Insular dysfunction within the salience network is associated with severity of symptoms and aberrant inter-network connectivity in major depressive disorder

Treatment-naïve first episode depression classification based on high-order brain functional network

BACKGROUND

Recent functional connectivity (FC) studies have proved the potential value of resting-state functional magnetic resonance imaging (rs-fMRI) in the study of major depressive disorder (MDD); yet, the rs-fMRI-based individualized diagnosis of MDD is still challenging.

METHODS

We enrolled 82 treatment-naïve first episode depression (FED) adults and 72 matched normal control (NC). A computer-aided diagnosis framework was utilized to classify the FEDs from the NCs based on the features extracted from not only traditional "low-order" FC networks (LON) based on temporal synchronization of original rs-fMRI signals, but also "high-order" FC networks (HON) that characterize more complex functional interactions via correlation of the dynamic (time-varying) FCs. We contrasted a classifier using HON feature (C_HON) and compared its performance with using LON only (C_LON). Finally, an integrated classification model with both features was proposed to further enhance FED classification.

RESULTS

The C_HON had significantly improved diagnostic accuracy compared to the C_LON (82.47% vs. 67.53%). Joint classification further improved the performance (83.77%). The brain regions with potential diagnostic values mainly encompass the high-order cognitive function-related networks. Importantly, we found previously less-reported potential imaging biomarkers that involve the vermis and the crus II in the cerebellum.

LIMITATIONS

We only used one imaging modality and did not examine data from different subtypes of depression.

CONCLUSIONS

Depression classification could be significantly improved by using HON features that better capture the higher-level brain functional interactions. The findings suggest the importance of higher-level cerebro-cerebellar interactions in the pathophysiology of MDD.

Altered dynamic functional connectivity in weakly-connected state in major depressive disorder

OBJECTIVE

Major depressive disorder (MDD) is accompanied by abnormal changes in dynamic functional connectivity (FC) among brain regions. The aim of this study is to investigate whether the abnormalities of dynamic FC in MDD are state-dependent (related to a specific connectivity state).

METHODS

We performed time-varying connectivity analysis on resting-state functional magnetic resonance imaging (rs-fMRI) of 49 MDD patients and 54 matched healthy controls (HCs). FC differences between groups in each connectivity state were analyzed and associations between disease severity and dynamics of aberrant FC were explored.

RESULTS

Two distinct connectivity states (i.e., weakly-connected and strongly-connected state) were identified. Compared to HCs, MDD patients were associated with increased mean dwell time and decreased FC between and within subnetworks in the weakly-connected state. Dynamics of reduced FC between cognitive control network and default mode network as well as within cognitive control network predicted individual differences in depression symptom severity.

CONCLUSIONS

Our findings suggested that the MDD-caused FC alterations mostly appeared in the weakly-connected state, which might contribute to clinical diagnosis of MDD.

SIGNIFICANCE

These findings provide new perspectives for understanding the state-dependent neurophysiological mechanisms in MDD.

Structural connectivity profile supports laterality of the salience network

The salience network (SN) is mainly involved in detecting and filtering multimodal salient stimuli, and mediating the switch between the default mode network and central executive network. Early studies have indicated a right‐sided dominance in the functional organization of the SN; however, the anatomical basis of the functional lateralization remains unclear. Here, we hypothesized that the structural connectivity profile between the frontoinsular cortex (FIC) and dorsal anterior cingulate cortex (dACC), which are two core hubs of the SN, is also dominant in the right hemisphere. Based on diffusion and resting‐state functional magnetic resonance imaging (rfMRI) of adult healthy volunteers in independent datasets, we found a stable right‐sided laterality of both the FIC‐dACC structural and functional connectivity in both the human connectome project cohort and a local Chinese cohort. Furthermore, a significant effect of aging on the integrity of the right FIC‐dACC structural connectivity was also identified. The right‐sided laterality of the structural organization of the SN may help us to better understand the functional roles of the SN in the normal human brain.

Ketamine has distinct electrophysiological and behavioral effects in depressed and healthy subjects

Ketamine's mechanism of action was assessed using gamma power from magnetoencephalography (MEG) as a proxy measure for homeostatic balance in 35 unmedicated subjects with major depressive disorder (MDD) and 25 healthy controls enrolled in a double-blind, placebo-controlled, randomized cross-over trial of 0.5 mg/kg ketamine. MDD subjects showed significant improvements in depressive symptoms, and healthy control subjects exhibited modest but significant increases in depressive symptoms for up to 1 day after ketamine administration. Both groups showed increased resting gamma power following ketamine. In MDD subjects, gamma power was not associated with the magnitude of the antidepressant effect. However, baseline gamma power was found to moderate the relationship between post-ketamine gamma power and antidepressant response; specifically, higher post-ketamine gamma power was associated with better response in MDD subjects with lower baseline gamma, with an inverted relationship in MDD subjects with higher baseline gamma. This relationship was observed in multiple regions involved in networks hypothesized to be involved in the pathophysiology of MDD. This finding suggests biological subtypes based on the direction of homeostatic dysregulation and has important implications for inferring ketamine's mechanism of action from studies of healthy controls alone.

Reconfiguration of Cortical Networks in MDD Uncovered by Multiscale Community Detection with fMRI

Major depressive disorder (MDD) is known to be associated with altered interactions between distributed brain regions. How these regional changes relate to the reorganization of cortical functional systems, and their modulation by antidepressant medication, is relatively unexplored. To identify changes in the community structure of cortical functional networks in MDD, we performed a multiscale community detection algorithm on resting-state functional connectivity networks of unmedicated MDD (uMDD) patients (n = 46), medicated MDD (mMDD) patients (n = 38), and healthy controls (n = 50), which yielded a spectrum of multiscale community partitions. we selected an optimal resolution level by identifying the most stable community partition for each group. uMDD and mMDD groups exhibited a similar reconfiguration of the community structure of the visual association and the default mode systems but showed different reconfiguration profiles in the frontoparietal control (FPC) subsystems. Furthermore, the central system (somatomotor/salience) and 3 frontoparietal subsystems showed strengthened connectivity with other communities in uMDD but, with the exception of 1 frontoparietal subsystem, returned to control levels in mMDD. These findings provide evidence for reconfiguration of specific cortical functional systems associated with MDD, as well as potential effects of medication in restoring disease-related network alterations, especially those of the FPC system.

Functional disconnectivity of the hippocampal network and neural correlates of memory impairment in treatment-resistant depression

BACKGROUND

Major depressive disorder (MDD) is a disabling neuropsychiatric condition associated with cognitive impairment. Neuroimaging studies have consistently linked memory deficits with hippocampal atrophy in MDD patients. However, there has been a paucity of research examining how the hippocampus functionally contributes to memory impairments in MDD. The present study examined whether hippocampal networks distinguish treatment-resistant depression (TRD) patients from healthy controls (HCs), and whether these networks underlie declarative memory deficits in TRD. We hypothesized that functional connectivity (FC) of the posterior hippocampus would correlate preferentially with memory in patients, whereas FC pattern of the anterior and intermediate hippocampus would correlate with emotion-mediated regions and show a significant correlation with memory.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) scans were acquired in 56 patients and 42 age- and sex-matched HCs. We parcellated the hippocampus into three subregions based on a sparse representation-based method recently developed by our group. FC networks of hippocampal subregions were compared between patients and HCs and correlated with clinical measures and cognitive performance.

RESULTS

Decreased connectivity of the right intermediate hippocampus (RIH) with the limbic regions was a distinguishing feature between TRD and HCs. These functional abnormalities were present in the absence of structural volumetric differences. Furthermore, lower right amygdalar connectivity to the RIH related to a longer current depressive episode. Declarative memory deficits in TRD were significantly associated with left posterior and right intermediate hippocampal FC patterns.

LIMITATIONS

Our patient samples were treatment-resistant, the conclusions from this study cannot be generalized to all MDD patients directly. Task-based imaging studies are needed to demonstrate hippocampal engagement in the memory deficits of patients. Finally, our findings are strongly in need of replication in independent validation samples.

CONCLUSIONS

These findings demonstrate a transitional property of the intermediate hippocampal subregion between its anterior and posterior counterparts in TRD patients, and provide new insights into the neural network-level dysfunction of the hippocampus in TRD.

Overlapping and distinct neural metabolic patterns related to impulsivity and hypomania in Parkinson's disease

Impulsivity and hypomania are common non-motor features in Parkinson's disease (PD). The aim of this study was to find the overlapping and distinct neural correlates of these symptoms in PD. Symptoms of impulsivity and hypomania were assessed in 24 PD patients using the Barratt Impulsiveness Scale (BIS-11) and Self-Report Manic Inventory (SRMI), respectively. In addition, fluorodeoxyglucose positron emission tomography (FDG-PET) imaging for each individual was performed. We conducted two separate multiple regression analyses for BIS-11 and SRMI scores with FDG-PET data to identify the brain regions that are associated with both impulsivity and hypomania scores, as well as those exclusive to each symptom. Then, seed-based functional connectivity analyses on healthy subjects identified the areas connected to each of the exclusive regions and the overlapping region, used as seeds. We observed a positive association between BIS-11 and SRMI scores and neural metabolism only in the prefrontal areas. Conjunction analysis revealed an overlapping region in the middle frontal gyrus. Regions exclusive to impulsivity were found in the medial part of the right superior frontal gyrus and regions exclusive to hypomania were in the right superior frontal gyrus, right precentral gyrus and right paracentral lobule. Connectivity patterns of seeds exclusively related to impulsivity were different from those for hypomania in healthy brains. These results provide evidence of both overlapping and distinct regions linked with impulsivity and hypomania scores in PD. The exclusive regions for each characteristic are connected to specific intrinsic functional networks.

Exploring common changes after acute mental stress and acute tryptophan depletion: Resting-state fMRI studies

Stress and low serotonin levels are important biological factors in depression and anxiety etiologies. Although studies indicate that low serotonin levels, stress, and other factors may interact in depression/anxiety psychopathology, few studies have investigated the potentially shared neural substrates. We conducted resting-state fMRI scans pre- and post-stress task, and under control and tryptophan depletion condition, to explore the common changes induced by acute mental stress (AMS) and acute tryptophan depletion (ATD). The present study targeted regions within core brain networks - default mode network, salience network, executive control network, and emotion network - reported altered in AMS and ATD, and used regional homogeneity (ReHo) and functional connectivity (FC) analyses to explore their overlapped effects. We additionally examined the relationships among core neural networks - operationalized as an index of resource allocation bias that quantifies the shift from internal to external modes of processing. We found both manipulations induced increased ReHo of the amygdala and decreased ReHo of the posterior cingulate cortex (PCC). The PCC-amygdala FC was negatively correlated with the change of negative affect, whereas the right dorsolateral prefrontal cortex and right anterior insula FC was positively associated with anxiety level. In addition, we found that a greater shift to an external mode was correlated with higher anxiety level under both conditions. Common changes induced by acute mental stress and acute tryptophan depletion confirmed our hypothesis that AMS and ATD induce changes in common neural pathways, which in turn might mark vulnerability to depression and anxiety.

Frequency-Dependent Spatial Distribution of Functional Hubs in the Human Brain and Alterations in Major Depressive Disorder

Alterations in large-scale brain intrinsic functional connectivity (FC), i.e., coherence between fluctuations of ongoing activity, have been implicated in major depressive disorder (MDD). Yet, little is known about the frequency-dependent alterations of FC in MDD. We calculated frequency specific degree centrality (DC) – a measure of overall FC of a brain region – within 10 distinct frequency sub-bands accessible from the full range of resting-state fMRI BOLD fluctuations (i.e., 0.01–0.25 Hz) in 24 healthy controls and 24 MDD patients. In healthy controls, results reveal a frequency-specific spatial distribution of highly connected brain regions – i.e., hubs – which play a fundamental role in information integration in the brain. MDD patients exhibited significant deviations from the healthy DC patterns, with decreased overall connectedness of widespread regions, in a frequency-specific manner. Decreased DC in MDD patients was observed predominantly in the occipital cortex at low frequencies (0.01–0.1 Hz), in the middle cingulate cortex, sensorimotor cortex, lateral parietal cortex, and the precuneus at middle frequencies (0.1–0.175 Hz), and in the anterior cingulate cortex at high frequencies (0.175–0.25 Hz). Additionally, decreased DC of distinct parts of the insula was observed across low, middle, and high frequency bands. Frequency-specific alterations in the DC of the temporal, insular, and lateral parietal cortices correlated with symptom severity. Importantly, our results indicate that frequency-resolved analysis within the full range of frequencies accessible from the BOLD signal – also including higher frequencies (>0.1 Hz) – reveals unique information about brain organization and its changes, which can otherwise be overlooked.

Role of inflammation in depression relapse

Major depressive disorder (MDD) is a leading cause of disability worldwide. After the first episode, patients with remitted MDD have a 60% chance of experiencing a second episode. Consideration of therapy continuation should be viewed in terms of the balance between the adverse effects of medication and the need to prevent a possible relapse. Relapse during the early stages of MDD could be prevented more efficiently by conducting individual risk assessments and providing justification for continuing therapy. Our previous work established the neuroimaging markers of relapse by comparing patients with recurrent major depressive disorder (rMDD) in depressive and remitted states. However, it is not known which of these markers are trait markers that present before initial relapse and, consequently, predict disease course. Here, we first describe how inflammation can be translated to subtype-specific clinical features and suggest how this could be used to facilitate clinical diagnosis and treatment. Next, we address the central and peripheral functional state of the immune system in patients with MDD. In addition, we emphasize the important link between the number of depressive episodes and rMDD and use neuroimaging to propose a model for the latter. Last, we address how inflammation can affect brain circuits, providing a possible mechanism for rMDD. Our review suggests a link between inflammatory processes and brain region/circuits in rMDD.

Link between insomnia and perinatal depressive symptoms: A meta-analysis

Evidence shows the possible link between insomnia and perinatal depressive symptoms. In order to find a convergent quantitative answer, we collected data via the search of Medline, EMBASE and reference tracking, which included nine studies (a total sample of 1,922 women). An aggregate effect size estimate (correlation coefficient) was generated using the comprehensive meta-analysis software. For the meta-analytic procedure, a random effects model was set a priori. Moderating factors, including study design, method of assessment of depression, geographical origin of data, publication year, mean age, % married, breastfeeding rate, quality and type of data, % primiparous and history of depression, were examined via categorical or univariate mixed-effects (method of moments) meta-regression methods. Heterogeneity and publication bias were examined using standard meta-analytic approaches. We found a significant, medium-size relationship between insomnia and perinatal depressive symptoms (point estimate, 0.366; 95% confidence interval [CI], 0.205-0.508; p < 0.001; n = 9) and this was significantly heterogeneous (Q, 118.77; df, 8; p < 0.001; I² , 93.26%). The effect size estimate was significant for studies reporting no history of depression (point estimate, 0.364; 95% CI, 0.035-0.622; p < 0.05; n = 5) and for study design. With meta-regression, no moderating factor (age, marriage rate, breastfeeding rate, pregnancy history or publication year) significantly mediated the effect size estimate. The depression assessment scale used, but not other categorical variables, explained the magnitude of heterogeneity. We found that insomnia during the perinatal period is associated with depressive symptoms, which warrants screening pregnant mothers for insomnia and depression.

Personalized repetitive transcranial magnetic stimulation temporarily alters default mode network in healthy subjects

High frequency repetitive transcranial magnetic stimulation (HF-rTMS) delivered to the left dorsolateral prefrontal cortex (DLPFC) is an effective treatment option for treatment resistant depression. However, the underlying mechanisms of a full session of HF-rTMS in healthy volunteers have not yet been described. Here we investigated, with a personalized selection of DLPFC stimulation sites, the effects driven by HF-rTMS in healthy volunteers (n = 23) over the default mode network (DMN) in multiple time windows. After a complete 10 Hz rTMS (3000 pulses) session, we observe a decrease of functional connectivity between the DMN and the subgenual Anterior Cingulate Cortex (sgACC), as well as the ventral striatum (vStr). A negative correlation between the magnitude of this decrease in the right sgACC and the harm avoidance domain measure from the Temperament and Character Inventory was observed. Moreover, we identify that coupling strength of right vStr with the DMN post-stimulation was proportional to a decrease in self-reports of negative mood from the Positive and Negative Affect Schedule. This shows HF-rTMS attenuates perception of negative mood in healthy recipients in agreement with the expected effects in patients. Our study, by using a personalized selection of DLPFC stimulation sites, contributes understanding the effects of a full session of rTMS approved for clinical use in depression over related brain regions in healthy volunteers.

Common and distinct changes of default mode and salience network in schizophrenia and major depression

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Regional default mode network connectivity in major depressive disorder: modulation by acute intravenous citalopram

The relationship between altered default mode network (DMN) connectivity and abnormal serotonin function in major depressive disorder (MDD) has not been investigated. Using intravenous citalopram and resting-state fMRI, we investigated DMN intra-network connectivity and serotonin function in 77 healthy controls and patients with MDD. There were no significant main effects of MDD or citalopram on DMN intra-network connectivity; however, significant interactions indicated that group differences under saline were modified by citalopram. In MDD patients during saline infusion, in contrast with controls, the DMN (i) did not include the precuneus that was instead part of an anti-correlated network but (ii) did include amygdala that was part of the anti-correlated network in controls. Citalopram infusion in MDD patients restored the pattern seen in controls under saline. In healthy controls, citalopram infusion disengaged the precuneus from the DMN and engaged the amygdala, partially reproducing the abnormalities seen under saline in MDD. In exploratory analyses within the MDD group, greater rumination self-ratings were associated with greater intra-network connectivity of the anterior cingulate cortex with the DMN. We hypothesise that, in MDD, disengagement of the precuneus from the DMN relates to overgeneral memory bias in rumination. The opposite effect, with greater engagement of the amygdala in the DMN, reflects the negative valence of rumination. Reversal of these abnormalities by citalopram suggests that they may be related to impaired serotonin function. That citalopram engaged the amygdala in the DMN in controls may relate to the paradoxical effects on aversive processing seen with acute SSRIs in healthy subjects.

Brain network functional connectivity and cognitive performance in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric disorders. Cognitive complaints are commonly reported in MDD and cognitive impairment is a criterion item for MDD diagnosis. As cognitive processes are increasingly understood as the consequences of distributed interactions between brain regions, a network-based approach may provide novel information about the neurobiological basis of cognitive deficits in MDD.

METHODS

51 Depressed (MDD, n = 23) and non-depressed (control, n = 28) adult participants completed neuropsychological testing and resting-state fMRI (rsfMRI). Cognitive domain scores (processing speed, working memory, episodic memory, and executive function) were calculated. Anatomical regions of interests were entered as seeds for functional connectivity analyses in: default mode (DMN), salience, and executive control (ECN) networks. Partial correlations controlling for age and sex were conducted for cognitive domain scores and functional connectivity in clusters with significant differences between groups.

RESULTS

Significant rsfMRI differences between groups were identified in multiple clusters in the DMN and ECN. Greater positive connectivity within the ECN and between ECN and DMN regions was associated with poorer episodic memory performance in the Non-Depressed group but better performance in the MDD group. Greater connectivity within the DMN was associated with better episodic and working memory performance in the Non-Depressed group but worse performance in the MDD group.

CONCLUSIONS

These results provide evidence that cognitive performance in MDD may be associated with aberrant functional connectivity in cognitive networks and suggest patterns of alternate brain function that may support cognitive processes in MDD.

Time dilation and acceleration in depression

BACKGROUND

A recent meta-analysis left open a significant question regarding altered time perception in depression: Why do depressed people overproduce short durations and under-produce longer durations if their present experience is that time flows slowly? Experience and judgement of time do not seem to accord with one another.

ANALYSIS

By excluding two of the six studies on methodological grounds from a previous meta-analysis of medium-length interval productions, and re-analysing the remaining four studies, the present paper finds that subjective time accelerates from initial dilation within present experience (approximately 1 s duration) to subsequent acceleration within working memory (approximately 30 s duration) when depressed.

PROPOSALS

It is proposed that depressive time dilation and acceleration refer to the default mode and central executive networks, respectively. The acceleration effect is suggested to occur due to mood congruency between long intervals, boredom, and depression. This mood congruency leads to the automatic recall of intrusive, negative, and non-specific autobiographical long-term memories used to judge intervals from previous experience. Acceleration in working memory then occurs according to the contextual change model of duration estimation.

LIMITATIONS

The meta-analysis is limited to four studies only, but provides a potential link between time experience and judgement within the same explanatory model.

CONCLUSIONS

Similarities between psychological time dilation/acceleration and physical time dilation/acceleration are discussed.

Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder

Brain imaging studies have revealed that functional and structural brain connectivity in the so-called triple network (i.e., default mode network (DMN), salience network (SN) and central executive network (CEN)) are consistently altered in schizophrenia. However, similar changes have also been found in patients with major depressive disorder, prompting the question of specific triple network signatures for the two disorders. In this study, we proposed Supervised Convex Nonnegative Matrix Factorization (SCNMF) to extract distributed multi-modal brain patterns. These patterns distinguish schizophrenia and major depressive disorder in a latent low-dimensional space of the triple brain network. Specifically, 21 patients of schizophrenia and 25 patients of major depressive disorder were assessed by T1-weighted, diffusion-weighted, and resting-state functional MRIs. Individual structural and functional connectivity networks, based on pre-defined regions of the triple network were constructed, respectively. Afterwards, SCNMF was employed to extract the discriminative patterns. Experiments indicate that SCNMF allows extracting the low-rank discriminative patterns between the two disorders, achieving a classification accuracy of 82.6% based on the extracted functional and structural abnormalities with support vector machine. Experimental results show the specific brain patterns for schizophrenia and major depressive disorder that are multi-modal, complex, and distributed in the triple network. Parts of the prefrontal cortex including superior frontal gyri showed variation between patients with schizophrenia and major depression due to structural properties. In terms of functional properties, the middle cingulate cortex, inferior parietal lobule, and cingulate cortex were the most discriminative regions.

Segregation of salience network predicts treatment response of depression to repetitive transcranial magnetic stimulation

Background

The present study tested the hypothesis that network segregation, a graph theoretic measure of functional organization of the brain, is correlated with treatment response in patients with major depressive disorder (MDD) undergoing repetitive transcranial magnetic stimulation (rTMS).

Methods

Network segregation, calculated from resting state functional magnetic resonance imaging scans, was measured in 32 patients with MDD who entered a sham-controlled, double-blinded, randomized trial of rTMS to the left dorsolateral prefrontal cortex, and a cohort of 20 healthy controls (HCs). Half of the MDD patients received sham treatment in the blinded phase, followed by active rTMS in the open-label phase. The analyses focused on segregation of the following networks: default mode (DMN), salience (SN), fronto-parietal (FPN), cingulo-opercular (CON), and memory retrieval (MRN).

Results

There was no differential change in network segregation comparing sham to active treatment. However, in the combined group of patients who completed active rTMS treatment (in the blinded plus open-label phases), higher baseline segregation of SN significantly predicted more symptom improvement after rTMS. Compared to HCs at baseline, MDD patients showed decreased segregation in DMN, and trend-level decreases in SN and MRN.

Conclusion

The results highlight the importance of network segregation in MDD, particularly in the SN, where more normal baseline segregation of SN may predict better treatment response to rTMS in depression.

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We examined network segregation in a cohort of MDD patients receiving rTMS treatment.

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More normal segregation of SN predicted better response of depression to rTMS.

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Patients with MDD had decreased network segregation in DMN.

Changes in Functional Connectivity Following Treatment With Emotion Regulation Therapy

Emotion regulation therapy (ERT) is an efficacious treatment for distress disorders (i.e., depression and anxiety), predicated on a conceptual model wherein difficult to treat distress arises from intense emotionality (e.g., neuroticism, dispositional negativity) and is prolonged by negative self-referentiality (e.g., worry, rumination). Individuals with distress disorders exhibit disruptions in two corresponding brain networks including the salience network (SN) reflecting emotion/motivation and the default mode network (DMN) reflecting self-referentiality. Using resting-state functional connectivity (rsFC) analyses, seeded with primary regions in each of these networks, we investigated whether ERT was associated with theoretically consistent changes across nodes of these networks and whether these changes related to improvements in clinical outcomes. This study examined 21 generalized anxiety disorder (GAD) patients [with and without major depressive disorder (MDD)] drawn from a larger intervention trial (Renna et al., 2018a), who completed resting state fMRI scans before and after receiving 16 sessions of ERT. We utilized seed-based connectivity analysis with seeds in the posterior cingulate cortex (PCC), right anterior insula, and right posterior insula, to investigate whether ERT was associated with changes in connectivity of nodes of the DMN and SN networks to regions across the brain. Findings revealed statistically significant treatment linked changes in both the DMN and SN network nodes, and these changes were associated with clinical improvement corresponding to medium effect sizes. The results are discussed in light of a nuanced understanding of the role of connectivity changes in GAD and MDD, and begin to provide neural network support for the hypothesized treatment model predicated by ERT.

Altered functional connectivity in binge eating disorder and bulimia nervosa: A resting-state fMRI study

INTRODUCTION

The etiology of bulimic-type eating (BTE) disorders such as binge eating disorder (BED) and bulimia nervosa (BN) is still largely unknown. Brain networks subserving the processing of rewards, emotions, and cognitive control seem to play a crucial role in the development and maintenance of eating disorders. Therefore, further investigations into the neurobiological underpinnings are needed to discern abnormal connectivity patterns in BTE disorders.

METHODS

The present study aimed to investigate functional as well as seed-based connectivity within well-defined brain networks. Twenty-seven individuals with BED, 29 individuals with BN, 28 overweight, and 30 normal-weight control participants matched by age, gender, and education underwent resting-state functional magnetic resonance imaging. Functional connectivity was assessed by spatial group independent component analysis and a seed-based correlation approach by examining the default mode network (DMN), salience network (SN), and executive network (EN).

RESULTS

Group comparisons revealed that BTE disorder patients exhibit aberrant functional connectivity in the dorsal anterior cingulate cortex (dACC) within the SN, as well as in the medial prefrontal cortex within the DMN. Furthermore, BED and BN groups differed from each other in functional connectivity within each network. Seed-based correlational analysis revealed stronger synchronous dACC-retrosplenial cortex activity in the BN group.

CONCLUSION

Our findings demonstrate abnormalities in brain networks involved in salience attribution, self-referential processing, and cognitive control in bulimic-type eating disorders. Together with our observation of functional connectivity differences between BED and BN, this study offers a differentiated account of both similarities and differences regarding brain connectivity in BED and BN.

Functional plasticity of the dorsomedial prefrontal cortex in depression reorganized by electroconvulsive therapy: Validation in two independent samples

Previous studies have implied a key role for the prefrontal cortex in the antidepressive effect of electroconvulsive therapy (ECT). However, there is still ubiquitous inconsistency across these studies, partly due to several confounding effects induced by the use of different samples. Studies with independent samples are necessary for validations to minimize confounding effects. In the current study, resting-state magnetic resonance imaging of 84 participants was collected using two scanners and two types of scanning parameters. One sample consisted of 28 patients and 23 healthy controls, and the other sample consisted of 33 patients. The local activity (indexed by the amplitude of low-frequency fluctuations) and functional connectivity were used to examine functional plasticity in the two independent samples before and after ECT. Both samples showed increased local activity of the dorsomedial prefrontal cortex (DMPFC) and enhanced connectivity of the DMPFC with the posterior cingulate cortex (PCC) following ECT. The enhanced connectivity between the DMPFC and PCC was positively associated with clinical improvement for both samples. These findings provide relatively strong evidence to support the functional plasticity of the dorsomedial prefrontal cortex and reorganization by ECT. The functional plasticity of the DMPFC-PCC may underlie the antidepressive effect of ECT.

Changes in Functional Connectivity Following Treatment With Emotion Regulation Therapy

Emotion regulation therapy (ERT) is an efficacious treatment for distress disorders (i.e., depression and anxiety), predicated on a conceptual model wherein difficult to treat distress arises from intense emotionality (e.g., neuroticism, dispositional negativity) and is prolonged by negative self-referentiality (e.g., worry, rumination). Individuals with distress disorders exhibit disruptions in two corresponding brain networks including the salience network (SN) reflecting emotion/motivation and the default mode network (DMN) reflecting self-referentiality. Using resting-state functional connectivity (rsFC) analyses, seeded with primary regions in each of these networks, we investigated whether ERT was associated with theoretically consistent changes across nodes of these networks and whether these changes related to improvements in clinical outcomes. This study examined 21 generalized anxiety disorder (GAD) patients [with and without major depressive disorder (MDD)] drawn from a larger intervention trial (Renna et al., 2018a), who completed resting state fMRI scans before and after receiving 16 sessions of ERT. We utilized seed-based connectivity analysis with seeds in the posterior cingulate cortex (PCC), right anterior insula, and right posterior insula, to investigate whether ERT was associated with changes in connectivity of nodes of the DMN and SN networks to regions across the brain. Findings revealed statistically significant treatment linked changes in both the DMN and SN network nodes, and these changes were associated with clinical improvement corresponding to medium effect sizes. The results are discussed in light of a nuanced understanding of the role of connectivity changes in GAD and MDD, and begin to provide neural network support for the hypothesized treatment model predicated by ERT.

Within-Network Connectivity in the Salience Network After Attention Bias Modification Training in Residual Depression: Report From a Preregistered Clinical Trial

Alterations in resting state networks (RSNs) are associated with emotional- and attentional control difficulties in depressed individuals. Attentional bias modification (ABM) training may lead to more adaptive emotional processing in depression, but little is known about the neural underpinnings associated with ABM. In the current study a sample of 134 previously depressed individuals were randomized into 14 days of computerized ABM- or a closely matched placebo training regime followed by a resting state magnetic resonance imaging (MRI) scan. Using independent component analysis (ICA) we examined within-network connectivity in three major RSN's, the default mode network (DMN), the salience network (SN) and the central executive network (CEN) after 2 weeks of ABM training. We found a significant difference between the training groups within the SN, but no difference within the DMN or CEN. Moreover, a significant symptom improvement was observed in the ABM group after training. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02931487.

Different Aspects of the Neural Response to Socio-Emotional Events Are Related to Instability and Inertia of Emotional Experience in Daily Life: An fMRI-ESM Study

Emotions are fundamentally temporal processes that dynamically change over time. This temporal nature is inherently involved in making emotions adaptive by guiding interactions with our environment. Both the size of emotional changes across time (i.e., emotional instability) and the tendency of emotions to persist across time (i.e., autocorrelation of emotional experience, emotional inertia) are key features of a person’s emotion dynamics, and have been found central to maladaptive functioning and psychopathology as well as linked to social functioning. However, whether different (neural) mechanisms are underlying these dynamics as well as how they are related to the processing of (socio-) emotional information is to date widely unknown. Using a combination of Experience Sampling methods (ESMs) and fMRI (involving a social feedback paradigm), we examine how emotional instability and inertia in everyday life are associated with different aspects of the neural response to socio-emotional events. The findings indicate that while emotional instability is connected to the response of the core salience network (SN), emotional inertia is associated to responses in the parahippocampal gyrus (PHG) and lateral orbitofrontal cortex (lOFC). This is the first study showing that different aspects of the neural response to socio-emotional events are associated with different aspects of the temporal dynamics of emotion in real life.

Moderating Effects of Harm Avoidance on Resting-State Functional Connectivity of the Anterior Insula

As an index of behavioral inhibition and an individual’s propensity to avoid, rather than seek, potentially dangerous situations, harm avoidance has been linked to internalizing psychopathology. Altered connectivity within intrinsic functional neural networks (i.e., default mode [DMN], central executive [CEN] and salience networks [SN]) has been related to internalizing psychopathology; however, less is known about the effects of harm avoidance on functional connectivity within and between these networks. Importantly, harm avoidance may be distinguishable from trait anxiety and have clinical relevance as a risk factor for internalizing psychopathology. A sample of young adults (n = 99) completed a resting state functional magnetic resonance imaging (fMRI) scan and self-report measures of harm avoidance and trait anxiety. Whole brain seed-to-voxel and seed-to-network connectivity analyses were conducted using anterior insula seeds to examine associations between harm avoidance/trait anxiety and connectivity. After adjusting for sex and age, there was a significant negative effect of harm avoidance on connectivity between the anterior insula and clusters in the precuneus/posterior cingulate cortex (PCC) left superior/middle frontal gyrus, dorsal anterior cingulate cortex (dACC) and bilateral inferior parietal lobule (IPL)/angular gyrus. Seed-to-network analyses indicated a negative effect of harm avoidance on connectivity between the right anterior insula and anterior and posterior DMN. There were no effects of trait anxiety on functional connectivity of the anterior insula. Overall, the results indicate that individual differences in harm avoidance relate to disruptions in internetwork connectivity that may contribute to deficits in appropriately modulating attentional focus.

A computational network control theory analysis of depression symptoms

Rumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how network control theory relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and Executive Control Networks in depression. We also find that subclinical depression is related to the ability to “drive” the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.

Aberrant Default Mode Network Underlying the Cognitive Deficits in the Patients With Late-Onset Depression

Late-onset depression (LOD) is regarded as a risk factor or a prodrome of Alzheimer’s disease (AD). Moreover, LOD patients with cognitive deficits have the higher risk of subsequent AD. Thus, it is necessary to understand the neural underpinnings of cognitive deficits and its pathological implications in LOD. Consistent findings show that the default mode network (DMN) is an important and potentially useful brain network for the cognitive deficits in LOD patients. In recent years, genetics has been actively researched as a possible risk factor in the pathogenesis of LOD. So, in this review, we discuss the current research progress on the cognitive deficits and DMN in LOD through a combined view of brain network and genetics. We find that different structural and functional impairments of the DMN might be involved in the etiological mechanisms of different cognitive impairments in LOD patients.

Anhedonia and depression severity dissociated by dmPFC resting-state functional connectivity in adolescents

INTRODUCTION

Given the heterogeneity within depression, in this study we aim to examine how resting-state functional connectivity (RSFC) in adolescents is related to anhedonia and depression severity on a continuum in line with the research domain criteria (RDoC) approach.

METHODS

We examined how RSFC in the dorsal medial prefrontal cortex (dmPFC), nucleus accumbens (NAcc) and pregenual anterior cingulate cortex (pgACC) was related to anhedonia and depression severity in 86 adolescents (13-21 years).

RESULTS

We found both anhedonia and depression severity related to decreased dmPFC RSFC with the precuneus, a part of the default mode network. However we also found that increased dmPFC connectivity with the ACC/paracingulate gyrus related to anhedonia whereas increased RSFC with the frontal pole related to depression severity.

DISCUSSION

This work extends the view that the dmPFC is a potential therapeutic target for depression in two ways: 1. We report dmPFC connectivity in adolescents; and 2. We show different dmPFC RSFC specific to anhedonia and depression severity, providing neural targets for intervention in young people at risk of depression.

Global connectivity of the fronto-parietal cognitive control network is related to depression symptoms in the general population

We all vary in our mental health, even among people not meeting diagnostic criteria for mental illness. Understanding this individual variability may reveal factors driving the risk for mental illness, as well as factors driving subclinical problems that still adversely affect quality of life. To better understand the large-scale brain network mechanisms underlying this variability, we examined the relationship between mental health symptoms and resting-state functional connectivity patterns in cognitive control systems. One such system is the fronto-parietal cognitive control network (FPN). Changes in FPN connectivity may impact mental health by disrupting the ability to regulate symptoms in a goal-directed manner. Here we test the hypothesis that FPN dysconnectivity relates to mental health symptoms even among individuals who do not meet formal diagnostic criteria but may exhibit meaningful symptom variation. We found that depression symptoms severity negatively correlated with between-network global connectivity (BGC) of the FPN. This suggests that decreased connectivity between the FPN and the rest of the brain is related to increased depression symptoms in the general population. These findings complement previous clinical studies to support the hypothesis that global FPN connectivity contributes to the regulation of mental health symptoms across both health and disease.

Hormonal Cycles, Brain Network Connectivity, and Windows of Vulnerability to Affective Disorder

The rate of affective disorder is substantially higher in women than in men, and considerable evidence points to the actions of ovarian hormones in mediating this disparity. In this Opinion, we discuss the hypothesis that cyclic changes in ovarian hormone levels produce cyclic alterations in connectivity between the intrinsic networks of the brain. These alterations produce specific temporal windows within the menstrual cycle when internetwork connectivity is increased, associated with increased stress reactivity and better memory for unpleasant, arousing events, leading to increased negative mood and susceptibility to affective disorder. Our windows of vulnerability model offers insights for both treatment of affective disorder and research on sex differences in the brain.

Distinct neural correlates of trait resilience within core neurocognitive networks in at-risk children and adolescents

Background

Most children who are exposed to threat-related adversity (e.g., violence, abuse, neglect) are resilient - that is, they show stable trajectories of healthy psychological development. Despite this, most research on neurodevelopmental changes following adversity has focused on the neural correlates of negative outcomes, such as psychopathology. The neural correlates of trait resilience in pediatric populations are unknown, and it is unclear whether they are distinct from those related to adversity exposure and the absence of negative outcomes (e.g., depressive symptomology).

Methods

This functional magnetic resonance imaging (fMRI) study reports on a diverse sample of 55 children and adolescents (ages 6-17 years) recruited from a range of stressful environments (e.g., lower income, threat-related adversity exposure). Participants completed a multi-echo multi-band resting-state fMRI scan and self-report measures of trait resilience and emotion-related symptomology (e.g., depressive symptoms). Resting-state data were submitted to an independent component analysis (ICA) to identify core neurocognitive networks (salience and emotion network [SEN], default mode network [DMN], central executive network [CEN]). We tested for links among trait resilience and dynamic (i.e., time-varying) as well as conventional static (i.e., averaged across the entire session) resting-state functional connectivity (rsFC) of core neurocognitive networks.

Results

Youth with higher trait resilience spent a lower fraction of time in a particular dynamic rsFC state, characterized by heightened rsFC between the anterior DMN and right CEN. Within this state, trait resilience was associated with lower rsFC of the SEN with the right CEN and anterior DMN. There were no associations among trait resilience and conventional static rsFC. Importantly, although more resilient youth reported lower depressive symptoms, the effects of resilience on rsFC were independent of depressive symptoms and adversity exposure.

Conclusions

The present study is the first to report on the neural correlates of trait resilience in youth, and offers initial insight into potential adaptive patterns of brain organization in the context of environmental stressors. Understanding the neural dynamics underlying positive adaptation to early adversity will aid in the development of interventions that focus on strengthening resilience rather than mitigating already-present psychological problems.

A mind full of self: Self-referential processing as a mechanism underlying the therapeutic effects of mindfulness training on internalizing disorders

The aim of the current review is to advance the hypothesis that change in self-referential processing is a key but under-examined mechanism through which mindfulness training confers its therapeutic benefits for individuals with internalizing disorders. Consequently, we integrated neuroscientific studies on aberrant self-referential processing in internalizing disorders with contemplative science scholarship examining the effects of mindfulness training on the self-referential system. Reviewing these literatures yielded four major conclusions: (1) internalizing disorders can be characterized by excessive self-referential processing and emotion dysregulation; (2) mindfulness training has moderate effects on reducing internalizing symptoms; (3) mindfulness training promotes the shifting from narrative self-focus to present-centered experiential awareness; (4) such mindfulness-induced changes in self-reference is accompanied by reduced activation in overactive self-referential brain regions that have been implicated in internalizing disorders. Clinical and research implications related to delineating the role of self-referential processing in producing the therapeutic effects of mindfulness training are discussed.

The effects of serotonin modulation on medial prefrontal connectivity strength and stability: A pharmacological fMRI study with citalopram

BACKGROUND

Static and dynamic functional connectivity are being increasingly used to measure the effects of disease and a range of different interventions on brain networks. While preliminary evidence suggests that static connectivity can be modulated by chronic antidepressants administration in healthy individuals and in major depression, much less is known about the acute effects of antidepressants especially on dynamic functional connectivity changes. Here we examine acute effects of antidepressants on dynamic functional connectivity within the default mode network. The default mode network is a well described network with many functions in which the role of serotonin is not clear.

METHODS

In this work we measured acute pharmacological effects of an infusion of the selective serotonin reuptake inhibitor (SSRI) citalopram (10 mg) in a sample of thirteen healthy volunteers randomised to receive on two occasions the active compound or placebo in a cross over dosing.

RESULTS

Acute citalopram administration relative to placebo increased static connectivity between the medial prefrontal cortex and right dorsolateral prefrontal cortex and posterior cingulate cortex. The SSRI also induced a reduction in variability of connectivity with the medial prefrontal cortex in the precuneus and posterior cingulate cortex.

DISCUSSION

The measured changes are compatible with modified serotonin cortical availability.

Differential privacy-based evaporative cooling feature selection and classification with relief-F and random forests

Motivation

Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than the number of observations p≫n , these differential privacy methods are susceptible to overfitting.

Methods

We introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection.

Results

On simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder.

Availability and implementation

Code available at http://insilico.utulsa.edu/software/privateEC .

Contact

brett-mckinney@utulsa.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression

BACKGROUND

The subgenual anterior cingulate cortex (sgACC) has been implicated in major depressive disorder (MDD), and this study evaluated sgACC connectivity before and after repetitive transcranial magnetic stimulation (rTMS) treatment.

METHODS

Thirty-two MDD patients entered a sham-controlled, double-blinded, randomized trial of rTMS to the left dorsolateral prefrontal cortex (dlFPC). Subjects underwent resting state functional magnetic resonance imaging before and after 20 sessions of high frequency rTMS. Seed voxels identified the affective network (AN; sgACC, amygdala), default mode network (DMN; posterior cingulate cortex [PCC]), and fronto-parietal network (FPN; dlPFC stimulation site).

RESULTS

There was no significant effect of active rTMS over sham on the primary outcome measure (Montgomery-Asberg Depression Scale rating), with both groups improving over time, and no specific effect of rTMS (sham vs active) on connectivity. However, among patients who showed significant improvement, sgACC connectivity decreased for sham (to AN, trend to DMN) and active rTMS responders (to AN, DMN, FPN), but not in non-responders, who tended to maintain connectivity. Including subjects who started with sham but then received open-label active treatment, baseline connectivity from the PCC to the anterior insula was greater in non-responders compared to responders (n = 27, excluding 5 sham responders).

LIMITATIONS

The sample size was small; the stimulation target was non-standard, and the lack of a significant clinical effect of rTMS limits conclusions about negative findings.

CONCLUSIONS

sgACC connectivity reduces along with depressive symptoms, not specific to rTMS therapy. Altered connectivity of DMN with anterior insula may reflect a type of patient less likely to respond to an intervention.

Changing Brain Networks Through Non-invasive Neuromodulation

Background/Objective: Non-invasive neuromodulation techniques, such as repetitive Transcranial Magnetic Stimulation (rTMS) and transcranial Direct Current Stimulation (tDCS), have increasingly been investigated for their potential as treatments for neurological and psychiatric disorders. Despite widespread dissemination of these techniques, the underlying therapeutic mechanisms and the ideal stimulation site for a given disorder remain unknown. Increasing evidence support the possibility of non-invasive neuromodulation affecting a brain network rather than just the local stimulation target. In this article, we present evidence in a clinical setting to support the idea that non-invasive neuromodulation changes brain networks.

Method: This article addresses the idea that non-invasive neuromodulation modulates brain networks, rather than just the local stimulation target, using neuromodulation studies in tinnitus and major depression as examples. We present studies that support this hypothesis from different perspectives.

Main Results/Conclusion: Studies stimulating the same brain region, such as the dorsolateral prefrontal cortex (DLPFC), have shown to be effective for several disorders and studies using different stimulation sites for the same disorder have shown similar results. These findings, as well as results from studies investigating brain network connectivity on both macro and micro levels, suggest that non-invasive neuromodulation affects a brain network rather than just the local stimulation site targeted. We propose that non-invasive neuromodulation should be approached from a network perspective and emphasize the therapeutic potential of this approach through the modulation of targeted brain networks.

Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression

Hyperconnectivity of the default-mode network (DMN) is one of the most widely replicated neuroimaging findings in major depressive disorder (MDD). Further, there is growing evidence for a central role of the lateral habenula (LHb) in the pathophysiology of MDD. There is preliminary neuroimaging evidence linking LHb and the DMN, but no causal relationship has been shown to date. We combined optogenetics and functional magnetic resonance imaging (fMRI), to establish a causal relationship, using an animal model of treatment-resistant depression, namely Negative Cognitive State rats. First, an inhibitory light-sensitive ion channel was introduced into the LHb by viral transduction. Subsequently, laser stimulation was performed during fMRI acquisition on a 9.4 Tesla animal scanner. Neural activity and connectivity were assessed, before, during and after laser stimulation. We observed a connectivity decrease in the DMN following laser-induced LHb perturbation. Our data indicate a causal link between LHb downregulation and reduction in DMN connectivity. These findings may advance our mechanistic understanding of LHb inhibition, which had previously been identified as a promising therapeutic principle, especially for treatment-resistant depression.

Multiple cortical thickness sub-networks and cognitive impairments in first episode, drug naïve patients with late life depression: A graph theory analysis

BACKGROUND

Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD.

METHODS

In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity.

RESULTS

We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula.

LIMITATIONS

We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus.

CONCLUSION

We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD.

Functional Connectivity Between Anterior Insula and Key Nodes of Frontoparietal Executive Control and Salience Networks Distinguish Bipolar Depression From Unipolar Depression and Healthy Control Subjects

BACKGROUND

Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment.

METHODS

Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity.

RESULTS

Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula-inferior parietal lobule connectivity significantly discriminated patients with bipolar depression.

CONCLUSIONS

Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar disorder, exhibiting reasonable sensitivity and specificity.

Orbital and Medial Prefrontal Cortex Functional Connectivity of Major Depression Vulnerability and Disease

BACKGROUND

Pathophysiology models of major depression (MD) center on the dysfunction of various cortical areas within the orbital and medial prefrontal cortex. While independent structural and functional abnormalities in these areas are consistent findings in MD, the complex interactions among them and the rest of the cortex remain largely unexplored.

METHODS

We used resting-state functional magnetic resonance imaging connectivity to systematically map alterations in the communication between orbital and medial prefrontal cortex fields and the rest of the brain in MD. Functional connectivity (FC) maps from participants with current MD (n = 35), unaffected first-degree relatives (n = 36), and healthy control subjects (n = 38) were subjected to conjunction analyses to distinguish FC markers of MD vulnerability and FC markers of MD disease.

RESULTS

FC abnormalities in MD vulnerability were found for dorsal medial wall regions and the anterior insula and concerned altered communication of these areas with the inferior parietal cortex and dorsal posterior cingulate, occipital areas and the brainstem. FC aberrations in current MD included the anterior insula, rostral and dorsal anterior cingulate cortex, and lateral orbitofrontal areas and concerned altered communication with the dorsal striatum, the cerebellum, the precuneus, the anterior prefrontal cortex, somatomotor cortex, dorsolateral prefrontal cortex, and visual areas in the occipital and inferior temporal lobes.

CONCLUSIONS

Functionally delineated parcellation maps can be used to identify putative connectivity markers in extended cortical regions such as the orbital and medial prefrontal cortex. The anterior insula and the rostral anterior cingulate cortex play a central role in the pathophysiology of MD, being consistently implicated both in the MD vulnerability and MD disease states.

Altered Resting State Effective Connectivity of Anterior Insula in Depression

Depression has been associated with changes in both functional and effective connectivity of large scale brain networks, including the default mode network, executive network, and salience network. However, studies of effective connectivity by means of spectral dynamic causal modeling (spDCM) are still rare and the interaction between the different resting state networks has not been investigated in detail. Thus, we aimed at exploring differences in effective connectivity among eight right hemisphere brain areas-anterior insula, inferior frontal gyrus, middle frontal gyrus (MFG), frontal eye field, anterior cingulate cortex, superior parietal lobe, amygdala, and hippocampus, between a group of healthy controls (N = 20) and medicated depressed patients (N = 20). We found that patients not only had significantly reduced strength of the connection from the anterior insula to the MFG (i.e., dorsolateral prefrontal cortex) but also a significant connection between the amygdala and the anterior insula. Moreover, depression severity correlated with connectivity of the hippocampal node. In conclusion, the results from this resting state spDCM study support and enrich previous data on the role of the right anterior insula in the pathophysiology of depression. Furthermore, our findings add to the growing evidence of an association between depression severity and disturbances of the hippocampal function in terms of impaired connectivity with other brain regions.

Neuroimaging Correlates of Resilience to Traumatic Events-A Comprehensive Review

Improved understanding of the neurobiological correlates of resilience would be an important step toward recognizing individuals at risk of developing post-traumatic stress disorder (PTSD) or other trauma-related diseases, enabling both preventative measures and individually tailored therapeutic approaches. Studies on vulnerability factors allow drawing conclusions on resilience. Structural changes of cortical and subcortical structures, as well as alterations in functional connectivity and functional activity, have been demonstrated to occur in individuals with PTSD symptoms. Relevant areas of interest are hippocampus, amygdala, insula, anterior cingulate cortex, and prefrontal cortex, as well as related brain networks, such as the default-mode, salience, and central executive network. This review summarizes the existing literature and integrates findings from cross-sectional study designs with two-group designs (trauma exposed individuals with and without PTSD), three-group designs (with an additional group of unexposed, healthy controls), twin-studies and longitudinal studies. In terms of structural findings, decreased hippocampal volume in PTSD individuals might be either a vulnerability factor or a result of trauma exposure, or both. Reduced anterior cingulate cortex and prefrontal cortex volumes seem to be predisposing factors for increased vulnerability. Regarding functional connectivity, increased amygdala connectivity has been demonstrated selectively in PTSD individuals, as well as increased default-mode-network and salience network connectivity. In terms of functional activity, increased amygdala and anterior cingulate cortex activities, and decreased prefrontal cortex activity as a response to external stimuli have been associated with higher vulnerability. Increased prefrontal cortex activity seemed to be a protective factor. Selecting adequate study designs, optimizing the diagnostic criteria, as well as differentiating between types of trauma and accounting for other factors, such as gender-specific differences, would be well-served in future research. Conclusions on potential preventative measures, as well as clinical applications, can be drawn from the present literature, but more studies are needed.

Integrated cross-network connectivity of amygdala, insula, and subgenual cingulate associated with facial emotion perception in healthy controls and remitted major depressive disorder

Emotion perception deficits could be due to disrupted connectivity of key nodes in the salience and emotion network (SEN), including the amygdala, subgenual anterior cingulate cortex (sgACC), and insula. We examined SEN resting-state (rs-)fMRI connectivity in rMDD in relation to Facial Emotion Perception Test (FEPT) performance. Fifty-two medication-free people ages 18 to 23 years participated. Twenty-seven had major depressive disorder (MDD) in remission (rMDD, 10 males), as MDD is associated with emotion perception deficits and alterations in rsfMRI. Twenty-five healthy controls (10 males) also participated. Participants completed the FEPT during fMRI, in addition to an 8-minute eyes-open resting-state scan. Seed regions of interest were defined in the amygdala, anterior insula and sgACC. Multiple regression analyses co-varied diagnostic group, sex and movement parameters. Emotion perception accuracy was positively associated with connectivity between amygdala seeds and regions primarily in the SEN and cognitive control network (CCN), and also the default mode network (DMN). Accuracy was also positively associated with connectivity between the sgACC seeds and other SEN regions, and the DMN, particularly for the right sgACC. Connectivity negatively associated with emotion perception was mostly with regions outside of these three networks, other than the left insula and part of the DMN. This study is the first to our knowledge to demonstrate relationships between facial emotion processing and resting-state connectivity with SEN nodes and between SEN nodes and regions located within other neural networks.

Mindfulness and dynamic functional neural connectivity in children and adolescents

BACKGROUND

Interventions that promote mindfulness consistently show salutary effects on cognition and emotional wellbeing in adults, and more recently, in children and adolescents. However, we lack understanding of the neurobiological mechanisms underlying mindfulness in youth that should allow for more judicious application of these interventions in clinical and educational settings.

METHODS

Using multi-echo multi-band fMRI, we examined dynamic (i.e., time-varying) and conventional static resting-state connectivity between core neurocognitive networks (i.e., salience/emotion, default mode, central executive) in 42 children and adolescents (ages 6-17).

RESULTS

We found that trait mindfulness in youth relates to dynamic but not static resting-state connectivity. Specifically, more mindful youth transitioned more between brain states over the course of the scan, spent overall less time in a certain connectivity state, and showed a state-specific reduction in connectivity between salience/emotion and central executive networks. The number of state transitions mediated the link between higher mindfulness and lower anxiety, providing new insights into potential neural mechanisms underlying benefits of mindfulness on psychological health in youth.

CONCLUSIONS

Our results provide new evidence that mindfulness in youth relates to functional neural dynamics and interactions between neurocognitive networks, over time.

Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research

The alterations of functional connectivity brain networks in major depressive disorder (MDD) have been subject of a large number of studies. Using different methodologies and focusing on diverse aspects of the disease, research shows heterogeneous results lacking integration. Disrupted network connectivity has been found in core MDD networks like the default mode network (DMN), the central executive network (CEN), and the salience network, but also in cerebellar and thalamic circuitries. Here we review literature published on resting state brain network function in MDD focusing on methodology, and clinical characteristics including symptomatology and antidepressant treatment related findings. There are relatively few investigations concerning the qualitative aspects of symptomatology of MDD, whereas most studies associate quantitative aspects with distinct resting state functional connectivity alterations. Such depression severity associated alterations are found in the DMN, frontal, cerebellar and thalamic brain regions as well as the insula and the subgenual anterior cingulate cortex. Similarly, different therapeutical options in MDD and their effects on brain function showed patchy results. Herein, pharmaceutical treatments reveal functional connectivity alterations throughout multiple brain regions notably the DMN, fronto-limbic, and parieto-temporal regions. Psychotherapeutical interventions show significant functional connectivity alterations in fronto-limbic networks, whereas electroconvulsive therapy and repetitive transcranial magnetic stimulation result in alterations of the subgenual anterior cingulate cortex, the DMN, the CEN and the dorsal lateral prefrontal cortex. While it appears clear that functional connectivity alterations are associated with the pathophysiology and treatment of MDD, future research should also generate a common strategy for data acquisition and analysis, as a least common denominator, to set the basis for comparability across studies and implementation of functional connectivity as a scientifically and clinically useful biomarker.

Nicotine and networks: Potential for enhancement of mood and cognition in late-life depression

Late-life depression is characterized by both lower mood and poor cognitive performance, symptoms that often do not fully respond to current antidepressant medications. Nicotinic acetylcholine receptor (nAChR) agonists such as nicotine may serve as a novel therapeutic approach for this population. Both preclinical and preliminary clinical studies suggest that nAChR agonists can improve depressive behavior in animal models and improve mood in depressed individuals. Substantial literature also supports that nAChR agonists benefit cognitive performance, particularly in older populations. These potential benefits may be mediated by the effects of nAChR stimulation on neural network function and connectivity. Functional neuroimaging studies detail effects of nAChR agonists on the default mode network, central-executive network, and salience network that may oppose or reverse network changes seen in depression. We propose that, given the existent literature and the clinical presentation of late-life depression, nicotine or other nAChR agonists may have unique therapeutic benefits in this population and that clinical trials examining nicotine effects on mood, cognition, and network dynamics in late-life depression are justified.

Abnormal functional connectivity within resting-state networks is related to rTMS-based therapy effects of treatment resistant depression: A pilot study

BACKGROUND

Treatment resistant depression (TRD) remains a clinical challenge, and finding biomarkers that predict treatment response are a long sought goal to precisely indicate treatments. This pilot study aims to characterize brain dysfunction in TRD patients who underwent rTMS to define neuroimaging biomarkers that discriminate non-responders (NR) from responders (R).

METHODS

20 TRD patients who underwent a course of rTMS to the left DLPFC were categorized into R and NR groups based on a >50% reduction in HRSD scores. Utilizing resting-state fMRI and ICA techniques, this study compared baseline RSNs of R vs. NR as well as TRD vs. healthy volunteer group. Regression analysis was conducted to link regions with clinical improvements. ROC analysis was further conducted to confirm the utility of the identified regions in classifying the patients.

RESULTS

Prior to treatment, non-responders displayed hyper-connectivity in ACC/VMPFC, PCC/pC, dACC and insula within RSNs that have been associated with MDD pathology. Regression results showed that regions associated with clinical improvements overlapped largely with regions that showed aberrant connectivity. ACC/VMPFC, dACC and left insula, which are hub regions of DMN and SN, exhibited excellent performance (highest sensitivity=100% and highest specificity=82%) in discriminating the response status of the patients.

LIMITATIONS

Relatively small sample size.

CONCLUSIONS

Our findings provide insight into fMRI predictive measures of treatment response to rTMS treatment, and demonstrate the potential of RSNs-based biomarkers in predicting response to rTMS treatment. Future studies are needed to validate the application of these measures to inform individual treatment indications.

Abnormal resting state effective connectivity within the default mode network in major depressive disorder: A spectral dynamic causal modeling study

INTRODUCTION

Understanding the neural basis underlying major depressive disorder (MDD) is essential for the diagnosis and treatment of this mental disorder. Aberrant activation and functional connectivity of the default mode network (DMN) have been consistently found in patients with MDD. It is not known whether effective connectivity within the DMN is altered in MDD.

OBJECTS

The primary object of this study is to investigate the effective connectivity within the DMN during resting state in MDD patients before and after eight weeks of antidepressant treatment.

METHODS

We defined four regions of the DMN (medial frontal cortex, posterior cingulate cortex, left parietal cortex, and right parietal cortex) for each participant using a group independent component analysis. The coupling parameters reflecting the causal interactions among the DMN regions were estimated using spectral dynamic causal modeling (DCM).

RESULTS

Twenty-seven MDD patients and 27 healthy controls were included in the statistical analysis. Our results showed declined influences from the left parietal cortex to other DMN regions in the pre-treatment patients as compared with healthy controls. After eight weeks of treatment, the influence from the right parietal cortex to the posterior cingulate cortex significantly decreased.

CONCLUSION

These findings suggest that the reduced excitatory causal influence of the left parietal cortex is the key alteration of the DMN in patients with MDD, and the disrupted causal influences that parietal cortex exerts on the posterior cingulate cortex is responsive to antidepressant treatment.

Neural Correlates of Outcome of the Psychotherapy Compared to Antidepressant Therapy in Anxiety and Depression Disorders: A Meta-Analysis

The most prevalent mental disorders, anxiety and depression, are commonly associated with structural and functional changes in the fronto-limbic brain areas. The clinical trials investigating patients with affective disorders showed different outcome to different treatments such as psychotherapy or pharmacotherapy. It is, however, still unexplored how these interventions approach affect the functional brain. This meta-analysis aims to compare the effects of psychotherapy compared to antidepressant therapy on functional brain activity in anxiety and depression disorders. Twenty-one samples with psychotherapy and seventeen samples with antidepressant therapy were included. The main finding showed an inverse effect of the two treatments on the right paracingulate activity. The patients undergoing psychotherapy showed an increase in the right paracingulate activity while pharmacological treatment led to a decrease of activation of this area. This finding seems to support the recent studies that hypothesize how psychotherapy, through the self-knowledge and the meaning processing, involves a top-down emotional regulation.