Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination

The default mode network is associated with changes in internalizing and externalizing problems differently in adolescent boys and girls

Internalizing and externalizing problems that emerge during adolescence differentially increase boys' and girls' risk for developing psychiatric disorders. It is not clear, however, whether there are sex differences in the intrinsic functional architecture of the brain that underlie changes in the severity of internalizing and externalizing problems in adolescents. Using resting-state fMRI data and self-reports of behavioral problems obtained from 128 adolescents (73 females; 9-14 years old) at two timepoints, we conducted multivoxel pattern analysis to identify resting-state functional connectivity markers at baseline that predict changes in the severity of internalizing and externalizing problems in boys and girls 2 years later. We found sex-differentiated involvement of the default mode network in changes in internalizing and externalizing problems. Whereas changes in internalizing problems were associated with the dorsal medial subsystem in boys and with the medial temporal subsystem in girls, changes in externalizing problems were predicted by hyperconnectivity between core nodes of the DMN and frontoparietal network in boys and hypoconnectivity between the DMN and affective networks in girls. Our results suggest that different neural mechanisms predict changes in internalizing and externalizing problems in adolescent boys and girls and offer insights concerning mechanisms that underlie sex differences in the expression of psychopathology in adolescence.

Resting heart rate variability is associated with neural adaptation when repeatedly exposed to emotional stimuli

Higher heart rate variability (HRV) at rest is associated with better emotion regulation ability. While the neurovisceral integration model explains this by postulating that HRV can index how the brain adaptively modulates responses to emotional stimuli, neuroimaging studies directly supporting this idea are scarce. We examined the neural correlates of regulating negative and positive emotion in relation to resting HRV based on the neuroimaging and heart rate data of one hundred young adults. The results showed that those with higher HRV better recruit the medial prefrontal cortex while intensifying positive compared to negative emotion. We also examined how individual differences in resting HRV are associated with adjusting brain activity to repeated emotional stimuli. During repeated viewing of emotional images, subjects with higher resting HRV better reduced activity in the medial prefrontal cortex, posterior cingulate gyrus, and angular gyrus, most of which overlapped with the default mode network. This HRV-DMN association was observed during passively viewing emotional images rather than during actively regulating emotion. While the regulating trials can better detect task-induced changes, the viewing trials might approximate resting state, better revealing individual differences. These findings suggest two possibilities: people with higher resting HRV might have a tendency to spontaneously engage with emotion regulation or possess a trait helping emotional arousal fade away.

Sex-specific resting state brain network dynamics in patients with major depressive disorder

Sex-specific neurobiological changes have been implicated in Major Depressive Disorder (MDD). Dysfunctions of the default mode network (DMN), salience network (SN) and frontoparietal network (FPN) are critical neural characteristics of MDD, however, the potential moderating role of sex on resting-state network dynamics in MDD has not been sufficiently evaluated. Thus, resting-state functional magnetic resonance imaging (fMRI) data were collected from 138 unmedicated patients with first-episode MDD (55 males) and 243 healthy controls (HCs; 106 males). Recurring functional network co-activation patterns (CAPs) were extracted, and time spent in each CAP (the total amount of volumes associated to a CAP), persistence (the average number of consecutive volumes linked to a CAP), and transitions across CAPs involving the SN, DMN and FPN were quantified. Relative to HCs, MDD patients exhibited greater persistence in a CAP involving activation of the DMN and deactivation of the FPN (DMN + FPN-). In addition, relative to the sex-matched HCs, the male MDD group spent more time in two CAPs involving the SN and DMN (i.e., DMN + SN- and DMN-SN + ) and transitioned more frequently from the DMN + FPN- CAP to the DMN + SN- CAP relative to the male HC group. Conversely, the female MDD group showed less persistence in the DMN + SN- CAP relative to the female HC group. Our findings highlight that the imbalance between SN and DMN could be a neurobiological marker supporting sex differences in MDD. Moreover, the dominance of the DMN accompanied by the deactivation of the FPN could be a sex-independent neurobiological correlate related to depression.

State rumination predicts inhibitory control failures and dysregulation of default, salience, and cognitive control networks in youth at risk of depressive relapse: Findings from the RuMeChange trial

Background

Trait rumination is a habitual response to negative experiences that can emerge during adolescence, increasing risk of depression. Trait rumination is correlated with poor inhibitory control (IC) and altered default mode network (DMN) and cognitive control network (CCN) engagement. Provoking state rumination in high ruminating youth permits investigation of rumination and IC at the neural level, highlighting potential treatment targets.

Methods

Fifty-three high-ruminating youth were cued with an unresolved goal that provoked state rumination, then completed a modified Sustained Attention to Response Task (SART) that measures IC (commissions on no-go trials) in a functional MRI study. Thought probes measured state rumination about that unresolved goal and task-focused thoughts during the SART.

Results

Greater state rumination during the SART was correlated with more IC failures. CCN engagement increased during rumination (relative to task-focus), including left dorsolateral prefrontal cortex and dorsalmedial prefrontal cortex. Relative to successful response suppression, DMN engagement increased during IC failures amongst individuals with higher state and trait rumination. Exploratory analyzes suggested more bothersome unresolved goals predicted higher left DLPFC activation during rumination.

Limitations

The correlational research design did not permit a direct contrast of causal accounts of the relationship between rumination and IC.

Conclusions

State rumination was associated with impaired IC and disrupted modulation of DMN and CCN. Increased CCN engagement during rumination suggested effortful suppression of negative thoughts, and this was greater for more bothersome unresolved goals. Relative task disengagement was observed during rumination-related errors. DMN-CCN dysregulation in high-ruminating youth may be an important treatment target.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Multimodal imaging measures in the prediction of clinical response to deep brain stimulation for refractory depression: A machine learning approach

OBJECTIVES

This study compared machine learning models using unimodal imaging measures and combined multi-modal imaging measures for deep brain stimulation (DBS) outcome prediction in treatment resistant depression (TRD).

METHODS

Regional brain glucose metabolism (CMRGlu), cerebral blood flow (CBF), and grey matter volume (GMV) were measured at baseline using 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography (PET), arterial spin labelling (ASL) magnetic resonance imaging (MRI), and T1-weighted MRI, respectively, in 19 patients with TRD receiving subcallosal cingulate (SCC)-DBS. Responders (n = 9) were defined by a 50% reduction in HAMD-17 at 6 months from the baseline. Using an atlas-based approach, values of each measure were determined for pre-selected brain regions. OneR feature selection algorithm and the naïve Bayes model was used for classification. Leave-out-one cross validation was used for classifier evaluation.

RESULTS

The performance accuracy of the CMRGlu classification model (84%) was greater than CBF (74%) or GMV (74%) models. The classification model using the three image modalities together led to a similar accuracy (84%0 compared to the CMRGlu classification model.

CONCLUSIONS

CMRGlu imaging measures may be useful for the development of multivariate prediction models for SCC-DBS studies for TRD. The future of multivariate methods for multimodal imaging may rest on the selection of complementing features and the developing better models.Clinical Trial Registration: ClinicalTrials.gov (#NCT01983904).

Psilocybin, an Effective Treatment for Major Depressive Disorder in Adults - A Systematic Review

Psilocybin is a classical psychedelic which has been utilised for healing purposes for millenia. However, with its classification as a Schedule I substance, research into this compound is scarce with few FDA-approved clinical studies. Despite this, profound findings into its antidepressant effects (largely through its action on 5-HT1a receptors) in mental illnesses such as major depressive disorder have rapidly increased interest back into their potential therapeutic benefits. This systematic review provides an analysis of the studies examining the clinical use of psilocybin for major depressive disorder. In total 6 studies were selected, including 319 participants, with half being randomised controlled trials and half open label trials. In every study psychological support was included as an integral part of the treatment. It was found that every study significantly favoured the use of psilocybin in reducing depressive symptoms, with few side effects. This gives psilocybin an advantage over commonly prescribed selective serotonin reuptake inhibitors (SSRIs), which carry more risk and cause more adverse effects. This drug therefore shows promise for being used as a clinical treatment for major depressive disorder, however future research should develop a paradigm for its use, with the timing of sessions and type of psychological support specified to allow for more precise analysis of the clinical effects of the drug. Additionally, more studies into its clinical efficacy are needed for appropriate detection of any publication bias. With this, psilocybin could prove to be revolutionary in treating depression and become an alternative medication to SSRIs.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSIONS

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

Rumination in bipolar disorder associated with brain network and behavioural measures of inhibitory executive control

OBJECTIVE

Rumination is a passive form of negative self-focused cognition that predicts depressive episodes for individuals with bipolar disorder (BD). Individuals with BD also have impaired inhibitory executive control; rumination in BD may therefore reflect executive dysfunction. We investigated the relationship between a neural measure of executive functioning (functional connectivity between the frontoparietal control network [FPCN] and the default mode network [DMN] during an effortful task), behavioural measures of executive functioning (the Behavior Rating Inventory of Executive Function) and rumination (the Ruminative Responses Scale).

METHODS

Fifteen individuals with BD and fifteen healthy controls underwent MRI scans during mental distraction. Using CONN toolbox, between-network FPCN-DMN connectivity values were calculated. We conducted Pearson's r bivariate correlations between connectivity values, BRIEF and RRS scores.

RESULTS

RRS scores were positively correlated with BRIEF Behavioral Regulation Index (BRI) scores. In individuals with BD, there was a positive correlation between FPCN-DMN functional connectivity during distraction and BRIEF BRI scores. FPCN-DMN functional connectivity was also positively correlated with RRS ruminative brooding scores. Healthy controls did not show significant correlations between these behavioural and neural measures of executive functioning and rumination.

CONCLUSION

For individuals with BD, the greater the tendency to ruminate and the higher the executive dysfunction, the stronger the connectivity between an executive control network and a network involved in rumination during an unrelated cognitive task. This could reflect continual attempts to inhibit ruminative thinking and shift back to the distraction task. Therefore, engagement in rumination may reflect failed inhibitory executive control.

Effects of Cortisol Administration on Resting-State Functional Connectivity in Women with Depression

Previous resting-state functional connectivity (rsFC) research has identified several brain networks impacted by depression and cortisol, including default mode (DMN), frontoparietal (FPN), and salience networks (SN). In the present study, we examined the effects of cortisol administration on rsFC of these networks in individuals varying in depression history and severity. We collected resting-state fMRI scans and self-reported depression symptom severity for 74 women with and without a history of depression after cortisol and placebo administration using a double-blind, crossover design. We conducted seed-based rsFC analyses for DMN, FPN, and SN seeds to examine rsFC changes after cortisol vs. placebo administration in relation to depression history group and severity. Results revealed a main effect of depression group, with lower left amygdala (SN)-middle temporal gyrus connectivity in women with a history of depression. Cortisol administration increased insula (SN)-inferior frontal gyrus and superior temporal gyrus connectivity. We also found that greater depression severity was associated with increased PCC (DMN)-cerebellum connectivity after cortisol. These results did not survive Bonferroni correction for seed ROIs and should be interpreted with caution. Our findings indicate that acute cortisol elevation may normalize aberrant connectivity of DMN and SN regions, which could help inform clinical treatments for depression.

Default Mode Network Hypoalignment of Function to Structure Correlates With Depression and Rumination

BACKGROUND

Recent studies have begun to examine how signals in the brain correspond to the underlying white matter structure using tools from the field of graph signal processing to quantify brain function alignment to brain network topology. Here, we applied this framework for the first time toward a transdiagnostic cohort of individuals with internalizing psychopathologies, including mood and anxiety disorders, to uncover how such alignment within the default mode network (DMN) is related to depression and rumination symptoms.

METHODS

Both diffusion-weighted and resting-state functional magnetic resonance imaging were obtained from participants at baseline (n = 60 patients, n = 19 healthy control participants). Patients were randomized to 12 weeks of treatment with either a selective serotonin reuptake inhibitor or cognitive behavioral therapy, and symptom scales were readministered posttreatment (n = 46 patients at follow-up). Using graph signal processing methodology, we quantified the alignment of functional signals to their underlying white matter structural networks.

RESULTS

We found that signal alignment within the posterior DMN was decreased in patients with internalizing psychopathologies compared with healthy control participants and was inversely (negatively) correlated with baseline depression and rumination scales. Signal alignment within the posterior DMN was also correlated with the ratio of total within-DMN to extra-DMN functional connectivity for these regions.

CONCLUSIONS

These findings are consistent with previous literature regarding pathological promiscuity of posterior DMN connectivity and provide the first graph signal processing-based analyses in a transdiagnostic cohort of patients with internalizing psychopathologies.

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.

Internalizing Symptoms and Adverse Childhood Experiences Associated With Functional Connectivity in a Middle Childhood Sample

BACKGROUND

Research has found overlapping associations in adults of resting-state functional connectivity (RSFC) to both internalizing disorders (e.g., depression, anxiety) and a history of traumatic events. The present study aimed to extend this previous research to a younger sample by examining RSFC associations with both internalizing symptoms and adverse childhood experiences (ACEs) in middle childhood.

METHODS

We used generalized linear mixed models to examine associations between a priori within- and between-network RSFC with child-reported internalizing symptoms and ACEs using the Adolescent Brain Cognitive Development dataset (N = 10,168, mean age = 9.95 years, SD = 0.627).

RESULTS

We found that internalizing symptoms and ACEs were associated with both multiple overlapping and unique RSFC network patterns. Both ACEs and internalizing symptoms were associated with a reduced anticorrelation between the default mode network and the dorsal attention network. However, internalizing symptoms were uniquely associated with lower within-network default mode network connectivity, while ACEs were uniquely associated with both lower between-network connectivity of the auditory network and cingulo-opercular network, and higher within-network frontoparietal network connectivity.

CONCLUSIONS

The present study points to overlap in the RSFC associations with internalizing symptoms and ACEs, as well as important areas of specificity in RSFC associations. Many of the RSFC associations found have been previously implicated in attentional control functions, including modulation of attention to sensory stimuli. This may have critical importance in understanding internalizing symptoms and outcomes of ACEs.

Reviewing the neurobiology of electroconvulsive therapy on a micro- meso- and macro-level

BACKGROUND

Electroconvulsive therapy (ECT) remains the one of the most effective of biological antidepressant interventions. However, the exact neurobiological mechanisms underlying the efficacy of ECT remain unclear. A gap in the literature is the lack of multimodal research that attempts to integrate findings at different biological levels of analysis METHODS: We searched the PubMed database for relevant studies. We review biological studies of ECT in depression on a micro- (molecular), meso- (structural) and macro- (network) level.

RESULTS

ECT impacts both peripheral and central inflammatory processes, triggers neuroplastic mechanisms and modulates large scale neural network connectivity.

CONCLUSIONS

Integrating this vast body of existing evidence, we are tempted to speculate that ECT may have neuroplastic effects resulting in the modulation of connectivity between and among specific large-scale networks that are altered in depression. These effects could be mediated by the immunomodulatory properties of the treatment. A better understanding of the complex interactions between the micro-, meso- and macro- level might further specify the mechanisms of action of ECT.

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

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

Dynamic phase-locking states and personality in sub-acute mild traumatic brain injury: An exploratory study

Research has shown that maladaptive personality characteristics, such as Neuroticism, are associated with poor outcome after mild traumatic brain injury (mTBI). The current exploratory study investigated the neural underpinnings of this process using dynamic functional network connectivity (dFNC) analyses of resting-state (rs) fMRI, and diffusion MRI (dMRI). Twenty-seven mTBI patients and 21 healthy controls (HC) were included. After measuring the Big Five personality dimensions, principal component analysis (PCA) was used to obtain a superordinate factor representing emotional instability, consisting of high Neuroticism, moderate Openness, and low Extraversion, Agreeableness, and Conscientiousness. Persistent symptoms were measured using the head injury symptom checklist at six months post-injury; symptom severity (i.e., sum of all items) was used for further analyses. For patients, brain MRI was performed in the sub-acute phase (~1 month) post-injury. Following parcellation of rs-fMRI using independent component analysis, leading eigenvector dynamic analysis (LEiDA) was performed to compute dynamic phase-locking brain states. Main patterns of brain diffusion were computed using tract-based spatial statistics followed by PCA. No differences in phase-locking state measures were found between patients and HC. Regarding dMRI, a trend significant decrease in fractional anisotropy was found in patients relative to HC, particularly in the fornix, genu of the corpus callosum, anterior and posterior corona radiata. Visiting one specific phase-locking state was associated with lower symptom severity after mTBI. This state was characterized by two clearly delineated communities (each community consisting of areas with synchronized phases): one representing an executive/saliency system, with a strong contribution of the insulae and basal ganglia; the other representing the canonical default mode network. In patients who scored high on emotional instability, this relationship was even more pronounced. Dynamic phase-locking states were not related to findings on dMRI. Altogether, our results provide preliminary evidence for the coupling between personality and dFNC in the development of long-term symptoms after mTBI.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD.

METHOD

Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN).

RESULTS

Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance.

CONCLUSION

Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

Resting-state functional magnetic resonance imaging alterations in borderline personality disorder: A systematic review

BACKGROUND

Borderline personality disorder (BPD) is a severe psychiatric disorder characterized by emotion dysregulation, impulsivity, and interpersonal disturbances. Several structural and functional neuroimaging abnormalities have been described in BPD. In particular, resting-state functional magnetic resonance imaging (rs-fMRI) studies have recently suggested various connectivity alterations within and between large-scale brain networks in BPD. This review aimed at providing an updated summary of the evidence reported by the available rs-fMRI studies in BPD individuals.

METHODS

A search on PubMed, Scopus, and Web of Science was performed to identify rs-fMRI alterations in BPD. A total of 15 studies met our inclusion criteria.

RESULTS

Overall, aberrant resting-state functional connectivity (rs-FC) within and between default mode network (DMN), salience network (SN), and central executive network (CEN) were observed in BPD compared to healthy controls, as well as selective functional impairments in bilateral amygdala, anterior and posterior cingulate cortex, hippocampus, and prefrontal cortex.

LIMITATIONS

The observational design, small sample size, prevalence of females, high rates of concurrent comorbidities and medications, and heterogeneity across imaging methodologies limit the generalizability of the results.

CONCLUSIONS

The identification of altered patterns of rs-FC within and between selective brain networks, including DMN, SN, and CEN, could further our knowledge of the clinical symptoms of BPD, and therefore, future studies with multimodal methodologies and longitudinal designs are warranted to further explore the neural correlates of this disorder.

The double-edged sword of the hippocampus-ventromedial prefrontal cortex resting-state connectivity in stress susceptibility and resilience: A prospective study

The hippocampus has long been considered a pivotal region implicated in both stress susceptibility and resilience. A wealth of evidence from animal and human studies underscores the significance of hippocampal functional connectivity with the ventromedial prefrontal cortex (vmPFC) in these stress-related processes. However, there remains a scarcity of research that explores and contrasts the roles of hippocampus-vmPFC connectivity in stress susceptibility and resilience when facing a real-life traumatic event from a prospective standpoint. In the present study, we investigated the contributions of undirected and directed connectivity between the hippocampus and vmPFC to stress susceptibility and resilience within the context of the COVID-19 pandemic. Our findings revealed that the left hippocampus-left vmPFC connectivity prior to the pandemic exhibited a negative correlation with both stress susceptibility and resilience. Specifically, individuals with stronger left hippocampus-left vmPFC connectivity reported experiencing fewer stress-related feelings during the outbreak period of the epidemic but displayed lower levels of stress resilience five months later. Our application of spectral dynamic causal modeling unveiled an additional inhibitory connectivity pathway from the left hippocampus to the left vmPFC in the context of stress susceptibility, which was notably absent in stress resilience. Furthermore, we observed a noteworthy positive association between self-inhibition of the vmPFC and stress susceptibility, with this effect proving substantial enough to predict an individual's susceptibility to stress; conversely, these patterns did not manifest in the realm of stress resilience. These findings enrich our comprehension of stress susceptibility and stress resilience and might have implications for innovative approaches to managing stress-related disorders.

Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation

BACKGROUND

Noninvasive neurostimulation treatments are increasingly being used to treat major depression, which is a common cause of disability worldwide. While electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) are both effective in treating depressive episodes, their mechanisms of action are, however, not completely understood. ECT is given under general anesthesia, where an electrical pulse is administered through electrodes placed on the patient's head to trigger a seizure. ECT is used for the most severe cases of depression and is usually not prescribed before other options have failed. With TMS, brain stimulation is achieved through rapidly changing magnetic fields that induce electric currents underneath a ferromagnetic coil. Its efficacy in depressive episodes has been well documented. This project aims to identify the neurobiological underpinnings of both the effects and side effects of the neurostimulation techniques ECT and TMS.

METHODS

The study will utilize a pre-post case control longitudinal design. The sample will consist of 150 subjects: 100 patients (bipolar and major depressive disorder) who are treated with either ECT (N = 50) or TMS (N = 50) and matched healthy controls (N = 50) not receiving any treatment. All participants will undergo multimodal magnetic resonance imaging (MRI) as well as neuropsychological and clinical assessments at multiple time points before, during and after treatment. Arterial spin labeling MRI at baseline will be used to test whether brain perfusion can predict outcomes. Signs of brain disruption, potentiation and rewiring will be explored with resting-state functional MRI, magnetic resonance spectroscopy and multishell diffusion weighted imaging (DWI). Clinical outcome will be measured by clinician assessed and patient reported outcome measures. Memory-related side effects will be investigated, and specific tests of spatial navigation to test hippocampal function will be administered both before and after treatment. Blood samples will be stored in a biobank for future analyses. The observation time is 6 months. Data will be explored in light of the recently proposed disrupt, potentiate and rewire (DPR) hypothesis.

DISCUSSION

The study will contribute data and novel analyses important for our understanding of neurostimulation as well as for the development of enhanced and more personalized treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05135897.

In situ fNIRS measurements during cognitive behavioral emotion regulation training in rumination-focused therapy: A randomized-controlled trial

Repetitive negative thinking (RNT), including rumination, plays a key role in various psychopathologies. Although several psychotherapeutic treatments have been developed to reduce RNT, the neural correlates of those specific treatments and of psychotherapy in general are largely unknown. Functional near-infrared spectroscopy (fNIRS) offers the potential to investigate the neural correlates of psychotherapeutic techniques in situ. Therefore, in this study we investigated the efficacy and neural correlates of a fNIRS adapted Mindfulness-based Emotion Regulation Training (MBERT) for the treatment of depressive rumination in 42 subjects with major depressive disorder (MDD) in a cross-over designed randomized controlled trial. Using psychometric measures, subjective ratings and fNIRS, we analyzed in situ changes in depressive symptom severity, ruminative thoughts and cortical activity in the Cognitive Control Network (CCN). Our results show that MBERT is effective in treating depressive symptoms and rumination. On a neural level, we found consistently higher cortical activation during emotion regulation training compared to control trials in the bilateral inferior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC). Furthermore, cortical oxygenation decreased from session to session in the bilateral DLPFC. The relevance of the results for the psychotherapeutic treatment of MDD as well as further necessary investigations are discussed.

Alterations of interhemispheric functional homotopic connectivity and corpus callosum microstructure in bulimia nervosa

Background

Accumulating evidence indicates maladaptive neural information interactions between different brain regions underlie bulimia nervosa (BN). However, little is known about the alterations in interhemispheric communication of BN, which is facilitated by the corpus callosum (CC), the major commissural fiber connecting the two hemispheres. To shed light on the interhemispheric communications in BN, the present study aims to explore alterations of interhemispheric homotopic functional connectivity and the CC microstructure in BN.

Methods

Based on magnetic resonance imaging (MRI) data collected from 42 BN patients and 38 healthy controls (HCs), the group differences of voxel-mirrored homotopic connectivity (VMHC) index and CC white matter microstructure were compared. Then brain regions with significant group differences in VMHC were selected as seeds for subsequent functional connectivity (FC) analysis. Seed-based fiber tracking and correlation analysis were used to analyze the relationship between VMHC and CC changes. And correlation analysis was used to reveal the correlation between abnormal imaging variables and the clinical features of BN.

Results

Compared with HCs, the BN group showed decreased fractional anisotropy (FA) in middle part of CC (CCMid) and increased VMHC in bilateral orbitofrontal cortex (OFC) and middle temporal gyrus (MTG) [false discovery rate (FDR) correction with a corrected threshold of P<0.05]. Subsequent FC analyses indicated increased FC between left OFC and right OFC, bilateral MTG, left middle occipital gyrus and right precuneus (PCUN); between right OFC and left cerebellum crus II and right PCUN; and between left MTG and right inferior temporal gyrus, right cerebellum lobule VI and right medial superior frontal gyrus (FDR correction with a corrected threshold of P<0.05). The VMHC values of OFC and MTG showed no correlations with FA values of the CCMid and the white fibers between the bilateral OFC and MTG were not through the CCMid. In addition, several regions with abnormal FC had a potential correlation trend with abnormal eating behaviors in BN patients (P<0.05, uncorrected).

Conclusions

Aberrant interhemispheric homotopic functional connectivity and CC microstructure were observed in BN, and they may be independent of each other. Regions with aberrant interhemispheric homotopic functional connectivity showed hyperconnectivity with regions related to reward processing, body shape perception, and self-reference.

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.

Transdiagnostic phenomena of psychopathology in the context of the RDoC: protocol of a multimodal cross-sectional study

In the past, affective and cognitive processes related to psychopathology have been examined within the boundaries of phenotype-based diagnostic labels, which has led to inconsistent findings regarding their underlying operating principles. Investigating these processes dimensionally in healthy individuals and by means of multiple modalities may provide additional insights into the psychological and neuronal mechanisms at their core. The transdiagnostic phenomena Neuroticism and Rumination are known to be closely linked. However, the exact nature of their relationship remains to be elucidated. The same applies to the associations between Hedonic Capacity, Negativity Bias and different Emotion Regulation strategies.This multimodal cross-sectional study examines the relationship of the transdiagnostic phenomena Neuroticism and Rumination as well as Hedonic Capacity, the Negativity Bias and Emotion Regulation from a RDoC (Research Domain Criteria) perspective. A total of 120 currently healthy subjects (past 12 months) will complete several questionnaires regarding personality, emotion regulation, hedonic capacity, and psychopathologies as well as functional magnetic resonance imaging (fMRI) during cognitive and emotional processing, to obtain data on the circuit, behavioral and self-report level.This study aims to contribute to the understanding of the relationship between cognitive and affective processes associated with psychopathologies as well as their neuronal correlates. Ultimately, a grounded understanding of these processes could guide improvement of diagnostic labels and treatments. Limitations include the cross-sectional design and the limited variability in psychopathology scores due to the restriction of the sample to currently healthy subjects.

The Effects of Dose, Practice Habits, and Objects of Focus on Digital Meditation Effectiveness and Adherence: Longitudinal Study of 280,000 Digital Meditation Sessions Across 103 Countries

BACKGROUND

The efficacy of digital meditation is well established. However, the extent to which the benefits remain after 12 weeks in real-world settings remains unknown. Additionally, findings related to dosage and practice habits have been mixed, and the studies were conducted on small and homogeneous samples and used a limited range of analytical procedures and meditation techniques. Findings related to the predictors of adherence are also lacking and may help inform future meditators and meditation programs on how to best structure healthy sustainable practices.

OBJECTIVE

This study aimed to measure outcome change across a large and globally diverse population of meditators and meditations in their naturalistic practice environments, assess the dose-response relationships between practice habits and outcome change, and identify predictors of adherence.

METHODS

We used ecological momentary assessment to assess participants' well-being over a 14-month period. We engineered outcomes related to the variability of change over time (equanimity) and recovery following a drop in mood (resilience) and established the convergent and divergent validity of these outcomes using a validated scale. Using linear mixed-effects and generalized additive mixed-effects models, we modeled outcome changes and patterns of dose-response across outcomes. We then used logistic regression to study the practice habits of participants in their first 30 sessions to derive odds ratios of long-term adherence.

RESULTS

Significant improvements were observed in all outcomes (P<.001). Generalized additive mixed models revealed rapid improvements over the first 50-100 sessions, with further improvements observed until the end of the study period. Outcome change corresponded to 1 extra day of improved mood for every 5 days meditated and half-a-day-faster mood recovery compared with baseline. Overall, consistency of practice was associated with the largest outcome change (4-7 d/wk). No significant differences were observed across session lengths in linear models (mood: P=.19; equanimity: P=.10; resilience: P=.29); however, generalized additive models revealed significant differences over time (P<.001). Longer sessions (21-30 min) were associated with the largest magnitude of change in mood from the 20th session onward and fewer sessions to recovery (increased resilience); midlength sessions (11-20 min) were associated with the largest decreases in recovery; and mood stability was similar across session lengths (equanimity). Completing a greater variety of practice types was associated with significantly greater improvements across all outcomes. Adhering to a long-term practice was best predicted by practice consistency (4-7 d/wk), a morning routine, and maintaining an equal balance between interoceptive and exteroceptive meditations.

CONCLUSIONS

Long-term real-world digital meditation practice is effective and associated with improvements in mood, equanimity, and resilience. Practice consistency and variety rather than length best predict improvement. Long-term sustainable practices are best predicted by consistency, a morning routine, and a practice balanced across objects of focus that are internal and external to the body.

Rumination symptoms in treatment-resistant major depressive disorder, and outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) treatment

Rumination is a maladaptive style of regulating thoughts and emotions. It is a common symptom of Major Depressive Disorder (MDD), and more severe rumination is associated with poorer medication and psychotherapy treatment outcomes, particularly among women. It is unclear to what extent rumination may influence the outcomes of, or be responsive to, repetitive Transcranial Magnetic Stimulation (rTMS) treatment of MDD. We retrospectively examined data collected during rTMS treatment of 155 patients (age 42.52 ± 14.22, 79 female) with moderately severe treatment-resistant MDD. The severity of rumination and depression was assessed before and during a course of 30 sessions of measurement-based rTMS treatment using the Ruminative Responses Scale (RSS) and the Patient Health Questionnaire (PHQ-9), respectively. Relationships among baseline levels of rumination, depression, and treatment outcome were assessed using a series of repeated measures linear mixed effects models. Both depression and rumination symptoms significantly improved after treatment, but improvement in depression was not a significant mediator of rumination improvement. Higher baseline rumination (but not depression severity) was associated with poorer depression outcomes independently of depression severity. Female gender was a significant predictor of worse outcomes for all RRS subscales. Both depressive and ruminative symptoms in MDD improved following rTMS treatment. These improvements were correlated, but improvement in rumination was not fully explained by reduction in depressive symptoms. These findings suggest that while improvement in rumination and depression severity during rTMS treatment are correlated, they are partly independent processes. Future studies should examine whether rumination symptoms should be specifically targeted with different rTMS treatment parameters.

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.

Understanding and predicting future relapse in depression from resting state functional connectivity and self-referential processing

BACKGROUND

The recurrent nature of Major Depressive Disorder (MDD) asks for a better understanding of mechanisms underlying relapse. Previously, self-referential processing abnormalities have been linked to vulnerability for relapse. We investigated whether abnormalities in self-referential cognitions and functioning of associated brain-networks persist upon remission and predict relapse.

METHODS

Remitted recurrent MDD patients (n = 48) and never-depressed controls (n = 23) underwent resting-state fMRI scanning at baseline and were additionally assessed for their implicit depressed self-associations and ruminative behaviour. A template-based dual regression approach was used to investigate between-group differences in default mode, cingulo-opercular and frontoparietal network resting-state functional connectivity (RSFC). Additional prediction of relapse status at 18-month follow-up was investigated within patients using both regression analyses and machine learning classifiers.

RESULTS

Remitted patients showed higher rumination, but no implicit depressed self-associations or RSFC abnormalities were observed between patients and controls. Nevertheless, relapse was related to i) baseline RSFC between the ventral default mode network and the precuneus, dorsomedial frontal gyrus, and inferior occipital lobe, ii) implicit self-associations, and iii) uncontrollability of ruminative thinking, when controlled for depressive symptomatology. Moreover, preliminary machine learning classifiers demonstrated that RSFC within the investigated networks predicted relapse on an individual basis.

CONCLUSIONS

Remitted MDD patients seem to be commonly characterized by abnormal rumination, but not by implicit self-associations or abnormalities in relevant brain networks. Nevertheless, relapse was predicted by self-related cognitions and default mode RSFC during remission, suggesting that variations in self-relevant processing play a role in the complex dynamics associated with the vulnerability to developing recurrent depressive episodes.

CLINICAL TRIAL REGISTRATION

Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15.

Rumination as a Transdiagnostic Phenomenon in the 21st Century: The Flow Model of Rumination

Rumination and its related mental phenomena share associated impairments in cognition, such as executive functions and attentional processes across different clinical conditions (e.g., in psychotic disorders). In recent decades, however, the notion of rumination has been increasingly narrowed to the "self-focused" type in depressive disorders. A closer review of the literature shows that rumination may be construed as a broader process characterized by repetitive thoughts about certain mental contents that interfere with one's daily activities, not only limited to those related to "self". A further examination of the construct of rumination beyond the narrowly focused depressive rumination would help expand intervention opportunities for mental disorders in today's context. We first review the development of the clinical construct of rumination with regard to its historical roots and its roles in psychopathology. This builds the foundation for the introduction of the "Flow Model of Rumination (FMR)", which conceptualizes rumination as a disruption of a smooth flow of mental contents in conscious experience that depends on the coordinated interactions between intention, memory, affect, and external events. The conceptual review concludes with a discussion of the impact of rapid technological advances (such as smartphones) on rumination. Particularly in contemporary societies today, a broader consideration of rumination not only from a cognition viewpoint, but also incorporating a human-device interaction perspective, is necessitated. The implications of the FMR in contemporary mental health practice are discussed.

Emotional Dysregulation is the Core Problem in Psychopathological Manifestations

The established opinion is that emotions are the gift given to us by nature in order to help us connect with other people. They are constantly generated, usually by stimuli in our intrapersonal as well as in external world. Problems raised in our relationships initiate emotions to help us to fix those problems. Almost all forms of human psychopathology are associated with dysregulated emotions. The failure to apply appropriate cognitive, attentive, and behavioural regulatory strategies is the core for emotion dysregulation. The brain regulates emotions through a biological mechanism. Emotions rise in intensity, peak, and then go flat once the emotion adaptive action tendency has been expressed. The aim of the therapist is to help clients express, face, and regulate their emotions, and to channel these emotions into healthy actions. The idea of this article is to present contributions from both affective neuroscience and psychotherapy in order to explain the ways how our emotions become dysregulated in life and how they can become regulated through psychotherapy.

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

The default mode network (DMN) is a network of brain regions active during rest and self-referential thinking. Individuals with major depressive disorder (MDD) show increased or decreased DMN activity relative to controls. DMN activity has been linked to a tendency to ruminate in MDD. It is unclear if individuals who are at risk for, but who have no current or past history of depression, also show differential DMN activity associated with rumination. We investigated whether females with high levels of neuroticism with no current or lifetime mood or anxiety disorders (n = 25) show increased DMN activation, specifically when processing negative self-referential information, compared with females with average levels of neuroticism (n = 28). Participants heard criticism and praise during functional magnetic resonance imaging (MRI) scans in a 3T Siemens Prisma scanner. The at-risk group showed greater activation in two DMN regions, the medial prefrontal cortex and the inferior parietal lobule (IPL), after hearing criticism, but not praise (relative to females with average levels of neuroticism). Criticism-specific activation in the IPL was significantly correlated with rumination. Individuals at risk for depression may, therefore, have an underlying neurocognitive vulnerability to use a brain network typically involved in thinking about oneself to preferentially ruminate about negative, rather than positive, information.

Disrupted Dynamic Interactions Between Large-Scale Brain Networks in Cocaine Users Are Associated With Dependence Severity

BACKGROUND

Substance use disorder is conceptualized as a neuropsychiatric disease with multifaceted phenotypic manifestations including disrupted interactions between brain networks. While the current understanding of brain network interactions is mostly based on static functional connectivity, accumulating evidence suggests that temporal dynamics of these network interactions may better reflect brain function and disease-related dysfunction. We thus investigated brain dynamics in cocaine use disorder and assessed their relationship with cocaine dependence severity.

METHODS

Using a time frame analytical approach on resting-state functional magnetic resonance imaging data of 54 cocaine users and 54 age- and sex-matched healthy control participants, we identified temporally recurring brain network configuration patterns, termed brain states. With Menon's triple network model as a guide, we characterized these state dynamics by quantifying their occurrence rate and transition probability. Group differences in the state dynamics and their association with cocaine dependence were assessed.

RESULTS

Three recurrent brain states with spatial patterns resembling the default mode, salience, and executive control networks were identified. Compared with healthy control subjects, cocaine users showed a higher default mode state occurrence rate and higher probability of transitioning from the salience state to the default mode state, with the former being attributed to the latter. A composite state transition probability negatively correlated with cocaine dependence severity.

CONCLUSIONS

Our results provide novel evidence supporting the triple network model. While confirming hyperactivity of default mode network in cocaine users, our findings indicate the failure of salience network in toggling between default mode and executive control networks in cocaine use disorder.

Unbalanced amygdala communication in major depressive disorder

BACKGROUND

Previous studies suggested an association between functional alteration of the amygdala and typical major depressive disorder (MDD) symptoms. Examining whether and how the interaction between the amygdala and regions/functional networks is altered in patients with MDD is important for understanding its neural basis.

METHODS

Resting-state functional magnetic resonance imaging data were recorded from 67 patients with MDD and 74 age- and sex-matched healthy controls (HCs). A framework for large-scale network analysis based on seed mappings of amygdala sub-regions, using a multi-connectivity-indicator strategy (cross-correlation, total interdependencies (TI), Granger causality (GC), and machine learning), was employed. Multiple indicators were compared between the two groups. The altered indicators were ranked in a supporting-vector machine-based procedure and associated with the Hamilton Rating Scale for Depression scores.

RESULTS

The amygdala connectivity with the default mode network and ventral attention network regions was enhanced and that with the somatomotor network, dorsal frontoparietal network, and putamen regions in patients with MDD was reduced. The machine learning analysis highlighted altered indicators that were most conducive to the classification between the two groups.

LIMITATIONS

Most patients with MDD received different pharmacological treatments. It is difficult to illustrate the medication state's effect on the alteration model because of its complex situation.

CONCLUSION

The results indicate an unbalanced interaction model between the amygdala and functional networks and regions essential for various emotional and cognitive functions. The model can help explain potential aberrancy in the neural mechanisms that underlie the functional impairments observed across various domains in patients with MDD.

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.

Alterations in EEG functional connectivity in individuals with depression: A systematic review

The brain works as an organised, network-like structure of functionally interconnected regions. Disruptions to interconnectivity in certain networks have been linked to symptoms of depression and impairments in cognition. Electroencephalography (EEG) is a low-burden tool by which differences in functional connectivity (FC) can be assessed. This systematic review aims to provide a synthesis of evidence relating to EEG FC in depression. A comprehensive electronic literature search for terms relating to depression, EEG, and FC was conducted on studies published before the end of November 2021, according to PRISMA guidelines. Studies comparing EEG measures of FC of individuals with depression to that of healthy control groups were included. Data was extracted by two independent reviewers, and the quality of EEG FC methods was assessed. Fifty-two studies assessing EEG FC in depression were identified: 36 assessed resting-state FC, and 16 assessed task-related or other (i.e., sleep) FC. Somewhat consistent findings in resting-state studies suggest for no differences between depression and control groups in EEG FC in the delta and gamma frequencies. However, while most resting-state studies noted a difference in alpha, theta, and beta, no clear conclusions could be drawn about the direction of the difference, due to considerable inconsistencies between study design and methodology. This was also true for task-related and other EEG FC. More robust research is needed to understand the true differences in EEG FC in depression. Given that the FC between brain regions drives behaviour, cognition, and emotion, characterising how FC differs in depression is essential for understanding the aetiology of depression.

Resting state connectivity predictors of symptom change during gaze-contingent music reward therapy of social anxiety disorder

BACKGROUND

Social anxiety disorder (SAD) is common, first-line treatments are often only partially effective, and reliable predictors of treatment response are lacking. Here, we assessed resting state functional connectivity (rsFC) at pre-treatment and during early treatment as a potential predictor of response to a novel attention bias modification procedure, gaze-contingent music reward therapy (GC-MRT).

METHODS

Thirty-two adults with SAD were treated with GC-MRT. rsFC was assessed with multi-voxel pattern analysis of fMRI at pre-treatment and after 2-3 weeks. For comparison, 20 healthy control (HC) participants without treatment were assessed twice for rsFC over the same time period. All SAD participants underwent clinical evaluation at pre-treatment, early-treatment (week 2-3), and post-treatment.

RESULTS

SAD and depressive symptoms improved significantly from pre-treatment to post-treatment. After 2-3 weeks of treatment, decreased connectivity between the executive control network (ECN) and salience network (SN), and increased connectivity within the ECN predicted improvement in SAD and depressive symptoms at week 8. Increased connectivity between the ECN and default mode network (DMN) predicted greater improvement in SAD but not depressive symptoms at week 8. Connectivity within the DMN decreased significantly after 2-3 weeks of treatment in the SAD group, while no changes were found in HC over the same time interval.

CONCLUSION

We identified early changes in rsFC during a course of GC-MRT for SAD that predicted symptom change. Connectivity changes within the ECN, ECN-DMN, and ECN-SN may be related to mechanisms underlying the clinical effects of GC-MRT and warrant further study in controlled trials.

Electroconvulsive therapy induces remodeling of hippocampal co-activation with the default mode network in patients with depression

INTRODUCTION

Electroconvulsive therapy (ECT) is a highly efficient treatment for depression. Previous studies repeatedly reported an ECT-induced volume increase in the hippocampi. We assume that this also affects extended hippocampal networks. This study aims to investigate the structural and functional interplay between hippocampi, hippocampal pathways and core regions of the default mode network (DMN). Twenty patients with a current depressive episode receiving ECT-treatment and twenty age and sex matched healthy controls (HC) were included in the study. ECT-patients underwent multimodal magnetic resonance imaging (MRI)-scans (diffusion weighted imaging, resting state functional MRI) before and after an ECT-index series. HC were also scanned twice in a similar between-scan time-interval. Parahippocampal cingulum (PHC) and uncinate fasciculus (UF) were reconstructed for each participant using manual tractography. Fractional anisotropy (FA) was averaged across tracts. Furthermore, we investigated seed-based functional connectivity (FC) from bilateral hippocampi and from the PCC, a core region of the DMN. At baseline, FA in PHC and UF did not differ between groups. There was no baseline group difference of hippocampal-FC. PCC-FC was decreased in ECT-patients. ECT induced a decrease in FA in the left PHC in the ECT group. No longitudinal changes of FA were found in the UF. Furthermore, there was a decrease in hippocampal-PCC-FC, an increase in hippocampal-supplementary motor area-FC, and an increase in PCC-FC in the ECT-group, reversing group differences at baseline. Our findings suggest that ECT induces structural and functional remodeling of a hippocampal-DMN. Those changes may contribute to ECT-induced clinical response in patients with depression.

Facial emotion recognition in patients with depression compared to healthy controls when using human avatars

The negative, mood-congruent cognitive bias described in depression, as well as excessive rumination, have been found to interfere with emotional processing. This study focuses on the assessment of facial recognition of emotions in patients with depression through a new set of dynamic virtual faces (DVFs). The sample consisted of 54 stable patients compared to 54 healthy controls. The experiment consisted in an emotion recognition task using non-immersive virtual reality (VR) with DVFs of six basic emotions and neutral expression. Patients with depression showed a worst performance in facial affect recognition compared to healthy controls. Age of onset was negatively correlated with emotion recognition and no correlation was observed for duration of illness or number of lifetime hospitalizations. There was no correlation for the depression group between emotion recognition and degree of psychopathology, excessive rumination, degree of functioning, or quality of life. Hence, it is important to improve and validate VR tools for emotion recognition to achieve greater methodological homogeneity of studies and to be able to establish more conclusive results.

Functional connectivity analysis of childhood depressive symptoms

BACKGROUND

Childhood depression is a highly distinct and prevalent condition with an unknown neurobiological basis. We wish to explore the resting state fMRI data in children for potential associations between neural connectivity and childhood depressive symptoms.

METHODS

A longitudinal birth cohort study with neuroimaging data obtained at 4.5, 6.0 and 7.5 years of age and the Children Depression Inventory 2 (CDI) administered between 8.5 and 10.5 years was used. The CDI score was used as the dependent variable and tested for correlation, both simple Pearson and network based statistic, with the functional connectivity values obtained from the resting state fMRI. Cross-validated permutation testing with a general linear model was used to validate that the identified functional connections were indeed implicated in childhood depression.

RESULTS

Ten functional connections and four brain regions (Somatomotor Area B, Temporoparietal Junction, Orbitofrontal Cortex and Insula) were identified as significantly associated with childhood depressive symptoms for girls at 6.0 and 7.5 years. No significant functional connections were found in girls at 4.5 years or for boys at any timepoint. Network based statistic and permutation testing confirmed these findings.

CONCLUSIONS

This study revealed significant sex-dependent associations of neural connectivity and childhood depressive symptoms. The regions identified are implicated in speech/language, social cognition and information integration and suggest unique pathways to childhood depressive symptoms.

A distinct intra-individual suppression subnetwork in the brain's default mode network across cognitive tasks

Suppression of the brain's default mode network (DMN) during external goal-directed cognitive tasks has been consistently observed in neuroimaging studies. However, emerging insights suggest the DMN is not a monolithic "task-negative" network but is comprised of subsystems that show functional heterogeneity. Despite considerable research interest, no study has investigated the consistency of DMN activity suppression across multiple cognitive tasks within the same individuals. In this study, 85 healthy 15- to 25-year-olds completed three functional magnetic resonance imaging tasks that were designed to reliably map DMN suppression from a resting baseline. Our findings revealed a distinct suppression subnetwork across the three tasks that comprised traditional DMN and adjacent regions. Specifically, common suppression was observed in the medial prefrontal cortex, the dorsal-to-mid posterior cingulate cortex extending to the precuneus, and the posterior insular cortex and parietal operculum. Further, we found the magnitude of suppression of these regions were significantly correlated within participants across tasks. Overall, our findings indicate that externally oriented cognitive tasks elicit common suppression of a distinct subnetwork of the broader DMN. The consistency to which the DMN is suppressed within individuals suggests a domain-general mechanism that may reflect a stable feature of cognitive function that optimizes external goal-directed behavior.

Associations between insomnia symptoms and functional connectivity in the UK Biobank cohort (n = 29,423)

An increasing number of studies harness resting-state fMRI functional connectivity analysis to investigate the neurobiological mechanisms of insomnia. The results to date are inconsistent and the detection of minor and widely distributed alterations in functional connectivity requires large sample sizes. The present study investigated associations between insomnia symptoms and resting-state functional connectivity at the whole-brain level in the largest sample to date. This cross-sectional analysis used resting-state imaging data from the UK Biobank, a large scale, population-based biomedical database. The analysis included 29,423 participants (age: 63.1 ± 7.5 years, 54.3% female), comprising 9210 with frequent insomnia symptoms and 20,213 controls without. Linear models were adjusted for relevant clinical, imaging, and socio-demographic variables. The Akaike information criterion was used for model selection. Multiple comparisons were corrected using the false discovery rate with a significance level of q < 0.05. Frequent insomnia symptoms were associated with increased connectivity within the default mode network and frontoparietal network, increased negative connectivity between the default mode network and the frontoparietal network, and decreased connectivity between the salience network and a node of the default mode network. Furthermore, frequent insomnia symptoms were associated with altered functional connectivity between nodes comprising sensory areas and the cerebellum. These functional alterations of brain networks may underlie dysfunctional affective and cognitive processing in insomnia and contribute to subjectively and objectively impaired sleep. However, it must be noted that the item that was used to assess frequent insomnia symptoms in this study did not assess all the characteristics of clinically diagnosed insomnia.

Decreased dorsal attention network homogeneity as a potential neuroimaging biomarker for major depressive disorder

BACKGROUND

Gaining insight into abnormal functional brain network homogeneity (NH) has the potential to aid efforts to target or otherwise study major depressive disorder (MDD). The NH of the dorsal attention network (DAN) in first-episode treatment-naive MDD patients, however, has yet to be studied. As such, the present study was developed to explore the NH of the DAN in order to determine the ability of this parameter to differentiate between MDD patients and healthy control (HC) individuals.

METHODS

This study included 73 patients with first-episode treatment-naive MDD and 73 age-, gender-, and educational level-matched healthy controls. All participants completed the attentional network test (ANT), Hamilton Rating Scale for Depression (HRSD), and resting-state functional magnetic resonance imaging (rs-fMRI) analyses. A group independent component analysis (ICA) was used to identify the DAN and to compute the NH of the DAN in patients with MDD. Spearman's rank correlation analyses were used to explore relationships between significant NH abnormalities in MDD patients, clinical parameters, and executive control reaction time.

RESULTS

Relative to HCs, patients exhibited reduced NH in the left supramarginal gyrus (SMG). Support vector machine (SVM) analyses and receiver operating characteristic curves indicated that the NH of the left SMG could be used to differentiate between HCs and MDD patients with respective accuracy, specificity, sensitivity, and AUC values of 92.47 %, 91.78 %, 93.15 %, and 65.39 %. A significant positive correlation was observed between the left SMG NH values and HRSD scores among MDD patients.

CONCLUSIONS

These results suggest that NH changes in the DAN may offer value as a neuroimaging biomarker capable of differentiating between MDD patients and healthy individuals.

Default Mode Network Modulation by Psychedelics: A Systematic Review

Psychedelics are a unique class of drug that commonly produce vivid hallucinations as well as profound psychological and mystical experiences. A grouping of interconnected brain regions characterized by increased temporal coherence at rest have been termed the Default Mode Network (DMN). The DMN has been the focus of numerous studies assessing its role in self-referencing, mind wandering, and autobiographical memories. Altered connectivity in the DMN has been associated with a range of neuropsychiatric conditions such as depression, anxiety, post-traumatic stress disorder, attention deficit hyperactive disorder, schizophrenia, and obsessive-compulsive disorder. To date, several studies have investigated how psychedelics modulate this network, but no comprehensive review, to our knowledge, has critically evaluated how major classical psychedelic agents-lysergic acid diethylamide, psilocybin, and ayahuasca-modulate the DMN. Here we present a systematic review of the knowledge base. Across psychedelics there is consistent acute disruption in resting state connectivity within the DMN and increased functional connectivity between canonical resting-state networks. Various models have been proposed to explain the cognitive mechanisms of psychedelics, and in one model DMN modulation is a central axiom. Although the DMN is consistently implicated in psychedelic studies, it is unclear how central the DMN is to the therapeutic potential of classical psychedelic agents. This article aims to provide the field with a comprehensive overview that can propel future research in such a way as to elucidate the neurocognitive mechanisms of psychedelics.

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test-retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. Thus, we sought to identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. We used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These "RSNM targets" were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region ("sgACC-derived targets"). The TBI-D cohort was also randomized to receive active (n = 9) or sham (n = 4) rTMS to RSNM targets with 20 daily sessions of sequential high-frequency left-sided stimulation and low-frequency right-sided stimulation. We found that the group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were thus identified based on DAN anti-correlation and DMN correlation. These RSNM targets showed greater test-retest reliability than sgACC-derived targets. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was also stronger and more reliable for RSNM-derived targets than for sgACC-derived targets. Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment also led to increased connectivity within and between the stimulation sites, the sgACC, and the DMN. Overall, these results suggest that RSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes.

Differential patterns of default mode network activity associated with negative and positive rumination in bipolar disorder

BACKGROUND

Patients with bipolar disorder (BD) engage in both negative and positive rumination, defined as maladaptive self-focused thinking, and this tendency predicts depressive and manic episodes, respectively. Prior research in patients with major depression implicates regions of the default mode network (DMN) consistent with the self-focused nature of rumination. Little is known about the neural correlates of rumination in bipolar disorder.

METHODS

Fifteen euthymic patients with BD (twelve with Type I) and 17 healthy controls (HC) performed negative and positive rumination induction tasks, as well as a distraction task, followed by a self-related trait judgment task while undergoing functional magnetic resonance imaging (fMRI). Participants also underwent resting state scans. We examined functional connectivity at rest and during the induction tasks, as well as task-based activation during the trait judgment task, in core regions of the DMN.

RESULTS

Compared to HC, patients with BD showed greater functional connectivity between the posterior cingulate cortex (PCC) and medial prefrontal cortex (MPFC) at rest and during positive rumination, compared to distraction. They also showed greater activity in the PCC and MPFC during processing of positive traits, following positive rumination. At rest and during negative rumination compared to distraction, patients with BD showed greater functional connectivity between the PCC and inferior parietal lobule than HC.

CONCLUSIONS

These findings demonstrate that negative and positive rumination are subserved by different patterns of connectivity within the DMN in BD. Additionally, the PCC and MPFC are key regions involved in the processing of positive self-relevant traits following positive rumination.

Temporal dynamic patterns of the ventromedial prefrontal cortex underlie the association between rumination and depression

As a major contributor to the development of depression, rumination has proven linked with aberrant default-mode network (DMN) activity. However, it remains unclear how the spontaneous spatial and temporal activity of DMN underlie the association between rumination and depression. To illustrate this issue, behavioral measures and resting-state functional magnetic resonance images were connected in 2 independent samples (NSample1 = 100, NSample2 = 95). Fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) were used to assess spatial characteristic patterns, while voxel-wise functional concordance (across time windows) (VC) and Hurst exponent (HE) were used to assess temporal dynamic patterns of brain activity. Results from both samples consistently show that temporal dynamics but not spatial patterns of DMN are associated with rumination. Specifically, rumination is positively correlated with HE and VC (but not fALFF and ReHo) values, reflecting more consistent and regular temporal dynamic patterns in DMN. Moreover, subregion analyses indicate that temporal dynamics of the ventromedial prefrontal cortex (VMPFC) reliably predict rumination scores. Furthermore, mediation analyses show that HE and VC of VMPFC mediate the association between rumination and depression. These findings shed light on neural mechanisms of individual differences in rumination and corresponding risk for depression.

Cerebello-cerebral Functional Connectivity Networks in Major Depressive Disorder: a CAN-BIND-1 Study Report

Neuroimaging studies have demonstrated aberrant structure and function of the "cognitive-affective cerebellum" in major depressive disorder (MDD), although the specific role of the cerebello-cerebral circuitry in this population remains largely uninvestigated. The objective of this study was to delineate the role of cerebellar functional networks in depression. A total of 308 unmedicated participants completed resting-state functional magnetic resonance imaging scans, of which 247 (148 MDD; 99 healthy controls, HC) were suitable for this study. Seed-based resting-state functional connectivity (RsFc) analysis was performed using three cerebellar regions of interest (ROIs): ROI₁ corresponded to default mode network (DMN)/inattentive processing; ROI₂ corresponded to attentional networks, including frontoparietal, dorsal attention, and ventral attention; ROI₃ corresponded to motor processing. These ROIs were delineated based on prior functional gradient analyses of the cerebellum. A general linear model was used to perform within-group and between-group comparisons. In comparison to HC, participants with MDD displayed increased RsFc within the cerebello-cerebral DMN (ROI₁) and significantly elevated RsFc between the cerebellar ROI₁ and bilateral angular gyrus at a voxel threshold (p < 0.001, two-tailed) and at a cluster level (p < 0.05, FDR-corrected). Group differences were non-significant for ROI₂ and ROI₃. These results contribute to the development of a systems neuroscience approach to the diagnosis and treatment of MDD. Specifically, our findings confirm previously reported associations between MDD, DMN, and cerebellum, and highlight the promising role of these functional and anatomical locations for the development of novel imaging-based biomarkers and targets for neuromodulation therapies. ClinicalTrials.gov TRN: NCT01655706; Date of Registration: August 2nd, 2012.

Changes in music-evoked emotion and ventral striatal functional connectivity after psilocybin therapy for depression

BACKGROUND

Music listening is a staple and valued component of psychedelic therapy, and previous work has shown that psychedelics can acutely enhance music-evoked emotion.

AIMS

The present study sought to examine subjective responses to music before and after psilocybin therapy for treatment-resistant depression, while functional magnetic resonance imaging (fMRI) data was acquired.

METHODS

Nineteen patients with treatment-resistant depression received a low oral dose (10 mg) of psilocybin, and a high dose (25 mg) 1 week later. fMRI was performed 1 week prior to the first dosing session and 1 day after the second. Two scans were conducted on each day: one with music and one without. Visual analogue scale ratings of music-evoked 'pleasure' plus ratings of other evoked emotions (21-item Geneva Emotional Music Scale) were completed after each scan. Given its role in musical reward, the nucleus accumbens (NAc) was chosen as region of interest for functional connectivity (FC) analyses. Effects of drug (vs placebo) and music (vs no music) on subjective and FC outcomes were assessed. Anhedonia symptoms were assessed pre- and post-treatment (Snaith-Hamilton Pleasure Scale).

RESULTS

Results revealed a significant increase in music-evoked emotion following treatment with psilocybin that correlated with post-treatment reductions in anhedonia. A post-treatment reduction in NAc FC with areas resembling the default mode network was observed during music listening (vs no music).

CONCLUSION

These results are consistent with current thinking on the role of psychedelics in enhancing music-evoked pleasure and provide some new insight into correlative brain mechanisms.

A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures

BACKGROUND

Major Depressive Disorder (MDD) is a psychiatric disorder characterized by functional brain deficits, as documented by resting-state functional magnetic resonance imaging (rs-fMRI) studies.

AIMS

In recent years, some studies used machine learning (ML) approaches, based on rs-fMRI features, for classifying MDD from healthy controls (HC). In this context, this review aims to provide a comprehensive overview of the results of these studies.

DESIGN

The studies research was performed on 3 online databases, examining English-written articles published before August 5, 2022, that performed a two-class ML classification using rs-fMRI features. The search resulted in 20 eligible studies.

RESULTS

The reviewed studies showed good performance metrics, with better performance achieved when the dataset was restricted to a more homogeneous group in terms of disease severity. Regions within the default mode network, salience network, and central executive network were reported as the most important features in the classification algorithms.

LIMITATIONS

The small sample size together with the methodological and clinical heterogeneity limited the generalizability of the findings.

CONCLUSIONS

In conclusion, ML applied to rs-fMRI features can be a valid approach to classify MDD and HC subjects and to discover features that can be used for additional investigation of the pathophysiology of the disease.

Associations between repetitive negative thinking and resting-state network segregation among healthy middle-aged adults

Background

Repetitive Negative Thinking (RNT) includes negative thoughts about the future and past, and is a risk factor for depression and anxiety. Prefrontal and anterior cingulate cortices have been linked to RNT but several regions within large-scale networks are also involved, the efficiency of which depends on their ability to remain segregated.

Methods

Associations between RNT and system segregation (SyS) of the Anterior Salience Network (ASN), Default Mode Network (DMN) and Executive Control Network (ECN) were explored in healthy middle-aged adults (N = 341), after undergoing resting-state functional magnetic resonance imaging. Regression analyses were conducted with RNT as outcome variable. Explanatory variables were: SyS, depression, emotional stability, cognitive complaints, age and sex.

Results

Analyses indicated that RNT was associated with depression, emotional stability, cognitive complaints, age and segregation of the left ECN (LECN) and ASN. Further, the ventral DMN (vDMN) presented higher connectivity with the ASN and decreased connectivity with the LECN, as a function of RNT.

Conclusion

Higher levels of perseverative thinking were related to increased segregation of the LECN and decreased segregation of the ASN. The dissociative connectivity of these networks with the vDMN may partially account for poorer cognitive control and increased self-referential processes characteristic of RNT.