Psychological resilience negatively correlates with resting-state brain network flexibility in young healthy adults: a dynamic functional magnetic resonance imaging study

Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease

Background

Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) are characterized by abnormal functional connectivity (FC) of default-mode network (DMN), salience network (SN), and central executive network (CEN). Static FC (sFC) and dynamic FC (dFC) combined with triple network model can better study the dynamic and static changes of brain networks, and improve its potential diagnostic value in the diagnosis of AD spectrum disorders.

Methods

Differences in sFC values and dFC variability patterns among the three brain networks of the three groups (53 AD patients, 40 aMCI patients, and 40 NCs) were computed by ANOVA using Gaussian Random Field theory (GRF) correction. The correlation between FC values (sFC values and dFC variability) in the three networks and cognitive scores (MMSE and MoCA) in AD and aMCI groups was analyzed separately.

Results

Within the DMN network, there were significant differences of sFC values in right/left medial superior frontal gyrus and dFC variability in left opercular part inferior frontal gyrus and right dorsolateral superior frontal gyrus among the three groups. Within the CEN network, there were significant differences of sFC values in left superior parietal gyrus. Within the SN network, there were significant differences of dFC variability in right Cerebelum_7b and left opercular part inferior frontal gyrus. In addition, there was a significant negative correlation between FC values (sFC values of CEN and dFC variability of SN) and MMSE and MoCA scores.

Conclusion

It suggests that sFC, dFC combined with triple network model can be considered as potential biomarkers for AD and aMCI.

Profile and mental health characterization of childhood overprotection/overcontrol experiences among Chinese university students: a nationwide survey

Introduction

The childhood experiences of being overprotected and overcontrolled by family members have been suggested to be potentially traumatic. However, the possible associated factors of these experiences among young people are still not well studied. This study aimed to partly fill such gaps by a relatively large, nationwide survey of Chinese university students.

Methods

A total of 5,823 university students across nine different provinces in China were included by the convenience sampling method in the data analyses. All participants completed the overprotection/overcontrol (OP/OC) subscale in a recently developed 33-item childhood trauma questionnaire (CTQ- 33). Data were also collected on all participants' socio-demographic profiles and characterization of mental health. Binary logistic regression was conducted to investigate the associated socio-demographic and psychological factors of OP/ OC.

Results

The prevalence of childhood OP/OC was estimated as 15.63% (910/5,823) based on a cutoff OP/OC subscale score of  ≥ 13. Binary logistic regression suggested that being male, being a single child, having depression, having psychotic-like experiences, lower family functioning, and lower psychological resilience were independently associated with childhood OP/OC experiences (all corrected-p < 0.05). The OP/OC was also positively associated with all the other trauma subtypes (abuses and neglects) in the CTQ-33, while there are both shared and unique associated factors between the OP/OC and other trauma subtypes. Post-hoc analyses suggested that OP/OC experiences were associated with depression in only females and associated with anxiety in only males.

Discussion

Our results may provide initial evidence that childhood OP/OC experiences would have negative effects on young people's mental health which merits further investigations, especially in clinical populations.

Enhanced rich club connectivity in mild or moderate depression after nonpharmacological treatment: A preliminary study

INTRODUCTION

It has been suggested that the rich club organization in major depressive disorder (MDD) was altered. However, it remained unclear whether the rich club organization could be served as a biomarker that predicted the improvement of clinical symptoms in MDD.

METHODS

The current study included 29 mild or moderate patients with MDD, who were grouped into a treatment group (receiving cognitive behavioral therapy or real-time fMRI feedback treatment) and a no-treatment group. Resting-state MRI scans were obtained for all participants. Graph theory was employed to investigate the treatment-related changes in network properties and rich club organization.

RESULTS

We found that patients in the treatment group had decreased depressive symptom scores and enhanced rich club connectivity following the nonpharmacological treatment. Moreover, the changes in rich club connectivity were significantly correlated with the changes in depressive symptom scores. In addition, the nonpharmacological treatment on patients with MDD increased functional connectivity mainly among the salience network, default mode network, frontoparietal network, and subcortical network. Patients in the no-treatment group did not show significant changes in depressive symptom scores and rich club organization.

CONCLUSIONS

Those results suggested that the remission of depressive symptoms after nonpharmacological treatment in MDD patients was associated with the increased efficiency of global information processing.

Frontal Alpha Asymmetry Argues for the Heterogeneity of Psychological Resilience

Depression is associated with frontal alpha asymmetry (FAA) and Psychological Resilience (PR), although in different ways. Only cursory attention has been given to how these three constructs interact despite the possible clinical and research implications of those associations. One limitation of recent research into these associations has been conceptualising PR as a unitary construct, whereas it has been shown to be multi-component. This study investigated the underlying components of PR, their correlations with FAA, and the effect that participants' depressive status had upon those correlations in a community sample of 54 males and 46 females aged between 18 yr and 75 years. Results confirmed the overall inverse association between total PR and depression for four of the original five PR components and for one of the two components found in this sample. Similarly, there were differences between the ways that FAA and PR components were associated, depending upon the depressive status of participants. Source localisation data indicated that the PR components were not uniformly correlated with alpha activity in the same brain regions. These findings of content, efficacy, and neurophysiological differences between the five components of PR and their associations with FAA argue against consideration of PR as a unitary construct.

Brain Connectivity Signature Extractions from TMS Invoked EEGs

(1) Background: The correlations between brain connectivity abnormality and psychiatric disorders have been continuously investigated and progressively recognized. Brain connectivity signatures are becoming exceedingly useful for identifying patients, monitoring mental health disorders, and treatment. By using electroencephalography (EEG)-based cortical source localization along with energy landscape analysis techniques, we can statistically analyze transcranial magnetic stimulation (TMS)-invoked EEG signals, for obtaining connectivity among different brain regions at a high spatiotemporal resolution. (2) Methods: In this study, we analyze EEG-based source localized alpha wave activity in response to TMS administered to three locations, namely, the left motor cortex (49 subjects), left prefrontal cortex (27 subjects), and the posterior cerebellum, or vermis (27 subjects) by using energy landscape analysis techniques to uncover connectivity signatures. We then perform two sample t-tests and use the (5 × 10^-5) Bonferroni corrected p-valued cases for reporting six reliably stable signatures. (3) Results: Vermis stimulation invoked the highest number of connectivity signatures and the left motor cortex stimulation invoked a sensorimotor network state. In total, six out of 29 reliable, stable connectivity signatures are found and discussed. (4) Conclusions: We extend previous findings to localized cortical connectivity signatures for medical applications that serve as a baseline for future dense electrode studies.

Evaluating test-retest reliability and sex-/age-related effects on temporal clustering coefficient of dynamic functional brain networks

The multilayer dynamic network model has been proposed as an effective method to understand the brain function. In particular, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of the topological stability of dynamic brain networks and shows potential in predicting altered brain functions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a data set from the Human Connectome Project (157 male and 180 female healthy adults; 22-37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels, (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, particularly within the default-mode and subcortical regions, and (3) temporal clustering coefficient of the subcortical subnetwork was positively correlated with age in young adults. The results of sex effects were robustly replicated in an independent REST-meta-MDD data set, while the results of age effects were not. Our findings suggest that the temporal clustering coefficient is a relatively reliable and reproducible approach for identifying individual differences in brain function, and provide evidence for demographically related effects on the human brain dynamic connectomes.

Sex moderates family history of alcohol use disorder and childhood maltreatment effects on an fMRI stop-signal task

Childhood maltreatment (CM) and a family history (FH) of alcohol use disorder (AUD) are each associated with increased impulsivity. However, their unique or shared brain targets remain unknown. Furthermore, both CM and FH demonstrate sex-dependent effects on brain and behavior. We hypothesized that CM and FH interact in brain regions involved in impulsivity with sex-dependent effects. 144 first-year college students (18-19 years old) with varying experiences of CM and/or FH but without current AUD performed an fMRI stop-signal task. We tested interactions between FH, CM, and sex on task performance and blood oxygen level-dependent (BOLD) signal during successful inhibitions. We examined correlations between BOLD response and psychiatric symptoms. Significant three-way interactions of FH, CM, and sex were detected for brain and behavioral data, largely driven by male subjects. In males, CM was associated with poorer response inhibition but only for those with less FH; males with higher levels of both CM and FH demonstrated better response inhibition. Three-way interaction effects on voxel-wise BOLD response during response inhibition were found in bilateral middle frontal gyrus, left inferior frontal gyrus, dorsomedial prefrontal cortex, and posterior cingulate cortex. Network-level analyses implicated the left frontoparietal network, executive control network, and default-mode network. Greater BOLD response in these networks correlated with lower depressive, impulsive, and attentional symptoms, reduced alcohol misuse, greater resilience scores, and heightened trait anxiety. The results highlight sex-divergent effects of heritable and environmental risk factors that may account for sex-dependent expression of psychopathology in response to risk factors.

Aberrant global and local dynamic properties in schizophrenia with instantaneous phase method based on Hilbert transform

BACKGROUND

Emerging functional imaging studies suggest that schizophrenia is associated with aberrant spatiotemporal interaction which may result in aberrant global and local dynamic properties.

METHODS

We investigated the dynamic functional connectivity (FC) by using instantaneous phase method based on Hilbert transform to detect abnormal spatiotemporal interaction in schizophrenia. Based on resting-state functional magnetic resonance imaging, two independent datasets were included, with 114 subjects from COBRE [51 schizophrenia patients (SZ) and 63 healthy controls (HCs)] and 96 from OpenfMRI (36 SZ and 60 HCs). Phase differences and instantaneous coupling matrices were firstly calculated at all time points by extracting instantaneous parameters. Global [global synchrony and intertemporal closeness (ITC)] and local dynamic features [strength of FC (sFC) and variability of FC (vFC)] were compared between two groups. Support vector machine (SVM) was used to estimate the ability to discriminate two groups by using all aberrant features.

RESULTS

We found SZ had lower global synchrony and ITC than HCs on both datasets. Furthermore, SZ had a significant decrease in sFC but an increase in vFC, which were mainly located at prefrontal cortex, anterior cingulate cortex, temporal cortex and visual cortex or temporal cortex and hippocampus, forming significant dynamic subnetworks. SVM analysis revealed a high degree of balanced accuracy (85.75%) on the basis of all aberrant dynamic features.

CONCLUSIONS

SZ has worse overall spatiotemporal stability and extensive FC subnetwork lesions compared to HCs, which to some extent elucidates the pathophysiological mechanism of schizophrenia, providing insight into time-variation properties of patients with other mental illnesses.

Temporal Stability of the Dynamic Resting-State Functional Brain Network: Current Measures, Clinical Research Progress, and Future Perspectives

Based on functional magnetic resonance imaging and multilayer dynamic network model, the brain network’s quantified temporal stability has shown potential in predicting altered brain functions. This manuscript aims to summarize current knowledge, clinical research progress, and future perspectives on brain network’s temporal stability. There are a variety of widely used measures of temporal stability such as the variance/standard deviation of dynamic functional connectivity strengths, the temporal variability, the flexibility (switching rate), and the temporal clustering coefficient, while there is no consensus to date which measure is the best. The temporal stability of brain networks may be associated with several factors such as sex, age, cognitive functions, head motion, circadian rhythm, and data preprocessing/analyzing strategies, which should be considered in clinical studies. Multiple common psychiatric disorders such as schizophrenia, major depressive disorder, and bipolar disorder have been found to be related to altered temporal stability, especially during the resting state; generally, both excessively decreased and increased temporal stabilities were thought to reflect disorder-related brain dysfunctions. However, the measures of temporal stability are still far from applications in clinical diagnoses for neuropsychiatric disorders partly because of the divergent results. Further studies with larger samples and in transdiagnostic (including schizoaffective disorder) subjects are warranted.

Age Related Functional Connectivity Signature Extraction Using Energy-Based Machine Learning Techniques

The study of brain connectivity plays an important role in understanding the functional organizations of the brain. It also helps to identify connectivity signatures that can be used for evaluating neural disorders and monitoring treatment efficacy. In this work, age-related changes in brain connectivity are studied to obtain aging signatures based on various modeling techniques. These include an energy-based machine learning technique to identify brain network interaction differences between two age groups with a large (30 years) age gap between them. Disconnectivity graphs and activation maps of the seven prominent resting-state networks (RSN) were obtained from functional MRI data of old and young adult subjects. Two-sample t-tests were performed on the local minimums with Bonferroni correction to control the family-wise error rate. These local minimums are connectivity states showing not only which brain regions but also how strong they are working together. They work as aging signatures that can be used to differentiate young and old groups. We found that the attention network's connectivity signature is a state with all the regions working together and young subjects have a stronger average connectivity among these regions. We have also found a common pattern between young and old subjects where the left and right brain regions of the frontal network are sometimes working separately instead of together. In summary, in this work, we combined machine learning and statistical approaches to extract connectivity signatures, which can be utilized to distinguish aging brains and monitor possible treatment efficacy.

Association between cognitive impairments and aberrant dynamism of overlapping brain sub-networks in unmedicated major depressive disorder: A resting-state MEG study

OBJECTIVE

Little is known about the pathogenesis underlying cognitive impairment in major depressive disorder (MDD). We aimed to explore the mechanisms of cognitive impairments among patients with MDD by investigating the dynamics of overlapping brain sub-networks.

METHODS

Forty unmedicated patients with MDD and 28 healthy controls (HC) were enrolled in this study. Cognitive function was measured using the Chinese versions of MATRICS Consensus Cognitive Battery (MCCB). All participants were scanned using a whole-head resting-state magnetoencephalography (MEG) machine. The dynamism of neural sub-networks was analyzed based on the detection of overlapping communities in five frequency bands of oscillatory brain signals.

RESULTS

MDD demonstrated poorer cognitive performance in six domains compared to HC. The difference in community detection (functional integration mode) in MDD was frequency-dependent. MDD showed significantly decreased community dynamics in all frequency bands compared to HC. Specifically, differences in the visual network (VN) and default mode network (DMN) were detected in all frequency bands, differences in the cognitive control network (CCN) were detected in the alpha2 and beta frequency bands, and differences in the bilateral limbic network (BLN) were only detected in the beta frequency band. Moreover, community dynamics in the alpha2 frequency band were positively correlated with verbal learning and reasoning problem solving abilities in MDD.

CONCLUSIONS

Our study found that decreasing in the dynamics of overlapping sub-networks may differ by frequency bands. The aberrant dynamics of overlapping neural sub-networks revealed by frequency-specific MEG signals may provide new information on the mechanism of cognitive impairments that result from MDD.

Problematic smartphone use is associated with differences in static and dynamic brain functional connectivity in young adults

Introduction

This study aimed to investigate the possible associations between problematic smartphone use and brain functions in terms of both static and dynamic functional connectivity patterns.

Materials and methods

Resting-state functional magnetic resonance imaging data were scanned from 53 young healthy adults, all of whom completed the Short Version of the Smartphone Addiction Scale (SAS-SV) to assess their problematic smartphone use severity. Both static and dynamic functional brain network measures were evaluated for each participant. The brain network measures were correlated the SAS-SV scores, and compared between participants with and without a problematic smartphone use after adjusting for sex, age, education, and head motion.

Results

Two participants were excluded because of excessive head motion, and 56.9% (29/51) of the final analyzed participants were found to have a problematic smartphone use (SAS-SV scores ≥ 31 for males and ≥ 33 for females, as proposed in prior research). At the global network level, the SAS-SV score was found to be significantly positively correlated with the global efficiency and local efficiency of static brain networks, and negatively correlated with the temporal variability using the dynamic brain network model. Large-scale subnetwork analyses indicated that a higher SAS-SV score was significantly associated with higher strengths of static functional connectivity within the frontoparietal and cinguloopercular subnetworks, as well as a lower temporal variability of dynamic functional connectivity patterns within the attention subnetwork. However, no significant differences were found when directly comparing between the groups of participants with and without a problematic smartphone use.

Conclusion

Our results suggested that problematic smartphone use is associated with differences in both the static and dynamic brain network organizations in young adults. These findings may help to identify at-risk population for smartphone addiction and guide targeted interventions for further research. Nevertheless, it might be necessary to confirm our findings in a larger sample, and to investigate if a more applicable SAS-SV cutoff point is required for defining problematic smartphone use in young Chinese adults nowadays.

Temporal Stability of Dynamic Default Mode Network Connectivity Negatively Correlates with Suicidality in Major Depressive Disorder

Previous studies have demonstrated that the suicidality in patients with major depressive disorder (MDD) is related to abnormal brain functional connectivity (FC) patterns. However, little is known about its relationship with dynamic functional connectivity (dFC) based on the assumption that brain FCs fluctuate over time. Temporal stabilities of dFCs within the whole brain and nine key networks were compared between 52 MDD patients and 21 age, sex-matched healthy controls (HCs) using resting-state functional magnetic resonance imaging and temporal correlation coefficients. The alterations in MDD were further correlated with the scores of suicidality item in the Hamilton Rating Scale for Depression (HAMD). Compared with HCs, the MDD patients showed a decreased temporal stability of dFC as indicated by a significantly decreased temporal correlation coefficient at the global level, as well as within the default mode network (DMN) and subcortical network. In addition, temporal correlation coefficients of the DMN were found to be significantly negatively correlated with the HAMD suicidality item scores in MDD patients. These results suggest that MDD may be characterized by excessive temporal fluctuations of dFCs within the DMN and subcortical network, and that decreased stability of DMN connectivity may be particularly associated with the suicidality in MDD.

Probing the association between resting-state brain network dynamics and psychological resilience

This study aimed at replicating a previously reported negative correlation between node flexibility and psychological resilience, that is, the ability to retain mental health in the face of stress and adversity. To this end, we used multiband resting-state BOLD fMRI (TR = .675 sec) from 52 participants who had filled out three psychological questionnaires assessing resilience. Time-resolved functional connectivity was calculated by performing a sliding window approach on averaged time series parcellated according to different established atlases. Multilayer modularity detection was performed to track network reconfigurations over time, and node flexibility was calculated as the number of times a node changes community assignment. In addition, node promiscuity (the fraction of communities a node participates in) and node degree (as proxy for time-varying connectivity) were calculated to extend previous work. We found no substantial correlations between resilience and node flexibility. We observed a small number of correlations between the two other brain measures and resilience scores that were, however, very inconsistently distributed across brain measures, differences in temporal sampling, and parcellation schemes. This heterogeneity calls into question the existence of previously postulated associations between resilience and brain network flexibility and highlights how results may be influenced by specific analysis choices.

Age-Related Decrease in Default-Mode Network Functional Connectivity Is Accelerated in Patients With Major Depressive Disorder

Major depressive disorder (MDD) is a common psychiatric disorder which is associated with an accelerated biological aging. However, little is known whether such process would be reflected by a more rapid aging of the brain function. In this study, we tested the hypothesis that MDD would be characterized by accelerated aging of the brain's default-mode network (DMN) functions. Resting-state functional magnetic resonance imaging data of 971 MDD patients and 902 healthy controls (HCs) was analyzed, which was drawn from a publicly accessible, multicenter dataset in China. Strength of functional connectivity (FC) and temporal variability of dynamic functional connectivity (dFC) within the DMN were calculated. Age-related effects on FC/dFC were estimated by linear regression models with age, diagnosis, and diagnosis-by-age interaction as variables of interest, controlling for sex, education, site, and head motion effects. The regression models revealed (1) a significant main effect of age in the predictions of both FC strength and dFC variability; and (2) a significant main effect of diagnosis and a significant diagnosis-by-age interaction in the prediction of FC strength, which was driven by stronger negative correlation between age and FC strength in MDD patients. Our results suggest that (1) both healthy participants and MDD patients experience decrease in DMN FC strength and increase in DMN dFC variability along age; and (2) age-related decrease in DMN FC strength may occur at a faster rate in MDD patients than in HCs. However, further longitudinal studies are still needed to understand the causation between MDD and accelerated aging of brain.

Altered Dynamic Functional Connectivity in Subcortical Ischemic Vascular Disease With Cognitive Impairment

Subcortical ischemic vascular disease (SIVD) can cause cognitive impairment and affect the static functional connectivity of resting functional magnetic resonance imaging (fMRI). Numerous previous studies have demonstrated that functional connectivities (FCs) fluctuate dynamically over time. However, little is known about the impact of cognitive impairment on brain dynamic functional connectivity (DFC) in SIVD patients with MCI. In the present study, the DFC analysis method was applied to the resting functional magnetic resonance imaging (fMRI) data of 37 SIVD controls (SIVD-Control) without cognitive impairment, 34 SIVD patients with amnestic MCI (SIVD-aMCI) and 30 SIVD patients with nonamnestic MCI (SIVD-naMCI). The results indicated that the cognitive impairment of SIVD mainly reduced the mean dwell time of State 3 with overall strong positive connections. The reduction degree of SIVD-aMCI was larger than that of SIVD-naMCI. The memory/execution function impairment of SIVD also changed the relationship between the mean dwell time of State 3 and the behavioral performance of the memory/execution task from significant to non-significant correlation. Moreover, SIVD-aMCI showed significantly lower system segregation of FC states than SIVD-Control and SIVD-naMCI. The system segregation of State 5 with overall weak connections was significantly positive correlated with the memory performance. The results may suggest that the mean dwell time of State 3 and the system segregation of State 5 may be used as important neural measures of cognitive impairments of SIVD.

Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders.

Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI.

Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI.

Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.

Evaluation on Long-Term Test-Retest Reliability of the Short-Form Childhood Trauma Questionnaire in Patients with Schizophrenia

Background

Many studies have reported an association between childhood trauma exposure and schizophrenia. Among these studies, the Short-form Childhood Trauma Questionnaire (CTQ-SF) is one of the most widely used measures of childhood trauma. However, little is known regarding the long-term reliability of the CTQ-SF, especially in patients with psychopathology.

Methods

The CTQ-SF was administered to 50 patients diagnosed with schizophrenia from a hospital in Changsha, Hunan, China. These patients were asked to re-complete the CTQ-SF when they were re-hospitalized or received outpatient treatments in the same hospital within 4 years of follow-up. Intraclass correlation coefficient (ICC) was used to assess test–retest reliability of the CTQ-SF over the intervals. Associations of the CTQ-SF with the Positive and Negative Syndrome Scale (PANSS) and Wechsler Adult Intelligence Scale (WAIS) were tested using Spearman correlation coefficients.

Results

Among the participants, 35 (70.0%) patients re-completed the CTQ-SF after an interval averaging 11.26 months. Excellent test–retest reliabilities (with ICC > 0.75) were found for the total CTQ-SF score (ICC = 0.772) as well as scores of the emotional abuse (ICC = 0.808), physical abuse (ICC = 0.756), sexual abuse (ICC = 0.877) and physical neglect (ICC = 0.751) subscales. Meanwhile, a moderate test–retest reliability was found for the emotional neglect subscale (ICC = 0.538). At both baseline and follow-up, no significant correlations (p > 0.05) were found between CTQ-SF scores and any other clinical assessments.

Conclusion

Our results suggest that CTQ-SF is reliable to assess childhood trauma exposures in schizophrenia over relatively long intervals, regardless of patients’ current symptoms and states of cognition.

Childhood trauma is linked to decreased temporal stability of functional brain networks in young adults

BACKGROUND

Both childhood trauma and disruptions in brain functional networks are implicated in the development of psychiatric disorders in early adulthood. However, the relationships between these two factors remain unclear. This study aimed to investigate whether and how childhood trauma would relate to changes of functional network dynamics in young adults.

METHODS

Resting-state functional magnetic resonance imaging data were collected from 53 young healthy adults, whose childhood trauma histories were assessed by the Childhood Trauma Questionnaire (CTQ). Network switching rate, a measure of stability of dynamic brain networks over time, was calculated at both global and local levels for each participant. Switching rates at both levels were compared between participants with and without childhood trauma, and further correlated with CTQ total score.

RESULTS

In the current sample, 19 (35.8%) participants reported a history of childhood trauma. At the global level, participants with childhood trauma showed significantly higher network switching rates than those without trauma (F = 10.021, p = 0.003). A significant positive correlation was found between network switching rates and CTQ scores in the entire sample (r = 0.378, p = 0.007). At the local level, these effects were mainly observed in the default-mode, fronto-parietal, cingulo-opercular, and occipital subnetworks.

CONCLUSIONS

Our study provides preliminary evidence for a possible long-term effect of childhood trauma on brain functional dynamism. These findings may have potential contributions to psychiatric disorders during adulthood.

Intracranial brain stimulation modulates fMRI-based network switching

The extent to which functional MRI (fMRI) reflects direct neuronal changes remains unknown. Using 160 simultaneous electrical stimulation (es-fMRI) and intracranial brain stimulation recordings acquired in 26 individuals with epilepsy (with varying electrode locations), we tested whether brain networks dynamically change during intracranial brain stimulation, aiming to establish whether switching between brain networks is reduced after intracranial brain stimulation. As the brain spontaneously switches between a repertoire of intrinsic functional network configurations and the rate of switching is likely increased in epilepsy, we hypothesised that intracranial stimulation would reduce the brain's switching rate, thus potentially normalising aberrant brain network dynamics. To test this hypothesis, we quantified the rate that brain regions changed networks over time in response to brain stimulation, using network switching applied to multilayer modularity analysis of time-resolved es-fMRI connectivity. Network switching and synchrony was decreased after the first brain stimulation, followed by a more consistent pattern of network switching over time. This change was commonly observed in cortical networks and adjacent to the electrode targets. Our results suggest that neuronal perturbation is likely to modulate large-scale brain networks, and multilayer network modelling may be used to inform the clinical efficacy of brain stimulation in epilepsy.

Acute Effect of Betel Quid Chewing on Brain Network Dynamics: A Resting-State Functional Magnetic Resonance Imaging Study

Betel quid (BQ) is one of the most popular addictive substances in the world. However, the neurophysiological mechanism underlying BQ addiction remains unclear. This study aimed to investigate whether and how BQ chewing would affect brain function in the framework of a dynamic brain network model. Resting-state functional magnetic resonance imaging scans were collected from 24 male BQ-dependent individuals and 26 male non-addictive healthy individuals before and promptly after chewing BQ. Switching rate, a measure of temporal stability of functional brain networks, was calculated at both global and local levels for each scan. The results showed that BQ-dependent and healthy groups did not significantly differ on switching rate before BQ chewing (F = 0.784, p = 0.381, analysis of covariance controlling for age, education, and head motion). After chewing BQ, both BQ-dependent (t = 2.674, p = 0.014, paired t-test) and healthy (t = 2.313, p = 0.029, paired t-test) individuals showed a significantly increased global switching rate compared to those before chewing BQ. Significant corresponding local-level effects were observed within the occipital areas for both groups, and within the cingulo-opercular, fronto-parietal, and cerebellum regions for BQ-dependent individuals. Moreover, in BQ-dependent individuals, switching rate was significantly correlated with the severity of BQ addiction assessed by the Betel Quid Dependence Scale scores (Spearman's rho = 0.471, p = 0.020) before BQ chewing. Our study provides preliminary evidence for the acute effects of BQ chewing on brain functional dynamism. These findings may provide insights into the neural mechanisms of substance addictions.

Altered Temporal Variability of Local and Large-Scale Resting-State Brain Functional Connectivity Patterns in Schizophrenia and Bipolar Disorder

Schizophrenia and bipolar disorder share some common clinical features and are both characterized by aberrant resting-state functional connectivity (FC). However, little is known about the common and specific aberrant features of the dynamic FC patterns in these two disorders. In this study, we explored the differences in dynamic FC among schizophrenia patients (n = 66), type I bipolar disorder patients (n = 53), and healthy controls (n = 66), by comparing temporal variabilities of FC patterns involved in specific brain regions and large-scale brain networks. Compared with healthy controls, both patient groups showed significantly increased regional FC variabilities in subcortical areas including the thalamus and basal ganglia, as well as increased inter-network FC variability between the thalamus and sensorimotor areas. Specifically, more widespread changes were found in the schizophrenia group, involving increased FC variabilities in sensorimotor, visual, attention, limbic and subcortical areas at both regional and network levels, as well as decreased regional FC variabilities in the default-mode areas. The observed alterations shared by schizophrenia and bipolar disorder may help to explain their overlapped clinical features; meanwhile, the schizophrenia-specific abnormalities in a wider range may support that schizophrenia is associated with more severe functional brain deficits than bipolar disorder. Together, these findings highlight the potentials of using dynamic FC as an objective biomarker for the monitoring and diagnosis of either schizophrenia or bipolar disorder.