Relation between patterns of intrinsic network connectivity, cognitive functioning, and symptom presentation in trauma-exposed patients with major depressive disorder

Triple network connectivity changes in patients with major depressive disorder versus healthy controls via structural network imaging after electroconvulsive therapy treatment

OBJECTIVE

To investigate the effect of electroconvulsive treatment (ECT) on dynamic structural network connectivity in major depressive disorder (MDD), based on the triple-network model.

METHODS

Twenty-one first-episode, drug-naïve patients with MDD and 21 age- and sex-matched healthy subjects were recruited. Bilateral electrical stimulation was performed thrice a week for a total of 4-5 weeks in the MDD group. MRI data were obtained, and triple-network structural connectivity was evaluated using source-based morphometry (SBM) analysis. A paired t-test was used to analyze structural connectivity differences between pre- and post-ECT MDD groups, one-way analysis was used to calculate three intrinsic network differences between HCs, pre- and post-ECT groups, and partial least squares structural equation modelling was used to investigate dynamic structural network connectivity (dSNC) across groups.

RESULTS

Pre-ECT patients with MDD exhibited significantly lower salience network (SN) structural connectivity (p = 0.010) than the healthy control (HC) group and after ECT therapy SN structural connectivity was significantly elevated (p = 0.002) in post-ECT group compared with pre-ECT. PLS-SEM analysis conducted on inter-network connectivity in the triple-network model indicated a significant difference between SN and central executive network (CEN) in all three groups. The HC and post-ECT MDD groups showed notable direct connectivity between the SN and default mode network (DMN), while the pre-ECT MDD group showed consequential pathological connectivity between the CEN and DMN. A mediation analysis revealed a significant indirect effect of the SN on the DMN through the CEN (β = 0.363, p = 0.008) only in the pre-ECT MDD group.

CONCLUSIONS

ECT may be an effective and minimally invasive treatment for addressing structural changes in the SN and direct communication abnormalities between the three core brain networks in patients with MDD, with possible beneficial correction of indirect connections.

Cognitive behavioral therapy may rehabilitate abnormally functional communication pattern among the triple-network in major depressive disorder: A follow-up study

BACKGROUND

Cognitive behavioral therapy (CBT) is an established treatment for Major Depressive Disorder (MDD). MDD is characterized by imbalanced communication patterns among three networks: the central executive network (CEN), the default mode network (DMN) and the salience network (SN). The effect of CBT in restoring communications among these networks in MDD is unknown.

METHODS

Thirty-three patients with MDD and 27 healthy controls (HC) participated in the study. Patients were treated with CBT. Resting-state functional magnetic resonance imaging (rs-fMRI) data were obtained in patients at three stages (T0: before treatment; T1: after 6 weeks CBT; T2: after 28 weeks CBT) and in HC (only T0). Both independent component analysis (ICA) and granger causality analysis (GCA) were used to explore dynamic causal communication patterns among the three networks (CEN, DMN, SN) over a course of CBT treatment.

RESULTS

In the HC group, the SN had an inhibitory causal effect on CEN; the CEN and DMN had an excitatory causal effect on the SN. The SN had an inhibitory causal effect on the CEN and the DMN; only the DMN had an excitatory causal effect on the SN in the MDD patients at the T0 stage. As the CBT treatment went on for MDD patients, the CEN restored excitatory causal effect on the SN, and the SN lost inhibitory effect on the DMN. This result mimicked the one found in the HC group. Four regions, left ventromedial prefrontal cortex (lvmPFC), posterior cingulate gyrus (PCC), right inferior parietal lobule (rIPL) and right insula, were implicated in mediating network communications.

LIMITATIONS

The findings should be considered preliminary given the small sample sizes, and assessed only one stage in HC subjects.

CONCLUSION

CBT may enhance the regulatory function of the SN, and rehabilitate the imbalanced brain network communication mode in the MDD. PCC, lvmPFC and rIPL may all be potential targets of CBT.

Dissociation, trauma, and borderline personality disorder

Dissociation is a complex phenomenon, which occurs in various clinical conditions, including dissociative disorders, (complex) post-traumatic stress disorder (CPTSD, PTSD), and borderline personality disorder (BPD). Traumatic stress is considered an important risk factor, while the etiology of dissociation is still debated. Next to traumatic experiences, temperamental and neurobiological vulnerabilities seem to contribute to the development of dissociation. Stress-related dissociation is a prevalent symptom of BPD, which may interfere with psychosocial functioning and treatment outcome. More research in the field is strongly needed to improve the understanding and management of this complex phenomenon. This article collection brings together research on dissociation and trauma, with a special focus on BPD or sub-clinical expressions of BPD. In this editorial, recent conceptualizations of dissociation and relevant previous research are introduced in order to provide a framework for this novel research.

Dissociation in Borderline Personality Disorder: Recent Experimental, Neurobiological Studies, and Implications for Future Research and Treatment

PURPOSE OF REVIEW

The aim of this review article is to give an overview over recent experimental neurobiological research on dissociation in borderline personality disorder (BPD), in order to inform clinicians and to stimulate further research. First, we introduce basic definitions and models that conceptualize dissociation from a transdiagnostic perspective. Then, we discuss recent findings in BPD.

RECENT FINDINGS

Stress-related dissociation is a key symptom of BPD, closely linked to other core domains of the disorder (emotion dysregulation, identity disturbances, and interpersonal disturbances). The understanding of neurobiological correlates of dissociation across different psychiatric disorders (e.g., dissociative disorders, post-traumatic stress disorder) is steadily increasing. At the same time, studies explicitly focusing on dissociation in BPD are still scarce. There is evidence for adverse effects of dissociation on affective-cognitive functioning (e.g., interference inhibition), body perception, and psychotherapeutic treatment response in BPD. On the neural level, increased activity in frontal regions (e.g., inferior frontal gyrus) and temporal areas (e.g., inferior and superior temporal gyrus) during symptom provocation tasks and during resting state was observed, although findings are still diverse and need to be replicated. Conceptual differences and methodological differences in study designs and sample characteristics (e.g., comorbidities, trauma history) hinder a straightforward interpretation and comparison of studies. Given the potentially detrimental impact of dissociation in BPD, more research on the topic is strongly needed to deepen the understanding of this complex clinical condition.

Brain Networks Connectivity in Mild to Moderate Depression: Resting State fMRI Study with Implications to Nonpharmacological Treatment

Network mechanisms of depression development and especially of improvement from nonpharmacological treatment remain understudied. The current study is aimed at examining brain networks functional connectivity in depressed patients and its dynamics in nonpharmacological treatment. Resting state fMRI data of 21 healthy adults and 51 patients with mild or moderate depression were analyzed with spatial independent component analysis; then, correlations between time series of the components were calculated and compared between-group (study 1). Baseline and repeated-measure data of 14 treated (psychotherapy or fMRI neurofeedback) and 15 untreated depressed participants were similarly analyzed and correlated with changes in depression scores (study 2). Aside from diverse findings, studies 1 and 2 both revealed changes in within-default mode network (DMN) and DMN to executive control network (ECN) connections. Connectivity in one pair, initially lower in depression, decreased in no treatment group and was inversely correlated with Montgomery-Asberg depression score change in treatment group. Weak baseline connectivity in this pair also predicted improvement on Montgomery-Asberg scale in both treatment and no treatment groups. Coupling of another pair, initially stronger in depression, increased in therapy though was unrelated to improvement. The results demonstrate possible role of within-DMN and DMN-ECN functional connectivity in depression treatment and suggest that neural mechanisms of nonpharmacological treatment action may be unrelated to normalization of initially disrupted connectivity.

Biomarkers of Pathological Dissociation: A Systematic Review

Pathological dissociation is a severe, debilitating and transdiagnostic psychiatric symptom. This review identifies biomarkers of pathological dissociation in a transdiagnostic manner to recommend the most promising research and treatment pathways in support of the precision medicine framework. A total of 205 unique studies that met inclusion criteria were included. Studies were divided into four biomarker categories, namely neuroimaging, psychobiological, psychophysiological and genetic biomarkers. The dorsomedial and dorsolateral prefrontal cortex, bilateral superior frontal regions, (anterior) cingulate, posterior association areas and basal ganglia are identified as neurofunctional biomarkers of pathological dissociation and decreased hippocampal, basal ganglia and thalamic volumes as neurostructural biomarkers. Increased oxytocin and prolactin and decreased tumor necrosis factor alpha (TNF-α) are identified as psychobiological markers. Psychophysiological biomarkers, including blood pressure, heart rate and skin conductance, were inconclusive. For the genetic biomarker category studies related to dissociation were limited and no clear directionality of effect was found to warrant identification of a genetic biomarker. Recommendations for future research pathways and possible clinical applicability are provided.

Intranetwork and Internetwork Effects of Navigated Transcranial Magnetic Stimulation Using Low- and High-Frequency Pulse Application to the Dorsolateral Prefrontal Cortex: A Combined rTMS-fMRI Approach

PURPOSE

Although transcranial magnetic stimulation (TMS) is routinely applied in neuroscience and clinical settings, not much is known about its effects on brain networks. Therefore, this pilot study was set up using repetitive navigated transcranial magnetic stimulation (rTMS) combined with resting-state functional MRI (rs-fMRI) to explore frequency-dependent stimulation effects on an intranetwork and internetwork level.

METHODS

Six healthy subjects (median age: 23.5 years) underwent two rTMS sessions (1 and 10 Hz), 7 days apart, and prestimulation and poststimulation rs-fMRI. Repetitive navigated transcranial magnetic stimulation was delivered to the left dorsolateral prefrontal cortex, with the exact stimulation target being determined by independent component analysis. Alterations of functional connectivity strength were evaluated using seed-based correlation analyses within and between the salience network, central executive network, and posterior and anterior default mode network.

RESULTS

Low-frequency rTMS resulted in significant intranetwork alterations only for the anterior default mode network and primarily within the left hemisphere. In contrast, high-frequency rTMS led to changes within all four networks of interest. Moreover, the posterior and anterior default mode network largely showed opposite effects to rTMS, and the anterior default mode network was rather isolated from the other networks, which was especially true for low-frequency rTMS. Changes in functional connectivity strength because of low-frequency rTMS were even detectable 7 days after stimulation.

CONCLUSIONS

This is one of the first studies using neuronavigated TMS with independent component analysis-based target selection to explore frequency-dependent stimulation effects in a combined rTMS-fMRI approach. Future studies including higher subject numbers may define the underlying mechanisms for the different responses to low- and high-frequency rTMS.

Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach

Introduction

Developing a machine learning-based approach which could provide quantitative identification of major depressive disorder (MDD) is essential for the diagnosis and intervention of this disorder. However, the performances of traditional algorithms using static functional connectivity (SFC) measures were unsatisfactory. In the present work, we exploit the hidden information embedded in dynamic functional connectivity (DFC) and developed an accurate and objective image-based diagnosis system for MDD.

Methods

MRI images were collected from 99 participants including 56 healthy controls and 43 MDD patients. DFC was calculated using a sliding-window algorithm. A non-linear support vector machine (SVM) approach was then used with the DFC matrices as features to distinguish MDD patients from healthy controls. The spatiotemporal characteristics of the most discriminative features were then investigated.

Results

The area under the curve (AUC) of the SVM classifier with DFC measures reached 0.9913, while this value is only 0.8685 for the algorithm using SFC measures. Spatially, the most discriminative 28 connections distributed in the visual network (VN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), limbic network (LN), frontoparietal network (FPN), and default mode network (DMN), etc. Notably, a large portion of these connections were associated with the FPN, DMN, and VN. Temporally, the most discriminative connections transited from the cortex to deeper regions.

Conclusion

The results clearly suggested that DFC is superior to SFC and provide a reliable quantitative identification method for MDD. Our findings may furnish a better understanding of the neural mechanisms of MDD as well as improve accurate diagnosis and early intervention of this disorder.

Sluggish cognitive tempo and exposure to interpersonal trauma in children

Background: Childhood adversity has been suggested, but not yet empirically examined, as a factor in sluggish cognitive tempo (SCT) in childhood.Objective: This study was an examination of SCT in relation to childhood adversity, and its association with exposure to non-interpersonal and interpersonal trauma.Method: Caregivers (N = 161) and a sub-sample of children, 8-17 years old, were recruited from mental health and pediatric practices/programs and interviewed.Results: SCT was positively associated with interpersonal trauma but not non-interpersonal trauma. Two hierarchical regression analyses revealed that interpersonal trauma exposure was associated with SCT score over and above symptoms of other psychopathologies.Conclusion: Results suggest that SCT is associated with interpersonal trauma exposure in children. Further research is needed to examine the association between SCT and interpersonal trauma exposure, and trauma-related biopsychosocial impairments.

Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics

The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be “atoms of thought,” involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.

Resting regional brain activity correlates of verbal learning deficit in major depressive disorder

Memory deficits are reported in major depressive disorder (MDD). Prefrontal cortical and mesiotemporal cortical (MTC)/subcortical regions are involved in the Buschke Selective Reminding Task (SRT), a verbal list-learning task. To determine whether depression-related changes in resting brain metabolism explain (in part) the deficits in SRT performance found in MDD, statistical correlation maps were calculated between SRT total recall score (TR) and relative regional cerebral metabolic rate for glucose (rCMRglu), measured by [¹⁸F]-flourodeoxyglucose (FDG) positron emission tomography (PET), in unmedicated, depressed MDD patients (N = 29). Subsequently, to explore hypothesized loss of top-down control in MDD, we compared the correlations between rCMRglu of SRT-relevant regions of the dorsolateral prefrontal cortex (dlPFC) and amygdala in a larger cohort of MDD (N = 60; 29 inclusive) versus healthy controls (HC) (N = 43). SRT performance of patients is on average 0.5 standard deviation below published normative mean. TR and rCMRglu positively correlate in bilateral dorsomedial PFC, dlPFC, dorsal anterior cingulate; negatively correlate in bilateral MTC/subcortical regions, and cerebellum. rCMRglu in dlPFC correlates negatively with that in amygdala in HC but not in MDD. Depression-related changes present in FDG-PET measured resting brain activity may be in part responsible for memory deficit found in MDD.

Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks

BACKGROUND

Abnormal functional connectivity (FC) in the default mode network (DMN) plays an important role in late-onset depression (LOD) patients. In this study, the risk predictors of LOD based on anterior and posterior DMN are explored.

METHODS

A total of 27 LOD patients and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging and cognitive assessments. Firstly, FCs within DMN sub-networks were determined by placing seeds in the ventral medial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC). Secondly, multivariable logistic regression was used to identify risk factors for LOD patients. Finally, correlation analysis was performed to investigate the relationship between risk factors and the cognitive value.

RESULTS

Multivariable logistic regression showed that the FCs between the vmPFC and right middle temporal gyrus (MTG) (vmPFC-MTG_R), FCs between the vmPFC and left precuneus (PCu), and FCs between the PCC and left PCu (PCC-PCu_L) were the risk factors for LOD. Furthermore, FCs of the vmPFC-MTG_R and PCC-PCu_L correlated with processing speed (R = 0.35, P = 0.002; R = 0.32, P = 0.009), and FCs of the vmPFC-MTG_R correlated with semantic memory (R = 0.41, P = 0.001).

LIMITATIONS

The study was a cross-sectional study. The results may be potentially biased because of a small sample.

CONCLUSIONS

In this study, we confirmed that LOD patients mainly present cognitive deficits in processing speed and semantic memory. Moreover, our findings further suggested that FCs within DMN sub-networks associated with cognitions were risk factors, which may be used for the prediction of LOD.

Neural correlates of childhood trauma with executive function in young healthy adults

The aim of this study was to investigate the relationship among childhood trauma, executive impairments, and altered resting-state brain function in young healthy adults. Twenty four subjects with childhood trauma and 24 age- and gender-matched subjects without childhood trauma were recruited. Executive function was assessed by a series of validated test procedures. Localized brain activity was evaluated by fractional amplitude of low frequency fluctuation (fALFF) method and compared between two groups. Areas with altered fALFF were further selected as seeds in subsequent functional connectivity analysis. Correlations of fALFF and connectivity values with severity of childhood trauma and executive dysfunction were analyzed as well. Subjects with childhood trauma exhibited impaired executive function as assessed by Wisconsin Card Sorting Test and Stroop Color Word Test. Traumatic individuals also showed increased fALFF in the right precuneus and decreased fALFF in the right superior temporal gyrus. Significant correlations of specific childhood trauma severity with executive dysfunction and fALFF value in the right precuneus were found in the whole sample. In addition, individuals with childhood trauma also exhibited diminished precuneus-based connectivity in default mode network with left ventromedial prefrontal cortex, left orbitofrontal cortex, and right cerebellum. Decreased default mode network connectivity was also associated with childhood trauma severity and executive dysfunction. The present findings suggest that childhood trauma is associated with executive deficits and aberrant default mode network functions even in healthy adults. Moreover, this study demonstrates that executive dysfunction is related to disrupted default mode network connectivity.

Relation between patterns of intrinsic network connectivity, cognitive functioning, and symptom presentation in trauma-exposed patients with major depressive disorder

OBJECTIVE

The present study investigated resting fMRI connectivity within the default mode (DMN), salience (SN), and central executive (CEN) networks in relation to neurocognitive performance and symptom severity in trauma-exposed patients with major depressive disorder (MDD).

METHOD

Group independent component analysis was conducted among patients with MDD (n = 21), examining DMN, SN, and CEN connectivity in relation to neurocognitive performance and symptom severity. Activation in these networks was also compared between the patient group and healthy controls (n = 20).

RESULTS

Among the patient group, higher levels of performance on measures of verbal memory and executive functioning were related to increased connectivity within the DMN (i.e., inferior parietal lobe; precuneus). Greater depression severity was related to reduced connectivity between the SN and a node of the DMN (i.e., posterior cingulate cortex) and higher depersonalization symptoms were related to enhanced connectivity between the SN and a node of the DMN (i.e., middle temporal gyrus). Higher symptoms of depersonalization were also associated with reduced integration of the DMN with the medial frontal gyrus. Relative to controls, patients with MDD showed greater connectivity of the ventromedial prefrontal cortex within the DMN.

CONCLUSION

Intrinsic connectivity network patterns are related to cognitive performance and symptom presentation among trauma-exposed patients with MDD.