Large-scale brain networks and psychopathology: a unifying triple network model

Hippocampal connectivity changes after traumatic memory reactivation with propranolol for posttraumatic stress disorder: a randomized fMRI study

Background: Reactivation of traumatic memory under the influence of propranolol has shown encouraging clinical results in the treatment of posttraumatic stress disorder (PTSD), but the neural correlates remain unknown. To identify these correlates, we examined the changes in brain functional connectivity specifically associated with the influence of propranolol and their correlation with improvement in PTSD symptoms.Objectives: To identify resting-state functional connectivity (rs-FC) changes specifically associated with propranolol after a traumatic memory reactivation procedure (TMRP) in PTSD patients.Method: Thirty patients (50% of women) with PTSD were enrolled in a randomized controlled study comprised of six sessions of a traumatic memory reactivation procedure (TMRP) under the influence of propranolol (n = 16), compared to the same reactivation under a placebo (n = 14). Patients were scanned twice by functional magnetic resonance before and after treatment. Resting state functional connectivity (rs-FC) was compared across groups and over time.Results: Post versus pretreatment comparisons found an increase in rs-FC between the right hippocampus and the left parahippocampal gyrus in the propranolol group, but not in the placebo group. Symptom improvement in both groups were associated with an increase in rs-FC between the parahippocampal gyrus and both the supramarginal gyrus and the amygdala.Conclusions: During TMRP treatment, propranolol appears to constrain functional connectivity changes in the explicit memory brain system. These findings require further replication and exploration but could distinguish the effect of TMRP on the brain from other forms of PTSD psychotherapy.

Short-term exposure to PM2.5 and high pollution events on depressive symptoms among adolescents

Association between short-term exposure to fine particulate matter (PM2.5) and adolescent depressive symptoms is an under-investigated area and is worthy of further research. Based on a government surveillance data for 195,687 Chinese adolescents, the mixed-effects logistic regression combined with a distributed lag nonlinear model was used to assess the cumulative effect of PM2.5 exposure on depressive symptoms. In addition, high pollution events were defined according to World Health Organization (WHO) air quality guidelines (AQGs) and the Chinese ambient air quality standards, and the associations of increased high pollution events with depressive symptoms and the associated excess risk were estimated. Our results showed that association between short-term exposure to PM2.5 and depressive symptoms was most significant at lag 0 weeks, with each 10 μg/m3 increase in PM2.5 concentration associated with a 3.11 % (95 % CI: 0.70 %, 5.58 %) change in ORs for depressive symptoms. High pollution events were found to contribute to a maximum 3.12 % (95 % CI: 0.52 %, 5.74 %) excess risk of depressive symptoms when defined as 24-hour average PM2.5 concentration exceeding 37.5 μg/m3, WHO AQG interim target 3. Our results highlight the importance of air quality improvement for adolescent depression prevention, and recommend increased psychological support during high pollution events.

Altered Intra-Network Functional Connectivity Predicts the 6-Month Prognosis in Patients With Medication Overuse Headache: A Case-Control Study

BACKGROUND

Previous studies suggested that changes in functional connectivity (FC) within intrinsic resting-state networks (RSNs) might be associated with treatment responses during withdrawal in patients experiencing medication overuse headache (MOH). This study examined alterations in intra- and internetwork FC in intrinsic RSNs among MOH patients and explored the relationship between neuroimage changes and six-month prognoses.

METHODS

This case-control study enrolled healthy controls and MOH patients. Six months after implementing a withdrawal and preventive strategy, patients who had successfully discontinued overusing acute medications and reduced headache days by at least 50% from baseline were classified as having 'good outcome' and those not reaching this outcome were classified as having a 'poor outcome'. Changes in intra- and inter-network FC in intrinsic RSNs across groups at baseline were evaluated. Univariate and multivariate logistic regression analyses were conducted to identify independent alterations associated with good outcomes.

RESULTS

In the MOH group, 16 patients had poor outcomes and 17 patients had good outcomes. Compared to 24 healthy controls, all patients showed significantly increased FC in the left middle temporal gyrus of the left frontoparietal network (FPN). Furthermore, those with good outcomes had significantly decreased FC in the left orbital inferior frontal gyrus (IFG) of the left FPN compared to both poor outcome patients and healthy controls. Altered FC in the left orbital IFG of the left FPN was significantly associated with good outcomes and positively correlated with baseline headache intensity.

CONCLUSIONS

The altered FC in the left orbital IFG of the left FPN may be associated with MOH treatment prognosis.

SIGNIFICANCE

The present study provides evidence of the association between alterations of intra-network functional connectivity in intrinsic resting-state networks and six-month prognoses in patients with medication overuse headache. Our results imply potential neuroimaging biomarkers associated with the prognosis of medication overuse headache.

Functional dysconnectivity of the triple network in women with premenstrual syndrome

OBJECTIVE

Premenstrual syndrome (PMS) is a risk factor for female depression, linked to neural circuit dysfunction. This study investigates PMS-related brain network patterns, focusing on the triple network's integration and segregation.

MATERIALS & METHODS

The study enrolled 56 PMS patients and 67 healthy controls (HCs), assessed via the Daily Record of Severity of Problems (DRSP). Functional MRI (fMRI) was analyzed using independent component analysis (ICA) to calculate functional connectivity (FC) and functional network connectivity (FNC) within and between brain networks. Correlation analysis examined links between imaging metrics and DRSP scores.

RESULTS

Compared with HCs, PMS patients showed increased FC in the left inferior frontal gyrus of the salience network (SN). Additionally, there was increased FNC between the dorsal default mode network (dDMN), while a decrease was observed between the right execution network (RECN) and SN. Conversely, the FNC between RECN and dDMN was enhanced. Significant correlations were found between the FC values within the SN and DRSP scores. Similarly, the abnormal FNC pattern also correlated significantly with DRSP scores.

CONCLUSION

Triple-network dysconnectivity may serve as a biomarker for PMS, offering insights into its pathophysiology and potential targets for network-based neuromodulation therapies.

CLINICAL RELEVANCE STATEMENT

Identifying network dysconnectivities in PMS offers potential biomarkers for diagnosis and targets for neuromodulation therapy, ultimately improving symptom management and patient outcomes.

Association of node assortativity and internalizing symptoms with ketogenic diet effectiveness in pediatric patients with drug-resistant epilepsy

BACKGROUND

The ketogenic diet (KD) is an effective alternative therapy for drug-resistant epilepsy (DRE). However, there are no established predictors for KD effectiveness. We aimed to investigate the impact of 12 months of KD therapy (KDT) on brain connectivity, as measured by functional magnetic resonance imaging (fMRI), and its correlation with seizure control, behavioral/mood alterations, and parental stress.

METHODS

Children with DRE were enrolled in this single-center, prospective cohort study from February 2020 to October 2021. They were divided into a control group and a KDT group. The Child Behavior Checklist (CBCL) and Parental Stress Index (PSI) were administered to parents at the initiation of KDT (T0) and at 12 months (T1). Resting-state fMRI was performed at T0 and at 6 months of KDT. The primary outcome was the between-group difference in the change of CBCL/PSI scores, and brain connectivity metrics after KDT, and the secondary outcome involved measuring their correlation with seizure reduction rates.

RESULTS

Twenty-two patients with DRE were enrolled. We had 13 patients in the control group and 9 in the KDT group. Our data revealed that 12 months of KDT can reduce monthly seizure frequency. Several subscales of CBCL T-scores were higher at T0 compared with the control group, then becoming comparable at T1. The PSI scores from 'mothers' reports reduced after receiving KDT. The changes in node assortativity (ΔAssortativity) were positively correlated with behavioral problems and negatively with seizure reduction rates in the KD group.

CONCLUSIONS

Twelve months of KDT can reduce monthly seizure frequency and improve mood/behavioral disturbances in patients with DRE. Furthermore, KDT could relieve primary caregivers' stress. A lower ΔAssortativity value was associated with better behavioral outcomes and greater seizure reduction. The ΔAssortativity value in fMRI may be a crucial predictor for the effectiveness of KDT.

Increased frontoparietal activity related to lower performance in neuropsychological assessment of working memory

Executive functions, including working memory, are typically assessed clinically with neuropsychological instruments. In contrast, computerized tasks are used to test these cognitive functions in laboratory human and animal studies. Little is known of how neural activity captured by laboratory tasks relates to ability measured by clinical instruments and, by extension, clinical diagnoses of pathological conditions. We therefore sought to determine what aspects of neural activity elicited in laboratory tasks are predictive of performance in neuropsychological instruments. We recorded neural activity from intracranial electrodes implanted in human epilepsy patients as they performed laboratory working memory tasks. These patients had completed neuropsychological instruments preoperatively, including the Weschler Adult Intelligent Scale and the Wisconsin Card Sorting test. Our results revealed that increased high-gamma (70-150 Hz) power in the prefrontal and parietal cortex after presentation of visual stimuli to be remembered was indicative of lower performance in the neuropsychological tasks. On the other hand, we observed a positive correlation between high-frequency power amplitude in the delay period of the laboratory tasks and neuropsychological performance. Our results demonstrate how neural activity around task events relates to executive function and may be associated with clinical diagnosis of specific cognitive deficits.

Interbrain synchrony attenuation during a peer cooperative task in young children with autistic traits -an EEG hyperscanning study

Young children with autism spectrum disorder (ASD) traits frequently encounter difficulties in peer interaction. Assessing peer interaction performance is crucial but challenging within the clinical diagnostic paradigm of ASD. Hyperscanning, which simultaneously monitors brain activity in multiple individuals, has become a popular tool for assessing social interaction's neural features. The present study aims to investigate the brain-to-brain connectivity between child-dyads engaged in a game-like collaborative peer interaction task via the hyperscanning electroencephalogram (EEG) approach. The final sample comprised 66 young children: 18 child dyads with typical development (TD), TD-TD, and 15 with ASD traits matched to TD, TD-ASD. The study indicated a depressed level of connectivity in the dyad group with ASD as the responder, with a notable decrease observed in the beta oscillation over the right parietal to left temporal coupling between subjects. A pattern that differed from that observed in the TD-TD group was identified with regard to full-band connectivity over the right-to-right temporal region. It was observed that the TD-TD group exhibited enhanced connectivity following the completion of the task, which was not the case for the TD-ASD group. Significant correlations were observed between scores on the ASD symptom rating scale and the selected significant interbrain connectivity index. The application of a hyperscanning EEG paradigm demonstrated that the participating children with autistic traits exhibited an attenuated and apparently distinct alteration pattern of interbrain connectivity in comparison to a control group. These findings highlight the value of physiologically based measures in informing etiological and interventional studies in neuropsychiatry.

Altered brain network dynamics in motor functional neurological disorders: the role of the right temporo-parietal junction

Functional neurological disorders' (FND) neuropathophysiology has been described as multi-network disturbances including aberrancies in the agency network highlighting the role of the right temporo-parietal junction (rTPJ). Refining the relevance of the rTPJ, we applied a co-activation pattern (CAP) based approach using the rTPJ as a seed in 58 patients with motor FND compared to 58 age- and sex-matched healthy controls (HC). Firstly, CAPs were derived from HC to identify functional alterations in the rTPJ network in FND patients. Secondly, motor subgroup characteristics in patients were examined using CAPs derived from the patient group. Compared to HC, patients were found to enter less frequently a state characterized by salience network and default mode network (DMN) co-activation along with executive control and somatomotor networks co-deactivation. Additionally, patients entered more often a state depicted by somatomotor-salience co-activation and DMN co-deactivation. Comparing motor subgroups, patients with functional weakness (FW) remained longer in a state characterised by salience and dorsal/ventral attention network co-activation and DMN co-deactivation compared to patients with no functional weakness (no-FW). FND patients overall exhibited a reduced coupling of the DMN and an increased coupling of the somatomotor network with the rTPJ compared to controls. Patient subgroups differed regarding coupling between the rTPJ and the attention network and DMN. rTPJ dynamic network alterations might reflect hampered flexibility in brain state switching and altered self-referential processes linked to impaired motor planning and execution, which seem to also differ between symptom types, indicating a potential phenotypic biomarker.

Neurobiologically interpretable causal connectome for predicting young adult depression: A graph neural network study

BACKGROUND

There is a surprising lack of neuroimaging studies of depression that not only identify the whole brain causal connectivity features but also explore whether these features have neurobiological correlates.

METHODS

Three graph neural networks (GNN) models were applied to three types of causal connectomes (CCs): granger causality, regression DCM (rDCM), and TwoStep, obtained from a total of 1296 young adult participants in three large-scale datasets.

RESULTS

GNN models showed better performance for predicting depression when using causal connectomes such as TwoStep (average precision score, 0.882), granger causality (0.878), or rDCM (0.853) compared with using functional connectomes like Pearson's (0.850) and partial (0.823) correlation. Notably, nodal features derived only from rDCM and TwoStep showed spatial associations with positron emission tomography measures of receptors for neurotransmitters such as dopamine and serotonin. Further analysis revealed the shared directed edges among the subject's edge features, which included cortical causal connections in networks such as the default mode, control, dorsal attention, peripheral visual, and parietofrontal networks.

LIMITATIONS

The classification performance of leave-one-site-out cross-validation did not achieve a similar level with that of 10-fold cross-validation.

CONCLUSIONS

Our findings suggest that the connectomes derived from CCs using GNN, rather than functional connectomes, provide more accurate and neurobiologically relevant information for depression. Moreover, the observed spatial heterogeneity of this relevance and subject-specific edge features emphasizes the complexity of depression. These results have the potential to advance our understanding of depression's nature and potentially contribute to precision psychiatry by aiding in its diagnosis and treatment.

Salience network resting-state functional connectivity predicts self-controlled decision-making

Salience network functional integration with the central executive network and the default mode network at rest has been shown to predict real-life self-control. It has been proposed that a network interaction index reflecting stronger functional integration of the salience network with the central executive network and reduced functional connectivity of the salience network with the default mode network represents a trait neural correlate of successful self-control exertion. Here, we attempted to replicate this result using data from our own study where 121 participants completed an fMRI self-control task comprising real-life scenarios and data from a second study (N = 79) retrieved from OpenNeuro (dataset ID: ds002643) where participants completed an fMRI food choice task. We could not replicate the proposed role of salience network resting-state functional connectivity in self-controlled decision-making in either of those data sets. Instead, we found evidence for the exact opposite effect, specifically a negative association between self-control performance and the network interaction index. The role of analysis pipelines, appropriate network ROIs, and the measurement of self-control are discussed in the context of our findings.

Resting-state functional connectivity of the rostral and dorsal anterior cingulate cortex in older bereaved adults

BACKGROUND

Older adults are at higher risk of losing a loved one, with approximately 10 % developing prolonged grief disorder (PGD) after loss. PGD is characterized by distressing and impairing symptoms, reduced life quality, and increased suicide risk. While attentional processes may contribute to PGD pathophysiology, the rostral (rACC) and dorsal anterior cingulate cortex (dACC) appear to play different yet complementary roles in attention in the bereavement context. However, the respective contributions of the connectivity of these two regions in PGD symptom severity have never been evaluated. This study investigated the associations between PGD symptom severity and resting-state functional connectivity (rsFC) of the rACC and dACC.

METHODS

Resting-state fMRI scans were collected from N = 81 older adults who experienced loss >1 year prior, along with the inventory of complicated grief (ICG). Seed-based voxel-wise rsFC analysis was performed to investigate associations between ICG total scores and rsFC for the rACC and dACC.

RESULTS

Higher ICG scores were associated with increased rsFC between the rACC and left frontal areas and right rACC, and between the dACC and clusters in the posterior cingulate and parietal cortex. Individuals with probable PGD (ICG ≥ 30) exhibited greater increases in dACC-parietal cortex rsFC than those without (ICG < 30).

CONCLUSIONS

PGD symptom severity in bereaved older adults was associated with disruptions in rsFC patterns within and between brain regions related to impaired emotion regulation, memory processing, and attentional biases in grief, with stronger changes in individuals with probable PGD. These brain regions might serve as targets for future treatment development efforts.

Neural correlates of insomnia with depression and anxiety from a neuroimaging perspective: A systematic review

Insomnia affects a substantial proportion of the population and frequently co-occurs with mental illnesses including depression and anxiety. However, the neurobiological correlates of these disorders remain unclear. Here we review magnetic resonance imaging (MRI) studies assessing structural and functional brain associations with depressive and anxiety symptoms in insomnia disorder (ID; n = 38), insomnia symptoms in depressive and anxiety disorders (n = 14), and these symptoms in the general populations (n = 3). The studies on insomnia disorder consistently showed overlapping (salience network: insula and anterior cingulate cortex) and differential MRI correlation patterns between depressive (thalamus, orbitofrontal cortex and its associated functional connectivity) and anxiety (functional connectivity associated with default mode network) symptoms. The insula was also consistently identified as indicating the severity of insomnia symptoms in depressive disorder. In contrast, findings for other regions related to insomnia symptoms in both depressive and anxiety disorders were generally inconsistent across studies, partly due to variations in methods and patient cohorts. In the general population, brain regions in the default mode network provided a functional link between insomnia and depressive symptoms. These findings underscore both the shared and distinct neural correlates among depression, anxiety, and insomnia, providing potential avenues for the clinical management of these conditions.

Efficacy and neural mechanisms of approach bias modification training in patients with internet gaming disorder: A randomized clinical trial

BACKGROUND

Internet gaming disorder (IGD) is a prevalent behavioral addiction linked to neural alterations and significant negative outcomes. Approach bias modification (ApBM) training aims to correct imbalances in reflective and impulsive systems, reducing cravings and addictions. This study examined the effectiveness of ApBM training in IGD patients and explored the brain response changes associated with the intervention.

METHODS

Fifty-one patients with IGD were randomly assigned to an ApBM group (n = 26) or a sham-ApBM group (n = 25). Resting-state functional magnetic resonance imaging scans and behavioral assessments, including Internet Addiction Test scores, DSM-5 criteria, game craving levels, and automatic approach bias, were conducted before and after a ten-day training with five sessions. An analysis of variance (ANOVA) was employed to assess time (pre- and post-test) × group (ApBM group vs. sham-ApBM group) effects on behavioral measures. Functional connectivity (FC) analyses focused on regions of interest identified through regional homogeneity and degree centrality calculations. Additionally, we analyzed the relationship between neuroimaging variables and intervention outcomes.

RESULTS

Significant group × time interactions were found for automatic approach bias, Internet Addiction Test scores, DSM-5 criteria, and game craving levels. Post-training, these measures significantly decreased in the ApBM group but showed no significant changes in the sham-ApBM group. FC analysis revealed increased connectivity within executive control regions, enhanced connectivity between executive control and reward-related regions, and decreased connectivity within reward-related regions, exclusively in the ApBM group.

CONCLUSIONS

ApBM training effectively reduces gaming cravings in patients with IGD, enhancing executive control and mitigating impulsive behaviors.

Amplitude coupling is altered in delirium of various etiologies: Results from a retrospective multi-center case-control EEG study

OBJECTIVE

Delirium manifests with comparable clinical presentations, regardless of its heterogeneous etiology. This suggests a final common pathway such as decreased electroencephalography (EEG) phase coupling. This study investigates if amplitude coupling, another mode of neural communication, is altered in delirium due to different etiologies.

METHODS

We analyzed EEGs of patients from three sites with either postoperative, poststroke or medical delirium and non-delirious control patients. Amplitude envelope correlation corrected for spatial leakage (AECc) was calculated and Mann-Whitney U-tests were used to compare patients with or without delirium. AECc differences among delirium types were compared using Kruskal-Wallis tests.

RESULTS

AECc was significantly increased in delirious (n = 173, age 79.2±9.3 years, 46 % female) as compared to non-delirious (n = 204, age 72.9±13.1 years, 45 % female) patients in the delta (median, effect size of difference: 0.16 vs. 0.12, r = 0.28, p < 0.01) and beta band (0.11 vs. 0.09, r = 0.14, p = 0.04). These changes did not differ among delirium types (p > 0.05).

CONCLUSIONS

We found modestly higher delta and beta band AECc in delirium compared to non-delirious control patients, regardless of the presumed etiology.

SIGNIFICANCE

This study provides evidence for altered amplitude coupling as mode of impaired neuronal communication in delirium, the role of which should be investigated in future studies of neural network pathophysiology.

Severity of anhedonia is associated with hyper-synchronization of the salience-default mode network in non-clinical individuals: a resting state EEG connectivity study

Anhedonia is a core transnosographic symptom in several neuropsychiatric disorders. Recently, the Triple Network (TN) model has been proposed as a useful neurophysiological paradigm for conceptualizing anhedonia, providing new insights to clinicians and researchers. Despite this, the relationship between the functional dynamics of TN and the severity of anhedonia has been relatively understudied in non-clinical samples, especially in the resting state (RS) condition. Therefore, in the current study, we investigated this relationship using electroencephalography (EEG) functional connectivity. Eighty-two participants (36 males; mean age: 24.28 ± 7.35 years) underwent RS EEG recording with eyes-closed and completed the Beck Depression Inventory-derived 4-item anhedonia scale (BDI-Anh4) and the Brief Symptoms Inventory (BSI). EEG data on functional connectivity were analyzed using the exact low-resolution electromagnetic tomography (eLORETA). A significant positive correlation was observed between the BDI-Anh4 total score and salience-default mode network connectivity in the beta frequency band (r = 0.409; p = 0.010). The results of the hierarchical linear regression analysis also showed that this connectivity pattern was positively and independently associated (β = 0.358; p < 0.001) with the BDI-Anh4 total score and explained an additional 11% of the anhedonia variability. The association between anhedonia severity and increased salience-default mode network synchronization detected in the current study may reflect difficulty disengaging from internal/self-related mental contents, which consequently impairs the processing of other stimuli, including rewarding stimuli.

Integrating neural substrates, diabetes self-management, and behavior change for tailored lifestyle interventions in type-2 diabetes: A neurobehavioral perspective

Understanding the neural mechanisms that underlie behavior change is critical for improving lifestyle management in type 2 diabetes. Individuals with type 2 diabetes face unique challenges in adopting and maintaining healthy behaviors, which can be influenced by alterations in brain function and plasticity, potentially leading to cognitive impairment. Diabetes self-management education and support (DSMES) programs aim to enhance lifestyle changes and promote better health outcomes while reducing cognitive decline. However, complex neural disruptions in critical regions for cognitive processes like the prefrontal cortex and parietal lobe present significant challenges. Given the likely role of neural mechanisms in behavioral choices, understanding how type 2 diabetes affects these neural substrates is crucial for developing effective interventions. Despite considerable research efforts aimed at testing lifestyle interventions, a critical gap remains in understanding the cognitive and behavioral components of successful diabetes self-management, the neural substrates of those components, and the impact of diabetes on those neural substrates. Bridging this gap necessitates a comprehensive examination integrating neural processes, DSMES strategies, and behavior change models. Thus, this perspective review highlights the urgent need to address the knowledge gaps surrounding the neural correlates of diabetes self-management and the integration of behavioral models into intervention frameworks. We propose a hypothesis-generating question and present preliminary findings comparing neural plasticity, executive functions, and lifestyle behavior among individuals with type 2 diabetes, pre-diabetes, and healthy controls. By elucidating the neural substrates underpinning diabetes and exploring their implications for DSMES and readiness to change, we can pave the way for more effective, personalized approaches to diabetes care.

Identifying cognitive, affective, and developmental mechanisms linking threat and deprivation with adolescent psychopathology

BACKGROUND

The mechanisms linking early-life adversity with psychopathology over the life-course are complex. In this prospective study, we collectively examined cognitive, affective, and developmental mediators previously found to individually link childhood threat and deprivation experiences to adolescent psychopathology to identify the most potent mechanisms.

METHODS

Data came from a community sample of 227 children (mean child age 11.5 ± 0.5 years, 48.5% female) from the Seattle metro area with recruitment designed to reflect diversity in family income. Candidate mechanisms included self-rated pubertal development and task-measured attention bias to threat, emotion regulation, theory of mind, fear learning, inhibitory control, language ability, reasoning, and reward sensitivity. Using a high-dimensional mediation approach, we determined which mediating pathways linking threat and deprivation to psychopathology persisted after controlling for all candidate mechanisms associated with psychopathology. Models additionally controlled for the child's age, sex, early-childhood emotional and behavioral symptoms, poverty, and maternal depression.

RESULTS

Blunted reward sensitivity mediated the prospective relationship between threat and internalizing psychopathology, explaining 17.25% (95% CI 1.08%, 69.96%) of this association. Advanced pubertal development was associated with increases in internalizing and externalizing symptoms (standardized associations of 0.16 (95% CI 0.03, 0.29) and 0.17 (95% CI 0.05, 0.29), respectively), but not with adversity. Although deprivation was strongly related to psychopathology, no mechanisms were empirically identified.

CONCLUSIONS

In a well-characterized community sample, we isolated reward sensitivity as a robust mediator of the prospective association between early-life threat and adolescent internalizing psychopathology. Interventions aimed at bolstering reward sensitivity may mitigate the impact of early-life threat experiences on internalizing problems.

Neural Signatures of Cognitive Control Predict Future Adolescent Substance Use Onset and Frequency

BACKGROUND

Adolescent substance use is a significant predictor of future addiction and related disorders. Understanding neural mechanisms underlying substance use initiation and frequency during adolescence is critical for early prevention and intervention.

METHODS

The current longitudinal study followed 91 substance-naïve adolescents annually for 7 years from ages 14 to 21 years to identify potential neural precursors that predict substance use initiation and frequency. Cognitive control processes were examined using the Multi-Source Interference Task to assess functional neural connectivity. A questionnaire was used to assess substance use frequency.

RESULTS

Stronger connectivity between the dorsal anterior cingulate cortex (dACC) and dorsolateral prefrontal cortex (dlPFC) at time 1 predicted a delayed onset of substance use, indicative of a protective effect. A notable decline in this dACC-dlPFC connectivity was observed 1 year prior to substance use initiation. Conversely, lower connectivity of the dACC with the supplementary motor area and heightened connectivity of the anterior insula with the dorsal medial prefrontal cortex and angular gyrus were predictive of greater frequency of future substance use. These findings remained after controlling for demographic and socioeconomic covariates.

CONCLUSIONS

This study highlights the critical role of cognitive control-related neural connectivity in predicting substance use initiation and frequency during adolescence. The results imply that efforts to strengthen and monitor the development of the top-down cognitive control system in the brain from early adolescence can be protective and deter progression into problematic substance use. Furthermore, for adolescents with heightened frequency of substance use, interventions may prove more effective by targeting interoceptive processes in cognitive control training.

Identifying Features of Resilience to Childhood Maltreatment in Resting-State Connectivity Data From Adults With and Without a History of Mood Disorder

Background

Childhood maltreatment (CM) is associated with negative mental health outcomes. Many studies conceptualize resilience as experiencing CM without developing psychopathology (primary resilience). However, some people may develop subsequent psychopathology but recover and demonstrate higher global functioning (secondary resilience). This study investigated the role of salience and emotion network (SEN) (including the amygdala, subgenual anterior cingulate cortex, and anterior insula) and cognitive control network (CCN) (including the dorsolateral prefrontal cortex, inferior parietal lobule, and thalamus) connectivity in primary and secondary resilience.

Methods

We examined resting-state functional connectivity in 108 nonclinical control participants and 154 individuals with any mood disorder (AMD). We measured functioning and CM using the Global Assessment of Functioning (GAF) scale and the Childhood Trauma Questionnaire (CTQ), respectively. For primary resilience, we conducted whole-brain analyses of SEN and CCN regions to test for group × CTQ interactions. For secondary resilience, within-AMD group analyses tested for CTQ × GAF interactions.

Results

Group × CTQ interactions revealed that control participants with higher levels of CM showed greater within-SEN and within-CCN connectivity than participants in the AMD group. In the AMD group, participants with higher levels of CM and functioning (secondary resilience) showed greater within-CCN connectivity while participants with higher levels of CM and lower functioning showed greater within-SEN connectivity.

Conclusions

Greater SEN connectivity appears to play a key role in primary resilience, as observed in the control group, but only within the context of greater CCN connectivity. Future work should explore which cognitive control features are most beneficial and whether targeted interventions help foster resilience to recurrent psychopathology.

Translating Molecular Psychiatry: From Biomarkers to Personalized Therapies-A Narrative Review

In this review, we explore the biomarkers of different psychiatric disorders, such as major depressive disorder, generalized anxiety disorder, schizophrenia, and bipolar disorder. Moreover, we show the interplay between genetic and environmental factors. Novel techniques such as genome-wide association studies (GWASs) have identified numerous risk loci and single-nucleotide polymorphisms (SNPs) implicated in these conditions, contributing to a better understanding of their mechanisms. Moreover, the impact of genetic variations on drug metabolisms, particularly through cytochrome P450 (CYP450) enzymes, highlights the importance of pharmacogenomics in optimizing psychiatric treatment. This review also explores the role of neurotransmitter regulation, immune system interactions, and metabolic pathways in psychiatric disorders. As the technology advances, integrating genetic markers into clinical practice will be crucial in advancing precision psychiatry, improving diagnostic accuracy and therapeutic interventions for individual patients.

Aging-dependent loss of functional connectivity in a mouse model of Alzheimer's disease and reversal by mGluR5 modulator

Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD (AppNL-G-F/hMapt), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923/ALX001) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.

The self-awareness brain network: Construction, characterization, and alterations in schizophrenia and major depressive disorder

Self-awareness (SA) research is crucial for understanding cognition, social behavior, mental health, and education, but SA's underlying network architecture, particularly connectivity patterns, remains largely uncharted. We integrated meta-analytic findings with connectivity-behavior correlation analyses to systematically identify SA-related regions and connections in healthy adults. Edge-weighted networks capturing public, private, and composite SA dimensions were established, where weights represented correlation strengths between tractography-derived structural connectivities and SA levels quantified through behavioral assessments. Then, multilevel SA networks were extracted across a spectrum of correlation thresholds. Robust full-threshold analyses revealed their hierarchical continuum encompassing distinct lateralization patterns, topological transitions, and characteristic hourglass-like architectures. Pathological analysis demonstrated SA connectivity disruptions in schizophrenia (SZ) and major depressive disorder (MDD): approximately 40 % of SA-related connectivities were altered in SZ and 20 % in MDD, with 90 % of MDD alterations overlapping with SZ. While disease-specific and shared alterations were also observed in network-level topological properties, the core SA connectivity framework remained preserved in both disorders. Collectively, these findings significantly advanced our understanding of SA's neurobiological substrates and their pathological deviations.

Differences in fMRI-based connectivity during abstinence or interventions between heroin-dependent individuals and healthy controls

The substantial personal, societal, and economic impacts of opioid addiction drive research investigating how opioid addiction affects the brain, and whether therapies attenuate addiction-related metrics of brain function. Evaluating the connectivity between brain regions is a useful approach to characterise the effects of opioid addiction on the brain. This work is a systematic narrative review of studies investigating the effect of abstinence or interventions on connectivity in people who are dependent on heroin (HD) and healthy controls (HC). We found that HD typically showed weaker connectivity than HC between three functional networks: the Executive Control Network, Default Mode Network, and the Salience Network. Abstinence and Transcranial Magnetic Stimulation (TMS) both attenuated differences in connectivity between HD and HC, often by strengthening connectivity in HD. We observed that increased connectivity due to abstinence or TMS consistently related to decreased craving/risk of relapse. Using these findings, we present an "urge and action framework" relating therapeutic factors contributing to craving/relapse, connectivity results, and neurobiological models of HD. To inform future research, we critically assessed the impact of study design and analysis methods on study results. We conclude that the weaker between-network connectivity in HD and HC and its relationship to craving/relapse merits further exploration as a biomarker and target for therapeutic interventions.

Childhood maltreatment and resting-state network connectivity: The risk-buffering role of positive parenting

Unraveling the neurobiological foundations of childhood maltreatment is important due to the persistent associations with adverse mental health outcomes. However, the mechanisms through which abuse and neglect disturb resting-state network connectivity remain elusive. Moreover, it remains unclear if positive parenting can mitigate the negative impact of childhood maltreatment on network connectivity. We analyzed a cohort of 194 adolescents and young adults (aged 14-25, 47.42% female) from the Neuroscience in Psychiatry Network (NSPN) to investigate the impact of childhood abuse and neglect on resting-state network connectivity. Specifically, we examined the SAN, DMN, FPN, DAN, and VAN over time. We also explored the moderating role of positive parenting. The results showed that childhood abuse was linked to stronger connectivity within the SAN and VAN, as well as between the DMN-DAN, DMN-VAN, DMN-SAN, SAN-DAN, FPN-DAN, SAN-VAN, and VAN-DAN networks about 18 months later. Positive parenting during childhood buffered the negative impact of childhood abuse on network connectivity. To our knowledge, this is the first study to demonstrate the protective effect of positive parenting on network connectivity following childhood abuse. These findings not only highlight the importance of positive parenting but also lead to a better understanding of the neurobiology and resilience mechanisms of childhood maltreatment.

Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD): An RCT of Memory Bias Modification Training vs. Cognitive Control Training vs. Attention Bias Modification Training in remitted recurrently depressed patients with 1.5 year follow-up

BACKGROUND

Major Depressive Disorder (MDD) has a 50-80% recurrence rate highlighting the urgent need for more efficient recurrence prevention programs. Currently, recurrences are often identified too late, while existing preventive strategies may not sufficiently address ethio-patho-physiological mechanisms for recurrence. Negative memory bias (the tendency to better remember negative than positive events), negative attention bias (selective attention favoring mood-congruent information), and cognitive control deficits are important factors involved in the onset, maintenance, and recurrence of depressive episodes.

METHODS

Here we describe the protocol for the Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD) study, aiming to investigate different forms of cognitive training programs administered via smartphones, in order to develop a second-generation recurrence prevention program. In addition, we will gather Experience Sampling Method (ESM) assessments during a 6-day period, and during the follow-up period we will obtain behavioral data on (social) activities with BEHAPP, a smartphone-based Mobile Passive Monitoring application for remote behavioral monitoring to identify behavioral changes indicative of an imminent depressive episode. In a randomized controlled trial, SMARD will compare the effects of a smartphone-based Memory Bias Modification Training (MBT), Cognitive Control Training (CCT), and Attention Bias Modification Training (ABT) versus cognitive domain-specific (active-) sham trainings in 120 remitted MDD-patients with recurrent-MDD. Over the course of three weeks, participants receive multiple daily training sessions. Thereafter, participants will be followed up for 1.5 years with 3-monthly interviews to assess recurrences.

DISCUSSION

The SMARD study aims to 1. assess the effects of the cognitive training programs versus their training-specific (active-) sham conditions on changes in memory, cognitive control dysfunction and attention; 2. relate training effects to neural networks previously identified in (recurrence of) MDD (therefore we obtain functional Magnetic Resonance Imaging ((f)MRI) scans before and after the training in a subset of participants); 3. link baseline and change in memory, cognitive control, attention and neural functioning, and ESM data to prospective recurrences; 4. examine whether passive smartphone-use monitoring can be used for prediction of recurrences.

TRIAL REGISTRATION

NL-OMON26184 and NL-OMON27513. Registered 12 August 2021-Retrospectively registered,  https://onderzoekmetmensen.nl/en/trial/26184 en https://onderzoekmetmensen.nl/en/trial/27513 .

Reliability of brain localization using task-based fMRI for late-life depression with suicidal risk

Late-life depression (LLD) is a heterogeneous mental disorder with a high risk of suicide, often linked to abnormalities in brain networks, particularly the prefrontal cortex. While transcranial magnetic stimulation targeting the dorsal and ventral lateral prefrontal cortex (DLPFC and VLPFC) has shown promise, its treatment efficacy may be compromised by the imprecise group-level standard methods. Although a personalized localization approach using fMRI is available, no study has yet systematically evaluated its reliability in LLD. This study evaluated the reliability of functional magnetic resonance imaging (fMRI) for targeting DLPFC and VLPFC using numerical Stroop and face/shape matching tasks in LLD patients with varying degrees of suicidality, the disorder's most devastating consequence. A total of 103 LLD patients, including 42 with non-suicidal risk (NS), 37 with suicidal ideation or plans (IP), and 24 with past suicide attempts (SA), underwent task-based fMRI. We performed both voxel-wise statistical analyses and the success rate of DLFPC/VLPFC localization in each subgroup by detecting significant brain activity within predefined masks. The numerical Stroop task reliably localized the bilateral DLPFC in all subgroups and the VLPFC in two-thirds. Success rates for localizing DLPFC were 98 % (41 out of 42 NS), 100 % (IP), and 100 % (SA), while VLPFC localization rates were 95 %, 97 %, and 88 %, respectively. Conversely, the face/shape matching task localized bilateral DLPFC in two-thirds and failed to detect the VLPFC in any subgroup. These findings underscore the potential of task-based fMRI, particularly the numerical Stroop task, as a reliable method for personalized targeting in LLD patients with different suicidality degrees.

Multimodal identification of the mouse brain using simultaneous Ca2+ imaging and fMRI

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the prevailing modality in this field-blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI)-suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome-based identification to be successful and explored various features of these data.

The desegregation of neural networks during worry induction in late-life-an effective connectivity analysis

BACKGROUND

Severe worry is a core component of anxiety and depressive disorders and is independently associated with significant morbidity and mortality. However, the neural basis of worry is poorly understood. We investigated effective connectivity (EC) using functional magnetic resonance imaging (fMRI) of a naturalistic worry induction and reappraisal task in late-life.

METHODS

112 participants age >50 years with varying worry severity completed a personalized, in-scanner worry induction and reappraisal task. We calculated voxel-wise EC in neutral, worry, and reappraisal conditions with generalized psychophysiological interactions using seeds in the subgenual anterior cingulate cortex (ACC), dorsal ACC, and left and right amygdalae, and used paired t-tests to compare conditions. We assessed clusters for association with in-scanner worry severity using linear regression.

RESULTS

During the worry condition, EC increased between the subgenual ACC and the default mode network (DMN) and major hubs of the executive control and salience networks. Left amygdala EC to the posterior cingulate also increased during worry, and dorsal ACC connectivity to primary sensory and motor regions decreased. Reappraisal reduced subgenual and dorsal ACC EC observed during worry and the EC between the left amygdala and regions of the dorsal attention network. Broadly, left amygdala EC was robustly associated with in-scanner worry severity.

CONCLUSIONS

Worry induction robustly engaged the DMN and increased connectivity with other high-order associative networks, potentially subsuming cortical resources. Reappraisal reduced these connectivities and disengaged the amygdala from areas associated with top-down attention. These findings could inform targets for neuromodulatory treatment of severe worry in older adults.

A systematic review of resting-state functional-MRI studies in the diagnosis, comorbidity and treatment of postpartum depression

BACKGROUND

Postpartum depression (PPD) is a common and serious mental health problem that affects many new mothers and their families worldwide. In recent years, there has been an increasing number of studies using magnetic resonance techniques (MRI), particularly functional MRI (fMRI), to explore the neuroimaging biomarker of this disease.

METHODS

PubMed database was used to search for English literature focusing on resting-state fMRI and PPD published up to June 2024.

RESULTS

After screening, 17 studies were finally identified, among which all 17 studies reported abnormal regions or connectivity compared to health controls (HC), 4 studies reported results considering the differences between PPD and PPD with anxiety (PPD-A), and 2 studies reported biomarkers for the treatment of PPD. The existing studies indicate that PPD is characterized by functional impairments in multiple brain regions, especially the medial prefrontal cortex (MPFC), precentral gyrus and cerebellum. Abnormal functional connectivity has been widely reported in the dorsomedial prefrontal cortex (dmPFC), anterior cingulate cortex (ACC) and the orbitofrontal cortex (OFC). However, none of the four comorbidity studies identified overlapping discriminative biomarkers between PPD and PPD-A. Additionally, the two treatment-related studies consistently reported functional improvements in the amygdala after effective treatment.

CONCLUSION

The affected brain regions were highly overlapped with major depressive disorder (MDD), suggesting that PPD may be categorized as a potential subtype of MDD. Considering the negative effects of medication on PPD, future efforts should focus on developing non-pharmacological therapies, such as transcranial magnetic stimulation (TMS) and acupuncture, to support women with PPD in overcoming this unique and important phase.

Alteration of cortical structure and functional connectivity in childhood trauma

Childhood trauma acts as an independent risk factor for mental disorders. This study utilized multi-modal MRI techniques to integrate cortical structural measurements and functional connectivity (FC) to identify neurobiological markers of trauma. This study recruited 215 participants, divided into a trauma group (n = 57) and a well-matched non-trauma group (n = 158) based on the childhood trauma questionnaire. We compared differences in cortical volume (CV) and surface area (SA) between the groups and performed a seed-based FC analysis using seeds at identified structural clusters. A machine learning approach with logistic regression was employed to classify individuals with and without childhood trauma. The childhood trauma group showed uniformly lower SA and CV. Reduced SA was found in a cluster consisting of the left precentral gyrus, postcentral gyrus, and paracentral lobule, and decreased CV was observed in a cluster involving the left postcentral gyrus. Seed-based FC analyses revealed decreased FC between the CV-cluster and regions of the bank of the superior temporal sulcus, inferior parietal gyrus, and supramarginal gyrus. In contrast, SA-related clusters showed increased FC with the left postcentral gyrus, superior parietal gyrus, and supramarginal gyrus. The logistic regression model, based on these structural and functional features, achieved a statistically significant classification accuracy of 78 % (p < 0.001) in distinguishing groups with and without childhood trauma. The childhood trauma group exhibits abnormalities in cortical structure and FC which are related to aberrant emotional and cognitive functions. These findings may serve as neuroimaging biomarkers of childhood trauma.

Differential brainstem connectivity according to sex and menopausal status in healthy male and female individuals

BACKGROUND

Brainstem nuclei play a critical role in both ascending monoaminergic modulation of cortical function and arousal, and in descending bulbospinal pain modulation. Even though sex-related differences in the function of both systems have been reported in animal models, a complete understanding of sex differences, as well as menopausal effects, in brainstem connectivity in humans is lacking. This study evaluated resting-state connectivity of the dorsal raphe nucleus, right and left locus coeruleus complex (LCC), and periaqueductal gray (PAG) according to sex and menopausal status in healthy individuals. In addition, relationships between systemic estrogen levels and brainstem-network connectivity were examined in a subset of participants.

METHODS

Resting-state fMRI was performed in 47 healthy male (age, 31.2 ± 8.0 years), 53 healthy premenopausal female (age, 24.7 ± 7.3 years; 22 in the follicular phase, 31 in the luteal phase), and 20 postmenopausal female participants (age, 54.6 ± 7.2 years). Permutation Analysis of Linear Models (5000 permutations) was used to evaluate differences in brainstem-network connectivity according to sex and menopausal status, controlling for age. In 10 males and 17 females (9 premenopausal; 8 postmenopausal), estrogen and estrogen metabolite levels in plasma and stool were determined by liquid chromatography-mass spectrometry/mass spectrometry. Relationships between estrogen levels and brainstem-network connectivity were evaluated by partial least squares analysis.

RESULTS

Left LCC-executive control network connectivity showed an overall sex difference (p = 0.02), with higher connectivity in females than in males; however, this was mainly due to differences between males and premenopausal females (p = 0.008). Additional sex differences were dependent on menopausal status: PAG-default mode network (DMN) connectivity was higher in postmenopausal females than in males (p = 0.04), and PAG-sensorimotor network (SMN) connectivity was higher in premenopausal females than in males (p = 0.03) and postmenopausal females (p = 0.007). Notably, higher free 2-hydroxyestrone levels in stool were reliably associated with higher PAG-SMN and PAG-DMN connectivity in premenopausal females (p < 0.01).

CONCLUSIONS

Healthy females show higher brainstem-network connectivity involved in cognitive control, sensorimotor function, and self-relevant processes than males, dependent on their menopausal status. Further, 2-hydroxyestrone, implicated in pain, may modulate PAG connectivity in premenopausal females. These findings may relate to differential vulnerabilities to chronic stress-sensitive disorders at different life stages.

Cross brain reshaping in congenital visual or hearing impairment: triple-network dysfunction

This research examines how congenital visual or hearing impairment reshapes brain function using EEG. The study involved 40 children with congenital visual impairment, 40 with hearing impairment and 42 age and gender-matched normal children as controls. The investigation included assessments of visual and auditory abilities, along with comprehensive EEG evaluations. Techniques such as source localization, functional connectivity and cross-frequency coupling were used to analyse variations in brain activity. Machine learning methods, specifically support vector machines, were utilized to identify key reshaping characteristics associated with congenital impairments. Results showed reduced activation in the visual cortex for visually impaired children and decreased activation in the auditory cortex for hearing-impaired children compared with the control group. Both impairment groups demonstrated significant reductions in functional connectivity across various brain regions, including the visual and auditory cortices, insula, parahippocampal gyrus, posterior cingulate gyrus and frontal cortex. The machine learning model highlighted aberrant connectivity between the visual/auditory cortex and the right insula, the medial prefrontal cortex and dorsolateral prefrontal cortex and the visual and auditory cortex in children with these impairments in the alpha frequency band. Spatially similar patterns of cross-frequency coupling of rhythmic activity were also observed. The study concludes that congenital visual and hearing impairments significantly impact brain development, identifying distinct functional characteristics and shared reshaping patterns. The consistent presence of dysrhythmic activity and reduced functional connectivity suggest the existence of a triple network anomaly.

Unveiling complex brain dynamics during movie viewing via deep recurrent autoencoder model

Naturalistic stimuli have become an effective tool to uncover the dynamic functional brain networks triggered by cognitive and emotional real-life experiences through multimodal and dynamic stimuli. However, current research predominantly focused on exploring dynamic functional connectivity generated via chosen templates under resting-state paradigm, with relatively limited investigation into the dynamic functional interactions among large-scale brain networks. Moreover, these studies might overlook the longer time-scale adaptability and information transmission that occur over extended periods during naturalistic stimuli. In this study, we introduced an unsupervised deep recurrent autoencoder (DRAE) model combined with a sliding window approach, effectively capturing the brain's long-term temporal dependencies, as measured in functional magnetic resonance imaging (fMRI), when subjects viewing a long-duration and emotional film. The experimental results revealed that naturalistic stimuli can induce dynamic large-scale brain networks, of which functional interactions covary with the development of the film's narrative. Furthermore, the dynamic interactions among brain networks were temporally synchronized with specific features of the movie, especially with the emotional arousal and valence. Our study provided novel insight to the underlying neural mechanisms of dynamic functional interactions among brain regions in an ecologically valid sensory experience.

Biased Information Routing Through the Basolateral Amygdala, Altered Valence Processing, and Impaired Affective States Associated With Psychiatric Illnesses

Accumulating evidence supports a role for altered circuit function in impaired valence processing and altered affective states as a core feature of psychiatric illnesses. We review the circuit mechanisms underlying normal valence processing and highlight evidence supporting altered function of the basolateral amygdala, valence processing, and affective states across psychiatric illnesses. The mechanisms controlling network activity that governs valence processing are reviewed in the context of potential pathophysiological mechanisms mediating circuit dysfunction and impaired valence processing in psychiatric illnesses. Finally, we review emerging data demonstrating experience-dependent, biased information routing through the basolateral amygdala promoting negative valence processing and discuss the potential relevance to impaired affective states and psychiatric illnesses.

Altered brain network dynamics during rumination in remitted depression

Rumination is a known risk factor for depression relapse. Understanding its neurobiological mechanisms during depression remission can inform strategies to prevent relapse, yet the temporal dynamics of brain networks during rumination in remitted depression remain unclear. Here, we collected rumination induction fMRI data from 42 patients with remitted depression and 41 healthy controls (HCs). Using an energy landscape approach, we investigated the temporal dynamics of brain networks during rumination. The appearance frequency (AF) and transition frequency (TF) metrics were defined to quantify the dynamic properties of brain states. Patients during remission showed higher levels of rumination than HCs. Both groups exhibited four brain states during rumination, which consisted of complementary network group activation (states 1 and 2, states 3 and 4). In patients, the AFs of and reciprocal TFs between states 1 and 2 during rumination were significantly increased, while AFs of states 3 and 4 and reciprocal TFs involving states 1-3, 1-4, 2-3, and 2-4 were decreased, both when compared to HCs and relative to patients themselves during distraction. Moreover, we found that for patients, the AF of state 1 was negatively correlated with rumination levels and marginally positively associated with attention, while the AF of state 2 was negatively associated with performance on attention tasks. Our study revealed altered dynamic characteristics of brain states composed of network groups during rumination in remitted depression. Additionally, the findings suggest that heightened self-focus linked to rumination may impair the brain's ability to efficiently allocate attentional resources.

Causal effect of three autoimmune diseases on brain functional networks and cerebrospinal fluid metabolites to underlie the pathogenesis of autoimmune psychosis: a two-sample mendelian randomization analysis

BACKGROUND

Autoimmune diseases such as Systemic Lupus Erythematosus (SLE), Sjögren's Syndrome (SS), and Hashimoto's Thyroiditis (HT) frequently exhibit neuropsychiatric manifestations, including cognitive impairment, depression, anxiety, and so on, yet the exact pathogenesis underlying this association remain incompletely understood. Dysfunction of brain resting-state functional networks and cerebrospinal fluid (CSF) metabolite disturbances have been widely reported in psychiatric disorders. However, the application of resting-state functional magnetic resonance imaging (rsfMRI) and CSF metabolomics in the diagnosis and monitoring of autoimmune psychosis is still limited.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed to investigate the causal relationships between three autoimmune diseases (SLE, SS, and HT, n = 14,267 to 402,090 individuals) and 191 rsfMRI phenotypes (n = 47,276 individuals), as well as 338 CSF metabolites. The genome-wide association study (GWAS) of three autoimmune diseases was used as the exposure, whereas rsfMRI phenotypes and 338 CSF metabolites were treated as the outcome. Inverse variance weighted (IVW) with P value < 0.05 was regarded as the primary approach for calculating causal estimates. Additionally, the false discovery rate (FDR)-adjusted P value (PFDR) < 0.05 was utilized to account for multiple testing. MR Egger method, weighted median method, simple mode method and weighted mode method were used for sensitive analysis.

RESULTS

Our analyses identified 5 causal relationships between SLE and the 191 rsfMRI phenotypes, 48 between SS and the 191 rsfMRI phenotypes, and 4 between HT and the 191 rsfMRI phenotypes. Additionally, we found 8 causal relationships between HT and CSF metabolites. Furthermore, all three diseases were significantly associated with the temporal lobe and triple networks (default mode network (DMN), salience network (SN), and central executive network (CEN)), which are the core brain regions and functional networks for cognition. Following FDR correction, 6 causal relationships between SS and the 191 rsfMRI phenotypes were further validated.

CONCLUSIONS

Our study pinpoints important brain functional networks and CSF metabolites potentially implicated in the pathogenesis of psychiatric disorders associated with autoimmune diseases and highlights critical brain regions for the development of novel therapeutics.

Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs)

BACKGROUND

Mental illnesses extract personal and societal costs, leading to significant challenges in cognitive function, emotional regulation, and social behavior. These disorders are thought to result from disruptions in how different brain regions communicate with each other. Despite advances in neuroimaging, current methods are not always precise enough to fully understand the complexity of these disruptions. More advanced approaches are needed to better identify and characterize the specific brain network alterations linked to different psychiatric conditions.

METHODS

We employed a hierarchical approach to derive Double Functionally Independent Primitives (dFIPs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. dFIPs represent independent patterns of functional network connectivity (FNC) across the brain. Our study utilized a large multi-site dataset comprising 5805 individuals diagnosed with schizophrenia (SCZ), autism spectrum disorder (ASD), bipolar disorder (BPD), major depressive disorder (MDD), and healthy controls. We analyzed how combinations of dFIPs differentiate psychiatric diagnoses.

RESULTS

Distinct dFIP patterns emerged for each disorder. Schizophrenia was characterized by heightened cerebellar connectivity and reduced cerebellar-subcortical connectivity. In ASD, sensory domain hyperconnectivity was prominent. Some dFIPs displayed disorder-specific connectivity patterns, while others exhibited commonalities across multiple conditions. These findings underscore the utility of dFIPs in revealing neural connectivity alterations unique to each disorder, serving as unique fingerprints for different mental disorders.

CONCLUSIONS

Our study demonstrates that dFIPs provide a novel, data-driven method for identifying disorder-specific functional connectivity patterns in psychiatric conditions. These distinct neural signatures offer potential biomarkers for mental illnesses, contributing to a deeper understanding of the neurobiological underpinnings of these disorders.

Aberrant Structural-Functional Coupling of Large-Scale Brain Networks in Older Women With Subthreshold Depression

OBJECTIVES

Subthreshold depression (SD) is common in the older population, more so in females than males, and can lead to serious physical and mental ill-health. However, the underlying neurobiology remains unclear. This study used multimodal magnetic resonance imaging (MRI) to investigate the topological organization and coupling of the structural and functional brain networks in older women with SD.

METHODS

We constructed the structural network from diffusion MRI and the functional network from resting-state functional MRI in 50 older women with SD and 52 demographically matched older women healthy controls (HC). We used graph theory analysis to examine the topological properties of functional and structural networks, and structural-functional connectivity (SC-FC) coupling, and their potential relationship to depressive symptoms.

RESULTS

Globally, compared with older women HC, the older women with SD showed lower local efficiency in the structural network but not the functional network. Locally, older women with SD showed altered convergent nodal metrics in the default mode, salience, and sensorimotor network regions in both structural and functional networks. Moreover, SC-FC coupling reduced in older women with SD compared to older women HC. These network metric alterations were correlated with depressive symptoms.

DISCUSSION

Older women with SD showed alterations in both structural and functional networks, and in their coupling, which throw light on the role of large-scale brain networks in older female SD.

The beneficial influence of night-shift napping on brain core cognition networks in nurses experiencing sleep deprivation: A preliminary resting-state fMRI study

PURPOSE

This study investigated the restorative effects of napping on cognitive brain networks in night-shift nurses experiencing sleep deprivation (SD).

METHODS

Functional magnetic resonance imaging data and neurocognitive assessments were collected from 20 nurses during three sessions (rested wakefulness (RW), SD, and night-shift napping (NS-NAP)). Functional connectivity (FC) was performed in three core cognitive networks, including the default-mode network (DMN), central executive network (CEN), and salience network (SN).

RESULTS

The SD session showed decreased FC across almost the entire DMN, while only showed increased FC in several key nodes of the CEN and SN. Napping partially mitigated SD-related FC alterations within the DMN and essentially restored FC abnormities in both the CEN and SN. Changes in neurocognitive performance observed between SD and NS-NAP sessions were correlated with alterations in FC within the DMN.

CONCLUSION

The functional integration of core neurocognitive networks can be restored to varying degrees through appropriate NS-NAP practices, potentially improving neurocognitive performance in nurses experiencing SD.

CLINICAL TRIAL NUMBER

not applicable.

Heterogeneity of human insular cortex: Five principles of functional organization across multiple cognitive domains

The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Project's multi-task fMRI dataset (N=524), we investigated how insular subregions dynamically engage during seven different cognitive tasks spanning executive function, social cognition, emotion, language, and motor control. Our findings reveal five key principles of human insular organization. First, insular subregions maintain distinct functional signatures that enable reliable differentiation based on activation and connectivity patterns across cognitive domains. Second, these subregions dynamically reconfigure their network interactions in response to specific task demands while preserving their core functional architecture. Third, clear functional specialization exists along the insula's dorsal-ventral axis: the dorsal anterior insula selectively responds to cognitive control demands through interactions with frontoparietal networks, while the ventral anterior insula preferentially processes emotional and social information via connections with limbic and default mode networks. Fourth, we observed counterintuitive connectivity patterns during demanding cognitive tasks, with the dorsal anterior insula decreasing connectivity to frontoparietal networks while increasing connectivity to default mode networks - suggesting a complex information routing mechanism rather than simple co-activation of task-relevant networks. Fifth, while a basic tripartite model captures core functional distinctions, finer-grained parcellations revealed additional cognitive domain-specific advantages that are obscured by simpler parcellation approaches. Our results illuminate how the insula's organization supports its diverse functional roles through selective engagement of distinct neural networks, providing a new framework for understanding both normal cognitive function and clinical disorders involving insular dysfunction.

Triple-network model-based graph theory analysis of the effectiveness of low-dose ketamine in patients with treatment-resistant depression: two resting-state functional MRI clinical trials

BACKGROUND

Evidence suggests the crucial role of dysfunctional default mode (DMN), salience and frontoparietal (FPN) networks, collectively termed the triple network model, in the pathophysiology of treatment-resistant depression (TRD).

AIMS

Using the graph theory- and seed-based functional connectivity analyses, we attempted to elucidate the role of low-dose ketamine in the triple networks, namely the DMN, salience and FPN.

METHOD

Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) data derived from two previous clinical trials of a single, low-dose ketamine infusion were analysed. In clinical trial 1 (Trial 1), patients with TRD were randomised to either a ketamine or normal saline group, while in clinical trial 2 (Trial 2) those patients with TRD and pronounced suicidal symptoms received a single infusion of either 0.05 mg/kg ketamine or 0.045 mg/kg midazolam. All participants underwent rs-fcMRI pre and post infusion at Day 3. Both graph theory- and seed-based functional connectivity analyses were performed independently.

RESULTS

Trial 1 demonstrated significant group-by-time effects on the degree centrality and cluster coefficient in the right posterior cingulate cortex (PCC) cortex ventral 23a and b (DMN) and the cluster coefficient in the right supramarginal gyrus perisylvian language (salience). Trial 2 found a significant group-by-time effect on the characteristic path length in the left PCC 7Am (DMN). In addition, both ketamine and normal saline infusions exerted a time effect on the cluster coefficient in the right dorsolateral prefrontal cortex a9-46v (FPN) in Trial 1.

CONCLUSIONS

These findings may support the utility of the triple-network model in elucidating ketamine's antidepressant effect. Alterations in DMN, salience and FPN function may underlie this effect.

Association of core brain networks with antipsychotic therapeutic effects in first-episode schizophrenia

Elucidating neurobiological mechanisms underlying the heterogeneity of antipsychotic treatment will be of great value for precision medicine in schizophrenia, yet there has been limited progress. We combined static and dynamic functional connectivity (FC) analysis to examine the abnormal communications among core brain networks [default-mode network (DMN), central executive network (CEN), salience network (SN), primary network (PN), and subcortical network (SCN) in clinical subtypes of schizophrenia (responders and nonresponders to antipsychotic monotherapy). Resting-state functional magnetic resonance imaging data were collected from 79 first-episode schizophrenia and 90 healthy controls. All patients received antipsychotic monotherapy for up to 12 weeks and underwent a second scan. We found that significantly reduced static FC in CEN-DMN/SN and SN-SCN were observed in nonresponders after treatment, whereas almost no difference was observed in responders. The nonresponders showed significantly higher dynamic FC in PN-DMN/SN than responders at baseline. Further, the baseline FC in core brain networks were treated as moderators involved in symptom relief and distinguished response subtypes with high classification accuracy. Collectively, the current work highlights the potential of communications among five core brain networks in searching biomarkers of antipsychotic monotherapy response and neuroanatomical subtypes, advancing the understanding of antipsychotic treatment mechanisms in schizophrenia.

Altered brain dynamic functional connectivity in patients with obstructive sleep apnea and its association with cognitive performance

OBJECTIVES

Obstructive sleep apnea (OSA) is associated with potential disruptions in brain function and structure. The aim was to investigate alterations in dynamic functional connectivity (dFC) in OSA patients utilizing resting-state functional magnetic resonance imaging (rs-fMRI) and multiplication of temporal derivatives (MTD) to better understand the neurological implications of OSA.

METHODS

This cross-sectional study eventually recruited 111 patients, aged 25-65 years. We categorized participants based on the apnea-hypopnea index (AHI) assessed via polysomnography (PSG), 43 patients were groupAHI <15 and 68 patients were group AHI ≥15. Rs-fMRI and neuropsychological assessments were conducted to assess the brain function and visual-spatial memory, respectively. We evaluated the intergroup differences in dFC as well as its correlation with clinical parameters.

RESULTS

The dFC analysis identified five distinct connectivity states, comprising four hyperconnected states (State 1, 2, 3, and 5) and one hypoconnected state (State 4). Group AHI≥ 15 showed altered fraction time (FT) and mean dwell time (MDT) in States 1, 3, and 4. The partial correlation showed that the FT/MDT of State 1 negatively correlated with hypoxia parameters, while the FT/MDT of State 3 positively correlated with total sleep time in Group AHI≥ 15. Group AHI≥ 15 exhibited a negative association between FT of state 3 and Visuospatial/Executive score in MoCA (r = -0.297, p = 0.033).

CONCLUSIONS

Untreated male moderate to severe OSA patients exhibited altered in dFC, which significantly correlated with hypoxia parameters and cognitive performance, high lighting that dFC changes may be an indicator of the neurological consequence of OSA, especially moderate to severe OSA.

Imaging Brain Networks: Insights into Mechanisms of Temporomandibular Disorders

Temporomandibular disorders are a group of craniomaxillofacial disorders mainly characterized by pain and motor dysfunction of the temporomandibular joints and surrounding masticatory muscles. Clinically, patients with temporomandibular disorders often display central nervous system dysfunction, such as negative mood disorders, but the underlying cause remains unclear. Recent developments in neuroimaging techniques have facilitated new understanding. Notably, the triple network model consisting of the default mode network, the central executive network, and the salience network is of particular interest in this regard and may provide new insights into brain network alterations. Specifically, we observed that patients with temporomandibular disorders have abnormal activation of attention-related brain regions in the default mode network, which may be related to pain rumination. In addition, cortical atrophy and altered functional connectivity were found in regions related to the regulation of emotion and pain. In the central executive network, decreased activity and metabolism were seen in pain regulation regions, while abnormal activation occurred in regions associated with negative emotions. The salience network showed aberrant activation and metabolic changes in pain perception regions, and negative emotions were associated with an abnormal activation pattern. Potentially treatment-induced changes included a return to normal activity in attention and emotion regulation regions, suggesting that assessing activity in these networks may be used to evaluate treatment efficacy. Finally, this review highlights current dilemmas and future opportunities for the field in terms of research cohorts, methods, scope, and analytical techniques. Further exploration is necessary to realize a better understanding of the neuropathophysiology of temporomandibular disorders and ultimately more effective treatments.

Biomarker identification in bipolar disorder

Bipolar disorder (BD) is a severe psychiatric condition whose pathophysiology is complex and multifactorial. Genetic, environmental and social risk factors play a role in its development as well as in its progressive course. Research is currently focusing on the identification of the biological basis underlying these processes in order to suggest novel biomarkers capable to predict BD etiopathogenesis and staging. Staging has been recognized as of great value for the treatment and management of many illnesses and might also be suitable for mental health issues, particularly in disorders like BD, which progress from an initial mild phase to a more severe and thus difficult-to-treat situation. Thus, it would be of great help the characterization of to suggest better treatment requirements and improve prognosis across the different stages of the illness. Here, we summarize current research on the biological hypotheses of BD and the biomarkers associated with its progression, reviewing clinical studies available in the literature.

Brain white matter structural connectivity of trauma and trauma-related dissociation disorders and symptoms

BACKGROUND

Experiencing repeated childhood traumatisation impacts brain structure and function in individuals with dissociative identity disorder (DID) and post-traumatic stress disorder (PTSD). Quantitative grey matter neuroimaging research has shown aberrant volumes in traumatised individuals, however studies examining white matter are sparse, particularly for DID. The present study aims to examine white matter alterations of people with trauma-related disorders.

METHODS

Sixty-five female participants were included in this study: 33 diagnosed with a trauma-related disorder, namely 17 with DID and 16 with PTSD, and 32 healthy control (HC) participants. All participants underwent diffusion tensor imaging (DTI) and completed dissociation and traumatisation self-report measures. White matter integrity was characterised using voxel-based analysis (VBA), with network lesion mapping used to identify the implicated grey matter end points of the VBA findings.

RESULTS

Between-group VBA comparisons showed reduced fractional anisotropy (FA) for participants with DID compared to HCs in bilateral pallidum (implicating striatal projections to pre/post central gyri), midbrain, and pontocerebellar white matter. Compared to those with PTSD, DID subjects showed increased FA in the right internal capsule and right temporal areas (predominantly implicating the inferior longitudinal fasciculus). Across DID and PTSD subjects, FA values within the aforementioned findings negatively correlated with depersonalisation, psychoform and somatoform dissociation, and/or traumatisation scores.

CONCLUSIONS

Our DTI findings indicate markedly differential white matter integrity in DID compared to PTSD and HCs. This provides valuable mechanistic insights regarding a role for aberrant white matter structural integrity in traumatised female individuals with DID.

Common and unique network basis for externally and internally driven flexibility in cognition: From a developmental perspective

Flexibility is a hallmark of cognitive control and can be driven externally and internally, corresponding to reactive and spontaneous flexibility. However, the convergence and divergence between these two types of flexibility and their underlying neural basis during development remain largely unknown. In this study, we aimed to determine the common and unique networks for reactive and spontaneous flexibility as a function of age and sex, leveraging both cross-sectional and longitudinal resting-state functional magnetic resonance imaging datasets with different temporal resolutions (N = 249, 6-35 years old). Functional connectivity strength and nodal flexibility, derived from static and dynamic frameworks respectively, were utilized. We found similar quadratic effects of age on reactive and spontaneous flexibility, which were mediated by the functional connectivity strength and nodal flexibility of the frontoparietal network. Divergence was observed, with the nodal flexibility of the ventral attention network at the baseline visit uniquely predicting the increase in reactive flexibility 24-30 months later, while the nodal flexibility or functional connectivity strength of the dorsal attention network could specifically predict the increase in spontaneous flexibility. Sex differences were found in tasks measuring reactive and spontaneous flexibility simultaneously, which were moderated by the nodal flexibility of the dorsal attention network. This study advances our understanding of distinct types of flexibility in cognition and their underlying mechanisms throughout developmental stages. Our findings also suggest the importance of studying specific types of cognitive flexibility abnormalities in developmental neuropsychiatric disorders.

Aberrant functional connectivity patterns in the pregenual anterior cingulate cortex and anterior midcingulate cortex of patients with irritable bowel syndrome accompanied by depressive symptoms

Irritable bowel syndrome (IBS) is a common brain-gut disorder often accompanied by depressive symptoms, with atrophy and hyperactivity of the anterior cingulate gyrus (ACC) being key drivers of both IBS and its psychiatric comorbidities. This study aimed to investigate the functional connectivity (FC) patterns of pregenual ACC (pgACC) and anterior midcingulate cortex (aMCC) in IBS patients with depressive symptoms (DEP-IBS). A whole-brain FC analysis was conducted using pgACC and aMCC as regions of interest in three groups: 28 DEP-IBS patients, 21 IBS patients without depressive symptoms (nDEP-IBS), and 36 matched healthy controls (HCs). Partial correlation and mediation analyses were performed between abnormal FC and clinical symptoms. The ability of aberrant FC to identify IBS and its psychiatric comorbidity was evaluated using receiver operating characteristic (ROC) curve. DEP-IBS patients exhibited increased pgACC-related FC in the left medial prefrontal cortex (mPFC) and aMCC-related FC in the right middle frontal gyrus, angular gyrus and cerebellum, while showing decreased aMCC-related FC in the right precentral gyrus, superior parietal gyrus and precuneus. Both patient groups demonstrated increased FC between aMCC and left dorsolateral prefrontal cortex (dlPFC), effectively distinguishing them from HCs (AUC = 0.755). The FC between pgACC and left mPFC partially mediated the relationship between gastrointestinal and depressive symptoms, effectively distinguishing DEP-IBS from nDEP-IBS patients (AUC = 0.808). Aberrant FC within the emotional arousal network may serve as a neurobiological marker for IBS with comorbid depression. Furthermore, abnormal FC between the aMCC and the dlPFC may underlie the neural mechanism of IBS.

Network dynamics in post-stroke cognitive impairment: insights from effective connectivity analysis

This study investigates post-stroke cognitive impairment (PSCI) by utilizing spectral dynamic causal modeling (spDCM) to examine changes in effective connectivity (EC) within the default mode, executive control, dorsal attention, and salience networks. Forty-one PSCI patients and 41 demographically matched healthy controls underwent 3D-T1WI and resting-state functional magnetic resonance imaging on a 3.0T MRI. The study compared EC among eight representative regions of interest using spDCM and analyzed the correlation between altered EC and cognitive test scores. Subgroup analysis was conducted based on lesion location. The study found a significant increase in EC in the PSCI group, specifically from the posterior cingulate cortex (PCC) to the left and right dorsolateral prefrontal cortex (L_DLPFC and R_DLPFC, respectively), and from the right insula to R_DLPFC (p < 0.05). These changes were significantly negatively correlated with cognitive scores. Subgroup analysis showed increased executive control in PSCI patients with left anterior circulation lesions. Validation through low-order functional connectivity analysis indicated abnormalities dominated by large-scale intra- and inter-network functional connectivity increases in patients with PSCI. The study suggests an increase in effective connectivity between networks, particularly within the triple network model. The findings implicate the PCC and R_DLPFC in the pathophysiology of PSCI, shedding light on its cognitive implications. This study emphasizes the importance of understanding network changes in PSCI from various perspectives, enhancing our understanding of the neural mechanisms underlying PSCI, and establishing a foundation for future research.