Changes in brain connectivity related to the treatment of depression measured through fMRI: a systematic review

Effects of oral contraceptive pills on brain networks: A replication and extension

Neuroimaging research has identified significant effects of oral contraceptive pills (OCPs) on brain networks. A wide variety of approaches have been employed, largely in observational samples, with few converging results. This study therefore was designed to test for replication and extend this previous work using a randomized, double-blind, placebo-controlled crossover trial of the effects of OCPs on brain networks. Using functional MRI, we focused on brain regions identified in prior studies. Our analyses did not strictly replicate previously reported effects of OCPs on functional connectivity. Exploratory analyses suggested that traditional seed-based approaches may miss broader, network-level effects of OCPs on brain circuits. We applied data-driven, multivariate techniques to assess these network-level changes, A deeper understanding of neural effects of OCPs can be important in helping patients make informed decisions regarding contraception, mitigating unwanted side effects. Such information can also identify potentially confounding effects of OCPs in other neuroimaging investigations.

Interaction of the gut microbiota and brain functional connectivity in late-life depression

BACKGROUND

Increasing evidence suggests an important role of the gut microbiome in the pathogenesis of mental disorders, including depression, along the microbiota-gut-brain axis. We sought to explore the interactions between gut microbe composition and neural circuits in late-life depression (LLD).

METHODS

We performed fecal 16S ribosomal RNA (rRNA) sequencing and resting-state functional magnetic resonance imaging in a case-control cohort of older adults with LLD and healthy controls to characterize the association between gut microbiota and brain functional connectivity (FC). We used the Hamilton Depression Rating Scale (HAMD) to assess depressive symptoms.

RESULTS

We included 32 adults with LLD and 16 healthy controls. At the genus level, the relative abundance of Enterobacter, Akkermansiaceae, Hemophilus, Burkholderia, and Rothia was significantly higher among patients with LDD than controls. Reduced FC within mood regulation circuits was mainly found in the frontal cortex (e.g., the right superior and inferior frontal gyrus, right lateral occipital cortex, left middle frontal gyrus, and left caudate) among patients with MDD. Group-characterized gut microbes among controls and patients showed opposite correlations with seed-based FC, which may account for the aberrant emotion regulation among patients with LDD. The abundance of Enterobacter (dominant genus among patients with LLD) was positively correlated with both HAMD scores (r = 0.49, p = 0.0004) and group-characterized FC (r = -0.37, p < 0.05), while Odoribacter (dominant genus among controls) was negatively correlated with both HAMD scores (r = -0.30, p = 0.04) and group-characterized FC.

LIMITATIONS

The study's cross-sectional design and small sample size limit causal inferences; larger longitudinal studies are required for detailed subgroup analyses.

CONCLUSION

We identified significant correlations between LDD-characterized gut microbes and brain FC, as well as depression severity, which may contribute to the pathophysiology of depression development among patients with LLD. Specific microbes were linked to altered brain connectivity, suggesting potential targets for treating LLD.

Effect of Low-Intensity Transcranial Focused Ultrasound Stimulation in Patients With Major Depressive Disorder: A Randomized, Double-Blind, Sham-Controlled Clinical Trial

OBJECTIVE

Low-intensity transcranial focused ultrasound (tFUS) has emerged as a promising non-invasive brain stimulation modality with high spatial selectivity and the ability to reach deep brain areas. The present study aimed to investigate the safety and effectiveness of low-intensity tFUS in treating major depressive disorder.

METHODS

Participants were recruited in an outpatient clinic and randomly assigned to either the verum tFUS or sham stimulation group. The intervention group received six sessions of tFUS stimulation to the left dorsolateral prefrontal cortex over two weeks. Neuropsychological assessments were conducted before and after the sessions. Resting-state functional magnetic resonance imaging (rsfMRI) was also performed to evaluate changes in functional connectivity (FC). The primary outcome measure was the change in depressive symptoms, assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS).

RESULTS

The tFUS stimulation sessions were well tolerated without any undesirable side effects. The analysis revealed a significant main effect of session sequence on the MADRS scores and significant interactions between the session sequences and groups. The rsfMRI analysis showed a higher FC correlation between the right superior part of the subgenual anterior cingulate cortex (sgACC) and several other brain regions in the verum group compared with the sham group.

CONCLUSION

Our results reveal that tFUS stimulation clinically improved MADRS scores with network-level modulation of a sgACC subregion. This randomized, sham-controlled clinical trial, the first study of its kind, demonstrated the safety and probable efficacy of tFUS stimulation for the treatment of depression.

Effects of antidepressants on brain structure and function in patients with obsessive-compulsive disorder: A review of neuroimaging studies

Obsessive-compulsive disorder (OCD) affects 2-3% of people worldwide. Although antidepressants are the standard pharmachological treatment of OCD, their effect on the brain of individuals with OCD has not yet been fully clarified. We conducted a systematic search on PubMed, Scopus, Embase, and Web of Science to explore the effects of antidepressants on neuroimaging findings in OCD. Thirteen neuroimaging investigations were included. After antidepressant treatment, structural magnetic resonance imaging studies suggested thalamic, amygdala, and pituitary volume changes in patients. In addition, the use of antidepressants was associated with alterations in diffusion tensor imaging metrics in the left striatum, the right midbrain, and the posterior thalamic radiation in the right parietal lobe. Finally, functional magnetic resonance imaging highlighted possible changes in the ventral striatum, frontal, and prefrontal cortex. The small number of included studies and sample sizes, short durations of follow-up, different antidepressants, variable regions of interest, and heterogeneous samples limit the robustness of the findings of the present review. In conclusion, our review suggests that antidepressant treatment is associated with brain changes in individuals with OCD, and these results may help to deepen our knowledge of the pathophysiology of OCD and the brain mechanisms underlying the effects of antidepressants.

Altered long-range functional connectivity in PTSD: Role of the infraslow oscillations of cortical activity amplitude envelopes

OBJECTIVE

Coupling between the amplitude envelopes (AEs) of regional cortical activity reflects mechanisms that coordinate the excitability of large-scale cortical networks. We used resting-state MEG recordings to investigate the association between alterations in the coupling of cortical AEs and symptoms of post-traumatic stress disorder (PTSD).

METHODS

Participants (n = 96) were service members with combat exposure and various levels of post-traumatic stress severity (PTSS). We assessed the correlation between PTSS and (1) coupling of broadband cortical AEs of beta band activity, (2) coupling of the low- (<0.5 Hz) and high-frequency (>0.5 Hz) components of the AEs, and (3) their time-varying patterns.

RESULTS

PTSS was associated with widespread hypoconnectivity assessed from the broadband AE fluctuations, which correlated with subscores for the negative thoughts and feelings/emotional numbing (NTF/EN) and hyperarousal clusters of symptoms. Higher NTF/EN scores were also associated with smaller increases in resting-state functional connectivity (rsFC) with time during the recordings. The distinct patterns of rsFC in PTSD were primarily due to differences in the coupling of low-frequency (infraslow) fluctuations of the AEs of beta band activity.

CONCLUSIONS

Our findings implicate the mechanisms underlying the regulation/coupling of infraslow oscillations in the alterations of rsFC assessed from broadband AEs and in PTSD symptomatology.

SIGNIFICANCE

Altered coordination of infraslow amplitude fluctuations across large-scale cortical networks can contribute to network dysfunction and may provide a target for treatment in PTSD.

Structure-function coupling and hierarchy-specific antidepressant response in major depressive disorder

BACKGROUND

Extensive research has explored altered structural and functional networks in major depressive disorder (MDD). However, studies examining the relationships between structure and function yielded heterogeneous and inconclusive results. Recent work has suggested that the structure-function relationship is not uniform throughout the brain but varies across different levels of functional hierarchy. This study aims to investigate changes in structure-function couplings (SFC) and their relevance to antidepressant response in MDD from a functional hierarchical perspective.

METHODS

We compared regional SFC between individuals with MDD (n = 258) and healthy controls (HC, n = 99) using resting-state functional magnetic resonance imaging and diffusion tensor imaging. We also compared antidepressant non-responders (n = 55) and responders (n = 68, defined by a reduction in depressive severity of >50%). To evaluate variations in altered and response-associated SFC across the functional hierarchy, we ranked significantly different regions by their principal gradient values and assessed patterns of increase or decrease along the gradient axis. The principal gradient value, calculated from 219 healthy individuals in the Human Connectome Project, represents a region's position along the principal gradient axis.

RESULTS

Compared to HC, MDD patients exhibited increased SFC in unimodal regions (lower principal gradient) and decreased SFC in transmodal regions (higher principal gradient) (p < 0.001). Responders primarily had higher SFC in unimodal regions and lower SFC in attentional networks (median principal gradient) (p < 0.001).

CONCLUSIONS

Our findings reveal opposing SFC alterations in low-level unimodal and high-level transmodal networks, underscoring spatial variability in MDD pathology. Moreover, hierarchy-specific antidepressant effects provide valuable insights into predicting treatment outcomes.

Large Individual Differences in Functional Connectivity in the Context of Major Depression and Antidepressant Pharmacotherapy

Clinical studies of major depression (MD) generally focus on group effects, yet interindividual differences in brain function are increasingly recognized as important and may even impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g., related to MD diagnosis and treatment response). Functional MRI data from 107 participants (63 female, 44 male) were collected at baseline, 2, and 8 weeks during which patients received pharmacotherapy (escitalopram, N = 68) and controls (N = 39) received no intervention. The unique contributions of different sources of variation were examined by calculating how much variance in functional connectivity was shared across all participants and sessions, within/across groups (patients vs controls, responders vs nonresponders, female vs male participants), recording sessions, and individuals. Individual differences and common connectivity across groups, sessions, and participants contributed most to the explained variance (>95% across analyses). Group differences related to MD diagnosis, treatment response, and biological sex made significant but small contributions (0.3-1.2%). High individual variation was present in cognitive control and attention areas, while low individual variation characterized primary sensorimotor regions. Group differences were much smaller than individual differences in the context of MD and its treatment. These results could be linked to the variable findings and difficulty translating research on MD to clinical practice. Future research should examine brain features with low and high individual variation in relation to psychiatric symptoms and treatment trajectories to explore the clinical relevance of the individual differences identified here.

Pharmacological and computational analysis of the involvement of the 5-HT4 receptor in the antidepressant-like effect of N-(3-(phenylselanyl)prop-2-yn-1-yl)benzamide in mice

The serotonin type 4 receptor (5-HT4R)shows promise as a target for treating major depressive disorder (MDD). Studies have demonstrated that 5-HT4R agonists have a faster antidepressant-like effect compared to conventional medications. Developing drugs that modulate this receptor could lead to faster and more effective MDD treatments. The compound N-(3-(phenylselanyl)prop-2-yn-1-yl)benzamide (SePB) induces an antidepressant-like effect in mice. The present study explored if the 5-HT4R mediates SePB's antidepressant effect. For this, male Swiss mice were treated with GR113808 (0.1 mg/kg, intraperitoneally - i.p.), a 5-HT4R antagonist, and SePB (10 mg/kg, intragastrically - i.g), and then subjected to the tail-suspension test (TST) and open-field test (OFT). In silico tests were conducted to analyze SePB's binding affinity to the 5-HT4R and identify participating amino acid residues. The administration of GR113808 blocked the antidepressant-like effect of SePB in the TST without changing locomotor activity in the OFT. Moreover, SePB exhibited a high binding affinity between the 5-HT4R (-7.9 kcal/mol) and the amino acid residues Leu298, Asp100, Thr97, Arg96, Glu80, Leu81, Cys184, Val185, and Phe186 seem to be important for this interaction. The involvement of the 5-HT4R in the antidepressant-like effect of SePB suggests potential for novel therapies in MDD.

Functional connectivity changes between amygdala and prefrontal cortex after ECT are associated with improvement in distinct depressive symptoms

Electroconvulsive therapy (ECT) is one of the most effective treatments for treatment-resistant depression. However, the underlying mechanisms of action are not yet fully understood. The investigation of depression-specific networks using resting-state fMRI and the relation to differential symptom improvement might be an innovative approach providing new insights into the underlying processes. In this naturalistic study, we investigated the relationship between changes in resting-state functional connectivity (rsFC) and symptom improvement after ECT in 21 patients with treatment-resistant depression. We investigated rsFC before and after ECT and focused our analyses on FC changes directly related to symptom reduction and on FC at baseline to identify neural targets that might predict individual clinical responses to ECT. Additional analyses were performed to identify the direct relationship between rsFC change and symptom dimensions such as sadness, negative thoughts, detachment, and neurovegetative symptoms. An increase in rsFC between the left amygdala and left dorsolateral prefrontal cortex (DLPFC) after ECT was related to overall symptom reduction (Bonferroni-corrected p = 0.033) as well as to a reduction in specific symptoms such as sadness (r = 0.524, uncorrected p = 0.014), negative thoughts (r = 0.700, Bonferroni-corrected p = 0.002) and detachment (r = 0.663, p = 0.004), but not in neurovegetative symptoms. Furthermore, high baseline rsFC between the left amygdala and the right frontal pole (FP) predicted treatment outcome (uncorrected p = 0.039). We conclude that changes in FC in regions of the limbic-prefrontal network are associated with symptom improvement, particularly in affective and cognitive dimensions. Frontal-limbic connectivity has the potential to predict symptom improvement after ECT. Further research combining functional imaging biomarkers and a symptom-based approach might be promising.

An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank

Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Neuroimaging-Derived Biomarkers of the Antidepressant Effects of Ketamine

Major depressive disorder is a highly prevalent psychiatric disorder. Despite an extensive range of treatment options, about a third of patients still struggle to respond to available therapies. In the last 20 years, ketamine has gained considerable attention in the psychiatric field as a promising treatment of depression, particularly in patients who are treatment resistant or at high risk for suicide. At a subanesthetic dose, ketamine produces a rapid and pronounced reduction in depressive symptoms and suicidal ideation, and serial treatment appears to produce a greater and more sustained therapeutic response. However, the mechanism driving ketamine's antidepressant effects is not yet well understood. Biomarker discovery may advance knowledge of ketamine's antidepressant action, which could in turn translate to more personalized and effective treatment strategies. At the brain systems level, neuroimaging can be used to identify functional pathways and networks contributing to ketamine's therapeutic effects by studying how it alters brain structure, function, connectivity, and metabolism. In this review, we summarize and appraise recent work in this area, including 51 articles that use resting-state and task-based functional magnetic resonance imaging, arterial spin labeling, positron emission tomography, structural magnetic resonance imaging, diffusion magnetic resonance imaging, or magnetic resonance spectroscopy to study brain and clinical changes 24 hours or longer after ketamine treatment in populations with unipolar or bipolar depression. Though individual studies have included relatively small samples, used different methodological approaches, and reported disparate regional findings, converging evidence supports that ketamine leads to neuroplasticity in structural and functional brain networks that contribute to or are relevant to its antidepressant effects.

Shared and Unique Changes in Brain Connectivity Among Depressed Patients After Remission With Pharmacotherapy Versus Psychotherapy

OBJECTIVE

The authors sought to determine the shared and unique changes in brain resting-state functional connectivity (rsFC) between patients with major depressive disorder who achieved remission with cognitive-behavioral therapy (CBT) or with antidepressant medication.

METHODS

The Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) trial randomized adults with treatment-naive major depressive disorder to 12 weeks of treatment with CBT (16 1-hour sessions) or medication (duloxetine 30-60 mg/day or escitalopram 10-20 mg/day). Resting-state functional MRI scans were performed at baseline and at week 12. The primary outcome was change in the whole-brain rsFC of four seeded brain networks among participants who achieved remission.

RESULTS

Of the 131 completers with usable MRI data (74 female; mean age, 39.8 years), remission was achieved by 19 of 40 CBT-treated and 45 of 91 medication-treated patients. Three patterns of connectivity changes were observed. First, those who remitted with either treatment shared a pattern of reduction in rsFC between the subcallosal cingulate cortex and the motor cortex. Second, reciprocal rsFC changes were observed across multiple networks, primarily increases in CBT remitters and decreases in medication remitters. And third, in CBT remitters only, rsFC increased within the executive control network and between the executive control network and parietal attention regions.

CONCLUSIONS

Remission from major depression via treatment with CBT or medication is associated with changes in rsFC that are mostly specific to the treatment modality, providing biological support for the clinical practice of switching between or combining these treatment approaches. Medication is associated with broadly inhibitory effects. In CBT remitters, the increase in rsFC strength between networks involved in cognitive control and attention provides biological support for the theorized mechanism of CBT. Reducing affective network connectivity with motor systems is a shared process important for remission with both CBT and medication.

The update of self-identity: Importance of assessing autobiographical memory in major depressive disorder

Major depressive disorder is a leading global cause of disability. There is a growing interest for memory in mood disorders since it might constitute an original tool for prevention, diagnosis, and treatment. MDD is associated with impaired autobiographical memory characterized by a tendency to overgeneral memory, rather than vivid episodic self-defining memory, which is mandatory for problem-solving and projection in the future. This memory bias is maintained by three mechanisms: ruminations, avoidance, and impaired executive control. If we adopt a broader and comprehensive perspective, we can hypothesize that all those alterations have the potential to impair self-identity updating. We posit that this update requires a double referencing process: (1) to internalized self-representation and (2) to an externalized framework dealing with the representation of the consequence of actions. Diagnostic and therapeutic implications are discussed in the light of this model and the importance of assessing autobiographical memory in MDD is highlighted. This article is categorized under: Psychology > Memory Psychology > Brain Function and Dysfunction Neuroscience > Clinical.

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.

Partly recovery and compensation in anterior cingulate cortex after SSRI treatment-evidence from multi-voxel pattern analysis over resting state fMRI in depression

BACKGROUND

Anterior cingulate cortex (ACC) plays an essential role in the pathophysiology of major depressive disorder (MDD) and its treatment. However, it's still unclear whether the effects of disease and antidepressant treatment on ACC perform diversely in neural mechanisms.

METHODS

Fifty-nine MDD patients completed resting-state fMRI scanning twice at baseline and after 12-week selective serotonin reuptake inhibitor (SSRI) treatment, respectively in acute state and remission state. Fifty-nine demographically matched healthy controls were enrolled. Using fractional amplitude of low-frequency fluctuation (fALFF) in ACC as features, we performed multi-voxel pattern analysis over pretreatment MDD patients vs health control (HC), and over pretreatment MDD patients vs posttreatment MDD patients.

RESULTS

Discriminative regions in ACC for MDD impairment and changes after antidepressants were obtained. The intersection set and difference set were calculated to form ACC subregions of recovered, unrecovered and compensative, respectively. The recovered ACC subregion mainly distributed in rostral ACC (80 %) and the other two subregions had nearly equal distribution over dorsal ACC and rostral ACC. Furthermore, only the compensative subregion had significant changed functional connectivity with cingulo-opercular control network (CON) after antidepressant treatment.

LIMITATIONS

The number of subjects was relatively small. The results need to be validated with larger sample sizes and multisite data.

CONCLUSIONS

This finding suggested that the local function of ACC was partly recovered on regulating emotion after antidepressant by detecting the common subregional targets of depression impairment and antidepressive effect. Besides, changed fALFF in the compensative ACC subregion and its connectivity with CON may partly compensate for the cognition deficits.

Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response

BACKGROUND

Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.

METHODS

The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.

RESULTS

Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.

CONCLUSIONS

Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

Communalistic use of psychoactive plants as a bridge between traditional healing practices and Western medicine: A new path for the Global Mental Health movement

The Global Mental Health (GMH) movement aims to provide urgently needed treatment to those with mental illness, especially in low- and middle-income countries. Due to the complexity of providing mental health services to people from various cultures, there is much debate among GMH advocates regarding the best way to proceed. While biomedical interventions offer some degree of help, complementary approaches should focus on the social/community aspects. Many cultures conduct traditional rituals involving the communal use of psychoactive plants. We propose that these practices should be respected, protected, and promoted as valuable tools with regard to mental health care at the community level. The traditional use of psychoactive plants promotes community engagement and participation, and they are relatively affordable. Furthermore, the worldviews and meaning-making systems of local population are respected. The medical systems surrounding the use of psychoactive plants can be explained in biomedical terms, and many recently published clinical trials have demonstrated their therapeutic potential. Psychoactive plants and associated rituals offer potential benefits as complementary aspects of mental health services. They should be considered as such by international practitioners and advocates of the GMH movement.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the "limbic," the "associative," and the "motor" subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Antidepressants combined with psychodrama improve the coping style and cognitive control network in patients with childhood trauma-associated major depressive disorder

BACKGROUND

The use of antidepressant therapy alone has a limited efficacy in patients with childhood trauma-associated major depressive disorder (MDD). However, the effectiveness of antidepressant treatment combined with psychodrama in these patients is unclear.

AIM

To evaluate the effectiveness of antidepressant treatment combined with psychodrama.

METHODS

Patients with childhood trauma-associated MDD treated with antidepressants were randomly assigned to either the psychodrama intervention (observation group) or the general health education intervention (control group) and received combination treatment for 6 mo. The observation group received general health education given by the investigator together with the “semi-structured group intervention model” of Yi Shu psychodrama. A total of 46 patients were recruited, including 29 cases in the observation group and 17 cases in the control group. Symptoms of depression and anxiety as well as coping style and resting-state functional magnetic resonance imaging were assessed before and after the intervention.

RESULTS

Symptoms of depression and anxiety, measured by the Hamilton Depression Scale, Beck Depression Inventory, and Beck Anxiety Inventory, were reduced after the intervention in both groups of patients. The coping style of the observation group improved significantly in contrast to the control group, which did not. In addition, an interaction between treatment and time in the right superior parietal gyrus node was found. Furthermore, functional connectivity between the right superior parietal gyrus and left inferior frontal gyrus in the observation group increased after the intervention, while in the control group the connectivity decreased.

CONCLUSION

This study supports the use of combined treatment with antidepressants and psychodrama to improve the coping style of patients with childhood trauma-associated MDD. Functional connectivity between the superior parietal gyrus and inferior frontal gyrus was increased after this combined treatment. We speculate that psychodrama enhances the internal connectivity of the cognitive control network and corrects the negative attention bias of patients with childhood trauma-associated MDD. Elucidating the neurobiological features of patients with childhood trauma-associated MDD is important for the development of methods that can assist in early diagnosis and intervention.

Common network effect-patterns after monoamine reuptake inhibition in dissociated hippocampus cultures

The pharmacological treatment of major depressive disorder with currently available antidepressant drugs is still unsatisfying as response to medication is delayed and in some patients even non-existent. To understand complex psychiatric diseases such as major depressive disorder and their treatment, research focus is shifting from investigating single neurons towards a view of the entire functional and effective neuronal network, because alterations on single synapses through antidepressant drugs may translate to alterations in the entire network. Here, we examined the effects of monoamine reuptake inhibitors on in vitro hippocampal network dynamics using calcium fluorescence imaging and analyzing the data with means of graph theoretical parameters. Hypothesizing that monoamine reuptake inhibitors operate through changes of effective connectivity on micro-scale neuronal networks, we measured the effects of the selective monoamine reuptake inhibitors GBR-12783, Sertraline, Venlafaxine, and Amitriptyline on neuronal networks. We identified a common pattern of effects of the different tested monoamine reuptake inhibitors. After treatment with GBR-12783, Sertraline, and Venlafaxine, the connectivity degree, measuring the number of existing connections in the network, was significantly decreased. All tested substances led to networks with more submodules and a reduced global efficiency. No monoamine reuptake inhibitor did affect network-wide firing rate, the characteristic path length, or the network strength. In our study, we found that monoamine reuptake inhibition in neuronal networks in vitro results in a sharpening of the network structure. These alterations could be the basis for the reorganization of a large-scale miswired network in major depressive disorder.

A Functional Near-Infrared Spectroscopy Examination of the Neural Correlates of Mental Rotation for Individuals With Different Depressive Tendencies

The present study aimed to examine the neural mechanisms underlying the ability to process the mental rotation with mirrored stimuli for different depressive tendencies with psychomotor retardation. Using functional near-infrared spectroscopy (fNIRS), we measured brain cortex activation of participants with higher and lower depressive tendencies while performing a left-right paradigm of object mental rotation or a same-different paradigm of subject mental rotation. Behavioral data revealed no differences in reaction time and rotation speed. The fNIRS data revealed a higher deactivation of oxyhemoglobin (HbO) change for the higher depression group in the perceptual stage of object mental rotation with mirrored stimuli in the superior external frontal cortex (BA46), inferior frontal gyrus (BA45), premotor cortex (BA6), and primary motor cortex (BA4) (study 1). In addition, there existed a significant difference between the two groups in premotor cortex (BA6) in subject mental rotation with mirrored stimuli (study 2). These results suggest that the neural mechanism of higher depression individuals connected with psychomotor retardation exists in the frontal and motor areas when processing object mental rotation with mirrored stimuli, and the motor cortex when processing subject mental rotation.

Predicting treatment selections for individuals with major depressive disorder according to functional connectivity subgroups

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent and disabling disease. Currently, patients' treatment choices depend on their clinical symptoms observed by clinicians, which are subjective. Rich evidence suggests that different functional networks' dysfunctions correspond to different intervention preferences. Here, we aimed to develop a prediction model based on data-driven subgroups to provide treatment recommendations.

METHODS

All 630 participants enrolled from four sites underwent functional magnetic resonances imaging at baseline. In the discovery dataset (n=228), we firstly identified MDD subgroups by the hierarchical clustering method using the canonical variates of resting-state functional connectivity (FC) through canonical correlation analyses. The demographic, symptom improvement and FC were compared among subgroups. The preference intervention for each subgroup was also determined. Next, we predicted the individual treatment strategy. Specifically, a patient was assigned into predefined subgroups based on FC similarities and then his/her treatment strategy was determined by the subgroups' preferred interventions.

RESULTS

Three subgroups with specific treatment recommendations were emerged including: (1) a selective serotonin reuptake inhibitors-oriented subgroup with early improvements in working and activities. (2) a stimulation-oriented subgroup with more alleviation in suicide. (3) a selective serotonin noradrenaline reuptake inhibitors-oriented subgroup with more alleviation in hypochondriasis. Through cross-dataset testing respectively conducted on three testing datasets, results showed an overall accuracy of 72.83%.

CONCLUSIONS

Our works revealed the correspondences between subgroups and their treatment preferences and predicted individual treatment strategy based on such correspondences. Our model has the potential to support psychiatrists in early clinical decision making for better treatment outcomes.

The "vestibular neuromatrix": A proposed, expanded vestibular network from graph theory in post-concussive vestibular dysfunction

Convergent clinical and neuroimaging evidence suggests that higher vestibular function is subserved by a distributed network including visuospatial, cognitive-affective, proprioceptive, and integrative brain regions. Clinical vestibular syndromes may perturb this network, resulting in deficits across a variety of functional domains. Here, we leverage structural and functional neuroimaging to characterize this extended network in healthy control participants and patients with post-concussive vestibular dysfunction (PCVD). Then, 27 healthy control subjects (15 females) and 18 patients with subacute PCVD (12 female) were selected for participation. Eighty-two regions of interest (network nodes) were identified based on previous publications, group-wise differences in BOLD signal amplitude and connectivity, and multivariate pattern analysis on affective tests. Group-specific "core" networks, as well as a "consensus" network comprised of connections common to all participants, were then generated based on probabilistic tractography and functional connectivity between the 82 nodes and subjected to analyses of node centrality and community structure. Whereas the consensus network was comprised of affective, integrative, and vestibular nodes, PCVD participants exhibited diminished integration and centrality among vestibular and affective nodes and increased centrality of visual, supplementary motor, and frontal and cingulate eye field nodes. Clinical outcomes, derived from dynamic posturography, were associated with approximately 62% of all connections but best predicted by amygdalar, prefrontal, and cingulate connectivity. No group-wise differences in diffusion metrics or tractography were noted. These findings indicate that cognitive, affective, and proprioceptive substrates contribute to vestibular processing and performance and highlight the need to consider these domains during clinical diagnosis and treatment planning.

Understanding complex functional wiring patterns in major depressive disorder through brain functional connectome

Brain function relies on efficient communications between distinct brain systems. The pathology of major depressive disorder (MDD) damages functional brain networks, resulting in cognitive impairment. Here, we reviewed the associations between brain functional connectome changes and MDD pathogenesis. We also highlighted the utility of brain functional connectome for differentiating MDD from other similar psychiatric disorders, predicting recurrence and suicide attempts in MDD, and evaluating treatment responses. Converging evidence has now linked aberrant brain functional network organization in MDD to the dysregulation of neurotransmitter signaling and neuroplasticity, providing insights into the neurobiological mechanisms of the disease and antidepressant efficacy. Widespread connectome dysfunctions in MDD patients include multiple, large-scale brain networks as well as local disturbances in brain circuits associated with negative and positive valence systems and cognitive functions. Although the clinical utility of the brain functional connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments, and clinical outcomes of MDD.

Novel method for identification of individualized resonant frequencies for treatment of Major Depressive Disorder (MDD) using repetitive Transcranial Magnetic Stimulation (rTMS): A proof-of-concept study

BACKGROUND

Repetitive Transcranial Magnetic Stimulation (rTMS) is an effective treatment for Major Depressive Disorder (MDD), but therapeutic benefit is highly variable. Clinical improvement is related to changes in brain circuits, which have preferred resonant frequencies (RFs) and vary across individuals.

OBJECTIVE

We developed a novel rTMS-electroencephalography (rTMS-EEG) interrogation paradigm to identify RFs using the association of power/connectivity measures with symptom severity and treatment outcome.

METHODS

35 subjects underwent rTMS interrogation at 71 frequencies ranging from 3 to 17 Hz administered to left dorsolateral prefrontal cortex (DLPFC). rTMS-EEG was used to assess resonance in oscillatory power/connectivity changes (phase coherence [PC], envelope correlation [EC], and spectral correlation coefficient [SCC]) after each frequency. Multiple regression was used to detect relationships between 10 Hz resonance and baseline symptoms as well as clinical improvement after 10 sessions of 10 Hz rTMS treatment.

RESULTS

Baseline symptom severity was significantly associated with SCC resonance in left sensorimotor (SM; p < 0.0004), PC resonance in fronto-parietal (p = 0.001), and EC resonance in centro-posterior channels (p = 0.002). Subjects significantly improved with 10 sessions of rTMS treatment. Only decreased SCC SM resonance was significantly associated with clinical improvement (r = 0.35, p = 0.04). Subjects for whom 10 Hz SM SCC was highly ranked as an RF among all stimulation frequencies had better outcomes from 10 Hz treatment.

CONCLUSIONS

Resonance of 10 Hz stimulation measured using SCC correlated with both symptom severity and improvement with 10 Hz rTMS treatment. Research should determine whether this interrogation paradigm can identify individualized rTMS treatment frequencies.

Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report

Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration:  ClinicalTrials.gov: NCT01655706.

Intrinsic Functional Connectomes Characterize Neuroticism in Major Depressive Disorder and Predict Antidepressant Treatment Outcomes

BACKGROUND

Antidepressant efficacy in people with major depressive disorder (MDD) remains modest, yet identifying treatment predictive neurobiological markers may improve outcomes. While disruptions in functional connectivity within and between large-scale brain networks predict poorer treatment outcome, it is unclear whether higher trait neuroticism - which has been associated with generally poorer outcome - contributes to these disruptions and to antidepressant-specific treatment outcomes. Here, we used whole-brain functional connectivity analysis to identify a neural connectomic signature of neuroticism and tested whether this signature predicted antidepressant treatment outcome.

METHOD

Participants were 229 adults with MDD and 68 healthy controls who underwent functional MRI and were assessed on clinical features at baseline. MDD participants were then randomized to one of three commonly prescribed antidepressants and after 8 weeks completed a second functional MRI and were reassessed for depressive symptom remission/response. Baseline intrinsic functional connectivity between each pair of 436 brain regions were analysed using network-based statistics to identify connectomic features associated with neuroticism. Features were then assessed on their ability to predict treatment outcome and whether they changed after 8 weeks of treatment.

RESULTS

Higher baseline neuroticism was associated with greater connectivity within and between the salience, executive control, and somatomotor brain networks. Greater connectivity across these networks predicted poorer treatment outcome that was not mediated by baseline neuroticism, and connectivity strength decreased after antidepressant treatment.

CONCLUSIONS

Our findings demonstrate that neuroticism is associated with organization of intrinsic neural networks that predict treatment outcome, elucidating its biological underpinnings and opportunity for better treatment personalization.

Therapeutic potential of ketamine for alcohol use disorder

Excessive alcohol consumption is involved in 1/10 of deaths of U.S. working-age adults and costs the country around $250,000,000 yearly. While Alcohol Use Disorder (AUD) pathology is complex and involves multiple neurotransmitter systems, changes in synaptic plasticity, hippocampal neurogenesis, and neural connectivity have been implicated in the behavioral characteristics of AUD. Depressed mood and stress are major determinants of relapse in AUD, and there is significant comorbidity between AUD, depression, and stress disorders, suggesting potential for overlap in their treatments. Disulfiram, naltrexone, and acamprosate are current pharmacotherapies for AUD, but these treatments have limitations, highlighting the need for novel therapeutics. Ketamine is a N-methyl-D-Aspartate receptor antagonist, historically used in anesthesia, but also affects other neurotransmitters systems, synaptic plasticity, neurogenesis, and neural connectivity. Currently under investigation for treating AUDs and other Substance Use Disorders (SUDs), ketamine has strong support for efficacy in treating clinical depression, recently receiving FDA approval. Ketamine's effect in treating depression and stress disorders, such as PTSD, and preliminary evidence for treating SUDs further suggests a role for treating AUDs. This review explores the behavioral and neural evidence for treating AUDs with ketamine and clinical data on ketamine therapy for AUDs and SUDs.

Transdiagnostic neuroimaging markers of psychiatric risk: A narrative review

•

We review the literature on neural correlates of a general psychopathology factor

•

General psychopathology relates to structural and functional neurodevelopment

•

Disrupted network connectivity maturation may underlie psychiatric vulnerability

Several decades of neuroimaging research in psychiatry have shed light on structural and functional neural abnormalities associated with individual psychiatric disorders. However, there is increasing evidence for substantial overlap in the patterns of neural dysfunction seen across disorders, suggesting that risk for psychiatric illness may be shared across diagnostic boundaries. Gaining insights on the existence of shared neural mechanisms which may transdiagnostically underlie psychopathology is important for psychiatric research in order to tease apart the unique and common aspects of different disorders, but also clinically, so as to help identify individuals early on who may be biologically vulnerable to psychiatric disorder in general. In this narrative review, we first evaluate recent studies investigating the functional and structural neural correlates of a general psychopathology factor, which is thought to reflect the shared variance across common mental health symptoms and therefore index psychiatric vulnerability. We then link insights from this research to existing meta-analytic evidence for shared patterns of neural dysfunction across categorical psychiatric disorders. We conclude by providing an integrative account of vulnerability to mental illness, whereby delayed or disrupted maturation of large-scale networks (particularly default-mode, executive, and sensorimotor networks), and more generally between-network connectivity, results in a compromised ability to integrate and switch between internally and externally focused tasks.

Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naïve patients with major depressive disorder

Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big‐data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first‐episode drug‐naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty‐one first‐episode drug‐naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting‐state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big‐data finding, we also conducted a cross‐sectional comparison of resting‐state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network‐Based Statistic analyses and large‐scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network‐Based Statistic analyses nor large‐scale network analyses detected significant functional connectivity differences between treatment‐naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD.

A PET imaging study of the brain changes of glucose metabolism in patients with temporal lobe epilepsy and depressive disorder

BACKGROUND

This study aims to compare the difference of the brain changes of glucose metabolism between temporal lobe epilepsy patients (TLE) with major depressive disorder and temporal TLE without major depressive disorder.

METHODS

A total of 24 TLE patients, who met the inclusion criteria of our hospital, were enrolled in this study. They were divided into a TLE with depression group (n = 11) and a TLE without depression group (n = 13), according to the results of the HAMD-24 Scale. Two groups patients were examined using 18F-FDG PET brain imaging.

RESULTS

The low metabolic regions of the TLE with depression group were mainly found in the left frontal lobe, temporal lobe and fusiform gyrus, while the high metabolic regions of the TLE with depression group were mainly located in the right frontal lobe, visual joint cortex and superior posterior cingulate cortex. Both of the TLE groups had high metabolic compensation in the non-epileptic area during the interictal period.

CONCLUSIONS

There is an uptake difference of 18F-FDG between TLE patients with depression and TLE patients without depression in multiple encephalic regions.

Emotion processing and regulation in major depressive disorder: A 7T resting-state fMRI study

Dysfunctions in bottom-up emotion processing (EP), as well as top-down emotion regulation (ER) are prominent features in pathophysiology of major depressive disorder (MDD). Nonetheless, it is not clear whether EP- and ER-related areas are regionally and/or connectively disturbed in MDD. In addition, it is yet to be known how EP- and ER-related areas are interactively linked to regulatory behavior, and whether this interaction is disrupted in MDD. In our study, regional amplitude of low frequency fluctuations (ALFF) and whole-brain functional connectivity (FC) of meta-analytic-driven EP- and ER-related areas were compared between 32 healthy controls (HC) and 20 MDD patients. Then, we aimed to investigate whether the EP-related areas can predict the ER-related areas and regulatory behavior in both groups. Finally, the brain-behavior correlations between the EP- and ER-related areas and depression severity were assessed. We found that: (a) affective areas are regionally and/or connectively disturbed in MDD; (b) EP-ER interaction seems to be disrupted in MDD; overburden of emotional reactivity in amygdala may inversely affect cognitive control processes in prefrontal cortices, which leads to diminished regulatory actions. (c) Depression severity is correlated with FC of affective areas. Our findings shed new lights on the neural underpinning of affective dysfunctions in depression.

Functional plasticity abnormalities over the lifespan of first-episode patients with major depressive disorder: a resting state fMRI study

Background

Neurodevelopmental and neurodegenerative theories of depression suggest that patients with major depressive disorder (MDD) may follow abnormal developmental, maturational, and aging processes. However, a lack of lifespan studies has precluded verification of these theories. Herein, we analyzed functional magnetic resonance imaging (fMRI) data to comprehensively characterize age-related functional trajectories, as measured by the fractional amplitude of low frequency fluctuations (fALFF), over the course of MDD.

Methods

In total, 235 MDD patients with age-differentiated onsets and 235 age- and sex-matched healthy controls (HC) were included in this study. We determined the pattern of age-related fALFF changes by cross-sectionally establishing the general linear model (GLM) between fALFF and age over a lifespan. Furthermore, the subjects were divided into four age groups to assess age-related neural changes in detail. Inter-group fALFF comparison (MDD vs. HC) was conducted in each age group and Granger causal analysis (GCA) was applied to investigate effective connectivity between regions.

Results

Compared with the HC, no significant quadratic or linear age effects were found in MDD over the entire lifespan, suggesting that depression affects the normal developmental, maturational, and degenerative process. Inter-group differences in fALFF values varied significantly at different ages of onset. This implies that MDD may impact brain functions in a highly dynamic way, with different patterns of alterations at different stages of life. Moreover, the GCA analysis results indicated that MDD followed a distinct pattern of effective connectivity relative to HC, and this may be the neural basis of MDD with age-differentiated onsets.

Conclusions

Our findings provide evidence that normal developmental, maturational, and ageing processes were affected by MDD. Most strikingly, functional plasticity changes in MDD with different ages of onset involved dynamic interactions between neuropathological processes in a tract-specific manner.

Electroconvulsive Therapy in a Renal Transplantation Patient: A Rare Combination of Disease and Treatment

The safety and efficacy of electroconvulsive therapy (ECT) for the treatment of psychiatric disorders have been demonstrated in a wide variety of patients, including postoperative patients and those who are pregnant. While several reports highlight the safety of this treatment in heart and liver transplantation patients, there is a relative lack of literature detailing the safety profile of ECT in an individual with recent kidney transplantation. Here, we explore the case of a patient with a recent renal transplant secondary to diabetes-related end-stage renal disease (ESRD) who underwent a successful course of ECT treatment. A 57-year-old Caucasian male with a past psychiatric history of schizoaffective disorder, bipolar type, and a past medical history of end-stage renal disease with recent right renal transplantation was admitted to the inpatient psychiatry unit. The admission was via a temporary detention order (TDO) for suicidality and auditory hallucinations promoting self-harm. The patient's depressive and delusional history was well-documented and had been refractory to several courses of psychotherapeutic and pharmacologic management. Electroconvulsive therapy was subsequently initiated and was well-tolerated. Treatments progressively alleviated his depressive and psychotic symptoms and did not adversely affect the function of his transplanted kidney, which was closely monitored throughout the treatment process. This case demonstrated the safety and efficacy of ECT treatment in an individual with recent renal transplant and may prompt further trials into establishing safety and efficacy in larger study populations.

Prediction on treatment improvement in depression with resting state connectivity: A coordinate-based meta-analysis

BACKGROUND

Previous neuroimaging studies revealed abnormal resting-state functional connectivity between distributed brain areas in patients with major depressive disorder. Those abnormalities were normalized after treatment. Moreover, the functional connectivity could predict clinical response to those treatments. However, there has currently been no meta-analysis to verify these findings.

METHODS

The current study aimed to investigate how the resting-state connectivity patterns predict antidepressant response to various treatments across depressive studies by using coordinate-based meta-analysis named activation likelihood estimation. The relevant articles were obtained by searching on PubMed and Web of Science.

RESULTS

Following exclusion criteria of inappropriate studies, seventeen papers with 392 individual depressive patients were included. Those articles contained repetitive transcranial magnetic stimulation (rTMS) treatment, pharmacotherapy, cognitive behavioral therapy (CBT), electroconvulsive therapy (ECT) and transcutaneous vagus nerve stimulation in patients with depression. Meta-analysis revealed that clinical response to all treatments could be predicted by baseline default mode network connectivity in patients with depression. The rTMS treatment had larger effect size compared to other treatment strategies. Furthermore, subgroup meta-analysis showed that the baseline connectivity of perigenual anterior cingulate cortex (pgACC) and ventral medial prefrontal cortex could predict symptoms improvement of rTMS treatment.

LIMITATIONS

More resting-state connectivity studies of CBT and ECT treatment are needed.

CONCLUSIONS

This study highlighted crucial role of DMN, especially the pgACC, in understanding the underlying treatment mechanism of depression.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education. In ROI pairs including the posterior cingulate (PCC) and anterior cingulate (ACC) cortex regions, the relationship between connectivity and cognition was found only with the Bayesian approach. Moreover, only the Bayesian approach was able to detect a significant diagnostic difference in the association in ROI pairs, including both PCC and ACC regions, due to smaller variance for the saFC estimator. The results confirm that a reliable and precise saFC estimator, based on the Bayesian model, can foster scientific discovery that may not be feasible with the conventional ROI-based FC estimator (denoted as 'AVG-FC').

A toolbox for brain network construction and classification (BrainNetClass)

Brain functional network has been increasingly used in understanding brain functions and diseases. While many network construction methods have been proposed, the progress in the field still largely relies on static pairwise Pearson's correlation-based functional network and group-level comparisons. We introduce a "Brain Network Construction and Classification (BrainNetClass)" toolbox to promote more advanced brain network construction methods to the filed, including some state-of-the-art methods that were recently developed to capture complex and high-order interactions among brain regions. The toolbox also integrates a well-accepted and rigorous classification framework based on brain connectome features toward individualized disease diagnosis in a hope that the advanced network modeling could boost the subsequent classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with both graphical user-friendly interfaces and a command line mode targeting cognitive neuroscientists and clinicians for promoting reliability, reproducibility, and interpretability of connectome-based, computer-aided diagnosis. It generates abundant classification-related results from network presentations to contributing features that have been largely ignored by most studies to grant users the ability of evaluating the disease diagnostic model and its robustness and generalizability. We demonstrate the effectiveness of the toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) is available at https://github.com/zzstefan/BrainNetClass.

Behavioral psychological symptoms of dementia and functional connectivity changes: a network-based study

Behavioral and psychological symptoms of dementia (BPSD) are commonly observed since the early stage of Alzheimer's disease (AD) associated with structural brain changes. It is conceivable that they may also relate to functional brain changes. This resting-state functional MRI (RS-fMRI) study investigated the alterations within functional brain networks of a cohort of AD patients at different clinical stages who presented with BPSD. One hundred one AD patients and 56 patients with amnestic mild cognitive impairment underwent a neuropsychological evaluation including the Neuropsychiatry Inventory-12 (NPI-12). All patients and 35 healthy controls (HS) underwent 3T-MRI. Factor analysis was used to extract the principal factors from NPI-12, while RS-fMRI data were processed using graph theory to investigate functional connectivity. Five factors were extracted from NPI-12. Sixty-two percent of patients showed BPSD and functional brain connectivity changes in various networks compared to those without BPSD and HS. These changes contributed to account for patients' BPSD. This work opens new perspectives in terms of nonpharmacological interventions that might be designed to modulate brain connectivity and improve patients' BPSD.

Improved and residual functional abnormalities in major depressive disorder after electroconvulsive therapy

Electroconvulsive therapy (ECT) can induce fast remission of depression but still retain the residual functional impairments in major depressive disorder (MDD) patients. To delineate the different functional circuits of effective antidepressant treatment and residual functional impairments is able to better guide clinical therapy for depression. Herein, voxel-level whole brain functional connectivity homogeneity (FcHo), functional connectivity, multivariate pattern classification approaches were applied to reveal the specific circuits for treatment response and residual impairments in MDD patients after ECT. Increased FcHo values in right dorsomedial prefrontal cortex (dmPFC) and left angular gyrus (AG) and their corresponding functional connectivities between dmPFC and right AG, dorsolateral prefrontal cortex (dlPFC), superior frontal gyrus, precuneus (Pcu) and between left AG with dlPFC, bilateral AG, and left ventrolateral prefrontal cortex in MDD patients after ECT. Moreover, we found decreased FcHo values in left middle occipital gyrus (MOG) and lingual gyrus (LG) and decreased functional connectivities between MOG and dorsal postcentral gyrus (PCG) and between LG and middle PCG/anterior superior parietal lobule in MDD patients before and after ECT compared to healthy controls (HCs). The increased or normalized FcHo and functional connections may be related to effective antidepressant therapy, and the decreased FcHo and functional connectivities may account for the residual functional impairments in MDD patients after ECT. The different change patterns in MDD after ECT indicated a specific brain circuit supporting fast remission of depression, which was supported by the following multivariate pattern classification analyses. Finally, we found that the changed FcHo in dmPFC was correlated with changed depression scores. These results revealed a specific functional circuit supporting antidepressant effects of ECT and neuroanatomical basis for residual functional impairments. Our findings also highlighted the key role of dmPFC in antidepressant and will provide an important reference for depression treatment.

Common and unique connectivity at the interface of motor, neuropsychiatric, and cognitive symptoms in Parkinson's disease: A commonality analysis

Parkinson's disease (PD) is characterized by overlapping motor, neuropsychiatric, and cognitive symptoms. Worse performance in one domain is associated with worse performance in the other domains. Commonality analysis (CA) is a method of variance partitioning in multiple regression, used to separate the specific and common influence of collinear predictors. We apply, for the first time, CA to the functional connectome to investigate the unique and common neural connectivity underlying the interface of the symptom domains in 74 non-demented PD subjects. Edges were modeled as a function of global motor, cognitive, and neuropsychiatric scores. CA was performed, yielding measures of the unique and common contribution of the symptom domains. Bootstrap confidence intervals were used to determine the precision of the estimates and to directly compare each commonality coefficient. The overall model identified a network with the caudate nucleus as a hub. Neuropsychiatric impairment accounted for connectivity in the caudate-dorsal anterior cingulate and caudate-right dorsolateral prefrontal-right inferior parietal circuits, while caudate-medial prefrontal connectivity reflected a unique effect of both neuropsychiatric and cognitive impairment. Caudate-precuneus connectivity was explained by both unique and shared influence of neuropsychiatric and cognitive symptoms. Lastly, posterior cortical connectivity reflected an interplay of the unique and common effects of each symptom domain. We show that CA can determine the amount of variance in the connectome that is unique and shared amongst motor, neuropsychiatric, and cognitive symptoms in PD, thereby improving our ability to interpret the data while gaining novel insight into networks at the interface of these symptom domains.

Transdiagnostic and disease-specific abnormalities in the default-mode network hubs in psychiatric disorders: A meta-analysis of resting-state functional imaging studies

Background.

The default mode network (DMN) dysfunction has emerged as a consistent biological correlate of multiple psychiatric disorders. Specifically, there is evidence of alterations in DMN cohesiveness in schizophrenia, mood and anxiety disorders. The aim of this study was to synthesize at a fine spatial resolution the intra-network functional connectivity of the DMN in adults diagnosed with schizophrenia, mood and anxiety disorders, capitalizing on powerful meta-analytic tools provided by activation likelihood estimation.

Methods.

Results from 70 whole-brain resting-state functional magnetic resonance imaging articles published during the last 15 years were included comprising observations from 2,789 patients and 3,002 healthy controls.

Results.

Specific regional changes in DMN cohesiveness located in the anteromedial and posteromedial cortex emerged as shared and trans-diagnostic brain phenotypes. Disease-specific dysconnectivity was also identified. Unmedicated patients showed more DMN functional alterations, highlighting the importance of interventions targeting the functional integration of the DMN.

Conclusion.

This study highlights functional alteration in the major hubs of the DMN, suggesting common abnormalities in self-referential mental activity across psychiatric disorders.

Connectivity of the Cognitive Control Network During Response Inhibition as a Predictive and Response Biomarker in Major Depression: Evidence From a Randomized Clinical Trial

BACKGROUND

In treating major depressive disorder, we lack tests anchored in neurobiology that predict antidepressant efficacy. Cognitive impairments are a particularly disabling feature of major depressive disorder. We tested whether functional connectivity during a response-inhibition task can predict response to antidepressants and whether its changes over time are correlated to symptom changes.

METHODS

We analyzed data from outpatients with major depressive disorder (n = 124) randomized to receive escitalopram, sertraline, or venlafaxine (8 weeks) and healthy control subjects (n = 59; age 18-65 years). Before and after treatment, participants were interviewed and scanned using functional magnetic resonance imaging, and functional connectivity was measured using generalized psychophysiological interaction during response inhibition (Go-NoGo task). We investigated the interaction between treatment type and response (≥50% reduction on self-reported symptoms), coupling differences between responders and nonresponders at baseline, their correlation with symptom improvement, and their changes in time.

RESULTS

During response inhibition, connectivity between the dorsolateral prefrontal cortex/supramarginal gyrus and supramarginal gyrus/middle temporal gyrus was associated with response to sertraline and venlafaxine, but not escitalopram. Sertraline responders had higher functional connectivity between these regions compared with nonresponders, whereas venlafaxine responders had lower functional connectivity. For sertraline, attenuation of connectivity in the precentral and superior temporal gyri correlated with posttreatment symptom improvement. For venlafaxine, enhancement of connectivity between the orbitofrontal cortex and subcortical regions correlated with symptom improvement.

CONCLUSIONS

Connectivity of the cognitive control circuit during response inhibition selectively and differentially predicts antidepressant treatment response and correlates with symptom improvement. These quantitative markers tied to the neurobiology of cognitive features of depression could be used translationally to predict and evaluate treatment response.

Effect of Intrinsic Patterns of Functional Brain Connectivity in Moderating Antidepressant Treatment Response in Major Depression

OBJECTIVE

Major depressive disorder is associated with aberrant resting-state functional connectivity across multiple brain networks supporting emotion processing, executive function, and reward processing. The purpose of this study was to determine whether patterns of resting-state connectivity between brain regions predict differential outcome to antidepressant medication (sertraline) compared with placebo.

METHODS

Participants in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study underwent structural and resting-state functional MRI at baseline. Participants were then randomly assigned to receive either sertraline or placebo treatment for 8 weeks (N=279). A region of interest-based approach was utilized to compute functional connectivity between brain regions. Linear mixed-model intent-to-treat analyses were used to identify brain regions that moderated (i.e., differentially predicted) outcomes between the sertraline and placebo arms.

RESULTS

Prediction of response to sertraline involved several within- and between-network connectivity patterns. In general, higher connectivity within the default mode network predicted better outcomes specifically for sertraline, as did greater between-network connectivity of the default mode and executive control networks. In contrast, both placebo and sertraline outcomes were predicted (in opposite directions) by between-network hippocampal connectivity.

CONCLUSIONS

This study identified specific functional network-based moderators of treatment outcome involving brain networks known to be affected by major depression. Specifically, functional connectivity patterns of brain regions between and within networks appear to play an important role in identifying a favorable response for a drug treatment for major depressive disorder.

Electroencephalogram Source Connectivity in the Prediction of Electroconvulsive Therapy Outcome in Major Depressive Disorder

Objectives. Major depressive disorder (MDD) is a common and potentially lethal disorder affecting up to 14% of all persons worldwide. However, one-third to thwo-thirds of patients are nonresponders to first-line therapy. Even the electroconvulsive therapy (ECT) as the option of choice in therapy-resistant MDD still shows a high proportion of nonresponders. In case of a predicted nonresponse to ECT, for example, by means of electrophysiological electroencephalogram (EEG) parameters, other therapies of MDD (eg, augmentation, polypharmacy etc) could be chosen. Methods. In this study, we retrospectively analyzed 2-minute resting state EEGs from patients with MDD who underwent ECT (6-12 sessions with 3 sessions per week) between 2006 and 2015 at the University Hospital of Zurich. Following several lines of evidence, we hypothesized altered linear EEG connectivity within the alpha band being predictive for treatment outcome. We used a network-based statistics (NBS) approach to compare connectivity measures between responders and nonresponders. Source estimates and connectivity measures were mapped using low-resolution brain tomography (LORETA). As the main outcome parameter served the retrospectively assessed efficacy index (CGI-E) from the Clinical Global Impression (CGI) rating scale. Results. Responders in comparison with non-responders showed a significant lower linear lagged connectivity in widespread cortical areas within the EEG alpha 2 band. Additionally, there were strong correlations between CGI ratings and connectivity strength mainly within frontal cortices. Conclusions. Pretreatment EEG-connectivity within the alpha 2 band has a predictive value for the efficacy of ECT treatment.

Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder

Although major depressive disorder (MDD) is associated with altered functional coupling between disparate neural networks, the degree to which such measures are ameliorated by antidepressant treatment is unclear. It is also unclear whether functional connectivity can be used as a predictive biomarker of treatment response. Here, we used whole-brain functional connectivity analysis to identify neural signatures of remission following antidepressant treatment, and to identify connectomic predictors of treatment response. 163 MDD and 62 healthy individuals underwent functional MRI during pre-treatment baseline and 8-week follow-up sessions. Patients were randomized to escitalopram, sertraline or venlafaxine-XR antidepressants and assessed at follow-up for remission. Baseline measures of intrinsic functional connectivity between each pair of 333 regions were analyzed to identify pre-treatment connectomic features that distinguish remitters from non-remitters. We then interrogated these connectomic differences to determine if they changed post-treatment, distinguished patients from controls, and were modulated by medication type. Irrespective of medication type, remitters were distinguished from non-remitters by greater connectivity within the default mode network (DMN); specifically, between the DMN, fronto-parietal and somatomotor networks, the DMN and visual, limbic, auditory and ventral attention networks, and between the fronto-parietal and somatomotor networks with cingulo-opercular and dorsal attention networks. This baseline hypo-connectivity for non-remitters also distinguished them from controls and increased following treatment. In contrast, connectivity for remitters was higher than controls at baseline and also following remission, suggesting a trait-like connectomic characteristic. Increased functional connectivity within and between large-scale intrinsic brain networks may characterize acute recovery with antidepressants in depression.

NMDA receptor antagonists traxoprodil and lanicemine improve hippocampal-prefrontal coupling and reward-related networks in rats

RATIONALE

The N-methyl-D-aspartate receptor (NMDAR) antagonist ketamine is known to have not only a rapid antidepressant effect but also dissociative side effects. Traxoprodil and lanicemine, also NMDA antagonists, are candidate antidepressant drugs with fewer side effects.

OBJECTIVES

In order to understand their mechanism of action, we investigated the acute effects of traxoprodil and lanicemine on brain connectivity using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

Functional connectivity (FC) alterations were examined using interregional correlation networks. Graph theoretical methods were used for whole brain network analysis. As interest in NMDAR antagonists as potential antidepressants was triggered by the antidepressant effect of ketamine, results were compared to previous findings from our ketamine studies.

RESULTS

Similar to ketamine but to a smaller extent, traxoprodil increased hippocampal-prefrontal (Hc-PFC) coupling. Unlike ketamine, traxoprodil decreased connectivity within the PFC. Lanicemine had no effect on these properties. The improvement of Hc-PFC coupling corresponds well to clinical result, showing ketamine to have a greater antidepressant effect than traxoprodil, while lanicemine has a weak and transient effect. Connectivity changes overlapping between the drugs as well as alterations of local network properties occurred mostly in reward-related regions.

CONCLUSION

The antidepressant effect of NMDA antagonists appears to be associated with enhanced Hc-PFC coupling. The effects on local network properties and regional connectivity suggest that improvement of reward processing might also be important for understanding the mechanisms underlying the antidepressant effects of these drugs.

Antidepressant and antisuicidal effects of ketamine on the functional connectivity of prefrontal cortex-related circuits in treatment-resistant depression: A double-blind, placebo-controlled, randomized, longitudinal resting fMRI study

BACKGROUND

Increasing evidence suggests that infusion of a subanesthetic dose of ketamine exerts antidepressant and antisuicidal effects in patients with treatment-resistant depression (TRD).

AIMS

In this investigation, we used the resting functional connectivity magnetic resonance imaging (fcMRI) to determine the effects of ketamine on the functional connectivity (FC) of prefrontal cortex (PFC)-related circuits in patients with TRD.

METHODS

Forty-eight patients with TRD were recruited and randomly divided into three groups on the basis of ketamine infusion dose: 0.5 mg/kg (standard dose), 0.2 mg/kg (low dose), or normal saline (a placebo infusion). Resting functional MRI data and clinical data were recorded at the baseline and on the third day after ketamine infusion treatment.

RESULTS

The standard-dose group showed a reduction in the FC of the left dorsal anterior cingulate cortex (dACC) and right dorsolateral (dl)PFC with the other frontal regions. The low-dose group demonstrated a more pervasive reduction of FC in the bilateral dACC with other frontal and parietal regions. A negative correlation was observed between the reduction in suicidal ideation and the reduction in the FC between the left dACC and right ACC regions in the standard-dose group, whereas a positive correlation was observed between the reduction in suicidal ideation and the increase in the FC between the right dlPFC and left superior parietal region in the low-dose group.

CONCLUSIONS

Our results support the hypothesis that PFC-related circuit modulation is crucial to the antidepressant and antisuicidal effects of the ketamine infusion treatment.

Altered Cortico-Limbic Network Connectivity in Parkinsonian Depression: The Effect of Antidepressants

BACKGROUND

Depression is a common comorbidity of Parkinson's disease (PD); however, the impact of antidepressant status on cortical function in parkinsonian depression is not fully understood. While studies of resting state functional MRI in major depression have shown that antidepressant treatment affects cortical connectivity, data on connectivity and antidepressant status in PD is sparse.

OBJECTIVE

We tested the hypothesis that cortico-limbic network (CLN) resting state connectivity is abnormal in antidepressant-treated parkinsonian depression.

METHODS

Thirteen antidepressant-treated depressed PD and 47 non-depressed PD participants from the Parkinson's Progression Markers Initiative (PPMI) database were included. Data was collected using 3T Siemens TIM Trio MR scanners and analyzed using SPM and CONN functional connectivity toolbox. Volumetric analysis was also performed using BrainSuite.

RESULTS

We found decreased connectivity in the antidepressant-treated depressed PD group when compared to non-depressed PD between the left frontal operculum and bilateral insula, and also reduced connectivity between right orbitofrontal cortex and left temporal fusiform structures. Increased depression scores were associated with decreased insular-frontal opercular connectivity. No ROI volumetric differences were found between groups.

CONCLUSION

Given the relationship between depression scores and cortico-limbic connectivity in PD, the abnormal insular-frontal opercular hypoconnectivity in this cohort may be associated with persistent depressive symptoms or antidepressant effects.

The association between antidepressant treatment and brain connectivity in two double-blind, placebo-controlled clinical trials: a treatment mechanism study

BACKGROUND

Antidepressant medications offer an effective treatment for depression, yet nearly 50% of patients either do not respond or have side-effects rendering them unable to continue the course of treatment. Mechanistic studies might help advance the pharmacology of depression by identifying pathways through which treatments exert their effects. Toward this goal, we aimed to identify the effects of antidepressant treatment on neural connectivity, the relationship with symptom improvement, and to test whether these effects were reproducible across two studies.

METHODS

We completed two double-blind, placebo-controlled trials of SNRI antidepressant medications with MRI scans obtained before and after treatment. One was a 10-week trial of duloxetine (30-120 mg daily; mean 92·1 mg/day [SD 30·00]) and the other was a 12-week trial of desvenlafaxine (50-100 mg daily; 93·6 mg/day [16·47]). Participants consisted of adults with persistent depressive disorder. Adjusting for sex and age, we examined the effect of treatment on whole-brain functional connectivity. We also examined correlations between change in functional connectivity and improvement in symptoms of depression (24-item Hamilton Depression Rating Scale) and pain symptom severity (Symptom Checklist-90-Revised).

FINDINGS

Participants were enrolled between Jan 26, 2006, and Nov 22, 2011, for the duloxetine RCT and Aug 5, 2012, and Jan 28, 2016, for the desvenlafaxine RCT. Before and after treatment MRI scans were collected in 32 participants for the duloxetine RCT and 34 participants for the desvenlafaxine RCT. In both studies, antidepressants decreased functional connectivity compared with placebo (duloxetine study: β=-0·06; 95% CI -0·08 to -0·03; p<0·0001, ηp2=0·44; desvenlafaxine study: -0·06, -0·09 to -0·03; p<0·0001, ηp2=0·35) within a thalamo-cortico-periaqueductal network that has previously been associated with the experience of pain. Within the active drug groups, reductions in functional connectivity within this network correlated with improvements in depressive symptom severity in both studies (duloxetine study: r=0·38, 95% CI 0·01-0·65; p=0·0426; desvenlafaxine study: 0·44, 0·10-0·69; p=0·0138) and pain symptoms in the desvenlafaxine study (0·39, 0·04 to 0·65; p=0·0299).

INTERPRETATION

The findings suggest the thalamo-cortico-periaqueductal network associated with the experience of pain is a new and potentially important target for novel antidepressant therapeutics.

FUNDING

National Mental Health Institute, Eli Lilly and Company, Pfizer Pharmaceuticals, and the Edwin S Webster Foundation.