Multimodal brain imaging connectivity analyses of emotional and motivational deficits in depression among women

Microstructural brain assessment in late-life depression and apathy using diffusion MRI multi-compartments models and tractometry

Late-life depression (LLD) is both common and disabling and doubles the risk of dementia onset. Apathy might constitute an additional risk of cognitive decline but clear understanding of its pathophysiology is lacking. While white matter (WM) alterations have been assessed using diffusion tensor imaging (DTI), this model cannot accurately represent WM microstructure. We hypothesized that a more complex multi-compartment model would provide new biomarkers of LLD and apathy. Fifty-six individuals (LLD n = 35, 26 females, 75.2 ± 6.4 years, apathy evaluation scale scores (41.8 ± 8.7) and Healthy controls, n = 21, 16 females, 74.7 ± 5.2 years) were included. In this article, a tract-based approach was conducted to investigate novel diffusion model biomarkers of LLD and apathy by interpolating microstructural metrics directly along the fiber bundle. We performed multivariate statistical analysis, combined with principal component analysis for dimensional data reduction. We then tested the utility of our framework by demonstrating classically reported from the literature modifications in LDD while reporting new results of biological-basis of apathy in LLD. Finally, we aimed to investigate the relationship between apathy and microstructure in different fiber bundles. Our study suggests that new fiber bundles, such as the striato-premotor tracts, may be involved in LLD and apathy, which bring new light of apathy mechanisms in major depression. We also identified statistical changes in diffusion MRI metrics in 5 different tracts, previously reported in major cognitive disorders dementia, suggesting that these alterations among these tracts are both involved in motivation and cognition and might explain how apathy is a prodromal phase of degenerative disorders.

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links Through Daily Activity Patterns and Brain Connectivity Analysis

BACKGROUND

Better understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors.

METHODS

Resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry.

RESULTS

We found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs.

CONCLUSIONS

Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

Regional gray matter volume correlates with anxiety, apathy, and resilience in geriatric depression

OBJECTIVES

Geriatric depression (GD) is associated with significant medical comorbidity, cognitive impairment, brain atrophy, premature mortality, and suboptimal treatment response. While apathy and anxiety are common comorbidities, resilience is a protective factor. Understanding the relationships between brain morphometry, depression, and resilience in GD could inform clinical treatment. Only few studies have addressed gray matter volume (GMV) associations with mood and resilience.

PARTICIPANTS

Forty-nine adults aged >60 years (38 women) with major depressive disorder undergoing concurrent antidepressant treatment participated in the study.

MEASUREMENTS

Anatomical T1-weighted scans, apathy, anxiety, and resilience data were collected. Freesurfer 6.0 was used to preprocess T1-weighted images and qdec to perform voxel-wise whole-brain analyses. Partial Spearman correlations controlling for age and sex tested the associations between clinical scores, and general linear models identified clusters of associations between GMV and clinical scores, with age and sex as covariates. Cluster correction and Monte-Carlo simulations were applied (corrected alpha = 0.05).

RESULTS

Greater depression severity was associated with greater anxiety (r = 0.53, p = 0.0001), lower resilience (r = -0.33, p = 0.03), and greater apathy (r = 0.39, p = 0.01). Greater GMV in widespread, partially overlapping clusters across the brain was associated with reduced anxiety and apathy, as well as increased resilience.

CONCLUSION

Our results suggest that greater GMV in extended brain regions is a potential marker for resilience in GD, while GMV in more focal and overlapping regions may be markers for depression and anxiety. Interventions focused on improving symptoms in GD may seek to examine their effects on these brain regions.

Connectivity patterns of the core resting-state networks associated with apathy in late-life depression

BACKGROUND

Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. We investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD.

METHODS

Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings.

RESULTS

Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intra-RSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network.

LIMITATIONS

The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions.

CONCLUSION

Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Biochemical metabolism in the anterior cingulate cortex and cognitive function in major depressive disorder with or without insomnia syndrome

BACKGROUND

Major depressive disorder (MDD) and insomnia have been linked to deficiencies in cognitive performance. However, the underlying mechanism of cognitive impairment in MDD patients with insomnia symptoms (IS) remains unclear. This study aimed to explore the effects of IS in patients with MDD by comparing cognitive function indices among those with IS, those without insomnia symptoms (NIS), and healthy controls (HCs). In addition, we assessed whether the dysfunction of central nervous system (CNS) is one of the important pathophysiologic mechanisms of IS in patients with MDD by comparing the biochemical metabolism ratios in the anterior cingulate cortex (ACC).

METHOD

Fifty-five MDD with IS, 39 MDD without IS, and 47 demographically matched HCs underwent the MATRICS Consensus Cognitive Battery (MCCB) assessment and proton magnetic resonance spectroscopy (¹H-MRS). MCCB cognitive scores and biochemical metabolism in ACC were assessed and compared between groups.

RESULTS

Compared to the HCs group, IS and NIS groups scored significantly lower in seven MCCB cognitive domains (speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning problem solving and social cognition). IS group showed a lower speed of processing and lower Cho/Cr ratio in the left ACC vs. NIS group and HCs. Also, in IS group, the Cho/Cr ratio in the left ACC was positively correlated with the composite T-score.

CONCLUSION

Patients with comorbidity of MDD with IS may exhibit more common MCCB cognitive impairments than those without IS, particularly speed of processing. Also, dysfunction of ACC may underlie the neural substrate of cognitive impairment in MDD with IS.

Effects of 12-week escitalopram treatment on resting-state functional connectivity of large-scale brain networks in major depressive disorder

In this study, the effects of antidepressants on large-scale brain networks and the neural basis of individual differences in response were explored. A total of 41 patients with major depressive disorder (MDD) and 42 matched healthy controls (HCs) were scanned by resting-state functional magnetic resonance imaging separately at baseline and after a 12-week follow-up. The patients with MDD received escitalopram for 12 weeks. After treatment, patients were classified into those with MDD in remission [MDDr, endpoint 17-item Hamilton Depression Rating Scale (HAMD) total score ≤7] and those in nonremission (MDDnr). The human Brainnetome Atlas was used to define large-scale networks and compute within- and between-network resting-state functional connectivity (rsFC). Results showed the decreased subcortical network (SCN)-ventral attention network (VAN) connectivity at baseline increased in patients with MDD after 12-week treatment, and it was comparable with that of HCs. This change was only observed in patients with MDDr. However, the decreased within-network rsFC in SCN and default mode network (DMN) persisted in all patients with MDD, including those with MDDr and MDDnr, after treatment. The strength of SCN-VAN connectivity at baseline was significantly negatively correlated with the reduction rate of HAMD score in all patients with MDD. Thus, SCN-VAN connectivity may be an antidepressant target associated with depressive state changes and a predictor of treatment response to serotonin reuptake inhibitors. The within-network rsFC in SCN and DMN may reflect a trait-like abnormality in MDD. These findings provide further insights into the mechanism of antidepressants and their individual differences in response. The trial name is "Appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement" (URL: http://www.chictr.org.cn/showproj.aspx?proj=21377; registration number: ChiCTR-OOC-17012566).

Strengths and Weaknesses of the Vascular Apathy Hypothesis: A Narrative Review

The vascular apathy hypothesis states that cerebral small vessel disease (CSVD) can cause apathy, even when no other symptoms of CSVD are present. In order to examine this hypothesis, the objectives of this narrative review are to evaluate the evidence for a pathophysiological mechanism linking CSVD to apathy and to examine whether CSVD can be a sole cause of apathy. The nature of the CSVD-apathy relationship was evaluated using the Bradford Hill criteria as a method for research on the distinction between association and causation. Pathological, neuroimaging, and behavioral studies show that CSVD can cause lesions in the reward network, which causes an apathy syndrome. Studies in healthy older individuals, stroke patients and cognitively impaired persons consistently show an association between CSVD markers and apathy, although studies in older persons suffering from depression are inconclusive. A biological gradient is confirmed, as well as a temporal relationship, although the evidence for the latter is still weak. The specificity of this causal relationship is low given there often are other contributing factors in CSVD patients with apathy, particularly depression and cognitive deterioration. Differentiating between vascular apathy and other apathy syndromes on the basis of clinical features is not yet possible, while in-depth knowledge about differences in the prognosis and efficacy of treatment options for apathy caused by CSVD and other apathy syndromes is lacking. Since we cannot differentiate between etiologically different apathy syndromes as yet, it is premature to use the term vascular apathy which would suggest a distinct clinical apathy syndrome.

Social avoidance behavior modulates motivational responses to social reward-threat conflict signals: A preliminary fMRI study

Social avoidance behavior (SAB) produces impairment in multiple domains and contributes to the development and maintenance of several psychiatric disorders. Social behaviors such as SAB are influenced by approach-avoidance (AA) motivational responses to affective facial expressions. Notably, affective facial expressions communicate varying degrees of social reward signals (happiness), social threat signals (anger), or social reward-threat conflict signals (co-occurring happiness and anger). SAB is associated with dysregulated modulation of automatic approach-avoidance (AA) motivational responses exclusively to social reward-threat conflict signals. However, no neuroimaging research has characterized SAB-related modulation of automatic and subjective AA motivational responses to social reward-threat conflict signals. We recruited 30 adults reporting clinical, moderate, or minimal SAB based on questionnaire cutoff scores. SAB groups were matched on age range and gender. During fMRI scanning, participants completed implicit and subjective approach-avoidance tasks (AATs), which involved more incidental or more explicit evaluation of facial expressions that parametrically varied in social reward signals (e.g., 50%_Happy), social threat signals (e.g., 50%_Angry), or social reward-threat conflict signals (e.g., 50%_Happy + 50%_Angry). In the implicit AAT, SAB was associated with slower automatic avoidance actions and weaker amygdala-pgACC connectivity exclusively as a function of social reward-threat conflict signals. In the subjective AAT, SAB was associated with smaller increases in approach ratings, smaller decreases in avoidance ratings, and weaker dlPFC-pgACC connectivity exclusively in response to social reward-threat conflict signals. Thus, SAB is associated with dysregulated modulation of automatic and subjective AA motivational sensitivity to social reward-threat conflict signals, which may be facilitated by overlapping neural systems.

Apathy in depression: An arterial spin labeling perfusion MRI study

INTRODUCTION

Apathy, as defined as a deficit in goal-directed behaviors, is a critical clinical dimension in depression associated with chronic impairment. Little is known about its cerebral perfusion specificities in depression. To explore neurovascular mechanisms underpinning apathy in depression by pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI).

METHODS

Perfusion imaging analysis was performed on 90 depressed patients included in a prospective study between November 2014 and February 2017. Imaging data included anatomical 3D T1-weighted and perfusion pCASL sequences. A multiple regression analysis relating the quantified cerebral blood flow (CBF) in different regions of interest defined from the FreeSurfer atlas, to the Apathy Evaluation Scale (AES) total score was conducted.

RESULTS

After confound adjustment (demographics, disease and clinical characteristics) and correction for multiple comparisons, we observed a strong negative relationship between the CBF in the left anterior cingulate cortex (ACC) and the AES score (standardized beta = -0.74, corrected p value = 0.0008).

CONCLUSION

Our results emphasized the left ACC as a key region involved in apathy severity in a population of depressed participants. Perfusion correlates of apathy in depression evidenced in this study may contribute to characterize different phenotypes of depression.

Altered Intrinsic Brain Activity in Patients With Toothache Using the Percent Amplitude of a Fluctuation Method: A Resting-State fMRI Study

Objective

The percent amplitude of fluctuation (PerAF) technique was utilized to evaluate the neural functions of specific cerebrum areas in patients with toothache (TA).

Patients and Methods

An aggregation of 18 patients with TA (eight males and 10 females) were included in the study. We also recruited 18 healthy controls (HCs; eight men and 10 women) aligned for sex and age. Resting functional magnetic resonance imaging (rs-fMRI) scans were obtained. Then, we utilized the PerAF method and a support vector machine (SVM) to analyze the image data and measure neural abnormalities in related cerebrum areas. Receiver operating characteristic (ROC) curve analysis was utilized to appraise the two data sets.

Results

The PerAF signals in the right dorsolateral superior frontal gyrus (RDSFG) and the right posterior central gyrus (RPCG) of TA sufferers were lower than HC signals. These results may reveal neural dysfunctions in relevant cerebrum regions. The AUC values of PerAF in the two areas were 0.979 in the RDSFG and 0.979 in the RPCG. The SVM results suggested that PerAF could be utilized to distinguish the TA group from HCs with a sensitivity of 75.00%, a specificity of 66.67%, and an accuracy of 70.83%.

Conclusion

Patients with TA had marked differences in PerAF values in some regions of the cerebrum. Changes in PerAF values represented distinctions in blood oxygen level dependent semaphore intensity, which reflected the overactivity or inactivation of some cerebrum areas in those suffering from TA. At the same time, we analyzed the PerAF values of TAs with ROC curve, which can be helpful for the diagnosis of TA severity and subsequent treatment. Our results may help to elucidate the pathological mechanism of TA.

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.