Role of electrophysiological activity and interactions of lateral habenula in the development of depression-like behavior in a chronic restraint stress model

Closed-loop deep brain stimulation (DBS) system offers a promising approach for treatment-resistant depression, but identifying universally accepted electrophysiological biomarkers for closed-loop DBS systems targeting depression is challenging. There is growing evidence suggesting a strong association between the lateral habenula (LHb) and depression. Here, we took LHb as a key target, utilizing multi-site local field potentials (LFPs) to study the acute and chronic changes in electrophysiology, functional connectivity, and brain network characteristics during the formation of a chronic restraint stress (CRS) model. Furthermore, our model combining the electrophysiological changes of LHb and interactions between LHb and other potential targets of depression can effectively distinguish depressive states, offering a new way for developing effective closed-loop DBS strategies.

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia

PURPOSE

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia.

METHODS

The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods.

RESULTS

The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups.

CONCLUSIONS

Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Decoupling of gray and white matter functional networks in cognitive impairment induced by occupational aluminum exposure

Aluminum (Al) is a low-toxic, accumulative substance with neurotoxicity properties that adversely affect human cognitive function. This study aimed to investigate the neurobiological mechanisms underlying cognitive impairment resulting from occupational Al exposure. Resting-state functional magnetic resonance imaging was conducted on 54 individuals with over 10 years of Al exposure. Al levels were measured, and cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Subsequently, the K-means clustering algorithm was employed to identify functional gray matter (GM) and white matter (WM) networks. Two-sample t-tests were conducted between the cognition impairment group and the control group. Al exhibited a negative correlation with MoCA scores. Participants with cognitive impairment demonstrated reduced functional connectivity (FC) between the middle cingulum network (WM1) and anterior cingulum network (WM2), as well as between the executive control network (WM6) and limbic network (WM10). Notably, decreased FCs were observed between the executive control network (GM5) and WM1, WM4, WM6, and WM10. Additionally, the FC of GM5-GM4 and WM1-WM2 negatively correlated with Trail Making Test Part A (TMT-A) scores. Prolonged Al accumulation detrimentally affects cognition, primarily attributable to executive control and limbic network disruptions.

Long-term olfactory enrichment promotes non-olfactory cognition, noradrenergic plasticity and remodeling of brain functional connectivity in older mice

Brain functional and structural changes lead to cognitive decline during aging, but a high level of cognitive stimulation during life can improve cognitive performances in the older adults, forming the cognitive reserve. Noradrenaline has been proposed as a molecular link between environmental stimulation and constitution of the cognitive reserve. Taking advantage of the ability of olfactory stimulation to activate noradrenergic neurons of the locus coeruleus, we used repeated olfactory enrichment sessions over the mouse lifespan to enable the cognitive reserve buildup. Mice submitted to olfactory enrichment, whether started in early or late adulthood, displayed improved olfactory discrimination at late ages and interestingly, improved spatial memory and cognitive flexibility. Moreover, olfactory and non-olfactory cognitive performances correlated with increased noradrenergic innervation in the olfactory bulb and dorsal hippocampus. Finally, c-Fos mapping and connectivity analysis revealed task-specific remodeling of functional neural networks in enriched older mice. Long-term olfactory enrichment thus triggers structural noradrenergic plasticity and network remodeling associated with better cognitive aging and thereby forms a promising mouse model of the cognitive reserve buildup.

Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder

OBJECTIVE

Emerging studies have identified treatment-related connectome predictors in major depressive disorder (MDD). However, quantifying treatment-responsive patterns in structural connectivity (SC) and functional connectivity (FC) simultaneously remains underexplored. We aimed to evaluate whether spatial distributions of FC and SC associated treatment responses are shared or unique.

METHODS

Diffusion tensor imaging and resting-state functional magnetic resonance imaging were collected from 210 patients with MDD at baseline. We separately developed connectome-based prediction models (CPM) to predict reduction of depressive severity after 6-week monotherapy based on structural, functional, and combined connectomes, then validated them on the external dataset. We identified the predictive SC and FC from CPM with high occurrence frequencies during the cross-validation.

RESULTS

Structural connectomes (r = 0.2857, p < 0.0001), functional connectomes (r = 0.2057, p = 0.0025), and their combined CPM (r = 0.4, p < 0.0001) can significantly predict a reduction of depressive severity. We didn't find shared connectivity between predictive FC and SC. Specifically, the most predictive FC stemmed from the default mode network, while predictive SC was mainly characterized by within-network SC of fronto-limbic networks.

CONCLUSIONS

These distinct patterns suggest that SC and FC capture unique connectivity concerning the antidepressant response.

SIGNIFICANCE

Our findings provide comprehensive insights into the neurophysiology of antidepressants response.

Impaired Cortico-Thalamo-Cerebellar Integration Across Schizophrenia, Bipolar II, and Attention Deficit Hyperactivity Disorder Patients Suggests Potential Neural Signatures for Psychiatric Illness

Understanding aberrant functional changes between brain regions has shown promise for characterizing and differentiating the symptoms associated with progressive psychiatric disorders. The functional integration between the thalamus and cerebellum significantly influences learning and memory in cognition. Observed in schizophrenic patients, dysfunction within the corticalthalamocerebellar (CTC) circuitry is linked to challenges in prioritizing, processing, coordinating, and responding to information. This study explored whether abnormal CTC functional network connectivity patterns are present across schizophrenia (SCHZ) patients, bipolar II disorder (BIPOL) patients, and ADHD patients by examining both task- and task-free conditions compared to healthy volunteers (HC). Leveraging fMRI data from 135 participants (39 HC, 27 SCHZ patients, 38 BIPOL patients, and 31 ADHD patients), we analyzed functional network connectivity (FNC) patterns across 115 cortical, thalamic, subcortical, and cerebellar regions of interest (ROIs). Guiding our investigation: First, do the brain regions of the CTC circuit exhibit distinct abnormal patterns at rest in SCHZ, ADHD, and BIPOL? Second, do working memory tasks in these patients engage common regions of the circuit in similar or unique patterns? Consistent with previous findings, our observations revealed FNC patterns constrained in the cerebellar, thalamic, striatal, hippocampal, medial prefrontal and insular cortices across all three psychiatric cohorts when compared to controls in both task and task-free conditions. Post hoc analysis suggested a predominance in schizophrenia and ADHD patients during rest, while the task condition demonstrated effects across all three disorders. Factor-by-covariance GLM MANOVA further specified regions associated with clinical symptoms and trait assessments. Our study provides evidence suggesting that dysfunctional CTC circuitry in both task-free and task-free conditions may be an important broader neural signature of psychiatric illness.

Functional Connectivity of the Nucleus Accumbens across Variants of Callous-Unemotional Traits: A Resting-State fMRI Study in Children and Adolescents

A large body of literature suggests that the primary (high callousness-unemotional traits [CU] and low anxiety) and secondary (high CU traits and anxiety) variants of psychopathy significantly differ in terms of their clinical profiles. However, little is known about their neurobiological differences. While few studies showed that variants differ in brain activity during fear processing, it remains unknown whether they also show atypical functioning in motivational and reward system. Latent Profile Analysis (LPA) was conducted on a large sample of adolescents (n = 1416) to identify variants based on their levels of callousness and anxiety. Seed-to-voxel connectivity analysis was subsequently performed on resting-state fMRI data to compare connectivity patterns of the nucleus accumbens across subgroups. LPA failed to identify the primary variant when using total score of CU traits. Using a family-wise cluster correction, groups did not differ on functional connectivity. However, at an uncorrected threshold the secondary variant showed distinct functional connectivity between the nucleus accumbens and posterior insula, lateral orbitofrontal cortex, supplementary motor area, and parietal regions. Secondary LPA analysis using only the callousness subscale successfully distinguish both variants. Group differences replicated results of deficits in functional connectivity between the nucleus accumbens and posterior insula and supplementary motor area, but additionally showed effect in the superior temporal gyrus which was specific to the primary variant. The current study supports the importance of examining the neurobiological markers across subgroups of adolescents at risk for conduct problems to precise our understanding of this heterogeneous population.

Functional Abnormality of the Reward System in Depressed Adolescents and Young Adults with and without Suicidal Behavior

OBJECTIVE

To identify local and functional connectivity abnormalities in the brain's reward network in depressed adolescents and young adults with and without suicidal behavior.

METHODS

Magnetic resonance imaging data were obtained from 41 major depressive disorder (MDD) patients with suicidal behavior (sMDD, males/females: 12/29), 44 MDD patients without suicidal behavior (nMDD, males/females: 13/32), and 52 healthy controls (HCs, males/females: 17/35). The Young Mania Scale, Hamilton Depression Scale, Columbia Suicide Scale, and Scale for Suicide Ideation were used to evaluate emotional state and suicidal ideation and behaviors. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo) and functional connectivity of 11 regions of interest (ROIs) in the reward network were determined.

RESULTS

ALFF values in the vmPFC of the nMDD group were significantly lower than those in the HC group (p = 0.031). The ReHo values of the nMDD group were lower in the lVS but higher in the vmPFC than those of the HC group (P = 0.018 and 0.025, respectively). Functional connectivity of the AC with the vmPFC, lVS, rVS, and vmPFC was increased in the sMDD group compared with that in the nMDD group (P = 0.038, 0.034, 0.006, respectively).

CONCLUSION

Local and functional connectivity abnormalities in the reward network were found in the MDD groups. However, increased functional connectivity was found in only the sMDD group.

Structural and functional connectivity associations with anterior cingulate sulcal variability

Background

Sulcation of the anterior cingulate may be defined by presence of a paracingulate sulcus, a tertiary sulcus developing during the third gestational trimester with implications on cognitive function and disease.

Methods

In this retrospective analysis we examine task-free resting state functional connectivity and diffusion-weighted tract segmentation data from a cohort of healthy adults (< 60-year-old, n = 129), exploring the impact of ipsilateral paracingulate sulcal presence on structural and functional connectivity.

Results

Presence of a left paracingulate sulcus was associated with reduced fractional anisotropy in the left cingulum (P = 0.02) bundle and the peri-genual (P = 0.002) and dorsal (P = 0.03) but not the temporal cingulum bundle segments. Left paracingulate sulcal presence was associated with increased left peri-genual radial diffusivity (P = 0.003) and tract volume (P = 0.012). A significant, predominantly intraregional frontal component of altered resting state functional connectivity was identified in individuals possessing a left PCS (P = 0.01). Seed-based functional connectivity in pre-defined networks was not associated with paracingulate sulcal presence.

Conclusion

These results identify a novel association between neurodevelopmentally derived sulcation and altered structural connectivity in a healthy adult population with implications for conditions where this variation is of interest. Furthermore, they provide evidence of a link between the structural and functional connectivity of the brain in the presence of a paracingulate sulcus which may be mediated by a highly connected local functional network reliant on short association fibres.

Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject's connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale.

Resting-State Functional Connectivity of the Anterior Cingulate Cortex Among Persons With Mood Disorders and Suicidal Behaviors

OBJECTIVE

To assess whether anterior cingulate cortex (ACC) abnormalities contribute to suicide risk in major depressive disorder and bipolar disorder, the investigators compared resting-state functional connectivity (rsFC) of ACC subdivisions between individuals with major depressive or bipolar disorder with and without a lifetime history of suicidal behavior.

METHODS

Forty-two inpatients with and 26 inpatients without a history of suicidal behavior (SB+ and SB-, respectively) associated with major depressive or bipolar disorder and 40 healthy control (HC) participants underwent rsFC neuroimaging. RsFC of the subgenual, perigenual, rostral, dorsal, and caudal subdivisions of the ACC was calculated. Possible confounders, such as psychosis and severity of depression, were controlled for, seed-to-voxel and post hoc region of interest (ROI)-to-ROI analyses were performed, and the accuracy of rsFC in classifying suicidal behavior was studied.

RESULTS

Compared with individuals in the SB- and HC groups, patients in the SB+ group had higher rsFC between the left rostral and right dorsal ACC seeds and visual cortex clusters. Conversely, rsFC between the left rostral and right dorsal ACC seeds and cingulate and frontal clusters was lower in the SB+ group than in the HC group. Left rostral ACC to left Brodmann's area 18 connectivity showed up to 75% discriminative accuracy in distinguishing SB+ from SB- patients.

CONCLUSIONS

A history of suicidal behavior among individuals with major depressive disorder or bipolar disorder was associated with altered rsFC of the rostral and caudal ACC, regions involved in conflict detection and error monitoring. Replication of these findings is needed to further explore the involvement of the ACC in the neurobiology of suicidal behavior and suicidal ideation.

Testing the triple network model of psychopathology in a transdiagnostic neurodevelopmental cohort

AIM

The triple network model of psychopathology posits that altered connectivity between the Salience (SN), Central Executive (CEN), and Default Mode Networks (DMN) may underlie neurodevelopmental conditions. However, this has yet to be tested in a transdiagnostic sample of young people.

METHOD

We investigated this in 175 children (60 girls) that represent a heterogeneous population who are experiencing neurodevelopmental difficulties in cognition and behavior, and 60 comparison children (33 girls). Hyperactivity/impulsivity and inattention were assessed by parent-report. Resting-state functional Magnetic Resonance Imaging data were acquired and functional connectivity was calculated between independent network components and regions of interest. We then examined whether connectivity between the SN, CEN and DMN was dimensionally related to hyperactivity/impulsivity and inattention, whilst controlling for age, gender, and motion.

RESULTS

Hyperactivity/impulsivity was associated with increased functional connectivity between the SN, CEN, and DMN in at-risk children, whereas it was associated with decreased functional connectivity between the CEN and DMN in comparison children. These effects replicated in an adult parcellation of brain function and when using increasingly stringent exclusion criteria for in-scanner motion.

CONCLUSION

Triple network connectivity characterizes transdiagnostic neurodevelopmental difficulties with hyperactivity/impulsivity. We suggest that this may arise from delayed network segregation, difficulties sustaining CEN activity to regulate behavior, and/or a heightened developmental mismatch between neural systems implicated in cognitive control relative to those implicated in reward/affect processing.

A comparison of functional activation and connectivity of the cerebellum in adults and children during single word processing

Meta-analyses on reading show cerebellar activation in adults, but not children, suggesting a possible age-dependent role of the cerebellum in reading. However, the few studies that compare adults and children during reading report mixed cerebellar activation results. Here, we studied (i) cerebellar activation during implicit word processing in adults and children and (ii) functional connectivity (FC) between the cerebellum and left cortical regions involved in reading. First, both groups activated bilateral cerebellum for word processing when compared to fixation, but not when compared to the active control. There were no differences between adults and children. Second, we found intrinsic FC between several cerebellar seed regions and cortical target regions in adults and children, as well as between-group differences. However, task-modulated FC specific to word processing revealed no within- nor between-group results. Together this study does not provide support for a role of the cerebellum in word processing at either age.

Age-Specific Diagnostic Classification of ASD Using Deep Learning Approaches

Autism Spectrum Disorder (ASD) is a highly heterogeneous condition, due to high variance in its etiology, comorbidity, pathogenesis, severity, genetics, and brain functional connectivity (FC). This makes it devoid of any robust universal biomarker. This study aims to analyze the role of age and multivariate patterns in brain FC and their accountability in diagnosing ASD by deep learning algorithms. We utilized functional magnetic resonance imaging data of three age groups (6 to 11, 11 to 18, and 6 to 18 years), available with public databases ABIDE-I and ABIDE-II, to discriminate between ASD and typically developing. The blood-oxygen-level dependent time series were extracted using the Gordon's, Harvard Oxford and Diedrichsen's atlases, over 236 regions of interest, as 236x236 sized FC matrices for each participant, with Pearson correlations. The feature sets, in the form of FC heat maps were computed with respect to each age group and were fed to a convolutional neural network, such as MobileNetV2 and DenseNet201 to build age-specific diagnostic models. The results revealed that DenseNet201 was able to adapt and extract better features from the heat maps, and hence returned better accuracy scores. The age-specific dataset, with participants of ages 6 to 11 years, performed best, followed by 11 to 18 years and 6 to 18 years, with accuracy scores of 72.19%, 71.88%, and 69.74% respectively, when tested using the DenseNet201. Our results suggest that age-specific diagnostic models are able to counter heterogeneity present in ASD, and that enables better discrimination.

EEG source functional connectivity in patients after a recent suicide attempt

OBJECTIVE

Electroencephalogram (EEG) based frequency measures within the alpha frequency range (AFR), including functional connectivity, show potential in assessing the underlying pathophysiology of depression and suicide-related outcomes. We investigated the association between AFR connectivity, suicidal thoughts and behaviors, and depression in a transdiagnostic sample of patients after a recent suicide attempt (SA).

METHODS

Lagged source-based measures of linear and nonlinear whole-brain connectivity within the standard AFR ([sAFR], 8-12 Hz) and the individually referenced AFR (iAFR) were applied to 70 15-minute resting-state EEGs from patients after a SA and 70 age- and gender-matched healthy controls (HC). Hypotheses were tested using network-based statistics and multiple regression models.

RESULTS

Results showed no significant differences between patients after a SA and HC in any of the assessed connectivity modalities. However, a subgroup analysis revealed significantly increased nonlinear connectivity within the sAFR for patients after a SA with a depressive disorder or episode ([DD], n = 53) compared to matched HC. Furthermore, a multiple regression model, including significant main effects for group and global nonlinear connectivity within the sAFR outperformed all other models in explaining variance in depressive symptom severity.

CONCLUSIONS

Our study further supports the importance of the AFR in pathomechanisms of suicidality and depression. The iAFR does not seem to improve validity of phase-based connectivity.

SIGNIFICANCE

Our results implicate distinct neurophysiological patterns in suicidal subgroups. Exploring the potential of these patterns for treatment stratification might advance targeted interventions for suicidal thoughts and behaviors.

Insights from personalized models of brain and behavior for identifying biomarkers in psychiatry

A main goal in translational neuroscience is to identify neural correlates of psychopathology ("biomarkers") that can be used to facilitate diagnosis, prognosis, and treatment. This goal has led to substantial research into how psychopathology symptoms relate to large-scale brain systems. However, these efforts have not yet resulted in practical biomarkers used in clinical practice. One reason for this underwhelming progress may be that many study designs focus on increasing sample size instead of collecting additional data within each individual. This focus limits the reliability and predictive validity of brain and behavioral measures in any one person. As biomarkers exist at the level of individuals, an increased focus on validating them within individuals is warranted. We argue that personalized models, estimated from extensive data collection within individuals, can address these concerns. We review evidence from two, thus far separate, lines of research on personalized models of (1) psychopathology symptoms and (2) fMRI measures of brain networks. We close by proposing approaches uniting personalized models across both domains to improve biomarker research.

Event-Related Spectral Perturbation, Inter Trial Coherence, and Functional Connectivity in motor execution: A comparative EEG study of old and young subjects

INTRODUCTION

The motor-related bioelectric brain activity of healthy young and old subjects was studied to understand the effect of aging on motor execution. A visually cued finger tapping movement paradigm and high-density EEG were used to examine the time and frequency characteristics.

METHODS

Twenty-two young and 22 healthy elderly adults participated in the study. Repeated trials of left and right index finger movements were recorded with a 128-channel EEG. Event-Related Spectral Perturbation (ERSP), Inter Trial Coherence (ITC), and Functional Connectivity were computed and compared between the age groups.

RESULTS

An age-dependent theta and alpha band ERSP decrease was observed over the frontal-midline area. Decrease of beta band ERSP was found over the ipsilateral central-parietal regions. Significant ITC differences were found in the delta and theta bands between old and young subjects over the contralateral parietal-occipital areas. The spatial extent of increased ITC values was larger in old subjects. The movement execution of older subjects showed higher global efficiency in the delta and theta bands, and higher local efficiency and node strengths in the delta, theta, alpha, and beta bands.

CONCLUSION

As functional compensation of aging, elderly motor networks involve more nonmotor, parietal-occipital, and frontal areas, with higher global and local efficiency, node strength. ERSP and ITC changes seem to be sensitive and complementary biomarkers of age-related motor execution.

Network Localization of Spontaneous Confabulation

OBJECTIVE

Spontaneous confabulation is a symptom in which false memories are conveyed by the patient as true. The purpose of the study was to identify the neuroanatomical substrate of this complex symptom and evaluate the relationship to related symptoms, such as delusions and amnesia.

METHODS

Twenty-five lesion locations associated with spontaneous confabulation were identified in a systematic literature search. The network of brain regions functionally connected to each lesion location was identified with a large connectome database (N=1,000) and compared with networks derived from lesions associated with nonspecific (i.e., variable) symptoms (N=135), delusions (N=32), or amnesia (N=53).

RESULTS

Lesions associated with spontaneous confabulation occurred in multiple brain locations, but they were all part of a single functionally connected brain network. Specifically, 100% of lesions were connected to the mammillary bodies (familywise error rate [FWE]-corrected p<0.05). This connectivity was specific for lesions associated with confabulation compared with lesions associated with nonspecific symptoms or delusions (FWE-corrected p<0.05). Lesions associated with confabulation were more connected to the orbitofrontal cortex than those associated with amnesia (FWE-corrected p<0.05).

CONCLUSIONS

Spontaneous confabulation maps to a common functionally connected brain network that partially overlaps, but is distinct from, networks associated with delusions or amnesia. These findings lend new insight into the neuroanatomical bases of spontaneous confabulation.

Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

BACKGROUND

Although stratifying autism spectrum disorder (ASD) into different subtypes is a common effort in the research field, few papers have characterized the functional connectivity alterations of ASD subgroups classified by their clinical presentations.

METHODS

This is a case-control rs-fMRI study, based on large samples of open database (Autism Brain Imaging Data Exchange, ABIDE). The rs-MRI data from n=415 ASD patients (males n=357), and n=574 typical development (TD) controls (males n=410) were included. Clinical features of ASD were extracted and classified using data from each patient's Autism Diagnostic Interview-Revised (ADI-R) evaluation. Each subtype of ASD was characterized by local functional connectivity using regional homogeneity (ReHo) for assessment, remote functional connectivity using voxel-mirrored homotopic connectivity (VMHC) for assessment, the whole-brain functional connectivity, and graph theoretical features. These identified imaging properties from each subtype were integrated to create a machine learning model for classifying ASD patients into the subtypes based on their rs-fMRI data, and an independent dataset was used to validate the model.

RESULTS

All ASD participants were classified into Cluster-1 (patients with more severe impairment) and Cluster-2 (patients with moderate impairment) according to the dimensional scores of ADI-R. When compared to the TD group, Cluster-1 demonstrated increased local connection and decreased remote connectivity, and widespread hyper- and hypo-connectivity variations in the whole-brain functional connectivity. Cluster-2 was quite similar to the TD group in both local and remote connectivity. But at the level of whole-brain functional connectivity, the MCC-related connections were specifically impaired in Cluster-2. These properties of functional connectivity were fused to build a machine learning model, which achieved ~75% for identifying ASD subtypes (Cluster-1 accuracy = 81.75%; Cluster-2 accuracy = 76.48%).

CONCLUSIONS

The stratification of ASD by clinical presentations can help to minimize disease heterogeneity and highlight the distinguished properties of brain connectivity in ASD subtypes.

Resting-state functional connectivity correlates of antipsychotic treatment in unmedicated schizophrenia

BACKGROUND

Antipsychotics may modulate the resting state functional connectivity(rsFC) to improve clinical symptoms in schizophrenia(Sz). Existing literature has potential confounders like past medication effects and evaluating preselected regions/networks. We aimed to evaluate connectivity pattern changes with antipsychotics in unmedicated Sz using Multivariate pattern analysis(MVPA), a data-driven technique for whole-brain connectome analysis.

METHODS

Forty-seven unmedicated patients with Sz(DSM-IV-TR) underwent clinical evaluation and neuroimaging at baseline and after 3-months of antipsychotic treatment. Resting-state functional MRI was analysed using group-MVPA to derive 5-components. The brain region with significant connectivity pattern changes with antipsychotics was identified, and post-hoc seed-to-voxel analysis was performed to identify connectivity changes and their association with symptom changes.

RESULTS

Connectome-MVPA analysis revealed the connectivity pattern of a cluster localised to left anterior cingulate and paracingulate gyri (ACC/PCG) (peak coordinates:x = -04,y = +30,z = +26;k = 12;cluster-p_FWE=0.002) to differ significantly after antipsychotics. Specifically, its connections with clusters of precuneus/posterior cingulate cortex(PCC) and left inferior temporal gyrus(ITG) correlated with improvement in positive and negative symptoms scores, respectively.

CONCLUSION

ACC/PCG, a hub of the default mode network, seems to mediate the antipsychotic effects in unmedicated Sz. Evaluating causality models with data from randomised controlled design using the MVPA approach would further enhance our understanding of therapeutic connectomics in Sz.

Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients

The Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around the world. Neuroimaging evidence suggests the novel coronavirus can attack the central nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors are largely unknown. In this study, we have assessed brain functional connectivity (FC) using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was estimated using independent component analysis (ICA) and dual regression. When compared to the healthy group, the COVID group demonstrated significantly enhanced FC in the basal ganglia and precuneus networks (family wise error (fwe) corrected, pfwe < 0.05), while, on the other hand, reduced FC in the language network (pfwe < 0.05). The COVID group also experienced higher fatigue levels during work, compared to the healthy group (p < 0.001). Moreover, within the precuneus network, we noticed a significant negative correlation between FC and fatigue scores across groups (Spearman's ρ = -0.47, p = 0.001, r2 = 0.22). Interestingly, this relationship was found to be significantly stronger among COVID survivors within the left parietal lobe, which is known to be structurally and functionally associated with fatigue in other neurological disorders.

Resting-State Connectivity and Response to Psychotherapy Treatment in Adolescents and Adults With OCD: A Randomized Clinical Trial

OBJECTIVE

Cortical-subcortical hyperconnectivity related to affective-behavioral integration and cortical network hypoconnectivity related to cognitive control have been demonstrated in obsessive-compulsive disorder (OCD); the study objective was to examine whether these connectivity patterns predict treatment response.

METHODS

Adolescents (ages 12-17) and adults (ages 24-45) were randomly assigned to 12 sessions of exposure and response prevention (ERP) or stress management therapy (SMT), an active control. Before treatment, resting-state connectivity of ventromedial prefrontal cortical (vmPFC), cingulo-opercular, frontoparietal, and subcortical regions was assessed with functional MRI. OCD severity was assessed with the Yale-Brown Obsessive Compulsive Scale before, during, and after treatment. Usable fMRI and longitudinal symptom data were obtained from 116 patients (68 female; 54 adolescents; 60 medicated).

RESULTS

ERP produced greater decreases in symptom scores than SMT. ERP was selectively associated with less vmPFC-subcortical (caudate and thalamus) connectivity in both age groups and primarily in unmedicated participants. Greater symptom improvement with both ERP and SMT was associated with greater cognitive-control (cingulo-opercular and frontoparietal) and subcortical (putamen) connectivity across age groups. Developmental specificity was observed across ERP and SMT treatments, such that greater improvements with ERP than SMT were associated with greater frontoparietal-subcortical (nucleus accumbens) connectivity in adolescents but greater connectivity between frontoparietal regions in adults. Comparison of response-predictive connections revealed no significant differences compared with a matched healthy control group.

CONCLUSIONS

The results suggest that less vmPFC-subcortical connectivity related to affect-influenced behavior may be important for ERP engagement, whereas greater cognitive-control and motor circuit connectivity may generally facilitate response to psychotherapy. Finally, neural predictors of treatment response may differ by age.

Rostral anterior cingulate connectivity in older adults with subthreshold depressive symptoms: A preliminary study

Subthreshold depressive symptoms are highly prevalent among older adults and are associated with numerous health risks including cognitive decline and decreased physical health. One brain region central to neuroanatomical models of depressive disorders is the anterior cingulate cortex (ACC). The rostral portion of the ACC-comprised of the pregenual ACC and subgenual ACC-is implicated in emotion control and reward processing. The goal of the current study was to examine how functional connectivity in subregions of the rostral ACC relate to depressive symptoms, measured by the Beck Depression Inventory-Second Edition, in an ethnically diverse sample of 28 community-dwelling older adults. Based on meta-analyses of previous studies in primarily young adults with clinical depression, we hypothesized that greater depressive symptoms would be associated with primarily increased resting-state functional connectivity from both the subgenual ACC and pregenual ACC to default mode network regions and the dorsolateral PFC. We instead found that higher depressive symptoms were associated with lower functional connectivity of the ACC to the dorsolateral PFC and regions within the default mode network, including from the subgenual ACC to the dorsolateral PFC and anterior cingulate and from the pregenual ACC to the middle cingulate gyrus. This preliminary study highlights brain alterations at subthreshold levels of depressive symptoms in older adults, which could serve as targets for interventions.

The human egomotion network

All volitional movement in a three-dimensional space requires multisensory integration, in particular of visual and vestibular signals. Where and how the human brain processes and integrates self-motion signals remains enigmatic. Here, we applied visual and vestibular self-motion stimulation using fast and precise whole-brain neuroimaging to delineate and characterize the entire cortical and subcortical egomotion network in a substantial cohort (n=131). Our results identify a core egomotion network consisting of areas in the cingulate sulcus (CSv, PcM/pCi), the cerebellum (uvula), and the temporo-parietal cortex including area VPS and an unnamed region in the supramarginal gyrus. Based on its cerebral connectivity pattern and anatomical localization, we propose that this region represents the human homologue of macaque area 7a. Whole-brain connectivity and gradient analyses imply an essential role of the connections between the cingulate sulcus and the cerebellar uvula in egomotion perception. This could be via feedback loops involved updating visuo-spatial and vestibular information. The unique functional connectivity patterns of PcM/pCi hint at central role in multisensory integration essential for the perception of self-referential spatial awareness. All cortical egomotion hubs showed modular functional connectivity with other visual, vestibular, somatosensory and higher order motor areas, underlining their mutual function in general sensorimotor integration.