Reduced functional connectivity of default mode network subsystems in depression: Meta-analytic evidence and relationship with trait rumination

Precision Network Modeling of Transcranial Magnetic Stimulation Across Individuals Suggests Therapeutic Targets and Potential for Improvement

Higher-order cognitive and affective functions are supported by large-scale networks in the brain. Dysfunction in different networks is proposed to associate with distinct symptoms in neuropsychiatric disorders. However, the specific networks targeted by current clinical transcranial magnetic stimulation (TMS) approaches are unclear. While standard-of-care TMS relies on scalp-based landmarks, recent FDA-approved TMS protocols use individualized functional connectivity with the subgenual anterior cingulate cortex (sgACC) to optimize TMS targeting. Leveraging previous work on precision network estimation and recent advances in network-level TMS targeting, we demonstrate that clinical TMS approaches target different functional networks between individuals. Homotopic scalp positions (left F3 and right F4) target different networks within and across individuals, and right F4 generally favors a right-lateralized control network. We also modeled the impact of targeting the dorsolateral prefrontal cortex (dlPFC) zone anticorrelated with the sgACC and found that the individual-specific anticorrelated region variably targets a network coupled to reward circuitry. Combining individualized, precision network mapping and electric field (E-field) modeling, we further illustrate how modeling can be deployed to prospectively target distinct closely localized association networks in the dlPFC with meaningful spatial selectivity and E-field intensity and retrospectively assess network engagement. Critically, we demonstrate the feasibility and reliability of this approach in an independent cohort of participants (including those with Major Depressive Disorder) who underwent repeated sessions of TMS to distinct networks, with precise targeting derived from a low-burden single session of data. Lastly, our findings emphasize differences between selectivity and maximal intensity, highlighting the need to consider both metrics in precision TMS efforts.

Functional connectivity of the default mode network in first-episode drug-naïve patients with major depressive disorder

BACKGROUND

Alterations in the default mode network (DMN) have been reported in major depressive disorder (MDD), well-replicated robust alterations of functional connectivity (FC) of DMN remain to be established. Investigating the functional connections of DMN at the overall and subsystem level in early MDD patients has the potential to advance our understanding of the physiopathology of this disorder.

METHODS

We recruited 115 first-episode drug-naïve patients with MDD and 137 demographic-matched healthy controls (HCs). We first compared FC within the DMN, within/between the DMN subsystems, and from DMN subsystems to the whole brain between groups. Subsequently, we explored correlations between clinical features and identified alterations in FC.

RESULTS

First-episode drug-naïve patients with MDD showed significantly increased FC within the DMN, dorsal DMN and medial DMN. Each subsystem showed a distinct FC pattern with other brain networks. Increased FC between the subsystems (core DMN, dorsal DMN) and other networks was associated with more severe depressive symptoms, while medial DMN-related connectivity correlated with memory performance.

LIMITATIONS

The relatively large "pure" MDD sample could only be generalized to a limited population. And, atypical asymmetric FCs in the DMN related to MDD might be missed for only left-lateralized ROIs were used to avoid strong correlations between mirrored (right/left) seed regions.

CONCLUSION

These findings suggest patients with early MDD showed distinct patterns of FC alterations throughout DMN and its subsystems, which were related to illness severity and illness-associated cognitive impairment, highlighting their clinical significance.

Exploring the neural link between childhood maltreatment and depression: a default mode network rs-fMRI study

Background

Childhood maltreatment (CM) is increasingly recognized as a significant risk factor for major depressive disorder (MDD), yet the neural mechanisms underlying the connection between CM and depression are not fully understood. This study aims to deepen our understanding of this relationship through neuroimaging, exploring how CM correlates with depression.

Methods

The study included 56 MDD patients (33 with CM experiences and 23 without) and 23 healthy controls. Participants were assessed for depression severity, CM experiences, and underwent resting-state functional MRI scans. Independent Component Analysis was used to examine differences in functional connectivity (FC) within the Default Mode Network (DMN) among the groups.

Results

MDD patients with CM experiences exhibited significantly stronger functional connectivity in the left Superior Frontal Gyrus (SFG) and right Anterior Cingulate Cortex (ACC) within the DMN compared to both MDD patients without CM experiences and healthy controls. FC in these regions positively correlated with Childhood Trauma Questionnaire scores. Receiver Operating Characteristic (ROC) curve analysis underscored the diagnostic value of FC in the SFG and ACC for identifying MDD related to CM. Additionally, MDD patients with CM experiences showed markedly reduced FC in the left medial Prefrontal Cortex (mPFC) relative to MDD patients without CM experiences, correlating negatively with Childhood Trauma Questionnaire scores.

Conclusion

Our findings suggest that increased FC in the ACC and SFG within the DMN is associated with CM in MDD patients. This enhanced connectivity in these brain regions is key to understanding the predisposition to depression related to CM.

Quantification of glutathione and its associated spontaneous neuronal activity in major depressive disorder and obsessive-compulsive disorder

BACKGROUND

Glutathione (GSH) is a crucial antioxidant in the human brain. Although proton magnetic resonance spectroscopy (MRS) using the MEscher-GArwood Point RESolved Spectroscopy (MEGA-PRESS) sequence is highly recommended, limited literature has measured cortical GSH using this method in major psychiatric disorders.

METHODS

By combining MRS using the MEGA-PRESS and resting-state functional magnetic resonance imaging, we quantified brain GSH and glutamate in the medial prefrontal cortex (mPFC) and precuneus and explore relationships between the GSH levels and intrinsic neuronal activity as well as clinical symptoms among the three groups of healthy controls (HCs, N=30), major depressive disorder (MDD, N=28), and obsessive-compulsive disorder (OCD, N=28).

RESULTS

GSH concentrations were lower in both the mPFC and precuneus in both the MDD and OCD groups compared to HCs. In HCs, positive correlations were noted between the GSH and glutamate levels, and between GSH and fractional amplitude of low-frequency fluctuations (fALFF) in both regions. However, while these correlations were absent in both patient groups, they showed a weak positive correlation between glutamate and fALFF values. Moreover, GSH levels negatively correlated with depressive and compulsive symptoms in MDD and OCD, respectively.

CONCLUSIONS

These findings suggest that reduced GSH levels and an imbalance between GSH and glutamate could increase oxidative stress and alter neurotransmitter signaling, leading to disruptions in GSH-related neurochemical-neuronal coupling and psychopathologies across MDD and OCD. Understanding these mechanisms could provide valuable insights into the underlying processes of these disorders, potentially becoming a springboard for future directions and advancing our knowledge of their neurobiological foundations.

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.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Differences in resting-state brain activity in first-episode drug-naïve major depressive disorder patients with and without suicidal ideation

Despite altered brain activities being associated with suicidal ideation (SI), the neural correlates of SI in major depressive disorder (MDD) have remained elusive. We enrolled 82 first-episode drug-naïve MDD patients including 41 with SI and 41 without SI, as well as 41 healthy controls (HCs). Resting-state functional and structural MRI data were collected. The measures of fractional amplitude of low-frequency fluctuation (fALFF) and grey matter volume (GMV) were calculated and compared. Compared with HCs, patients with SI exhibited increased fALFF values in the right rectus gyrus and left medial superior frontal gyrus, middle frontal gyrus and precuneus. Decreased GMV in the right parahippocampal gyrus, insula and middle occipital gyrus and increased GMV in the left superior frontal gyrus were detected in patients with SI. In addition, patients without SI demonstrated increased fALFF values in the right superior frontal gyrus and decreased fALFF values in the right postcentral gyrus. Decreased GMV in the left superior frontal gyrus, right medial superior frontal gyrus, opercular part of inferior frontal gyrus, postcentral gyrus, fusiform gyrus and increased left supplementary motor area, superior occipital gyrus, right anterior cingulate gyrus and superior temporal gyrus were revealed in patients with SI. Moreover, in comparison with patients without SI, increased fALFF values were identified in the left precuneus of patients with SI. However, no significant differences were found in GMV between patients with and without SI. These findings might be helpful for finding neuroimaging markers predicting individual suicide risk and detecting targeted brain regions for effective early interventions.

Effects of repetitive transcranial magnetic stimulation on individual variability of resting-state functional connectivity in major depressive disorder

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), but substantial heterogeneity in outcomes remains. We examined a potential mechanism of action of rTMS to normalize individual variability in resting-state functional connectivity (rs-fc) before and after a course of treatment.

METHODS

Variability in rs-fc was examined in healthy controls (baseline) and individuals with MDD (baseline and after 4-6 weeks of rTMS). Seed-based connectivity was calculated to 4 regions associated with MDD: left dorsolateral prefrontal cortex (DLPFC), right subgenual anterior cingulate cortex (sgACC), bilateral insula, and bilateral precuneus. Individual variability was quantified for each region by calculating the mean correlational distance of connectivity maps relative to the healthy controls; a higher variability score indicated a more atypical/idiosyncratic connectivity pattern.

RESULTS

We included data from 66 healthy controls and 252 individuals with MDD in our analyses. Patients with MDD did not show significant differences in baseline variability of rs-fc compared with controls. Treatment with rTMS increased rs-fc variability from the right sgACC and precuneus, but the increased variability was not associated with clinical outcomes. Interestingly, higher baseline variability of the right sgACC was significantly associated with less clinical improvement (p = 0.037, uncorrected; did not survive false discovery rate correction).Limitations: The linear model was constructed separately for each region of interest.

CONCLUSION

This was, to our knowledge, the first study to examine individual variability of rs-fc related to rTMS in individuals with MDD. In contrast to our hypotheses, we found that rTMS increased the individual variability of rs-fc. Our results suggest that individual variability of the right sgACC and bilateral precuneus connectivity may be a potential mechanism of rTMS.

Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study

Evidence suggests that depressive symptomatology is a consequence of network dysfunction rather than lesion pathology. We studied whole-brain functional connectivity using a Minimum Spanning Tree as a graph-theoretical approach. Furthermore, we examined functional connectivity in the Default Mode Network, the Frontolimbic Network (FLN), the Salience Network, and the Cognitive Control Network. All 183 elderly subjects underwent a comprehensive neuropsychological evaluation and a 3 Tesla brain MRI scan. To assess the potential presence of depressive symptoms, the 13-item version of the Beck Depression Inventory (BDI) or the Geriatric Depression Scale (GDS) was utilized. Participants were assigned into three groups based on their cognitive status: amnestic mild cognitive impairment (MCI), non-amnestic MCI, and healthy controls. Regarding affective symptoms, subjects were categorized into depressed and non-depressed groups. An increased mean eccentricity and network diameter were found in patients with depressive symptoms relative to non-depressed ones, and both measures showed correlations with depressive symptom severity. In patients with depressive symptoms, a functional hypoconnectivity was detected between the Anterior Cingulate Cortex (ACC) and the right amygdala in the FLN, which impairment correlated with depressive symptom severity. While no structural difference was found in subjects with depressive symptoms, the volume of the hippocampus and the thickness of the precuneus and the entorhinal cortex were decreased in subjects with MCI, especially in amnestic MCI. The increase in eccentricity and diameter indicates a more path-like functional network configuration that may lead to an impaired functional integration in depression, a possible cause of depressive symptomatology in the elderly.

Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

OBJECTIVE

Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study.

METHODS

Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed.

RESULTS

Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes.

CONCLUSION

DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.

Rumination-Focused Cognitive Behavioral Therapy Reduces Rumination and Targeted Cross-network Connectivity in Youth With a History of Depression: Replication in a Preregistered Randomized Clinical Trial

Background

Rumination-focused cognitive behavioral therapy (RF-CBT) is designed to reduce depressive rumination or the habitual tendency to dwell on experiences in a repetitive, negative, passive, and global manner. RF-CBT uses functional analysis, experiential exercises, and repeated practice to identify and change the ruminative habit. This preregistered randomized clinical trial (NCT03859297, R61) is a preregistered replication of initial work. We hypothesized a concurrent reduction of both self-reported rumination and cross-network connectivity between the left posterior cingulate cortex and right inferior frontal and inferior temporal gyri.

Methods

Seventy-six youths with a history of depression and elevated rumination were randomized to 10 to 14 sessions of RF-CBT (n = 39; 34 completers) or treatment as usual (n = 37; 28 completers). Intent-to-treat analyses assessed pre-post change in rumination response scale and in functional connectivity assessed using two 5 minute, 12 second runs of resting-state functional magnetic resonance imaging.

Results

We replicated previous findings: a significant reduction in rumination response scale and a reduction in left posterior cingulate cortex to right inferior frontal gyrus/inferior temporal gyrus connectivity in participants who received RF-CBT compared with those who received treatment as usual. Reductions were large (z change = 0.84; 0.73, respectively [ps < .05]).

Conclusions

This adolescent clinical trial further demonstrates that depressive rumination is a brain-based mechanism that is modifiable via RF-CBT. Here, we replicated that RF-CBT reduces cross-network connectivity, a possible mechanism by which rumination becomes less frequent, intense, and automatic. This National Institute of Mental Health-funded fast-fail study continues to the R33 phase during which treatment-specific effects of RF-CBT will be compared with relaxation therapy.

Thalamo-cortical circuits associated with trait- and state-repetitive negative thinking in major depressive disorder

BACKGROUND

Repetitive negative thinking (RNT), often referred to as rumination in the mood disorders literature, is a symptom dimension associated with poor prognosis and suicide in major depressive disorder (MDD). Given the transdiagnostic nature of RNT, this study aimed to evaluate the hypothesis that neurobiological substrates of RNT in MDD may share the brain mechanisms underlying obsessions, particularly those involving cortico-striatal-thalamic-cortical (CSTC) circuits.

METHODS

Thirty-nine individuals with MDD underwent RNT induction during fMRI. Trait-RNT was measured by the Ruminative Response Scale (RRS) and state-RNT was measured by a visual analogue scale. We employed a connectome-wide association analysis examining the association between RNT intensity with striatal and thalamic connectivity.

RESULTS

A greater RRS score was associated with hyperconnectivity of the right mediodorsal thalamus with prefrontal cortex, including lateral orbitofrontal cortex, along with Wernicke's area and posterior default mode network nodes (t = 4.66-6.70). A greater state-RNT score was associated with hyperconnectivity of the right laterodorsal thalamus with bilateral primary sensory and motor cortices, supplementary motor area, and Broca's area (t = 4.51-6.57). Unexpectedly, there were no significant findings related to the striatum.

CONCLUSIONS

The present results suggest RNT in MDD is subserved by abnormal connectivity between right thalamic nuclei and cortical regions involved in both visceral and higher order cognitive processing. Emerging deep-brain neuromodulation methods may be useful to establish causal relationships between dysfunction of right thalamic-cortical circuits and RNT in MDD.

Striatal correlates of Bayesian beliefs in self-efficacy in adolescents and their relation to mood and autonomy: a pilot study

Major depressive disorder often originates in adolescence and is associated with long-term functional impairment. Mechanistically characterizing this heterogeneous illness could provide important leads for optimizing treatment. Importantly, reward learning is known to be disrupted in depression. In this pilot fMRI study of 21 adolescents (16-20 years), we assessed how reward network disruption impacts specifically on Bayesian belief representations of self-efficacy (SE-B) and their associated uncertainty (SE-U), using a modified instrumental learning task probing activation induced by the opportunity to choose, and an optimal Hierarchical Gaussian Filter computational model. SE-U engaged caudate, nucleus accumbens (NAcc), precuneus, posterior parietal and dorsolateral prefrontal cortex (PFWE < 0.005). Sparse partial least squares analysis identified SE-U striatal activation as associating with one's sense of perceived choice and depressive symptoms, particularly anhedonia and negative feelings about oneself. As Bayesian uncertainty modulates belief flexibility and their capacity to steer future actions, this suggests that these striatal signals may be informative developmentally, longitudinally and in assessing response to treatment.

Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state

Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.

Functional connectivity in rumination: a systematic review of magnetic resonance imaging studies

INTRODUCTION

Rumination, defined as intrusive and repetitive thoughts in response to negative emotions, uncertainty, and inconsistency between goal and current situation, is a significant risk factor for depressive disorders. The rumination literature presents diverse findings on functional connectivity and shows heterogeneity in research methods. This systematic review seeks to integrate these findings and provide readers diverse perspectives.

METHOD

For this purpose, the literature on functional connectivity in rumination was reviewed according to the PRISMA guidelines. Regional connectivity and network connectivity results were scrutinized according to the presence of depression, research methods, and type of rumination. After screening 492 articles, a total of 36 studies were included.

RESULTS

The results showed that increased connectivity of the default mode network (DMN) was consistently reported. Other important findings include alterations in the connectivity between the DMN and the frontoparietal network and the salience network (SN) and impaired regulatory function of the SN. Region-level connectivity studies consistently show that increased connectivity between the posterior cingulate cortex and the prefrontal cortex is associated with rumination, which may cause the loss of control of the frontoparietal network over self-referential processes. We have seen that the number of studies examining brooding and reflective rumination as separate dimensions are relatively limited. Although there are overlaps between the connectivity patterns of the two types of rumination in these studies, it can be thought that reflective rumination is more associated with more increased functional connectivity of the prefrontal cortex.

CONCLUSIONS

Although there are many consistent functional connectivity outcomes associated with trait rumination, less is known about connectivity changes during state rumination. Relatively few studies have taken into account the subjective aspect of this thinking style. In order to better explain the relationship between rumination and depression, rumination induction studies during episode and remission periods of depression are needed.

Repetitive Negative Thinking-Specific and -Nonspecific White Matter Tracts Engaged by Historical Psychosurgical Targets for Depression

BACKGROUND

Repetitive negative thinking (RNT) is a frequent symptom of major depressive disorder (MDD) that is associated with poor outcomes and treatment resistance. While most studies on RNT have focused on structural and functional characteristics of gray matter, this study aimed to examine the association between white matter (WM) tracts and interindividual variability in RNT.

METHODS

A probabilistic tractography approach was used to characterize differences in the size and anatomical trajectory of WM fibers traversing psychosurgery targets historically useful in the treatment of MDD (anterior capsulotomy, anterior cingulotomy, and subcaudate tractotomy) in patients with MDD and low (n = 53) or high (n = 52) RNT, and healthy control subjects (n = 54). MDD samples were propensity matched on depression and anxiety severity and demographics.

RESULTS

WM tracts traversing left hemisphere targets and reaching the ventral anterior body of the corpus callosum (thus extending to contralateral regions) were larger in the high-RNT MDD group compared with low-RNT (effect size D = 0.27, p = .042) and healthy control (D = 0.23, p = .02) groups. MDD was associated with greater size of tracts that converge onto the right medial orbitofrontal cortex regardless of RNT intensity. Other RNT-nonspecific findings in MDD involved tracts reaching the left primary motor and right primary somatosensory cortices.

CONCLUSIONS

This study provides the first evidence to our knowledge that WM connectivity patterns, which could become targets of intervention, differ between high- and low-RNT participants with MDD. These WM differences extend to circuits that are not specific to RNT, possibly subserving reward mechanisms and psychomotor activity.

Childhood trauma is linked to abnormal static-dynamic brain topology in adolescents with major depressive disorder

Childhood trauma is a leading risk factor for adolescents developing major depressive disorder (MDD); however, the underlying neuroimaging mechanisms remain unclear. This study aimed to investigate the association among childhood trauma, MDD and brain dysfunctions by combining static and dynamic brain network models. We recruited 46 first-episode drug-naïve adolescent MDD patients with childhood trauma (MDD-CT), 53 MDD patients without childhood trauma (MDD-nCT), and 90 healthy controls (HCs) for resting-state functional magnetic resonance imaging (fMRI) scans; all participants were aged 13-18 years. Compared to the HCs and MDD-nCT groups, the MDD-CT group exhibited significantly higher global and local efficiency in static brain networks and significantly higher temporal correlation coefficients in dynamic brain network models at the whole-brain level, and altered the local efficiency of default mode network (DMN) and temporal correlation coefficients of DMN, salience (SAN), and attention (ATN) networks at the local perspective. Correlation analysis indicated that altered brain network features and clinical symptoms, childhood trauma, and particularly emotional neglect were highly correlated in adolescents with MDD. This study may provide new evidence for the dysconnectivity hypothesis regarding the associations between childhood trauma and MDD in adolescents from the perspectives of both static and dynamic brain topology.

Trait- and state-like co-activation pattern dynamics in current and remitted major depressive disorder

BACKGROUND

Distinguishing between trait- and state-like neural alternations in major depressive disorder (MDD) may advance our understanding of this recurring disorder. We aimed to investigate dynamic functional connectivity alternations in unmedicated individuals with current or past MDD using co-activation pattern analyses.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from individuals with first-episode current MDD (cMDD, n = 50), remitted MDD (rMDD, n = 44), and healthy controls (HCs, n = 64). Using a data-driven consensus clustering technique, four whole-brain states of spatial co-activation were identified and associated metrics (dominance, entries, transition frequency) were analyzed with respect to clinical characteristics.

RESULTS

Relative to rMDD and HC, cMDD showed increased dominance and entries of state 1 (primarily involving default mode network (DMN)), and decreased dominance of state 4 (mostly involving frontal-parietal network (FPN)). Among cMDD, state 1 entries correlated positively with trait rumination. Conversely, relative to cMDD and HC, individuals with rMDD were characterized by increased state 4 entries. Relative to HC, both MDD groups showed increased state 4-to-1 (FPN to DMN) transition frequency but reduction in state 3 (spanning visual attention, somatosensory, limbic networks), with the former metric specifically related to trait rumination.

LIMITATIONS

Further confirmation with longitudinal studies are required.

CONCLUSIONS

Regardless of symptoms, MDD was characterized by increased FPN-to-DMN transitions and reduced dominance of a hybrid network. State-related effect emerged in regions critically implicated in repetitive introspection and cognitive control. Asymptomatic individuals with past MDD were uniquely linked to increased FPN entries. Our findings identify trait-like brain network dynamics that might increase vulnerability to future MDD.

Intensity of repetitive negative thinking in depression is associated with greater functional connectivity between semantic processing and emotion regulation areas

BACKGROUND

Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity.

METHODS

We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups.

RESULTS

There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity.

CONCLUSIONS

RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT.

Regions with Altered Degree Centrality and Their Functional Connectivity in First-Episode Drug-Naïve Major Depressive Disorder: A Resting-State Functional Magnetic Resonance Imaging Study

Objective

The aim of this study was to identify regions with altered degrees of centrality (DC) and changes in their functional connectivity (FC) in first-episode drug-naïve major depressive disorder (FEDN-MDD) patients using resting-state functional magnetic resonance imaging (fMRI).

Methods

The study included 74 FEDN-MDD patients who met the study criteria and 41 healthy controls (HCs). All had undergone fMRI scanning in the resting condition. To evaluate differences between FEDN-MDD patients and HCs, we first compared the DC between the 2 groups. The DC regions with the most significant differences were then taken as seeds, and their FC was calculated.

Results

Right posterior cingulum cortex (PCC.R), right precuneus (PCUN.R), and right putamen (PUT.R) all showed significantly different DC values (P < .001) between FEDN-MDD patients and HC groups, which helped in distinguishing these groups. The PUT.R in FEDN-MDD patients showed increased FC (P < .001) with the right inferior temporal gyrus and right inferior occipital gyrus compared to HC. Moreover, the PCUN.R in FEDN-MDD patients showed decreased FC (P < .001) with bilateral cerebellum crus I, left cerebellum crus II, bilateral orbital medial frontal gyrus, right superior medial frontal gyrus, left precuneus, left posterior cingulum cortex, right superior frontal gyrus, and PCC.R compared with the HC group. The P-values for cluster testing were .050, while for voxel testing they were .001.

Conclusion

These findings imply that PUT.R, PCUN.R, and PCC.R serve as the core brain net hub in FEDN-MDD patients, and their FC displays aberrant function. This may involve a specific psychiatric neuropathology associated with FEDN-MDD.

Predicting outcome with Intranasal Esketamine treatment: A machine-learning, three-month study in Treatment-Resistant Depression (ESK-LEARNING)

Treatment-resistant depression (TRD) represents a severe clinical condition with high social and economic costs. Esketamine Nasal Spray (ESK-NS) has recently been approved for TRD by EMA and FDA, but data about predictors of response are still lacking. Thus, a tool that can predict the individual patients' probability of response to ESK-NS is needed. This study investigates sociodemographic and clinical features predicting responses to ESK-NS in TRD patients using machine learning techniques. In a retrospective, multicentric, real-world study involving 149 TRD subjects, psychometric data (Montgomery-Asberg-Depression-Rating-Scale/MADRS, Brief-Psychiatric-Rating-Scale/BPRS, Hamilton-Anxiety-Rating-Scale/HAM-A, Hamilton-Depression-Rating-Scale/HAMD-17) were collected at baseline and at one month/T1 and three months/T2 post-treatment initiation. We trained three different random forest classifiers, able to predict responses to ESK-NS with accuracies of 68.53% at T1 and 66.26% at T2 and remission at T2 with 68.60% of accuracy. Features like severe anhedonia, anxious distress, mixed symptoms as well as bipolarity were found to positively predict response and remission. At the same time, benzodiazepine usage and depression severity were linked to delayed responses. Despite some limitations (i.e., retrospective study, lack of biomarkers, lack of a correct interrater-reliability across the different centers), these findings suggest the potential of machine learning in personalized intervention for TRD.

Physical activity and depression of Chinese college students: chain mediating role of rumination and anxiety

Objective

To explore the relationship between physical activity and depression among college students, as well as the mediating role of rumination and anxiety.

Methods

A total of 1,292 Chinese college students were investigated by physical activity questionnaire, rumination scale, self-rating anxiety scale (SAS), and depression scale.

Results

(1) There was a significant negative correlation between physical activity and depression (r = -0.399, p < 0.01), and the direct path of physical activity on depression was significant (β = -0.399, t = -13.374, p < 0.01). (2) Physical activity negatively predicted rumination (β = -0.322, t = -10.440, p < 0.01) and anxiety (β = -0.222, t = -7.089, p < 0.01). Rumination positively predicted anxiety (β = 0.283, t = 9.017, p < 0.01) and depression (β = 0.267, t = 9.046, p < 0.01). Anxiety positively predicted depression (β = 0.262, t = 8.902, p < 0.01). (3) Rumination and anxiety play a significant mediating role between physical activity and depression. The mediating effect involves three paths: physical activity → rumination → depression (the mediating effect value: -0.076); physical activity → anxiety → depression (the mediating effect value: -0.052). Physical activity → rumination → anxiety → depression (the mediating effect value: -0.021).

Conclusion

(1) Physical activity can negatively predict the rumination, anxiety, and depression of college students, which means physical activity can reduce rumination, anxiety, and depression of college students. (2) Physical activity can not only directly affect the depression of college students, but also indirectly affect depression through the independent intermediary role of rumination and anxiety, and the chain mediation of rumination and anxiety.

Triple network model of brain connectivity changes related to adverse mood effects in an oral contraceptive placebo-controlled trial

Combined oral contraceptives (COC) are among the most commonly used contraceptive methods worldwide, and mood side effects are the major reason for discontinuation of treatment. We here investigate the directed connectivity patterns associated with the mood side effects of an androgenic COC in a double-blind randomized, placebo-controlled trial in women with a history of affective COC side effects (n = 34). We used spectral dynamic causal modeling on a triple network model consisting of the default mode network (DMN), salience network (SN) and executive control network (ECN). Within this framework, we assessed the treatment-related changes in directed connectivity associated with adverse mood side effects. Overall, during COC use, we found a pattern of enhanced connectivity within the DMN and decreased connectivity within the ECN. The dorsal anterior cingulate cortex (SN) mediates an increased recruitment of the DMN by the ECN during treatment. Mood lability was the most prominent COC-induced symptom and also arose as the side effect most consistently related to connectivity changes. Connections that were related to increased mood lability showed increased connectivity during COC treatment, while connections that were related to decreased mood lability showed decreased connectivity during COC treatment. Among these, the connections with the highest effect size could also predict the participants' treatment group above chance.

A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Rumination is a cognitive style characterized by repetitive thoughts about one's negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.

Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state

Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.

Biological factors influencing depression in later life: role of aging processes and treatment implications

Late-life depression occurring in older adults is common, recurrent, and malignant. It is characterized by affective symptoms, but also cognitive decline, medical comorbidity, and physical disability. This behavioral and cognitive presentation results from altered function of discrete functional brain networks and circuits. A wide range of factors across the lifespan contributes to fragility and vulnerability of those networks to dysfunction. In many cases, these factors occur earlier in life and contribute to adolescent or earlier adulthood depressive episodes, where the onset was related to adverse childhood events, maladaptive personality traits, reproductive events, or other factors. Other individuals exhibit a later-life onset characterized by medical comorbidity, pro-inflammatory processes, cerebrovascular disease, or developing neurodegenerative processes. These later-life processes may not only lead to vulnerability to the affective symptoms, but also contribute to the comorbid cognitive and physical symptoms. Importantly, repeated depressive episodes themselves may accelerate the aging process by shifting allostatic processes to dysfunctional states and increasing allostatic load through the hypothalamic-pituitary-adrenal axis and inflammatory processes. Over time, this may accelerate the path of biological aging, leading to greater brain atrophy, cognitive decline, and the development of physical decline and frailty. It is unclear whether successful treatment of depression and avoidance of recurrent episodes would shift biological aging processes back towards a more normative trajectory. However, current antidepressant treatments exhibit good efficacy for older adults, including pharmacotherapy, neuromodulation, and psychotherapy, with recent work in these areas providing new guidance on optimal treatment approaches. Moreover, there is a host of nonpharmacological treatment approaches being examined that take advantage of resiliency factors and decrease vulnerability to depression. Thus, while late-life depression is a recurrent yet highly heterogeneous disorder, better phenotypic characterization provides opportunities to better utilize a range of nonspecific and targeted interventions that can promote recovery, resilience, and maintenance of remission.

Subsystem mechanisms of default mode network underlying white matter hyperintensity-related cognitive impairment

Functional changes of default mode network (DMN) have been proven to be closely associated with white matter hyperintensity (WMH) related cognitive impairment (CI). However, subsystem mechanisms of DMN underlying WMH-related CI remain unclear. The present study recruited WMH patients (n = 206) with mild CI and normal cognition, as well as healthy controls (HC, n = 102). Static/dynamic functional connectivity (FC) of the DMN's three subsystems were calculated using resting-state functional MRI. K-means clustering analyses were performed to extract distinct dynamic connectivity states. Compared with the WMH-NC group, the WMH-MCI group displayed lower static FC within medial temporal lobe (MTL) and core subsystem, between core-MTL subsystem, as well as between core and dorsal medial prefrontal cortex subsystem. All these static alterations were positively associated with information processing speed (IPS). Regarding dynamic FC, the WMH-MCI group exhibited higher dynamic FC within MTL subsystem than the HC and WMH-NC groups. Altered dynamic FC within MTL subsystem mediated the relationship between WMH and memory span (indirect effect: -0.2251, 95% confidence interval [-0.6295, -0.0267]). Additionally, dynamic FCs of DMN subsystems could be clustered into two recurring states. For dynamic FCs within MTL subsystem, WMH-MCI subjects exhibited longer mean dwell time (MDT) and higher reoccurrence fraction (RF) in a sparsely connected state (State 2). Altered MDT and RF in State 2 were negatively associated with IPS. Taken together, these findings indicated static/dynamic FC of DMN subsystems can provide relevant information on cognitive decline from different aspects, which provides a comprehensive view of subsystem mechanisms of DMN underlying WMH-related CI.

Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms

The default mode network (DMN) plays a crucial role in internal self-processing, rumination, and social functions. Disruptions to DMN connectivity have been linked with early adversity and the emergence of psychopathology in adolescence and early adulthood. Herein, we investigate how subclinical psychiatric symptoms can impact DMN functional connectivity during the pubertal transition. Resting-state fMRI data were collected annually from 190 typically-developing youth (9-15 years-old) at three timepoints and within-network DMN connectivity was computed. We used latent growth curve modeling to determine how self-reported depressive and posttraumatic stress symptoms predicted rates of change in DMN connectivity over the three-year period. In the baseline model without predictors, we found no systematic changes in DMN connectivity over time. However, significant modulation emerged after adding psychopathology predictors; greater depressive symptomatology was associated with significant decreases in connectivity over time, whereas posttraumatic stress symptoms were associated with significant increases in connectivity over time. Follow-up analyses revealed that these effects were driven by connectivity changes involving the dorsal medial prefrontal cortex subnetwork. In conclusion, these data suggest that subclinical depressive and posttraumatic symptoms alter the trajectory of DMN connectivity, which may indicate that this network is a nexus of clinical significance in mental health disorders.

The Characteristics of Entorhinal Cortex Functional Connectivity in Alzheimer's Disease Patients with Depression

BACKGROUND

Depression is one of the most common neuropsychiatric symptoms of Alzheimer's disease (AD) which decreases the life quality of both patients and caregivers. There are currently no effective drugs. It is therefore important to explore the pathogenesis of depression in AD patients.

OBJECTIVE

The present study aimed to investigate the characteristics of the entorhinal cortex (EC) functional connectivity (FC) in the whole brain neural network of AD patients with depression (D-AD).

METHODS

Twenty-four D-AD patients, 14 AD patients without depression (nD-AD), and 20 healthy controls underwent resting-state functional magnetic resonance imaging. We set the EC as the seed and used FC analysis. One-way analysis of variance was used to examine FC differences among the three groups.

RESULTS

Using the left EC as the seed point, there were FC differences among the three groups in the left EC-inferior occipital gyrus. Using the right EC as the seed point, there were FC differences among the three groups in the right EC-middle frontal gyrus, -superior parietal gyrus, -superior medial frontal gyrus, and -precentral gyrus. Compared with the nD-AD group, the D-AD group had increased FC between the right EC and right postcentral gyrus.

CONCLUSION

Asymmetry of FC in the EC and increased FC between the EC and right postcentral gyrus may be important in the pathogenesis of depression in AD.

Decreased functional connectivity in patients with major depressive disorder and a history of childhood traumatization through experiences of abuse

BACKGROUND

Childhood trauma (CT) increases vulnerability for the development of major depressive disorder (MDD). Alterations in resting-state functional connectivity (RSFC) have frequently been reported for MDD. These alterations may be much more prominent in depressive patients with a history of CT. The present study aims to compare RSFC in different brain networks of patients with MDD and CT (MDD+CT) vs. MDD and no CT compared to healthy controls.

METHODS

45 patients (22 with CT) were compared to 23 age-and-gender-matched healthy control subjects. Demographic parameters, severity of MDD, severity of CT and comorbid anxiety disorders were assessed. For assessment of RSFC alterations, a seed-based approach within five well-established RSFC networks was used.

RESULTS

CT in MDD patients predicts severity of comorbid anxiety. A significant decrease in in-between network RSFC-values of MDD patients compared to controls was found in the network pairs of default mode network (DMN) - dorsal attention network (DAN), ventral attention network (VAN) - DMN and DAN - affective network (AN). MDD+CT patients presented more aberrant RSFC than MDD-CT patients. MDD scores predicted the decrease in RSFC for MDD patients. Higher Childhood Trauma Questionnaire (CTQ) scores are linked to reduced functional connectivity (FC) between DMN - DAN.

CONCLUSIONS

Our study shows reduced RSFC in MDD patients for DMN - DAN, VAN - DMN, DAN - AN and MDD+CT patients presented more aberrant RSFC so that we suspect CT to be a considerable factor in the etiology of MDD. Through dysregulated neural circuits, CT is likely to contribute to a distinct MDD pathophysiology.

Questionnaires based on natural language processing elicit immersive ruminative thinking in ruminators: Evidence from behavioral responses and EEG data

Rumination is closely related to mental disorders and can thus be used as a marker of their presence or a predictor of their development. The presence of masking and fabrication in psychological selection can lead to inaccurate detection of psychological disorders. Human language is considered crucial in eliciting specific conscious activities, and the use of natural language processing (NLP) in the development of questionnaires for psychological tests has the potential to elicit immersive ruminative thinking, leading to changes in neural activity. Electroencephalography (EEG) is commonly used to detect and record neural activity in the human brain and is sensitive to changes in brain activity. In this study, we used NLP to develop a questionnaire to induce ruminative thinking and then recorded the EEG signals in response to the questionnaire. The behavioral results revealed that ruminators exhibited higher arousal rates and longer reaction times, specifically in response to the ruminative items of the questionnaire. The EEG results showed no significant difference between the ruminators and the control group during the resting state; however, a significant alteration in the coherence of the entire brain of the ruminators existed while they were answering the ruminative items. No differences were found in the control participants while answering the two items. These behavioral and EEG results indicate that the questionnaire elicited immersive ruminative thinking, specifically in the ruminators. Therefore, the questionnaire designed using NLP is capable of eliciting ruminative thinking in ruminators, offering a promising approach for the early detection of mental disorders in psychological selection.

Functional connectivity of the default mode network subsystems in patients with major depressive episodes with mixed features

Background

The neuroimaging mechanism of major depressive episodes with mixed features (MMF) is not clear.

Aims

This study aimed to investigate the functional connectivity of the default mode network (DMN) subsystems among patients with MMF and patients with major depressive disorder without mixed features (MDD_noMF).

Methods

This study recruited 47 patients with MDD_noMF and 27 patients with MMF from Beijing Anding Hospital, Capital Medical University, between April 2021 and June 2022. Forty-five healthy controls (HCs) were recruited. All subjects underwent resting-state functional magnetic resonance imaging scanning and clinical assessments. Intranetwork and internetwork functional connectivity were computed in the DMN core subsystem, dorsal medial prefrontal cortex (dMPFC) subsystem and medial temporal lobe (MTL) subsystem. Analysis of covariance method was performed to compare the intranetwork and internetwork functional connectivity in the DMN subsystems among the MDD_noMF, MMF and HC groups.

Results

The functional connectivity within the DMN core (F=6.32, p_FDR=0.008) and MTL subsystems (F=4.45, p_FDR=0.021) showed significant differences among the MDD_noMF, MMF and HC groups. Compared with the HC group, the patients with MDD_noMF and MMF had increased functional connectivity within the DMN MTL subsystem, and the patients with MMF also showed increased functional connectivity within the DMN core subsystem. Meanwhile, compared with the MDD_noMF, the patients with MMF had increased functional connectivity within the DMN core subsystem (mean difference (MDD_noMF-MMF)=-0.08, SE=0.04, p=0.048). However, no significant differences were found within the DMN dMPFC subsystem and all the internetwork functional connectivity.

Conclusions

Our results indicated abnormal functional connectivity patterns of DMN subsystems in patients with MMF, findings potentially beneficial to deepen our understanding of MMF's neural basis.

Rostral anterior cingulate connectivity in older adults with subthreshold depressive symptoms: A preliminary study

Subthreshold depressive symptoms are highly prevalent among older adults and are associated with numerous health risks including cognitive decline and decreased physical health. One brain region central to neuroanatomical models of depressive disorders is the anterior cingulate cortex (ACC). The rostral portion of the ACC-comprised of the pregenual ACC and subgenual ACC-is implicated in emotion control and reward processing. The goal of the current study was to examine how functional connectivity in subregions of the rostral ACC relate to depressive symptoms, measured by the Beck Depression Inventory-Second Edition, in an ethnically diverse sample of 28 community-dwelling older adults. Based on meta-analyses of previous studies in primarily young adults with clinical depression, we hypothesized that greater depressive symptoms would be associated with primarily increased resting-state functional connectivity from both the subgenual ACC and pregenual ACC to default mode network regions and the dorsolateral PFC. We instead found that higher depressive symptoms were associated with lower functional connectivity of the ACC to the dorsolateral PFC and regions within the default mode network, including from the subgenual ACC to the dorsolateral PFC and anterior cingulate and from the pregenual ACC to the middle cingulate gyrus. This preliminary study highlights brain alterations at subthreshold levels of depressive symptoms in older adults, which could serve as targets for interventions.

Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach

Objective

Type 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.

Methods

A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.

Results

In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.

Conclusion

Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.

Shared brain and genetic architectures between mental health and physical activity

Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear. Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (N = 6389), we applied canonical correlation analysis to estimate associations between the amplitude and connectivity strength of subnetworks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health measures (primarily of depression, anxiety disorders, neuroticism, subjective well-being, and risk-taking behaviors). We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS N = 91,105-500,199). Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (r's ≥ 0.12, p's < 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity (including sleep) were also genetically correlated (|rg| = 0.085-0.121), but we found no evidence for causal relationships between them. Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate subnetworks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health.

Neural signatures of default mode network in major depression disorder after electroconvulsive therapy

Functional abnormalities of default mode network (DMN) have been well documented in major depressive disorder (MDD). However, the association of DMN functional reorganization with antidepressant treatment and gene expression is unclear. Moreover, whether the functional interactions of DMN could predict treatment efficacy is also unknown. Here, we investigated the link of treatment response with functional alterations of DMN and gene expression with a comparably large sample including 46 individuals with MDD before and after electroconvulsive therapy (ECT) and 46 age- and sex-matched healthy controls. Static and dynamic functional connectivity (dFC) analyses showed increased intrinsic/static but decreased dynamic functional couplings of inter- and intra-subsystems and between nodes of DMN. The changes of static functional connections of DMN were spatially correlated with brain gene expression profiles. Moreover, static and dFC of the DMN before treatment as features could predict depressive symptom improvement following ECT. Taken together, these results shed light on the underlying neural and genetic basis of antidepressant effect of ECT and the intrinsic functional connectivity of DMN have the potential to serve as prognostic biomarkers to guide accurate personalized treatment.

Possible Association of Nucleobindin-1 Protein with Depressive Disorder in Patients with HIV Infection

Background: Mental disorders linked with dysfunction in the temporal cortex, such as anxiety and depression, can increase the morbidity and mortality of people living with HIV (PLWHA). Expressions of both nucleobindin 1 (NUCB1) and cannabinoid receptor 1 (CNR1) in the neurons have been found to alter in patients with depressive disorder, but whether it is involved in the development of depression in the context of HIV infection is unknown. Objectives To investigate the effects of NUCB1 on depressive disorder among PLWHA and preliminarily explore the underlying molecular mechanisms. Methods: Individuals who were newly HIV diagnosed were assessed on the Hospital Anxiety and Depression scale (HADS). Then SHIV-infected rhesus monkeys were used to investigate the possible involvement of the NUCB1 and the CNR1 protein in depression-like behavior. Results: The prevalence rate of depression among PLWHA was 27.33% (41/150). The mechanism results showing elevated NUCB1 levels in cerebrospinal fluid from HIV-infected patients suffering from depression were confirmed compared to those of HIV-infected patients. Moreover, the immunohistochemical analysis indicated the expression of NUCB1 in the temporal cortex neurons of SHIV-infected monkeys was higher than that of the healthy control. Conversely, CNR1 expression was down-regulated at protein levels. Conclusions: Depression symptoms are common among PLWHA and associate with NUCB1 expression increases, and NUCB1 may be a potential target for depression.

Brain Response of Major Depressive Disorder Patients to Emotionally Positive and Negative Music

Depression is characterized by poor emotion regulation that makes it difficult to escape the effects of emotional pain, but the neuromodulation behind these symptoms is still unclear. This study investigated the neural mechanism of emotional state-related responses during music stimuli in participants with major depressive disorder (MDD) compared to never-depressed (ND) controls. A novel two-level feature selection method, integrating recursive feature elimination based on support vector machine (SVM-RFE) and random forest algorithm (RF), was proposed to screen emotional recognition brain regions (ERBRs). On this basis, the differences of functional connectivity (FC) were systematically analyzed by two-sample t-test. The results demonstrate that ND participants show eight pairs of FCs with a significant difference between positive emotional music stimuli (pEMS) versus negative emotional music stimuli (nEMS) in 15 ERBRs of MDD, but the participants with MDD show one pair of significant difference in FC. The decreased number reflects the fuzzy response to positive and negative emotions in MDD, which appears to arise from obstacle to emotional cognition and regulation. Furthermore, there was no significant difference in FC between MDDs and NDs under pEMS, but a significant difference was detected between the two groups under nEMS (p < 0.01), revealing a 'bias' against the negative state in MDD. The current study may help to better comprehend the abnormal evolution from normal to depression and inform the utilization of pEMS in formal treatment for depression.

Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum

Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.

Inflammation Disrupts Cognitive Integrity via Plasma Neurofilament Light Chain Coupling Brain Networks in Alzheimer’s Disease

Objective: Background: Plasma neurofilament light chain (NFL) is a recognized biomarker for Alzheimer’s disease (AD) and inflammation. Intrinsically organized default mode network core subsystem and frontoparietal network (FPN) and their interactions support complex cognitive function. The present study investigated the inflammatory effect on cognitive integrity via plasma NFL coupling internetwork interactions in AD. Objective: Objective: This study investigates the hypothesis that inflammation-related plasma NFL could affect the interactions of the core subsystem and FPN, which leads to the aggravation of the clinical symptoms of AD-spectrum patients. Objective: Methods: A total of 112 AD-spectrum participants underwent complete resting-state fMRI, neuropsychological tests, and plasma NFL at baseline (n = 112) and after approximately 17 months of follow-up (n = 112). The specific intersystem changes in the core subsystem and FPN were calculated and compared across groups. Then, the classifications of different AD-spectrum groups were analyzed using the association of plasma NFL and the changed intersystem interacting regions. Finally, mediation analysis was applied to investigate the significance of plasma NFL coupling networks on cognitive impairments in these subjects. Objective: Results: Discrimination of disease-related interactions of the core subsystem and FPN was found in AD-spectrum patients, which was the neural circuit fundamental to plasma NFL disrupting cognitive integrity. Furthermore, the clinical significance of plasma NFL coupling networks on AD identification and monitoring cognitive impairments were revealed in these subjects. Conclusion: The characteristic change in inflammation-related plasma NFL coupled with brain internetwork interactions could be used as a potential observation indicator in the progression of AD patients.

Effects of an Oral Contraceptive on Dynamic Brain States and Network Modularity in a Serial Single-Subject Study

Hormonal contraceptive drugs are used by adolescent and adult women worldwide. Increasing evidence from human neuroimaging research indicates that oral contraceptives can alter regional functional brain connectivity and brain chemistry. However, questions remain regarding static whole-brain and dynamic network-wise functional connectivity changes. A healthy woman (23 years old) was scanned every day over 30 consecutive days during a naturally occurring menstrual cycle and again a year later while using a combined hormonal contraceptive. Here we calculated graph theory-derived, whole-brain, network-level measures (modularity and system segregation) and global brain connectivity (characteristic path length) as well as dynamic functional brain connectivity using Leading Eigenvector Dynamic Analysis and diametrical clustering. These metrics were calculated for each scan session during the serial sampling periods to compare metrics between the subject's natural and contraceptive cycles. Modularity, system segregation, and characteristic path length were statistically significantly higher across the natural compared to contraceptive cycle scans. We also observed a shift in the prevalence of two discrete brain states when using the contraceptive. Our results suggest a more network-structured brain connectivity architecture during the natural cycle, whereas oral contraceptive use is associated with a generally increased connectivity structure evidenced by lower characteristic path length. The results of this repeated, single-subject analysis allude to the possible effects of oral contraceptives on brain-wide connectivity, which should be evaluated in a cohort to resolve the extent to which these effects generalize across the population and the possible impact of a year-long period between conditions.

Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder

BACKGROUND

Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response.

METHOD

Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity.

RESULTS

MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms.

CONCLUSIONS

The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.

Sustained attention alterations in major depressive disorder: A review of fMRI studies employing Go/No-Go and CPT tasks

BACKGROUND

Major depressive disorder (MDD) is a severe psychiatric condition characterized by selective cognitive dysfunctions. In this regard, functional Magnetic Resonance Imaging (fMRI) studies showed, both at resting state and during tasks, alterations in the brain functional networks involved in cognitive processes in MDD patients compared to controls. Among those, it seems that the attention network may have a role in the disease pathophysiology. Therefore, in this review we aim at summarizing the current fMRI evidence investigating sustained attention in MDD patients.

METHODS

We conducted a search on PubMed on case-control studies on MDD employing fMRI acquisitions during Go/No-Go and continuous performance tasks. A total of 12 studies have been included in the review.

RESULTS

Overall, the majority of fMRI studies reported quantitative alterations in the response to attentive tasks in selective brain regions, including the prefrontal cortex, the cingulate cortex, the temporal and parietal lobes, the insula and the precuneus, which are key nodes of the attention, the executive, and the default mode networks.

LIMITATIONS

The heterogeneity in the study designs, fMRI acquisition techniques and processing methods have limited the generalizability of the results.

CONCLUSIONS

The results from the included studies showed the presence of alterations in the activation patterns of regions involved in sustained attention in MDD, which are in line with current evidence and seemed to explain some of the key symptoms of depression. However, given the paucity and heterogeneity of studies available, it may be worthwhile to continue investigating the attentional domain in MDD with ad-hoc study designs to retrieve more robust evidence.

Mapping Neural Circuit Biotypes to Symptoms and Behavioral Dimensions of Depression and Anxiety

BACKGROUND

Despite tremendous advances in characterizing human neural circuits that govern emotional and cognitive functions impaired in depression and anxiety, we lack a circuit-based taxonomy for depression and anxiety that captures transdiagnostic heterogeneity and informs clinical decision making.

METHODS

We developed and tested a novel system for quantifying 6 brain circuits reproducibly and at the individual patient level. We implemented standardized circuit definitions relative to a healthy reference sample and algorithms to generate circuit clinical scores for the overall circuit and its constituent regions.

RESULTS

In new data from primary and generalizability samples of depression and anxiety (N = 250), we demonstrated that overall disconnections within task-free salience and default mode circuits map onto symptoms of anxious avoidance, loss of pleasure, threat dysregulation, and negative emotional biases-core characteristics that transcend diagnoses-and poorer daily function. Regional dysfunctions within task-evoked cognitive control and affective circuits may implicate symptoms of cognitive and valence-congruent emotional functions. Circuit dysfunction scores also distinguished response to antidepressant and behavioral intervention treatments in an independent sample (n = 205).

CONCLUSIONS

Our findings articulate circuit dimensions that relate to transdiagnostic symptoms across mood and anxiety disorders. Our novel system offers a foundation for deploying standardized circuit assessments across research groups, trials, and clinics to advance more precise classifications and treatment targets for psychiatry.

Investigating default mode network connectivity disruption in children of mothers with depression

BACKGROUND

Exposure to maternal major depressive disorder (MDD) bears long-term negative consequences for children's well-being; to date, no research has examined how exposure at different stages of development differentially affects brain functioning.

AIMS

Utilising a unique cohort followed from birth to preadolescence, we examined the effects of early versus later maternal MDD on default mode network (DMN) connectivity.

METHOD

Maternal depression was assessed at birth and ages 6 months, 9 months, 6 years and 10 years, to form three groups: children of mothers with consistent depression from birth to 6 years of age, which resolved by 10 years of age; children of mothers without depression; and children of mothers who were diagnosed with MDD in late childhood. In preadolescence, we used magnetoencephalography and focused on theta rhythms, which characterise the developing brain.

RESULTS

Maternal MDD was associated with disrupted DMN connectivity in an exposure-specific manner. Early maternal MDD decreased child connectivity, presenting a profile typical of early trauma or chronic adversity. In contrast, later maternal MDD was linked with tighter connectivity, a pattern characteristic of adult depression. Aberrant DMN connectivity was predicted by intrusive mothering in infancy and lower mother-child reciprocity and child empathy in late childhood, highlighting the role of deficient caregiving and compromised socio-emotional competencies in DMN dysfunction.

CONCLUSIONS

The findings pinpoint the distinct effects of early versus later maternal MDD on the DMN, a core network sustaining self-related processes. Results emphasise that research on the influence of early adversity on the developing brain should consider the developmental stage in which the adversity occured.

The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.

Mental health in the UK Biobank: A roadmap to self-report measures and neuroimaging correlates

The UK Biobank (UKB) is a highly promising dataset for brain biomarker research into population mental health due to its unprecedented sample size and extensive phenotypic, imaging, and biological measurements. In this study, we aimed to provide a shared foundation for UKB neuroimaging research into mental health with a focus on anxiety and depression. We compared UKB self-report measures and revealed important timing effects between scan acquisition and separate online acquisition of some mental health measures. To overcome these timing effects, we introduced and validated the Recent Depressive Symptoms (RDS-4) score which we recommend for state-dependent and longitudinal research in the UKB. We furthermore tested univariate and multivariate associations between brain imaging-derived phenotypes (IDPs) and mental health. Our results showed a significant multivariate relationship between IDPs and mental health, which was replicable. Conversely, effect sizes for individual IDPs were small. Test-retest reliability of IDPs was stronger for measures of brain structure than for measures of brain function. Taken together, these results provide benchmarks and guidelines for future UKB research into brain biomarkers of mental health.

The Brain Is Adaptive Not Triune: How the Brain Responds to Threat, Challenge, and Change

Theory impacts how research is conducted. A popular theory used to conceptualize brain functioning is the triune brain theory. The triune brain theory is an evolutionary theory of brain development that emphasizes three key brain regions consisting of the brainstem, the limbic system, and the cortex that function relatively independently in coping with stress via fight or flight, emotion, and cognition, respectively. However, modern neuroscience research demonstrates that the triune brain theory does not accurately explain how the brain functions in everyday life or during the stress response. Specifically, emotion and cognition are interdependent and work together, the limbic system is not a purely emotional center nor are there purely emotional circuits in the brain, and the cortex is not a purely cognitive center nor are there purely cognitive circuits in the brain. We propose a new evolutionarily based model, the adaptive brain, that is founded on adaptive prediction resulting from interdependent brain networks using interoception and exteroception to balance current needs, and the interconnections among homeostasis, allostasis, emotion, cognition, and strong social bonds in accomplishing adaptive goals.

Neuroimaging Correlates of Treatment Response with Psychedelics in Major Depressive Disorder: A Systematic Review

Preliminary evidence supports the use of psychedelics for major depressive disorder (MDD). However, less attention has been given to the neural mechanisms behind their effects. We conducted a systematic review examining the neuroimaging correlates of antidepressant response following psychedelic interventions for MDD. Through MEDLINE, Embase, and APA PsycINFO, 187 records were identified and 42 articles were screened. Six published studies and one conference abstract were included. Five ongoing trials were included from subjective outcomesTrials.gov. Our search covered several psychedelics, though included studies were specific to psilocybin, ayahuasca, and lysergic acid diethylamide. Three psilocybin studies noted amygdala activity and functional connectivity (FC) alterations that correlated with treatment response. Two psilocybin studies reported that FC changes in the medial and ventromedial prefrontal cortices correlated with treatment response. Two trials from a single study reported global decreases in brain network modularity which correlated with antidepressant response. One ayahuasca study reported increased activity in the limbic regions following treatment. Preliminary evidence suggests that the default mode and limbic networks may be a target for future research on the neural mechanisms of psychedelics. More data is required to corroborate these initial findings as the evidence summarized in this review is based on four datasets.

Convergence, preliminary findings and future directions across the four human connectome projects investigating mood and anxiety disorders

In this paper we provide an overview of the rationale, methods, and preliminary results of the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders. The first study, "Dimensional connectomics of anxious misery" (HCP-DAM), characterizes brain-symptom relations of a transdiagnostic sample of anxious misery disorders. The second study, "Human connectome Project for disordered emotional states" (HCP-DES), tests a hypothesis-driven model of brain circuit dysfunction in a sample of untreated young adults with symptoms of depression and anxiety. The third study, "Perturbation of the treatment resistant depression connectome by fast-acting therapies" (HCP-MDD), quantifies alterations of the structural and functional connectome as a result of three fast-acting interventions: electroconvulsive therapy, serial ketamine therapy, and total sleep deprivation. Finally, the fourth study, "Connectomes related to anxiety and depression in adolescents" (HCP-ADA), investigates developmental trajectories of subtypes of anxiety and depression in adolescence. The four projects use comparable and standardized Human Connectome Project magnetic resonance imaging (MRI) protocols, including structural MRI, diffusion-weighted MRI, and both task and resting state functional MRI. All four projects also conducted comprehensive and convergent clinical and neuropsychological assessments, including (but not limited to) demographic information, clinical diagnoses, symptoms of mood and anxiety disorders, negative and positive affect, cognitive function, and exposure to early life stress. The first round of analyses conducted in the four projects offered novel methods to investigate relations between functional connectomes and self-reports in large datasets, identified new functional correlates of symptoms of mood and anxiety disorders, characterized the trajectory of connectome-symptom profiles over time, and quantified the impact of novel treatments on aberrant connectivity. Taken together, the data obtained and reported by the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders describe a rich constellation of convergent biological, clinical, and behavioral phenotypes that span the peak ages for the onset of emotional disorders. These data are being prepared for open sharing with the scientific community following screens for quality by the Connectome Coordinating Facility (CCF). The CCF also plans to release data from all projects that have been pre-processed using identical state-of-the-art pipelines. The resultant dataset will give researchers the opportunity to pool complementary data across the four projects to study circuit dysfunctions that may underlie mood and anxiety disorders, to map cohesive relations among circuits and symptoms, and to probe how these relations change as a function of age and acute interventions. This large and combined dataset may also be ideal for using data-driven analytic approaches to inform neurobiological targets for future clinical trials and interventions focused on clinical or behavioral outcomes.