our study suggests that abdominal acupuncture could treat MDD by regulating the integration of the functional networks DMN, AN, SN, and CCN. The baseline FCs within the DMN and AN or between them could be used as neural markers for predicting the efficacy of abdominal acupuncture.

Investigating the impact of rumination and adverse childhood experiences on resting-state neural activity and connectivity in depression

BACKGROUND

Both ruminative thought processes and adverse childhood experiences (ACEs) are well-established risk factors for the emergence and maintenance of depression. However, the neurobiological mechanisms underlying these associations remain poorly understood.

METHODS

We examined resting-state functional magnetic resonance imaging data (3 T Tim Trio MR scanner; Siemens, Erlangen) of 44 individuals diagnosed with an acute depressive episode. Specifically, we focused on investigating functional brain activity and connectivity within and between three large-scale neural networks associated with processes affected in depression: the default mode network (DMN), the salience network (SN), and the central executive network (CEN). Correlational and regression-based analyses were performed.

RESULTS

Our regions of interest analyses revealed that region-specific spontaneous neural activity in the anterior DMN was associated with self-reported trait rumination, specifically, the pregenual anterior cingulate cortex (pgACC). Furthermore, using a liberal statistical threshold, we found that spontaneous neural activity of the ventromedial prefrontal cortex and the pgACC were associated with depression symptom severity. Neither spontaneous neural activity in the SN and CEN nor functional connectivity within and across the investigated networks was associated with depression severity or rumination. Furthermore, there was no association between ACEs and brain activity and connectivity.

LIMITATIONS

Lack of a formal control group or low-risk group for comparison.

CONCLUSIONS

Overall, our results indicate network-specific changes in spontaneous brain activity, that are linked to both depression severity and rumination. Findings underscore the crucial role of the pgACC in depression and contribute to a dimensional and symptom-based understanding of depression-related network imbalances.

Rumination and Overrecruitment of Cognitive Control Circuits in Depression

BACKGROUND

Rumination is associated with greater cognitive dysfunction and treatment resistance in major depressive disorder (MDD), but its underlying neural mechanisms are not well understood. Because rumination is characterized by difficulty in controlling negative thoughts, the current study investigated whether rumination was associated with aberrant cognitive control in the absence of negative emotional information.

METHODS

Individuals with MDD (n = 176) and healthy control individuals (n = 52) completed the stop signal task with varied stop signal difficulty during functional magnetic resonance imaging. In the task, a longer stop signal asynchrony made stopping difficult (hard stop), whereas a shorter stop signal asynchrony allowed more time for stopping (easy stop).

RESULTS

In participants with MDD, higher rumination intensity was associated with greater neural activity in response to difficult inhibitory control in the frontoparietal regions. Greater activation for difficult inhibitory control associated with rumination was also positively related to state fear. The imaging results provide compelling evidence for the neural basis of inhibitory control difficulties in individuals with MDD with high rumination.

CONCLUSIONS

The association between higher rumination intensity and greater neural activity in regions involved in difficult inhibitory control tasks may provide treatment targets for interventions aimed at improving inhibitory control and reducing rumination in this population.

Frontal pole-precuneus connectivity is associated with a discrepancy between self-rated and observer-rated depression severity in mood disorders: a resting-state functional magnetic resonance imaging study

Discrepancies in self-rated and observer-rated depression severity may underlie the basis for biological heterogeneity in depressive disorders and be an important predictor of outcomes and indicators to optimize intervention strategies. However, the neural mechanisms underlying this discrepancy have been understudied. This study aimed to examine the brain networks that represent the neural basis of the discrepancy between self-rated and observer-rated depression severity using resting-state functional MRI. To examine the discrepancy between self-rated and observer-rated depression severity, self- and observer-ratings discrepancy (SOD) was defined, and the higher and lower SOD groups were selected from depressed patients as participants showing extreme deviation. Resting-state functional MRI analysis was performed to examine regions with significant differences in functional connectivity in the two groups. The results showed that, in the higher SOD group compared to the lower SOD group, there was increased functional connectivity between the frontal pole and precuneus, both of which are subregions of the default mode network that have been reported to be associated with ruminative and self-referential thinking. These results provide insight into the association of brain circuitry with discrepancies between self- and observer-rated depression severity and may lead to more treatment-oriented diagnostic reclassification in the future.

Engaging Mood Brain Circuits with Psilocybin (EMBRACE): a study protocol for a randomized, placebo-controlled and delayed-start, neuroimaging trial in depression

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide across domains of health and cognition, affecting overall quality of life. Approximately one third of individuals with depression do not fully respond to treatments (e.g., conventional antidepressants, psychotherapy) and alternative strategies are needed. Recent early phase trials suggest psilocybin may be a safe and efficacious intervention with rapid-acting antidepressant properties. Psilocybin is thought to exert therapeutic benefits by altering brain network connectivity and inducing neuroplastic changes that endure for weeks post-treatment. Although early clinical results are encouraging, psilocybin's acute neurobiological effects on neuroplasticity have not been fully investigated. We aim to examine for the first time how psilocybin acutely (intraday) and subacutely (weeks) alters functional brain networks implicated in depression.

METHODS

Fifty participants diagnosed with MDD or persistent depressive disorder (PDD) will be recruited from a tertiary mood disorders clinic and undergo 1:1 randomization into either an experimental or control arm. Participants will be given either 25 mg psilocybin or 25 mg microcrystalline cellulose (MCC) placebo for the first treatment. Three weeks later, those in the control arm will transition to receiving 25 mg psilocybin. We will investigate whether treatments are associated with changes in arterial spin labelling and blood oxygenation level-dependent contrast neuroimaging assessments at acute and subacute timepoints. Primary outcomes include testing whether psilocybin demonstrates acute changes in (1) cerebral blood flow and (2) functional brain activity in networks associated with mood regulation and depression when compared to placebo, along with changes in MADRS score over time compared to placebo. Secondary outcomes include changes across complementary clinical psychiatric, cognitive, and functional scales from baseline to final follow-up. Serum peripheral neurotrophic and inflammatory biomarkers will be collected at baseline and follow-up to examine relationships with clinical response, and neuroimaging measures.

DISCUSSION

This study will investigate the acute and additive subacute neuroplastic effects of psilocybin on brain networks affected by depression using advanced serial neuroimaging methods. Results will improve our understanding of psilocybin's antidepressant mechanisms versus placebo response and whether biological measures of brain function can provide early predictors of treatment response.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT06072898. Registered on 6 October 2023.

Effects of Pollution Burden on Neural Function During Implicit Emotion Regulation and Longitudinal Changes in Depressive Symptoms in Adolescents

Background

Exposure to environmental pollutants early in life has been associated with increased prevalence and severity of depression in adolescents; however, the neurobiological mechanisms underlying this association are not well understood. In the current longitudinal study, we investigated whether pollution burden in early adolescence (9-13 years) was associated with altered brain activation and connectivity during implicit emotion regulation and changes in depressive symptoms across adolescence.

Methods

One hundred forty-five participants (n = 87 female; 9-13 years) provided residential addresses, from which we determined their relative pollution burden at the census tract level, and performed an implicit affective regulation task in the scanner. Participants also completed questionnaires assessing depressive symptoms at 3 time points, each approximately 2 years apart, from which we calculated within-person slopes of depressive symptoms. We conducted whole-brain activation and connectivity analyses to examine whether pollution burden was associated with alterations in brain function during implicit emotion regulation of positively and negatively valenced stimuli and how these effects were related to slopes of depressive symptoms across adolescence.

Results

Greater pollution burden was associated with greater bilateral medial prefrontal cortex activation and stronger bilateral medial prefrontal cortex connectivity with regions within the default mode network (e.g., temporoparietal junction, posterior cingulate cortex, precuneus) during implicit regulation of negative emotions, which was associated with greater increases in depressive symptoms across adolescence in those exposed to higher pollution burden.

Conclusions

Adolescents living in communities characterized by greater pollution burden showed altered default mode network functioning during implicit regulation of negative emotions that was associated with increases in depressive symptoms across adolescence.

Neurobiological and psychological factors to depression

Major Depressive Disorder (MDD) is a common condition with complex psychological and biological background. While its aetiology is still unclear, chronic stress stands amongst major risk factors to MDD pathogenesis. When researching on MDD, it is necessary to be familiar with the neurobiological effects of several prominent contributors to the chronic stress factor experienced across hypothalamic-pituitary-adrenal (HPA) axis, neurotransmission, immune system reflexivity, and genetic alterations. Bi-directional flow of MDD pathogenesis suggests that psychological factors produce biological effects. Here, a summary of how the MDD expresses its mechanisms of action across an overactive HPA axis, the negative impacts of reduced neurotransmitter functions, the inflammatory responses and their gene x environment interactions. This paper builds on these conceptual factors and their input towards the MDD symptomatology with a purpose of synthesising the current findings and create an integrated view of the MDD pathogenesis. Finally, relevant treatment implications will be summarised, along with recommendations to a multimodal clinical practice.

Alterations in brain network connectivity and subjective experience induced by psychedelics: a scoping review

Intense interest surrounds current research on psychedelics, particularly regarding their potential in treating mental health disorders. Various studies suggest a link between the subjective effects produced by psychedelics and their therapeutic efficacy. Neuroimaging evidence indicates an association of changes in brain functional connectivity with the subjective effects of psychedelics. We conducted a review focusing on psychedelics and brain functional connectivity. The review focused on four psychedelic drugs: ayahuasca, psilocybin and LSD, and the entactogen MDMA. We conducted searches in databases of MEDLINE, Embase, APA PsycInfo and Scopus from inception to Jun 2023 by keywords related to functional connectivity and psychedelics. Using the PRISMA framework, we selected 24 articles from an initial pool of 492 for analysis. This scoping review and analysis investigated the effects of psychedelics on subjective experiences and brain functional connectivity in healthy individuals. The studies quantified subjective effects through psychometric scales, revealing significant experiences of altered consciousness, mood elevation, and mystical experiences induced by psychedelics. Neuroimaging results indicated alterations in the functional connectivity of psychedelics, with consistent findings across substances of decreased connectivity within the default mode network and increased sensory and thalamocortical connectivity. Correlations between these neurophysiological changes and subjective experiences were noted, suggesting a brain network basis of the psychedelics' neuropsychological impact. While the result of the review provides a potential neural mechanism of the subjective effects of psychedelics, direct clinical evidence is needed to advance their clinical outcomes. Our research serves as a foundation for further exploration of the therapeutic potential of psychedelics.

Brain connectivity changes underlying depression and fatigue in relapsing-remitting multiple sclerosis: A systematic review

Multiple Sclerosis (MS) is an autoimmune disease affecting the central nervous system, characterised by neuroinflammation and neurodegeneration. Fatigue and depression are common, debilitating, and intertwined symptoms in people with relapsing-remitting MS (pwRRMS). An increased understanding of brain changes and mechanisms underlying fatigue and depression in RRMS could lead to more effective interventions and enhancement of quality of life. To elucidate the relationship between depression and fatigue and brain connectivity in pwRRMS we conducted a systematic review. Searched databases were PubMed, Web-of-Science and Scopus. Inclusion criteria were: studied participants with RRMS (n ≥ 20; ≥ 18 years old) and differentiated between MS subtypes; published between 2001-01-01 and 2023-01-18; used fatigue and depression assessments validated for MS; included brain structural, functional magnetic resonance imaging (fMRI) or diffusion MRI (dMRI). Sixty studies met the criteria: 18 dMRI (15 fatigue, 5 depression) and 22 fMRI (20 fatigue, 5 depression) studies. The literature was heterogeneous; half of studies reported no correlation between brain connectivity measures and fatigue or depression. Positive findings showed that abnormal cortico-limbic structural and functional connectivity was associated with depression. Fatigue was linked to connectivity measures in cortico-thalamic-basal-ganglial networks. Additionally, both depression and fatigue were related to altered cingulum structural connectivity, and functional connectivity involving thalamus, cerebellum, frontal lobe, ventral tegmental area, striatum, default mode and attention networks, and supramarginal, precentral, and postcentral gyri. Qualitative analysis suggests structural and functional connectivity changes, possibly due to axonal and/or myelin loss, in the cortico-thalamic-basal-ganglial and cortico-limbic network may underlie fatigue and depression in pwRRMS, respectively, but the overall results were inconclusive, possibly explained by heterogeneity and limited number of studies. This highlights the need for further studies including advanced MRI to detect more subtle brain changes in association with depression and fatigue. Future studies using optimised imaging protocols and validated depression and fatigue measures are required to clarify the substrates underlying these symptoms in pwRRMS.

A theory of the neural mechanisms underlying negative cognitive bias in major depression

The widely acknowledged cognitive theory of depression, developed by Aaron Beck, focused on biased information processing that emphasizes the negative aspects of affective and conceptual information. Current attempts to discover the neurological mechanism underlying such cognitive and affective bias have successfully identified various brain regions associated with severally biased functions such as emotion, attention, rumination, and inhibition control. However, the neurobiological mechanisms of how individuals in depression develop this selective processing toward negative is still under question. This paper introduces a neurological framework centered around the frontal-limbic circuit, specifically analyzing and synthesizing the activity and functional connectivity within the amygdala, hippocampus, and medial prefrontal cortex. Firstly, a possible explanation of how the positive feedback loop contributes to the persistent hyperactivity of the amygdala in depression at an automatic level is established. Building upon this, two hypotheses are presented: hypothesis 1 revolves around the bidirectional amygdalohippocampal projection facilitating the amplification of negative emotions and memories while concurrently contributing to the impediment of the retrieval of opposing information in the hippocampus attractor network. Hypothesis 2 highlights the involvement of the ventromedial prefrontal cortex in the establishment of a negative cognitive framework through the generalization of conceptual and emotional information in conjunction with the amygdala and hippocampus. The primary objective of this study is to improve and complement existing pathological models of depression, pushing the frontiers of current understanding in neuroscience of affective disorders, and eventually contributing to successful recovery from the debilitating affective disorders.

Unraveling how the adolescent brain deals with criticism using dynamic causal modeling

Sensitivity to criticism, which can be defined as a negative evaluation that a person receives from someone else, is considered a risk factor for the development of psychiatric disorders in adolescents. They may be more vulnerable to social evaluation than adults and exhibit more inadequate emotion regulation strategies such as rumination. The neural network involved in dealing with criticism in adolescents may serve as a biomarker for vulnerability to depression. However, the directions of the functional interactions between the brain regions within this neural network in adolescents are still unclear. In this study, 64 healthy adolescents (aged 14 to 17 years) were asked to listen to a series of self-referential auditory segments, which included negative (critical), positive (praising), and neutral conditions, during fMRI scanning. Dynamic Causal Modeling (DCM) with Parametric Empirical Bayesian (PEB) analysis was performed to map the interactions within the neural network that was engaged during the processing of these segments. Three regions were identified to form the interaction network: the left pregenual anterior cingulate cortex (pgACC), the left dorsolateral prefrontal cortex (DLPFC), and the right precuneus (preCUN). We quantified the modulatory effects of exposure to criticism and praise on the effective connectivity between these brain regions. Being criticized was found to significantly inhibit the effective connectivity from the preCUN to the DLPFC. Adolescents who scored high on the Perceived Criticism Measure (PCM) showed less inhibition of the preCUN-to-DLPFC connectivity when being criticized, which may indicate that they required more engagement of the Central Executive Network (which includes the DLPFC) to sufficiently disengage from negative self-referential processing. Furthermore, the inhibitory connectivity from the DLPFC to the pgACC was strengthened by exposure to praise as well as criticism, suggesting a recruitment of cognitive control over emotional responses when dealing with positive and negative evaluative feedback. Our novel findings contribute to a more profound understanding of how criticism affects the adolescent brain and can help to identify potential biomarkers for vulnerability to develop mood disorders before or during adulthood.

Metabolic Covariance Connectivity of Posterior Cingulate Cortex Associated with Depression Symptomatology Level in Healthy Young Adults

Early detection in the development of a Major Depressive Disorder (MDD) could guide earlier clinical interventions. Although MDD can begin at a younger age, most people have their first episode in young adulthood. The underlying pathophysiological mechanisms relating to such an increased risk are not clear. The posterior cingulate cortex (PCC), exhibiting high levels of brain connectivity and metabolic activity, plays a pivotal role in the pathological mechanism underlying MDD. In the current study, we used the (F-18) fluorodeoxyglucose (FDG) positron emission tomography (PET) to measure metabolic covariance connectivity of the PCC and investigated its association with depression symptomatology evaluated by the Centre for Epidemiological Studies Depression Inventory-Revised (CESD-R) among 27 healthy individuals aged between 18 and 23 years. A significant negative correlation has been observed between CESD-R scale scores and the PCC metabolic connectivity with the anterior cingulate, medial prefrontal cortex, inferior and middle frontal gyrus, as well as the insula. Overall, our findings suggest that the neural correlates of depressive symptomatology in healthy young adults without a formal diagnosis involve the metabolic connectivity of the PCC. Our findings may have potential implications for early identification and intervention in people at risk of developing depression.