Short-term antidepressant administration reduces default mode and task-positive network connectivity in healthy individuals during rest

Increased functional connectivity between brainstem substructures and cortex in treatment resistant depression

Previous functional magnetic resonance imaging (fMRI) studies showed an abnormal brainstem-to-cortex functional connectivity (FC) in major depressive disorder. However, only few studies analyzed brainstem substructures in treatment-resistant depression (TRD). In this study, we analyzed resting-state seed-based FC between midbrain, pons, medulla oblongata and cortical/subcortical brain regions in patients with TRD (n = 24) and age- and sex-matched healthy controls (n = 24). FC was analyzed in each group and compared between groups. Correlation analyses assessed the relationship between FC strength and depressive symptom severity in regions showing significant group differences in seed-based connectivity. Our findings reveal an increased FC in the midbrain and pons to the precentral gyrus, postcentral gyrus, and temporal gyrus in patients with TRD compared to healthy controls. Interestingly, in TRD patients, FC between midbrain and cortex was negatively correlated with BDI-II scores, indicating a relationship between altered connectivity and self-reported depression severity. It is essential to note that our naturalistic, cross-sectional approach precludes causal conclusions regarding the relationship between FC and pathophysiology of TRD. The small sample size necessitates confirmation in a larger cohort. Midbrain/pons-to-cortex FC was increased in patients with TRD compared to healthy controls. Future studies should explore the relationship between abnormal brainstem-to-cortex FC and depressive symptomatology in more detail.

Development and validation of a machine learning model to predict cognitive behavioral therapy outcome in obsessive-compulsive disorder using clinical and neuroimaging data

Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. In this study, we aimed to develop predictive models using clinical and neuroimaging data from the multicenter Enhancing Neuro-Imaging and Genetics through Meta-Analysis (ENIGMA)-OCD consortium. Baseline clinical and resting-state functional magnetic imaging (rs-fMRI) data from 159 adult patients aged 18-60 years (88 female) with OCD who received CBT at four treatment/neuroimaging sites were included. Fractional amplitude of low frequency fluctuations, regional homogeneity and atlas-based functional connectivity were computed. Clinical CBT response and remission were predicted using support vector machine and random forest classifiers on clinical data only, rs-fMRI data only, and the combination of both clinical and rs-fMRI data. The use of only clinical data yielded an area under the ROC curve (AUC) of 0.69 for predicting remission (p=0.001). Lower baseline symptom severity, younger age, an absence of cleaning obsessions, unmedicated status, and higher education had the highest model impact in predicting remission. The best predictive performance using only rs-fMRI was obtained with regional homogeneity for remission (AUC=0.59). Predicting response with rs-fMRI generally did not exceed chance level. Machine learning models based on clinical data may thus hold promise in predicting remission after CBT for OCD, but the predictive power of multicenter rs-fMRI data is limited.

Dynamic quantitative monitoring of cerebrospinal fluid monoamine neurotransmitter markers during the modeling process of chronic stress-induced depression in monkeys (Macaca mulatta)

BACKGROUND

Depression is known as the "mental cold" and is also considered a major cause of disability worldwide. It is estimated that over 300 million people worldwide suffer from severe depression, equivalent to 4.4% of the world's population. The monoamine hypothesis of depression predicts the underlying pathophysiological mechanisms of depression, but in-depth research has failed to find convincing evidence.

METHOD

In this study, we will dynamically and strictly quantitatively monitor the concentration changes of monoamine transmitters in the cerebrospinal fluid (CSF) of macaques, based on our previous work. In the experiment, timed and quantitative collection of CSF samples from macaques was performed and the concentration of monoamine transmitters was determined.

RESULT

The results showed that after 2 months of chronic stress, the concentrations of high vanillin acid (HVA) and 3,4-dihydroxy-phenylacetic acid were significantly higher in the maternal separation (MS) group, whereas there was no significant difference in dopamine and 5-hydroxyindoleacetic acid.

CONCLUSION

This study is the first to observe the long-term dynamic relationship between early adversity, chronic stress, adolescent depression, and CSF monoamine concentrations. The research suggests that MS and chronic stress play an undeniable role in the pathogenesis of depression and that concentrations of HVA and dihydroxyphenylacetic acid are likely to serve as early markers of depressive-like symptoms in macaques.

Bright light therapy-induced improvements of mood, cognitive functions and cerebellar functional connectivity in subthreshold depression: A randomized controlled trial

Background

The efficacy of bright light therapy (BLT) in ameliorating depression has been validated. The present study is to investigate the changes of depressive symptoms, cognitive function and cerebellar functional connectivity (FC) following BLT in individuals with subthreshold depression (StD).

Method

Participants were randomly assigned to BLT group (N = 47) or placebo (N = 41) in this randomized controlled trial between March 2020 and June 2022. Depression severity and cognitive function were assessed, as well as resting-state functional MRI scan was conducted before and after 8-weeks treatment. Seed-based whole-brain static FC (sFC) and dynamic FC (dFC) analyses of the bilateral cerebellar subfields were conducted. Besides, a multivariate regression model examined whether baseline brain FC was associated with changes of depression severity and cognitive function during BLT treatment.

Results

After 8-week BLT treatment, individuals with StD showed improved depressive symptoms and attention/vigilance cognitive function. BLT also increased sFC between the right cerebellar lobule IX and left temporal pole, and decreased sFC within the cerebellum, and dFC between the right cerebellar lobule IX and left medial prefrontal cortex. Moreover, the fusion of sFC and dFC at baseline could predict the improvement of attention/vigilance in response to BLT.

Conclusions

The current study identified that BLT improved depressive symptoms and attention/vigilance, as well as changed cerebellum-DMN connectivity, especially in the cerebellar-frontotemporal and cerebellar internal FC. In addition, the fusion features of sFC and dFC at pre-treatment could serve as an imaging biomarker for the improvement of attention/vigilance cognitive function after BLT in StD.

Heart rate variability, interoceptive accuracy and functional connectivity in middle-aged and older patients with depression

BACKGROUND AND OBJECTIVE

Major depressive disorder (MDD) is associated with increased cardiac morbidity. Reduced heart rate variability (HRV) as well as lower interoceptive accuracy (IAc) have been observed in MDD as possible sympathomimetic mechanisms related to insula activity. The salience network (SN) anchored by the insula has been posited as a crucial functional network for cardiac sensations and the default mode network (DMN) for MDD. This study aimed to investigate the relation between insula-centered and depression-related brain networks, IAc and HRV in patients with depression as a possible mechanism by which MDD increases cardiac morbidity.

METHODS

30 depressed inpatients and 30 healthy subjects (derived from the population-based "Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression" cohort study, STAAB) all over 50 years were examined. HRV and IAc were assessed via electrocardiogram and a heartbeat perception task prior to a 3 T resting-state functional magnetic resonance imaging. Seed-to-voxel resting-state functional connectivity (FC) analysis was conducted with six seeds in the insula and two seeds in the DMN.

RESULTS

Depressed patients on the one hand showed decreased FC between insula cortex and frontal as well occipital cortical brain regions compared to controls. Depressed patients on the other hand exhibited higher FC between the medial prefrontal cortex and the insula cortex compared to controls. However, depressed patients did not differ in HRV nor in IAc compared to controls.

CONCLUSION

Thus, differences in insula-related brain networks in depression in our study were not mirrored by differences in HRV and IAc. Future research is needed to define the mechanism by which depression increases cardiac morbidity.

Dimensional subtyping of first-episode drug-naïve major depressive disorder: A multisite resting-state fMRI study

Major depressive disorder (MDD) is a heterogeneous syndrome, and understanding its neural mechanisms is crucial for the advancement of personalized medicine. However, conventional subtyping studies often categorize MDD patients into a single subgroup, neglecting the continuous interindividual variations. This implies a pressing need for a dimensional approach. 230 first-episode drug-naïve MDD patients and 395 healthy controls were obtained from 5 sites via the Rest-meta-MDD project. A Bayesian model was used to decompose the resting-state functional connectivity (RSFC) into multiple distinct RSFC patterns (refer to as "factors"), and each individual was allowed to express multiple factors to varying degrees (dimensional subtyping). The associations between demographic and clinical variables with the identified factors were calculated. We identified three latent factors with distinct but partially overlapping hypo- and hyper-RSFC patterns. Most participants co-expressed multiple latent factors. All factors shared abnormal RSFC involving the default mode network and frontoparietal network, but the directionality partially differed across factors. All factors were not significantly associated with demographic and clinical variables. These findings shed light on the interindividual variability in MDD and could form the basis for developing novel therapeutic approaches that capitalize on the heterogeneity of MDD.

Modulation of functional networks related to the serotonin neurotransmitter system by citalopram: Evidence from a multimodal neuroimaging study

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR).

AIM

We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge.

METHODS

We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography.

RESULTS

5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task.

CONCLUSIONS

Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

A new causal centrality measure reveals the prominent role of subcortical structures in the causal architecture of the extended default mode network

Network representation has been an incredibly useful concept for understanding the behavior of complex systems in social sciences, biology, neuroscience, and beyond. Network science is mathematically founded on graph theory, where nodal importance is gauged using measures of centrality. Notably, recent work suggests that the topological centrality of a node should not be over-interpreted as its dynamical or causal importance in the network. Hence, identifying the influential nodes in dynamic causal models (DCM) remains an open question. This paper introduces causal centrality for DCM, a dynamics-sensitive and causally-founded centrality measure based on the notion of intervention in graphical models. Operationally, this measure simplifies to an identifiable expression using Bayesian model reduction. As a proof of concept, the average DCM of the extended default mode network (eDMN) was computed in 74 healthy subjects. Next, causal centralities of different regions were computed for this causal graph, and compared against several graph-theoretical centralities. The results showed that the subcortical structures of the eDMN were more causally central than the cortical regions, even though the graph-theoretical centralities unanimously favored the latter. Importantly, model comparison revealed that only the pattern of causal centrality was causally relevant. These results are consistent with the crucial role of the subcortical structures in the neuromodulatory systems of the brain, and highlight their contribution to the organization of large-scale networks. Potential applications of causal centrality-to study causal models of other neurotypical and pathological functional networks-are discussed, and some future lines of research are outlined.

The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen's d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen's d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder

BACKGROUND

Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD.

METHODS

Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD.

RESULTS

Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up.

CONCLUSION

Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.

Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias

Introduction

Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission.

Methods

We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks.

Results

The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles.

Discussion

These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies

The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.

Alteration of default mode network: association with executive dysfunction in frontal glioma patients

OBJECTIVE

Patients with frontal gliomas often experience executive dysfunction (EF-D) before surgery, and the changes in brain plasticity underlying this effect remain obscure. In this study, the authors aimed to assess whole-brain structural and functional alterations by using structural MRI and resting-state functional MRI (rs-fMRI) in frontal glioma patients with or without EF-D.

METHODS

Fifty-seven patients with frontal gliomas were admitted prospectively to the authors' institution and assigned to one of two groups: 1) the normal executive function (EF-N) group and 2) the EF-D group, based on patient results for the Trail Making Test, Part B and Stroop Color-Word Test, Part C. Twenty-nine baseline-matched healthy controls were also recruited. All participants underwent multimodal MRI examination. Cortical surface thickness, surface-based resting-state activity (fractional amplitude of low-frequency fluctuation [fALFF] and regional homogeneity [ReHo]), and edge-based network functional connectivity (FC) were measured with FreeSurfer and fMRIPrep. The correlation between altered MRI parameters and executive function (EF) was assessed using Pearson correlation and receiver operating characteristic (ROC) analysis.

RESULTS

Demographic characteristics (sex, age, and education level) and clinical characteristics (location, volume, grade of tumor, and preoperative epilepsy) were not significantly different between the groups, but the Karnofsky Performance Scale score was worse in the EF-D group. There was no significant difference in cortical surface thickness between the EF-D and EF-N groups. In both low-grade and high-grade glioma patients the fALFF value (permutation test + threshold-free cluster enhancement, p value after family-wise error correction < 0.05) and ReHo value (t-test, p < 0.001) of the left precuneus cortex in the EF-D group were greater than those in the EF-N group, which were negatively correlated with EF (p < 0.05) and enabled prediction of EF (area under the ROC curve 0.826 for fALFF and 0.855 for ReHo, p < 0.001). Compared with the EF-N group, the FCs between the default mode network (DMN) from DMN node to DMN node (DMN-DMN) and from the DMN to the central executive network (DMN-CEN) in the EF-D group were increased significantly (network-based statistics corrected p < 0.05) and negatively correlated with EF (Pearson correlation, p < 0.05).

CONCLUSIONS

Apart from local disruption, the abnormally activated DMN in the resting state is related to EF-D in frontal glioma patients. DMN activity should be considered during preoperative planning and postoperative neurorehabilitation for frontal glioma patients to preserve EF. Clinical trial registration no.: NCT03087838 (ClinicalTrials.gov).

Tolerability and efficacy of duloxetine for the prevention of persistent musculoskeletal pain after trauma and injury: a pilot three-group randomized controlled trial

ABSTRACT

This study investigated the tolerability and preliminary efficacy of duloxetine as an alternative nonopioid therapeutic option for the prevention of persistent musculoskeletal pain (MSP) among adults presenting to the emergency department with acute MSP after trauma or injury. In this randomized, double-blind, placebo-controlled study, eligible participants (n = 78) were randomized to 2 weeks of a daily dose of one of the following: placebo (n = 27), 30 mg duloxetine (n = 24), or 60 mg duloxetine (n = 27). Tolerability, the primary outcome, was measured by dropout rate and adverse effects. Secondary outcomes assessed drug efficacy as measured by (1) the proportion of participants with moderate to severe pain (numerical rating scale ≥ 4) at 6 weeks (pain persistence); and (2) average pain by group over the six-week study period. We also explored treatment effects by type of trauma (motor vehicle collision [MVC] vs non-MVC). In both intervention groups, duloxetine was well tolerated and there were no serious adverse events. There was a statistically significant difference in pain over time for the 60 mg vs placebo group ( P = 0.03) but not for the 30 mg vs placebo group ( P = 0.51). In both types of analyses, the size of the effect of duloxetine was larger in MVC vs non-MVC injury. Consistent with the role of stress systems in the development of chronic pain after traumatic stress, our data indicate duloxetine may be a treatment option for reducing the transition from acute to persistent MSP. Larger randomized controlled trials are needed to confirm these promising results.

Altered resting-state cerebral blood flow and functional connectivity mediate suicidal ideation in major depressive disorder

The relationships among cerebral blood flow (CBF), functional connectivity (FC) and suicidal ideation (SI) in major depressive disorder (MDD) patients have remained elusive. In this study, we characterized the changes in CBF and FC among 175 individuals including 47 MDD without SI (MDDNSI), 59 MDD with SI (MDDSI), and 69 healthy control (HC) who underwent arterial spin labeling and resting-state functional MRI scans. Then the voxel-wise CBF, seed-based FC and partial correlation analyses were measured. Mediation analysis was carried out to reveal the effects of FC on the association between CBF and behavioral performances in both subgroups. Results showed that CBF was higher in MDDSI patients in the bilateral precuneus compared to HC and MDDNSI participants. MDDSI patients exhibited enhanced FC in the prefrontal-limbic system and decreased FC in the sensorimotor cortex (SMC) relative to MDDNSI patients. CBF and FC were significantly correlated with clinical variables. More importantly, exploratory mediation analyses identified that abnormal FC can mediate the association between regional CBF and behavioral performances. These results highlight the potential role of precuneus gyrus, prefrontal-limbic system as well as SMC in the process of suicide and provide new insights into the neural mechanism underlying suicide in MDD patients.

Different depression: motivational anhedonia governs antidepressant efficacy in Huntington's disease

Depression is more common in neurodegenerative diseases such as Huntington's disease than the general population. Antidepressant efficacy is well-established for depression within the general population: a recent meta-analysis showed serotonin norepinephrine reuptake inhibitors, tricyclic antidepressants and mirtazapine outperformed other antidepressants. Despite the severe morbidity, antidepressant choice in Huntington's disease is based on Class IV evidence. We used complementary approaches to determine treatment choice for depression in Huntington's disease: propensity score analyses of antidepressant treatment outcome using the ENROLL-HD data set, and a dissection of the cognitive mechanisms underlying depression in Huntington's disease using a cognitive battery based on the Research Domain Criteria for Depression. Study 1 included ENROLL-HD 5486 gene-positive adult patients started on an antidepressant medication for depression. Our outcome measures were depression (Hospital Anxiety and Depression Scale or Problem Behaviours Assessment 'Depressed Mood' item) at first follow-up (primary outcome) and all follow-ups (secondary outcome). The intervention was antidepressant class. We used Svyglm&Twang in R to perform propensity scoring, using known variables (disease progression, medical comorbidity, psychiatric morbidity, sedatives, number of antidepressants, demographics and antidepressant contraindications) to determine the probability of receiving different antidepressants (propensity score) and then included the propensity score in a model of treatment efficacy. Study 2 recruited 51 gene-positive adult patients and 26 controls from the South Wales Huntington's Disease Management Service. Participants completed a motor assessment, in addition to measures of depression and apathy, followed by tasks measuring consummatory anhedonia, motivational anhedonia, learning from reward and punishment and reaction to negative outcome. We used generalised linear models to determine the association between task performance and depression scores. Study 1 showed selective serotonin reuptake inhibitors outperformed serotonin norepinephrine reuptake inhibitors on the primary outcome (P = 0.048), whilst both selective serotonin reuptake inhibitors (P = 0.00069) and bupropion (P = 0.0045) were superior to serotonin norepinephrine reuptake inhibitors on the secondary outcome. Study 2 demonstrated an association between depression score and effort for reward that was not explained by apathy. No other mechanisms were associated with depression score. We found that selective serotonin reuptake inhibitors and bupropion outperform serotonin norepinephrine reuptake inhibitors at alleviating depression in Huntington's disease. Moreover, motivational anhedonia appears the most significant mechanism underlying depression in Huntington's disease. Bupropion is improves motivational anhedonia and has a synergistic effect with selective serotonin reuptake inhibitors. This work provides the first large-scale, objective evidence to determine treatment choice for depression in Huntington's disease, and provides a model for determining antidepressant efficacy in other neurodegenerative diseases.

Neurocircuitry basis of the opioid use disorder-post-traumatic stress disorder comorbid state: conceptual analyses using a dimensional framework

Understanding the interface between opioid use disorder (OUD) and post-traumatic stress disorder (PTSD) is challenging. By use of a dimensional framework, such as research domain criteria, convergent and targetable neurobiological processes in OUD-PTSD comorbidity can be identified. We hypothesise that, in OUD-PTSD, circuitry that is implicated in two research domain criteria systems (ie, negative valence and cognitive control) underpins dysregulation of incentive salience, negative emotionality, and executive function. We also propose that the OUD-PTSD state might be systematically investigated with approaches outlined within a neuroclinical assessment framework for addictions and PTSD. Our dimensional analysis of the OUD-PTSD state shows how first-line therapeutic approaches (ie, partial μ-type opioid receptor [MOR1] agonism) modulate overlapping neurobiological and clinical features and also provides mechanistic rationale for evaluating polytherapeutic strategies (ie, partial MOR1 agonism, κ-type opioid receptor [KOR1] antagonism, and α-2A adrenergic receptor [ADRA2A] agonism). A combination of these therapeutic mechanisms is projected to facilitate recovery in patients with OUD-PTSD by mitigating negative valence states and enhancing executive control.

How do serotonergic psychedelics treat depression: The potential role of neuroplasticity

Depression is a common mental disorder and one of the leading causes of disability around the world. Monoaminergic antidepressants often take weeks to months to work and are not effective for all patients. This has led to a search for a better understanding of the pathogenesis of depression as well as to the development of novel antidepressants. One such novel antidepressant is ketamine, which has demonstrated both clinically promising results and contributed to new explanatory models of depression, including the potential role of neuroplasticity in depression. Early clinical trials are now showing promising results of serotonergic psychedelics for depression; however, their mechanism of action remains poorly understood. This paper seeks to review the effect of depression, classic antidepressants, ketamine, and serotonergic psychedelics on markers of neuroplasticity at a cellular, molecular, electrophysiological, functional, structural, and psychological level to explore the potential role that neuroplasticity plays in the treatment response of serotonergic psychedelics.

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.

Interrelations between dopamine and serotonin producing sites and regions of the default mode network

Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.

The alteration of cognitive function networks in remitted patients with major depressive disorder: an independent component analysis

INTRODUCTION

Dysfunctional connectivity of resting-state functional networks has been observed in patients with major depressive disorder (MDD), particularly in cognitive function networks including the central executive network (CEN), default mode network (DMN) and salience network (SN). Findings from studies examining how aberrant functional connectivity (FC) changed after antidepressant treatment, however, have been inconsistent. Thus, the purpose of the present study was to explore potential mechanisms of altered cognitive function networks during resting-state between remitted major depressive disorder (rMDD) patients and healthy controls (HCs) and furthermore, the relationship between dysfunctional connectivity patterns in rMDD and clinical symptoms.

METHODOLOGY

In this study, 19 HCs and 19 rMDD patients were recruited for resting-state functional magnetic resonance imaging (fMRI) scanning. FC was evaluated with independent component analysis for CEN, DMN and SN. Two sample t tests were conducted to compare differences between rMDD and HCs. A Pearson correlation analysis was also performed to examine the relationship between connectivity of networks and cognitive function scores and clinical symptoms.

RESULTS

Compared to healthy controls, remitted patients showed lower connectivity in CEN, mostly in the superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior parietal lobule (IPL) and part of the supramarginal gyrus (SMG). Conversely, the bilateral insula, part of the SMG (a key node of the CEN) and dorsal anterior cingulate cortex (dACC) of the DMN showed higher connectivity in rMDD patients. Pearson correlation results demonstrated that connectivity of the right IPL in CEN was positively correlated with cognitive function scores, and connectivity of the left insula was negatively correlated with BDI scores.

CONCLUSIONS

Though rMDD patients reached the standard of clinal remission, unique impairments of FC in cognitive function networks remained. Aberrant FC between cognitive function networks responsible for executive control was observed in rMDD and may be associated with residual clinical symptoms.

Frequency-Specific Changes in the Fractional Amplitude of the Low-Frequency Fluctuations in the Default Mode Network in Medication-Free Patients With Bipolar II Depression: A Longitudinal Functional MRI Study

Objective: This study aimed to examine the treatment-related changes of the fractional amplitude of low-frequency fluctuations (fALFF) in the default mode network (DMN) across different bands after the medication-free patients with bipolar II depression received a 16-week treatment of escitalopram and lithium. Methods: A total of 23 medication-free patients with bipolar II depression and 29 healthy controls (HCs) were recruited. We evaluated the fALFF values of slow 4 (0.027-0.073 Hz) band and slow 5 (0.01-0.027 Hz) band of the patients and compared the results with those of the 29 HCs at baseline. After 16-week treatment of escitalopram with lithium, the slow 4 and slow 5 fALFF values of the patients were assessed and compared with the baselines of patients and HCs. The depressive symptoms of bipolar II depression in patients were assessed with a 17-item Hamilton Depression Rating Scale (HDRS) before and after treatment. Results: Treatment-related effects showed increased slow 5 fALFF in cluster D (bilateral medial superior frontal gyrus, bilateral superior frontal gyrus, right middle frontal gyrus, and bilateral anterior cingulate), cluster E (bilateral precuneus/posterior cingulate, left cuneus), and cluster F (left angular, left middle temporal gyrus, left superior temporal gyrus, and left supramarginal gyrus) in comparison with the baseline of the patients. Moreover, a positive association was found between the increase in slow 5 fALFF values (follow-up value minus the baseline values) in cluster D and the decrease in HDRS scores (baseline HDRS scores minus follow-up HDRS scores) at follow-up, and the same association between the increase in slow 5 fALFF values and the decrease in HDRS scores was found in cluster E. Conclusions: The study reveals that the hypoactivity of slow 5 fALFF in the DMN is related to depression symptoms and might be corrected by the administration of escitalopram with lithium, implying that slow 5 fALFF of the DMN plays a key role in bipolar depression.

In vivo metabotropic glutamate receptor 5 availability-associated functional connectivity alterations in drug-naïve young adults with major depression

There has been increasing interest in glutamatergic neurotransmission as a putative underlying mechanism of depressive disorders. We performed [¹¹C]ABP688 positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) in drug-naïve young adult patients with major depression to examine alterations in metabotropic glutamate receptor-5 (mGluR5) availability, and to investigate their functional significance relating to neural systems-level changes in major depression. Sixteen psychotropic drug-naïve patients with major depression without comorbidity (median age: 22.8 years) and fifteen matched healthy controls underwent [¹¹C]ABP688 PET imaging and 3-T MRI. For mGluR5 availability, we quantified [¹¹C]ABP688 binding potential (BP_ND) using the simplified reference tissue model. Seed-based functional connectivity analysis was performed using rs-fMRI data with regions derived from quantitative [¹¹C]ABP688 PET analysis as seeds. In region-of-interest (ROI)-based and voxel-based analyses, the [¹¹C]ABP688 BP_ND was significantly lower in patients than in controls in the prefrontal cortex ROI and in voxel clusters within the prefrontal, temporal, and parietal cortices, and supramarginal gyrus. The [¹¹C]ABP688 BP_ND seed-based functional connectivity analysis showed significantly less negative connectivity from the inferior parietal cortex seed to the fusiform gyrus and inferior occipital cortex in patients than in controls. The correlation patterns between [¹¹C]ABP688 BP_ND and functional connectivity strength (β) for the superior prefrontal cortex seed were opposite in the depression and control groups. In conclusion, using a novel approach combining [¹¹C]ABP688 PET and rs-fMRI analyses, our study provides a first evidence of lower mGluR5 availability and related functional connectivity alterations in drug-naïve young adults with major depression without comorbidity.

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.

Resting-state dynamics as a neuromarker of dopamine administration in healthy female adults

BACKGROUND

Different neuromarkers of people's emotions, personality traits and behavioural performance have recently been identified. However, not much attention has been devoted to neuromarkers of neural responsiveness to drug administration.

AIMS

We investigated the predictive neuromarkers of acute dopamine (DA) administration.

METHODS

In a double-blind, within-subject study, we administrated a DA agonist (pramipexole) or placebo to 27 healthy female subjects. Using multivariate classification and prediction analyses, we examined whether dopaminergic modulations of task-free resting-state brain dynamics predict individual differences in pramipexole's modulation of facial attractiveness evaluations.

RESULTS

Our results demonstrate that pramipexole's effects on brain dynamics could be successfully discriminated from resting-state functional connectivity (accuracy: 78.9%; p < 0.0001). On the behavioural level, pramipexole increased facial attractiveness evaluations (t₍₃₉₎ = 4.44; p < 0.0001). In particular, pramipexole administration enhanced connectivity strength of the cinguloopercular network (t₍₂₃₎ = 3.29; p = 0.003) and increased brain signal variability in subcortical and prefrontal brain areas (t₍₁₃₎ = 3.05, p = 0.009). Importantly, multivariate predictive models reveal that pramipexole-dependent modulation of resting-state dynamics predicted the increase of facial attractiveness evaluations after pramipexole (connectivity strength: standardized mean squared error, smse = 0.65; p = 0.0007; brain signal variability: smse = 0.94, p = 0.015).

CONCLUSION

These results demonstrate that modulations of resting-state brain dynamics induced by a DA agonist predict drug-related effects on evaluation processes, providing a neuromarker of the neural responsiveness of specific brain networks to DA administration.

Cholinergic and serotonergic modulation of resting state functional brain connectivity in Alzheimer's disease

Disruption of cholinergic and serotonergic neurotransmitter systems is associated with cognitive, emotional and behavioural symptoms of Alzheimer's disease (AD). To investigate the responsiveness of these systems in AD we measured the effects of a single-dose of the selective serotonin reuptake inhibitor citalopram and acetylcholinesterase inhibitor galantamine in 12 patients with AD and 12 age-matched controls on functional brain connectivity with resting state functional magnetic resonance imaging. In this randomized, double blind, placebo-controlled crossover study, functional magnetic resonance images were repeatedly obtained before and after dosing, resulting in a dataset of 432 scans. Connectivity maps of ten functional networks were extracted using a dual regression method and drug vs. placebo effects were compared between groups with a multivariate analysis with signals coming from cerebrospinal fluid and white matter as covariates at the subject level, and baseline and heart rate measurements as confound regressors in the higher-level analysis (at p < 0.05, corrected). A galantamine induced difference between groups was observed for the cerebellar network. Connectivity within the cerebellar network and between this network and the thalamus decreased after galantamine vs. placebo in AD patients, but not in controls. For citalopram, voxelwise network connectivity did not show significant group × treatment interaction effects. However, we found default mode network connectivity with the precuneus and posterior cingulate cortex to be increased in AD patients, which could not be detected within the control group. Further, in contrast to the AD patients, control subjects showed a consistent reduction in mean connectivity with all networks after administration of citalopram. Since AD has previously been characterized by reduced connectivity between the default mode network and the precuneus and posterior cingulate cortex, the effects of citalopram on the default mode network suggest a restoring potential of selective serotonin reuptake inhibitors in AD. The results of this study also confirm a change in cerebellar connections in AD, which is possibly related to cholinergic decline.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Abnormalities in functional connectivity in borderline personality disorder: Correlations with metacognition and emotion dysregulation

A few studies reported functional abnormalities at rest in borderline personality disorder (BPD), but their relationship with clinical aspect is unclear. We aimed to assess functional connectivity (FC) in BPD patients and its association with BPD clinical features. Twenty-one BPD patients and 14 healthy controls (HC) underwent a multidimensional assessment and resting-state fMRI. Independent component analysis was performed to identify three resting-state networks: default mode network (DMN), salience network (SN), and executive control network (ECN). FC differences between BPD and HC were assessed with voxel-wise two-sample t-tests. Additionally, we investigated the mean FC within each network and the relationship between connectivity measures and BPD clinical features. Patients showed significant lower mean FC in the DMN and SN, while, at the local level, a cluster of lower functional connectivity emerged in the posterior cingulate cortex of the DMN. The DMN connectivity was positively correlated with the anger-state intensity and expression, while the SN connectivity was positively correlated with metacognitive abilities and a negative correlation emerged with the interpersonal aggression. The dysfunctional connectivity within these networks might explain clinical features of BPD patients.

Functional Connectivity of Brain Regions According to Resting State fMRI: Differences between Healthy and Depressed Subjects and Variability of the Results

In depressed patients, changes in spontaneous brain activity, in particular, the strength of functional connectivity between different regions are observed. The data on changes in the synchrony of different regions of interest in the brain can serve as markers of depressive symptoms and as the targets for the corresponding therapy. The study involved 21 patients with mild depression and 21 healthy volunteers; by the time of second fMRI scanning, 15 and 19 subjects, respectively). The subjects underwent two 4-min sessions of resting state fMRI with 2-4 months interval between the recordings; on the basis of these data, functional connectivity between regions of interest was assessed. During the first session, depressed patients demonstrated more pronounced connection between the right frontal eye field and cerebellar area III. When the sample was restricted to subjects who underwent both fMRI sessions, depressed patients demonstrated closer relations of the right parietal operculum and cerebellar vermis area VIII. During the second recording, healthy subjects showed stronger connectivity between more than 20 frontal, temporal, and subcortical regions of interest and cerebellum area II. In healthy participants, brainstem functional interactions increased from the first to the second fMRI-recording. In depressed subjects a number of cortical areas split from left intraparietal sulcus, but the left temporal cortex became more intra-connected. The results confirm the differences in functional connectivity between depressed and healthy subjects. At the same time, attention should be paid to the variability of the data obtained.

Differential effects of oxycodone and venlafaxine on resting state functional connectivity-A randomized placebo-controlled magnetic resonance imaging study

AIM

Different mechanisms may be involved in the antinociceptive effects of oxycodone (opioid) and venlafaxine (serotonin-norepinephrine reuptake inhibitor), and the aim of this study was to investigate the effect of these drugs on brain functional connectivity.

METHODS

Resting state functional magnetic resonance imaging was acquired in 20 healthy volunteers before and after a 5-day treatment with oxycodone, venlafaxine, or placebo in a randomized, double-blind, crossover study. Functional connectivity analyses were performed between four predefined seeds (dorsal anterior cingulate cortex, rostral anterior cingulate cortex, posterior insula, and prefrontal cortex), and the whole brain.

RESULTS

The overall interpretation was that there were differences between the effects of oxycodone and venlafaxine on functional connectivity. Oxycodone mainly showed decreased functional connectivity between limbic structures and to supralimbic areas (all P < 0.05). Venlafaxine also showed decreased functional connectivity between limbic structures and to supralimbic areas, but increased functional connectivity to structures in the midbrain and brain stem was also found (all P < 0.05).

CONCLUSIONS

Oxycodone and venlafaxine showed differential effects on resting-state functional connectivity as compared to placebo. This supports that the two drugs exert different mechanisms, and that the drugs in combination may exert additive effects and could potentially improve pain therapy.

The role of fMRI in drug development

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.

Common and distinct brain networks underlying panic and social anxiety disorders

Although panic disorder (PD) and phobic disorders are independent anxiety disorders with distinct sets of diagnostic criteria, there is a high level of overlap between them in terms of pathogenesis and neural underpinnings. Functional connectivity research using resting-state functional magnetic resonance imaging (rsfMRI) shows great potential in identifying the similarities and differences between PD and phobias. Understanding common and distinct networks between PD and phobic disorders is critical for identifying both specific and general neural characteristics of these disorders. We review recent rsfMRI studies and explore the clinical relevance of resting-state functional connectivity (rsFC) in PD and phobias. Although findings differ between studies, there are some meaningful, consistent findings. Social anxiety disorder (SAD) and PD share common default mode network alterations. Alterations within the sensorimotor network are observed primarily in PD. Increased connectivity in the salience network is consistently reported in SAD. This review supports hypotheses that PD and phobic disorders share common rsFC abnormalities and that the different clinical phenotypes between the disorders come from distinct brain functional network alterations.

Serotonergic and cholinergic modulation of functional brain connectivity: A comparison between young and older adults

Aging is accompanied by changes in neurotransmission. To advance our understanding of how aging modifies specific neural circuitries, we examined serotonergic and cholinergic stimulation with resting state functional magnetic resonance imaging (RS-fMRI) in young and older adults. The instant response to the selective serotonin reuptake inhibitor citalopram (30 mg) and the acetylcholinesterase inhibitor galantamine (8 mg) was measured in 12 young and 17 older volunteers during a randomized, double blind, placebo-controlled, crossover study. A powerful dataset consisting of 522 RS-fMRI scans was obtained by acquiring multiple scans per subject before and after drug administration. Group × treatment interaction effects on voxelwise connectivity with ten functional networks were investigated (p < .05, FWE-corrected) using a non-parametric multivariate analysis technique with cerebrospinal fluid, white matter, heart rate and baseline measurements as covariates. Both groups showed a decrease in sensorimotor network connectivity after citalopram administration. The comparable findings after citalopram intake are possibly due to relatively similar serotonergic systems in the young and older subjects. Galantamine altered connectivity between the occipital visual network and regions that are implicated in learning and memory in the young subjects. The lack of a cholinergic response in the elderly might relate to the well-known association between cognitive and cholinergic deterioration at older age.

Treatment Associated Changes of Functional Connectivity of Midbrain/Brainstem Nuclei in Major Depressive Disorder

Previous functional magnetic resonance imaging (fMRI) studies demonstrated an abnormally coordinated network functioning in Major Depression Disorder (MDD) during rest. The main monoamine-producing nuclei within midbrain/brainstem are functionally integrated within these specific networks. Therefore, we aimed to investigate the resting-state functional connectivity (RSFC) of these nuclei in 45 MDD patients and differences between patients receiving two different classes of antidepressant drugs. Patients showed reduced RSFC from the ventral tegmental area (VTA) to dorsal anterior cingulate cortex (dACC) and stronger RSFC to the left amygdala and dorsolateral prefrontal cortex (DLPFC). Patients treated with antidepressants influencing noradrenergic and serotonergic neurotransmission showed different RSFC from locus coeruleus to DLPFC compared to patients treated with antidepressants influencing serotonergic neurotransmission only. In the opposite contrast patients showed stronger RSFC from dorsal raphe to posterior brain regions. Enhanced VTA-RSFC to amygdala as a central region of the salience network may indicate an over‐attribution of the affective salience to internally-oriented processes. Significant correlation between decreased VTA-dACC functional connectivity and the BDI-II somatic symptoms indicates an association with diminished volition and behavioral activation in MDD. The observed differences in the FC of the midbrain/brainstem nuclei between two classes of antidepressants suggest differential neural effects of SSRIs and SNRIs.

Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex

Background

Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown.

Methods

Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity.

Results

Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network.

Conclusions

These results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients.

Imaging TMS: antidepressant mechanisms and treatment optimization

With the antidepressant efficacy of Transcranial Magnetic Stimulation well-established by several meta-analyses, there is growing interest in its mechanism of action. TMS has been shown to engage, and in some cases, normalize functional connectivity and neurotransmitter levels within networks dysfunctional in the depressed state. In this review, I will suggest candidate biomarkers, based on neuroimaging, that may be predictive of response to TMS. I will then review the effects of TMS on networks and neurotransmitter systems involved in depression. Throughout, I will also discuss how our current understanding of response predication and network engagement may be used to personalize treatment and optimize its efficacy.

Network-Guided Transcranial Magnetic Stimulation for Depression

PURPOSE OF REVIEW

First, we will identify candidate predictive biomarkers of antidepressant response of TMS based on the neuroimaging literature. Next, we will review the effects of TMS on networks involved in depression. Finally, we will discuss ways in which our current understanding of network engagement by TMS may be used to optimize its antidepressant effect.

RECENT FINDINGS

The past few years has seen significant interest in the antidepressant mechanisms of TMS. Studies using functional neuroimaging and neurochemical imaging have demonstrated engagement of networks known to be important in depression. Current evidence supports a model whereby TMS normalizes network function gradually over the course of several treatments. This may, in turn, mediate its antidepressant effect.

SUMMARY

One strategy to optimize the antidepressant effect of TMS is to more precisely target networks relevant in depression. We propose methods to achieve this using functional and neurochemical imaging.

Time related effects on functional brain connectivity after serotonergic and cholinergic neuromodulation

Psychopharmacological research, if properly designed, may offer insight into both timing and area of effect, increasing our understanding of the brain's neurotransmitter systems. For that purpose, the acute influence of the selective serotonin reuptake inhibitor citalopram (30 mg) and the acetylcholinesterase inhibitor galantamine (8 mg) was repeatedly measured in 12 healthy young volunteers with resting state functional magnetic resonance imaging (RS‐fMRI). Eighteen RS‐fMRI scans were acquired per subject during this randomized, double blind, placebo‐controlled, crossover study. Within‐group comparisons of voxelwise functional connectivity with 10 functional networks were examined (P < 0.05, FWE‐corrected) using a non‐parametric multivariate approach with cerebrospinal fluid, white matter, heart rate, and baseline measurements as covariates. Although both compounds did not change cognitive performance on several tests, significant effects were found on connectivity with multiple resting state networks. Serotonergic stimulation primarily reduced connectivity with the sensorimotor network and structures that are related to self‐referential mechanisms, whereas galantamine affected networks and regions that are more involved in learning, memory, and visual perception and processing. These results are consistent with the serotonergic and cholinergic trajectories and their functional relevance. In addition, this study demonstrates the power of using repeated measures after drug administration, which offers the chance to explore both combined and time specific effects. Hum Brain Mapp 38:308–325, 2017. © 2016 Wiley Periodicals, Inc.

Brain Functional Effects of Psychopharmacological Treatment in Major Depression: a Focus on Neural Circuitry of Affective Processing

In the last two decades, neuroimaging research has reached a much deeper understanding of the neurobiological underpinnings of major depression (MD) and has converged on functional alterations in limbic and prefrontal neural networks, which are mainly linked to altered emotional processing observed in MD patients. To date, a considerable number of studies have sought to investigate how these neural networks change with pharmacological antidepressant treatment. In the current review, we therefore discuss results from a) pharmacological functional magnetic resonance imaging (fMRI) studies investigating the effects of selective serotonin or noradrenalin reuptake inhibitors on neural activation patterns in relation to emotional processing in healthy individuals, b) treatment studies in patients with unipolar depression assessing changes in neural activation patterns before and after antidepressant pharmacotherapy, and c) predictive neural biomarkers of clinical response in depression. Comparing results from pharmacological fMRI studies in healthy individuals and treatment studies in depressed patients nicely showed parallel findings, mainly for a reduction of limbic activation in response to negative stimuli. A thorough investigation of the empirical findings highlights the importance of the specific paradigm employed in every study which may account for some of the discrepant findings reported in treatment studies in depressed patients.

Resting state default mode network connectivity in children and adolescents with ADHD after acute tryptophan depletion

OBJECTIVE

Alterations of the default mode network (DMN) have been described in patients with neuropsychiatric disorders, including attention deficit hyperactivity disorder (ADHD), and the neurotransmitter serotonin (5-HT) is known to modulate DMN activity. This study aimed to explore the role of 5-HT on the DMN and its functional connectivity (FC) in young patients with ADHD.

METHODS

Young male patients with ADHD (n = 12) and healthy controls (n = 10) (both aged 12-17 years) were subjected to acute tryptophan depletion (ATD) and subsequently diminished brain 5-HT synthesis. Three hours after challenge intake (ATD or a balanced control condition, BAL), resting state fMRI scans were obtained.

RESULTS

In patients, ATD led to attenuated FC of the right superior premotor cortex (BA 6) with the DMN, comparable to the extent found in controls after BAL administration. ATD lowered FC of the left somatosensory cortex (BA 3) with the DMN, independently of the factor group, but with stronger effects in controls.

CONCLUSIONS

Data reveal a serotonergic modulation of FC between BA 6 and 3, known to be relevant for motor planning and sensory perception, and the DMN, thereby possibly pointing toward ATD acting beneficially on neural planning of motor activity in patients with ADHD.

Resting functional connectivity in social anxiety disorder and the effect of pharmacotherapy

Neuroimaging research has reported differences in resting-state functional connectivity (RFC) between social anxiety disorder (SAD) patients and healthy controls (HCs). Limited research has examined the effect of treatment on RFC in SAD. We performed a study to identify differences in RFC between SAD and HC groups, and to investigate the effect of pharmacotherapy on RFC in SAD. Seed-based RFC analysis was performed on technetium-99m hexamethylpropylene amine oxime (Tc-99m HMPAO) SPECT scans using a cross-subject approach in SPM-12. Seeds were chosen to represent regions in a recently published network model of SAD. A second-level regression analysis was performed to further characterize the underlying relationships identified in the group contrasts. Twenty-three SAD participants were included, of which 18 underwent follow-up measures after an 8-week course of citalopram or moclobemide. Fifteen healthy control (HC) scans were included. SAD participants at baseline demonstrated several significant connectivity disturbances consistent with the existing network model as well as one previously unreported finding (increased connectivity between cerebellum and posterior cingulate cortex). After therapy, the SAD group demonstrated significant increases in connectivity with dorsal anterior cingulate cortex which may explain therapy-induced modifications in how SAD sufferers interpret emotions in others and improvements in self-related and emotional processing.

Inter-individual differences in the experience of negative emotion predict variations in functional brain architecture

Current evidence suggests that two spatially distinct neuroanatomical networks, the dorsal attention network (DAN) and the default mode network (DMN), support externally and internally oriented cognition, respectively, and are functionally regulated by a third, frontoparietal control network (FPC). Interactions among these networks contribute to normal variations in cognitive functioning and to the aberrant affective profiles present in certain clinical conditions, such as major depression. Nevertheless, their links to non-clinical variations in affective functioning are still poorly understood. To address this issue, we used fMRI to measure the intrinsic functional interactions among these networks in a sample of predominantly younger women (N=162) from the Human Connectome Project. Consistent with the previously documented dichotomous motivational orientations (i.e., withdrawal versus approach) associated with sadness versus anger, we hypothesized that greater sadness would predict greater DMN (rather than DAN) functional dominance, whereas greater anger would predict the opposite. Overall, there was evidence of greater DAN (rather than DMN) functional dominance, but this pattern was modulated by current experience of specific negative emotions, as well as subclinical depressive and anxiety symptoms. Thus, greater levels of currently experienced sadness and subclinical depression independently predicted weaker DAN functional dominance (i.e., weaker DAN-FPC functional connectivity), likely reflecting reduced goal-directed attention towards the external perceptual environment. Complementarily, greater levels of currently experienced anger and subclinical anxiety predicted greater DAN functional dominance (i.e., greater DAN-FPC functional connectivity and, for anxiety only, also weaker DMN-FPC coupling). Our findings suggest that distinct affective states and subclinical mood symptoms have dissociable neural signatures, reflective of the symbiotic relationship between cognitive processes and emotional states.

Single-dose serotonergic stimulation shows widespread effects on functional brain connectivity

The serotonergic system is widely distributed throughout the central nervous system. It is well known as a mood regulating system, although it also contributes to many other functions. With resting state functional magnetic resonance imaging (RS-fMRI) it is possible to investigate whole brain functional connectivity. We used this non-invasive neuroimaging technique to measure acute pharmacological effects of the selective serotonin reuptake inhibitor sertraline (75 mg) in 12 healthy volunteers. In this randomized, double blind, placebo-controlled, crossover study, RS-fMRI scans were repeatedly acquired during both visits (at baseline and 3, 5, 7 and 9h after administering sertraline or placebo). Within-group comparisons of voxelwise functional connectivity with ten functional networks were examined (p<0.005, corrected) using a mixed effects model with cerebrospinal fluid, white matter, motion parameters, heart rate and respiration as covariates. Sertraline induced widespread effects on functional connectivity with multiple networks; the default mode network, the executive control network, visual networks, the sensorimotor network and the auditory network. A common factor among these networks was the involvement of the precuneus and posterior cingulate cortex. Cognitive and subjective measures were taken as well, but yielded no significant treatment effects, emphasizing the sensitivity of RS-fMRI to pharmacological challenges. The results are consistent with the existence of an extensive serotonergic system relating to multiple brain functions with a possible key role for the precuneus and cingulate.

Decreased Resting-State Connectivity between Neurocognitive Networks in Treatment Resistant Depression

Approximately one-third of patients with major depressive disorder (MDD) do not achieve remission after various treatment options and develop treatment resistant depression (TRD). So far, little is known about the pathophysiology of TRD. Studies in MDD patients showed aberrant functional connectivity (FC) of three "core" neurocognitive networks: the salience network (SN), cognitive control network (CCN), and default mode network (DMN). We used a cross-sectional design and performed resting-state FC MRI to assess connectivity of the SN, CCN, and both anterior and posterior DMN in 17 severe TRD, 18 non-TRD, and 18 healthy control (HC) subjects. Relative to both non-TRD and HC subjects, TRD patients showed decreased FC between the dorsolateral prefrontal cortex and angular gyrus, which suggests reduced FC between the CCN and DMN, and reduced FC between the medial prefrontal cortex and precuneus/cuneus, which suggests reduced FC between the anterior and posterior DMN. No significant differences in SN FC were observed. Our results suggest that TRD is characterized by a disturbance in neurocognitive networks relative to non-TRD and HC.

Amygdala and Dorsal Anterior Cingulate Connectivity during an Emotional Working Memory Task in Borderline Personality Disorder Patients with Interpersonal Trauma History

Working memory is critically involved in ignoring emotional distraction while maintaining goal-directed behavior. Antagonistic interactions between brain regions implicated in emotion processing, e.g., amygdala, and brain regions involved in cognitive control, e.g., dorsolateral and dorsomedial prefrontal cortex (dlPFC, dmPFC), may play an important role in coping with emotional distraction. We previously reported prolonged reaction times associated with amygdala hyperreactivity during emotional distraction in interpersonally traumatized borderline personality disorder (BPD) patients compared to healthy controls (HC): Participants performed a working memory task, while neutral versus negative distractors (interpersonal scenes from the International Affective Picture System) were presented. Here, we re-analyzed data from this study using psychophysiological interaction analysis. The bilateral amygdala and bilateral dorsal anterior cingulate cortex (dACC) were defined as seed regions of interest. Whole-brain regression analyses with reaction times and self-reported increase of dissociation were performed. During emotional distraction, reduced amygdala connectivity with clusters in the left dorsolateral and ventrolateral PFC was observed in the whole group. Compared to HC, BPD patients showed a stronger coupling of both seeds with a cluster in the right dmPFC and stronger positive amygdala connectivity with bilateral (para)hippocampus. Patients further demonstrated stronger positive dACC connectivity with left posterior cingulate, insula, and frontoparietal regions during emotional distraction. Reaction times positively predicted amygdala connectivity with right dmPFC and (para)hippocampus, while dissociation positively predicted amygdala connectivity with right ACC during emotional distraction in patients. Our findings suggest increased attention to task-irrelevant (emotional) social information during a working memory task in interpersonally traumatized patients with BPD.

Default mode network mechanisms of transcranial magnetic stimulation in depression

BACKGROUND

Repetitive transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for depression, but its underlying mechanism of action remains unknown. Abnormalities in two large-scale neuronal networks-the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN)-are consistent findings in depression and potential therapeutic targets for TMS. Here, we assessed the impact of TMS on activity in these networks and their relation to treatment response.

METHODS

We used resting state functional magnetic resonance imaging to measure functional connectivity within and between the DMN and CEN in 17 depressed patients, before and after a 5-week course of TMS. Motivated by prior reports, we focused on connectivity seeded from the DLPFC and the subgenual cingulate, a key region closely aligned with the DMN in depression. Connectivity was also compared with a cohort of 35 healthy control subjects.

RESULTS

Before treatment, functional connectivity in depressed patients was abnormally elevated within the DMN and diminished within the CEN, and connectivity between these two networks was altered. Transcranial magnetic stimulation normalized depression-related subgenual hyperconnectivity in the DMN but did not alter connectivity in the CEN. Transcranial magnetic stimulation also induced anticorrelated connectivity between the DLPFC and medial prefrontal DMN nodes. Baseline subgenual connectivity predicted subsequent clinical improvement.

CONCLUSIONS

Transcranial magnetic stimulation selectively modulates functional connectivity both within and between the CEN and DMN, and modulation of subgenual cingulate connectivity may play an important mechanistic role in alleviating depression. The results also highlight potential neuroimaging biomarkers for predicting treatment response.

Platelet serotonin transporter function predicts default-mode network activity

Background

The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.

Methods

A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (V_max) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet V_max.

Results

The present study demonstrates that increases in platelet V_max significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet V_max is related to global DMN activation and not intrinsic DMN connectivity.

Conclusion

This study provides evidence that platelet V_max predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal V_max coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

Imaging the pathophysiology of major depressive disorder - from localist models to circuit-based analysis

The neuroimaging literature of Major Depressive Disorder (MDD) has grown substantially over the last several decades, facilitating great advances in the identification of specific brain regions, neurotransmitter systems and networks associated with depressive illness. Despite this progress, fundamental questions remain about the pathophysiology and etiology of MDD. More importantly, this body of work has yet to directly influence clinical practice. It has long been a goal for the fields of clinical psychology and psychiatry to have a means of making objective diagnoses of mental disorders. Frustratingly little movement has been achieved on this front, however, and the 'gold-standard’ of diagnostic validity and reliability remains expert consensus. In light of this challenge, the focus of the current review is to provide a critical summary of key findings from different neuroimaging approaches in MDD research, including structural, functional and neurochemical imaging studies. Following this summary, we discuss some of the current conceptual obstacles to better understanding the pathophysiology of depression, and conclude with recommendations for future neuroimaging research.