Habenula functional connectivity variability increases with disease severity in individuals with major depression

Habenula contributions to negative self-cognitions

Self-related cognitions are integral to personal identity and psychological wellbeing. Persistent engagement with negative self-cognitions can precipitate mental ill health; whereas the ability to restructure them is protective. Here, we leverage ultra-high field 7T fMRI and dynamic causal modelling to characterise a negative self-cognition network centred on the habenula - a small midbrain region linked to the encoding of punishment and negative outcomes. We model habenula effective connectivity in a discovery sample of healthy young adults (n = 45) and in a replication cohort (n = 56) using a cognitive restructuring task during which participants repeated or restructured negative self-cognitions. The restructuring of negative self-cognitions elicits an excitatory effect from the habenula to the posterior orbitofrontal cortex that is reliably observed across both samples. Furthermore, we identify an excitatory effect of the habenula on the posterior cingulate cortex during both the repeating and restructuring of self-cognitions. Our study provides evidence demonstrating the habenula's contribution to processing self-cognitions. These findings yield unique insights into habenula's function beyond processing external reward/punishment to include abstract internal experiences.

The disappointment centre of the brain gets exciting: a systematic review of habenula dysfunction in depression

BACKGROUND

The habenula is an epithalamic brain structure that acts as a neuroanatomical hub connecting the limbic forebrain to the major monoamine centres. Abnormal habenula activity is increasingly implicated in depression, with a surge in publications on this topic in the last 5 years. Direct activation of the habenula is sufficient to induce a depressive phenotype in rodents, suggesting a causative role in depression. However, the molecular basis of habenula dysfunction in depression remains elusive and it is unclear how the preclinical advancements translate to the clinical field.

METHODS

A systematic literature search was conducted following the PRISMA guidelines. The two search terms depress* and habenula* were applied across Scopus, Web of Science and PubMed databases. Studies eligible for inclusion must have examined the habenula in clinical cases of depression or preclinical models of depression and compared their measures to an appropriate control.

RESULTS

Preclinical studies (n = 63) measured markers of habenula activity (n = 16) and neuronal firing (n = 22), largely implicating habenula hyperactivity in depression. Neurotransmission was briefly explored (n = 15), suggesting imbalances within excitatory and inhibitory habenula signalling. Additional preclinical studies reported neuroconnectivity (n = 1), inflammatory (n = 3), genomic (n = 3) and circadian rhythm (n = 3) abnormalities. Seven preclinical studies (11%) included both males and females. From these, 5 studies (71%) reported a significant difference between the sexes in at least one habenula measure taken. Clinical studies (n = 24) reported abnormalities in habenula connectivity (n = 15), volume (n = 6) and molecular markers (n = 3). Clinical studies generally included male and female subjects (n = 16), however, few of these studies examined sex as a biological variable (n = 6).

CONCLUSIONS

Both preclinical and clinical evidence suggest the habenula is disrupted in depression. However, there are opportunities for sex-specific analyses across both areas. Preclinical evidence consistently suggests habenula hyperactivity as a primary driver for the development of depressive symptoms. Clinical studies support gross habenula abnormalities such as altered activation, connectivity, and volume, with emerging evidence of blood brain barrier dysfunction, however, progress is limited by a lack of detailed molecular analyses and limited imaging resolution.

Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder

BACKGROUND

Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain connectome dynamics after ECT in MDD and to explore their associations with treatment outcome.

METHODS

We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. A multilayer network model was used to assess modular switching over time in functional connectomes. Support vector regression was used to assess whether pre-ECT network dynamics could predict treatment response in terms of symptom severity.

RESULTS

At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly in the default mode and somatomotor networks. Moreover, ECT was associated with decreased modular variability in the left dorsal anterior cingulate cortex of MDD-SI but not MDD-NSI patients, and pre-ECT modular variability significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group.

CONCLUSIONS

We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. This study advances our understanding of the neural mechanisms of ECT from a dynamic brain network perspective and suggests potential prognostic biomarkers for predicting ECT efficacy in patients with MDD.

Exploring habenular structural connectivity in Parkinson's disease: insights from 7 T MRI study

BACKGROUND

PD is marked by both motor and non-motor symptoms, with its pathophysiology involving many neural pathways and brain regions beyond the dopaminergic system. While mainly gray matter changes have been noted, white matter changes also exist in PD. Habenula, known for its role in reward processing, mood regulation, motor functions, and cognition, is of interest due to its connection to mood disorders in PD. This study aims to explore diffusion metrics and structural connectivity changes in the habenula of newly diagnosed PD patients using 7 T MRI.

METHODS

84 PDs and 38 HCs were recruited from Maastricht University Medical Centre. Clinical, demographic, and total Beck Depression Inventory (BDI) scores were recorded. A 7 T brain MRI was conducted. Diffusion metrics and structural connectivity were evaluated.

RESULTS

The mean diffusion metrics of Hb were not significantly different between the groups. However, in PD patients, there was an increase in mean structural connectivity from the right Hb to the right hippocampus (p = 0.006) and the right fusiform gyrus (p = 0.007). On the left side, enhanced connectivity was observed with the left pallidum (p = 0.040) and left accumbens (p = 0.009). In the PD group, a significant correlation was found between the BDI total score and increased structural connectivity from the right Hb to the left cingulate isthmus (R2 = 0.090, p = 0.003).

CONCLUSION

This pioneering study examines diffusion metrics and structural connectivity of Hb in PD patients using high-resolution 7 T MRI. Our findings highlight the habenula's potential role in PD pathophysiology, with altered connectivity suggesting early neurodegenerative or compensatory processes. These results underscore the importance of the habenula as a biomarker for PD and its potential as a therapeutic target.

Spatio-temporal learning and explaining for dynamic functional connectivity analysis: Application to depression

BACKGROUND

Functional connectivity has been shown to fluctuate over time. The present study aimed to identifying major depressive disorders (MDD) with dynamic functional connectivity (dFC) from resting-state fMRI data, which would be helpful to produce tools of early depression diagnosis and enhance our understanding of depressive etiology.

METHODS

The resting-state fMRI data of 178 subjects were collected, including 89 MDD and 89 healthy controls. We propose a spatio-temporal learning and explaining framework for dFC analysis. A yet effective spatio-temporal model is developed to classifying MDD from healthy controls with dFCs. The model is a stacking neural network model, which learns network structure information by a multi-layer perceptron based spatial encoder, and learns time-varying patterns by a Transformer based temporal encoder. We propose to explain the spatio-temporal model with a two-stage explanation method of importance feature extracting and disorder-relevant pattern exploring. The layer-wise relevance propagation (LRP) method is introduced to extract the most relevant input features in the model, and the attention mechanism with LRP is applied to extract the important time steps of dFCs. The disorder-relevant functional connections, brain regions, and brain states in the model are further explored and identified.

RESULTS

We achieved the best classification performance in identifying MDD from healthy controls with dFC data. The top important functional connectivity, brain regions, and dynamic states closely related to MDD have been identified.

LIMITATIONS

The data preprocessing may affect the classification performance of the model, and this study needs further validation in a larger patient population.

CONCLUSIONS

The experimental results demonstrate that the proposed spatio-temporal model could effectively classify MDD, and uncover structural and temporal patterns of dFCs in depression.

Major depressive disorder and perceived social support: Moderated mediation model of security and brain dysfunction

Low social support increases the risk of Major depressive disorder (MDD), yet its effects on brain function are unclear. Thirty-two MDD patients with low social support, 52 with high social support, and 54 healthy controls were recruited. We investigated regional brain activity in MDD patients with low social support using resting-state functional Magnetic Resonance Imaging, employing measures such as degree centrality (DC), regional homogeneity, amplitude of low-frequency fluctuations, and fractional amplitude of low-frequency fluctuations. Abnormal regions identified in these analyses were selected as regions of interest for functional connectivity (FC) analysis. We then explored relationships among social support, brain dysfunction, MDD severity, and insecurity using partial correlation and moderated mediation models. Our findings reveal that MDD patients with low social support show decreased DC in the right superior temporal pole and right medial geniculate nucleus, coupled with increased FC between the right superior temporal pole and right inferior temporal gyrus, and the right supramarginal gyrus compared to those with high social support. Furthermore, the DC of the right medial geniculate nucleus positively correlates with social support, while the FC between the right superior temporal pole and right supramarginal gyrus negatively correlates with both social support and subjective support. Additionally, a moderated mediation model demonstrates that the FC between the right superior temporal pole and right supramarginal gyrus mediates the relationship between social support and depression severity, with security moderating this mediation. These findings underscore the impact of low social support on brain function and depression severity in MDD patients.

Modulation of habenular and nucleus accumbens functional connectivity by ketamine in major depression

INTRODUCTION

Major depressive disorder (MDD) is associated with dysfunctional reward processing, which involves functional circuitry of the habenula (Hb) and nucleus accumbens (NAc). Since ketamine elicits rapid antidepressant and antianhedonic effects in MDD, this study sought to investigate how serial ketamine infusion (SKI) treatment modulates static and dynamic functional connectivity (FC) in Hb and NAc functional networks.

METHODS

MDD participants (n = 58, mean age = 40.7 years, female = 28) received four ketamine infusions (0.5 mg/kg) 2-3 times weekly. Resting-state functional magnetic resonance imaging (fMRI) scans and clinical assessments were collected at baseline and 24 h post-SKI. Static FC (sFC) and dynamic FC variability (dFCv) were calculated from left and right Hb and NAc seeds to all other brain regions. Changes in FC pre-to-post SKI, and correlations with changes with mood and anhedonia were examined. Comparisons of FC between patients and healthy controls (HC) at baseline (n = 55, mean age = 32.6, female = 31), and between HC assessed twice (n = 16) were conducted as follow-up analyses.

RESULTS

Following SKI, significant increases in left Hb-bilateral visual cortex FC, decreases in left Hb-left inferior parietal cortex FC, and decreases in left NAc-right cerebellum FC occurred. Decreased dFCv between left Hb and right precuneus and visual cortex, and decreased dFCv between right NAc and right visual cortex both significantly correlated with improvements in mood ratings. Decreased FC between left Hb and bilateral visual/parietal cortices as well as increased FC between left NAc and right visual/parietal cortices both significantly correlated with improvements in anhedonia. No differences were observed between HC at baseline or over time.

CONCLUSION

Subanesthetic ketamine modulates functional pathways linking the Hb and NAc with visual, parietal, and cerebellar regions in MDD. Overlapping effects between Hb and NAc functional systems were associated with ketamine's therapeutic response.