Shared and distinct intrinsic functional network centrality in autism and attention-deficit/hyperactivity disorder

Gray matter asymmetry alterations in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder

Despite the high coexistence of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) (ASD + ADHD), the underlying neurobiological basis of this disorder remains unclear. Altered brain structural asymmetries have been verified in ASD and ADHD, respectively, making brain asymmetry a candidate for characterizing this coexisting disorder. Here, we measured the gray matter (GM) volume asymmetry in ASD + ADHD versus ASD without ADHD (ASD-only), ADHD without ASD (ADHD-only), and typically developing controls (TDc). High-resolution T1-weighted data from 48 ASD + ADHD, 63 ASD-only, 32 ADHD-only, and 211 matched TDc were included in our study. We also assessed brain-behavior relationships and the effects of age on GM asymmetry. We found that there were both shared and disorder-specific GM volume asymmetry alterations in ASD + ADHD, ASD-only, and ADHD-only compared with TDc. This finding demonstrates that ASD + ADHD is neither an endophenocopy nor an additive pathology of ASD and ADHD, but an entirely different neuroanatomical pathology. In addition, ASD + ADHD displayed altered GM volume asymmetries in the prefrontal regions responsible for executive function and theory of mind compared with ASD-only. We also found significant effects of age on GM asymmetry. The present study may provide structural insights into the neural basis of ASD + ADHD.

Neural correlates of inattention in adults with ADHD

In the last two decades, numerous magnetic resonance imaging (MRI) studies have examined differences in cortical structure between individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) and healthy controls. These studies primarily emphasized alterations in gray matter volume (GMV) and cortical thickness (CT). Still, the scientific literature is notably scarce in regard to investigating associations of cortical structure with ADHD psychopathology, specifically inattention within adults with ADHD. The present study aimed to elucidate neurobiological underpinnings of inattention beyond GMV and CT by including cortical gyrification, sulcal depth, and fractal dimension. Building upon the Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS), cortical structure parameters were investigated using 141 T1-weighted anatomical scans of adult patients with ADHD. All brain structural analyses were performed using the threshold-free cluster enhancement (TFCE) approach and the Computational Anatomy Toolbox (CAT12) integrated into the Statistical Parametric Mapping Software (Matlab Version R2021a). Results revealed significant correlations of inattention in multiple brain regions. Cortical gyrification was negatively correlated, whereas cortical thickness and fractal dimension were positively associated with inattention. The clusters showed widespread distribution across the cerebral cortex, with both hemispheres affected. The cortical regions most prominently affected included the precuneus, para-, pre-, and postcentral gyri, superior parietal lobe, and posterior cingulate cortex. This study highlights the importance of cortical alterations in attentional processes in adults with ADHD. Further research in this area is warranted to elucidate intricacies of inattention in adults with ADHD to potentially enhance diagnostic accuracy and inform personalized treatment strategies.

Change in Striatal Functional Connectivity Networks Across Two Years Due to Stimulant Exposure in Childhood ADHD: Results from the ABCD Sample

Widely prescribed for Attention-Deficit/Hyperactivity Disorder (ADHD), stimulants (e.g., methylphenidate) have been studied for their chronic effects on the brain in prospective designs controlling dosage and adherence. While controlled approaches are essential, they do not approximate real-world stimulant exposure contexts where medication interruptions, dosage non-compliance, and polypharmacy are common. Brain changes in real-world conditions are largely unexplored. To fill this gap, we capitalized on the observational design of the Adolescent Brain Cognitive Development (ABCD) study to examine effects of stimulants on large-scale bilateral cortical networks' resting-state functional connectivity (rs-FC) with 6 striatal regions (left and right caudate, putamen, and nucleus accumbens) across two years in children with ADHD. Bayesian hierarchical regressions revealed associations between stimulant exposure and change in rs-FC of multiple striatal-cortical networks, affiliated with executive and visuo-motor control, which were not driven by general psychotropic medication. Of these connections, three were selective to stimulants versus stimulant naive: reduced rs-FC between caudate and frontoparietal network, and between putamen and frontoparietal and visual networks. Comparison with typically developing children in the ABCD sample revealed stronger rs-FC reduction in stimulant-exposed children for putamen and frontoparietal and visual networks, suggesting a normalizing effect of stimulants. 14% of stimulant-exposed children demonstrated reliable reduction in ADHD symptoms, and were distinguished by stronger rs-FC reduction between right putamen and visual network. Thus, stimulant exposure for a two-year period under real-world conditions modulated striatal-cortical functional networks broadly, had a normalizing effect on a subset of networks, and was associated with potential therapeutic effects involving visual attentional control.

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Quantitative Expression of Latent Disease Factors in Individuals Associated with Psychopathology Dimensions and Treatment Response

Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.

A chromosome region linked to neurodevelopmental disorders acts in distinct neuronal circuits in males and females to control locomotor behavior

Biological sex shapes the manifestation and progression of neurodevelopmental disorders (NDDs). These disorders often demonstrate male-specific vulnerabilities; however, the identification of underlying mechanisms remains a significant challenge in the field. Hemideletion of the 16p11.2 region (16p11.2 del/+) is associated with NDDs, and mice modeling 16p11.2 del/+ exhibit sex-specific striatum-related phenotypes relevant to NDDs. Striatal circuits, crucial for locomotor control, consist of two distinct pathways: the direct and indirect pathways originating from D1 dopamine receptor (D1R) and D2 dopamine receptor (D2R) expressing spiny projection neurons (SPNs), respectively. In this study, we define the impact of 16p11.2 del/+ on striatal circuits in male and female mice. Using snRNA-seq, we identify sex- and cell type-specific transcriptomic changes in the D1- and D2-SPNs of 16p11.2 del/+ mice, indicating distinct transcriptomic signatures in D1-SPNs and D2-SPNs in males and females, with a ∼5-fold greater impact in males. Further pathway analysis reveals differential gene expression changes in 16p11.2 del/+ male mice linked to synaptic plasticity in D1- and D2-SPNs and GABA signaling pathway changes in D1-SPNs. Consistent with our snRNA-seq study revealing changes in GABA signaling pathways, we observe distinct changes in miniature inhibitory postsynaptic currents (mIPSCs) in D1- and D2-SPNs from 16p11.2 del/+ male mice. Behaviorally, we utilize conditional genetic approaches to introduce the hemideletion selectively in either D1- or D2-SPNs and find that conditional hemideletion of genes in the 16p11.2 region in D2-SPNs causes hyperactivity in male mice, but hemideletion in D1-SPNs does not. Within the striatum, hemideletion of genes in D2-SPNs in the dorsal lateral striatum leads to hyperactivity in males, demonstrating the importance of this striatal region. Interestingly, conditional 16p11.2 del/+ within the cortex drives hyperactivity in both sexes. Our work reveals that a locus linked to NDDs acts in different striatal circuits, selectively impacting behavior in a sex- and cell type-specific manner, providing new insight into male vulnerability for NDDs.

Highlights

- 16p11.2 hemideletion (16p11.2 del/+) induces sex- and cell type-specific transcriptomic signatures in spiny projection neurons (SPNs). - Transcriptomic changes in GABA signaling in D1-SPNs align with changes in inhibitory synapse function. - 16p11.2 del/+ in D2-SPNs causes hyperactivity in males but not females. - 16p11.2 del/+ in D2-SPNs in the dorsal lateral striatum drives hyperactivity in males. - 16p11.2 del/+ in cortex drives hyperactivity in both sexes.

Graphic abstract

Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del/+) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and highlighted three genes within the deleted region: thousand and one amino acid protein kinase 2 (Taok2), seizure-related 6 homolog-like 2 (Sez6l2), and major vault protein (Mvp). Using CRISPR/Cas9, we generated mice carrying null mutations in Taok2, Sez6l2, and Mvp (3 gene hemi-deletion (3g del/+)). Hemi-deletion of these 3 genes recapitulates sex-specific behavioral alterations in striatum-dependent behavioral tasks observed in 16p11.2 del/+ mice, specifically male-specific hyperactivity and impaired motivation for reward seeking. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice exclusively in males. Subsequent analysis identified translation dysregulation and/or extracellular signal-regulated kinase signaling as plausible molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Interestingly, ribosomal profiling supported the notion of translation dysregulation in both 3g del/+ and 16p11.2 del/+ male mice. However, mice carrying a 4-gene deletion (with an additional deletion of Mapk3) exhibited fewer phenotypic similarities with 16p11.2 del/+ mice. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice. These results support the importance of a polygenic approach to study NDDs and underscore that the effects of the large genetic deletions result from complex interactions between multiple candidate genes.

Comparing Executive Functions in Children and Adolescents with Autism and ADHD-A Systematic Review and Meta-Analysis

Two neurodevelopmental conditions, autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), have been associated with executive function (EF) impairments but the specificity of their impairments is still controversial. The present meta-analysis aimed to identify the differences in EF profiles of ASD, ADHD, and ASD+ADHD in relation to a control group of individuals with typical development (TD) and to understand whether the EF performance could change depending upon the type of measure used to assess EF (performance tests vs. questionnaires). Results from 36 eligible studies revealed that ADHD and ASD showed more difficulties than the TD group in tests and, particularly, in questionnaires. No significant differences in the EF profile emerged between ASD and ADHD when assessed through neuropsychological tests (d = 0.02), while significant differences emerged when assessed through questionnaires, with ADHD having higher ratings than ASD (d = -0.34). EF questionnaires and neuropsychological tests may catch two different constructs of EF, with the former being more predictive of everyday life EF impairments. The comparison between the double diagnosis group (ADHD+ASD) and the clinical groups pointed out that the former has a more similar EF profile to the ADHD-alone one and that it shows more difficulties than ASD-alone.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder

BACKGROUND

This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD).

METHODS

A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software.

RESULTS

A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences.

CONCLUSIONS

The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Altered Intrinsic Brain Spontaneous Activities in Children With Autism Spectrum Disorder Comorbid ADHD

OBJECTIVE

The study involved 17 children with Autism Spectrum Disorder (ASD), 21 with ADHD, 30 with both (ASD + ADHD), and 28 typically developing children (TD).

METHODS

The amplitude of low-frequency fluctuations (ALFF) was measured as a regional brain function index. Intrinsic functional connectivity (iFC) was also analyzed using the region of interest (ROI) identified in ALFF analysis. Statistical analysis was done via one-way ANCOVA, Gaussian random field (GRF) theory, and post-hoc pair-wise comparisons.

RESULTS

The ASD + ADHD group showed increased ALFF in the left middle frontal gyrus (MFG.L) compared to the TD group. In terms of global brain function, the ASD group displayed underconnectivity in specific regions compared to the ASD + ADHD and TD groups.

CONCLUSION

The findings contribute to understanding the neural mechanisms underlying ASD + ADHD.

The role of stimulant washout status in functional connectivity of default mode and fronto-parietal networks in children with neurodevelopmental conditions

BACKGROUND

Stimulant medication is the primary pharmacological treatment for attention dysregulation and is commonly prescribed for children with Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism. Neuroimaging studies of these groups commonly use a 24-48-hour washout period to mediate the effects of stimulant medication on functional connectivity (FC) metrics. However, the impact of washout on functional connectivity has received limited study.

METHODS

We used fMRI data from participants with diagnosis of Autism and ADHD (and an off stimulant control) from the Adolescent Brain and Cognitive Development (ABCD) and Autism Brain Imaging Data Exchange (ABIDE) databases to explore the effect of simulant washout on FC. Connectivity within and between the default mode (DMN) and fronto-parietal networks (FPN) was examined, as these networks have previously been implicated in attention dysregulation and associated with stimulant medication usage. For each diagnostic group, we assessed effects in interconnectivity between DMN and FPN, intraconnectivity within DMN, and intraconnectivity within FPN.

RESULTS

We found no significant effect of medication status in intra- and inter-connectivity of the DMN and the FPN in either diagnostic group.

IMPLICATIONS

Our findings suggest that more information is needed about the effect of stimulant medication, and washout, on the FC of attention networks in clinical populations.

Functional brain network alterations in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are two highly prevalent and commonly co-occurring neurodevelopmental disorders. The neural mechanisms underpinning the comorbidity of ASD and ADHD (ASD + ADHD) remain unclear. We focused on the topological organization and functional connectivity of brain networks in ASD + ADHD patients versus ASD patients without ADHD (ASD-only). Resting-state functional magnetic resonance imaging (rs-fMRI) data from 114 ASD and 161 typically developing (TD) individuals were obtained from the Autism Brain Imaging Data Exchange II. The ASD patients comprised 40 ASD + ADHD and 74 ASD-only individuals. We constructed functional brain networks for each group and performed graph-theory and network-based statistic (NBS) analyses. Group differences between ASD + ADHD and ASD-only were analyzed at three levels: nodal, global, and connectivity. At the nodal level, ASD + ADHD exhibited topological disorganization in the temporal and occipital regions, compared with ASD-only. At the global level, ASD + ADHD and ASD-only displayed no significant differences. At the connectivity level, the NBS analysis revealed that ASD + ADHD showed enhanced functional connectivity between the prefrontal and frontoparietal regions, as well as between the orbitofrontal and occipital regions, compared with ASD-only. The hippocampus was the shared region in aberrant functional connectivity patterns in ASD + ADHD and ASD-only compared with TD. These findings suggests that ASD + ADHD displays altered topology and functional connectivity in the brain regions that undertake social cognition, language processing, and sensory processing.

Shared and distinctive dysconnectivity patterns underlying pure generalized anxiety disorder (GAD) and comorbid GAD and depressive symptoms

The resting-state connectivity features underlying pure generalized anxiety disorder (GAD, G1) and comorbid GAD and depressive symptoms (G2) have not been directly compared. Furthermore, it is unclear whether these features might serve as potential prognostic biomarkers and change with treatment. Degree centrality (DC) in G1 (40 subjects), G2 (58 subjects), and healthy controls (HCs, 54 subjects) was compared before treatment, and the DC of G1 or G2 at baseline was compared with that after 4 weeks of paroxetine treatment. Using support vector regression (SVR), voxel-wise DC across the entire brain and abnormal DC at baseline were employed to predict treatment response. At baseline, G1 and G2 exhibited lower DC in the left mid-cingulate cortex and vermis IV/V compared to HCs. Additionally, compared to HCs, G1 had lower DC in the left middle temporal gyrus, while G2 showed higher DC in the right inferior temporal/fusiform gyrus. However, there was no significant difference in DC between G1 and G2. The SVR based on abnormal DC at baseline could successfully predict treatment response in responders in G2 or in G1 and G2. Notably, the predictive performance based on abnormal DC at baseline surpassed that based on DC across the entire brain. After treatment, G2 responders showed lower DC in the right medial orbital frontal gyrus, while no change in DC was identified in G1 responders. The G1 and G2 showed common and distinct dysconnectivity patterns and they could potentially serve as prognostic biomarkers. Furthermore, DC in patients with GAD could change with treatment.

Aberrant Functional Connectivity in Core-Periphery Structure Based on WSBM in ADHD

OBJECTIVE

Brain network studies have revealed that the community structure of ADHD is altered. However, these studies have only focused on modular community structure, ignoring the core-periphery community structure.

METHOD

This paper employed the weighted stochastic block model to divide the functional connectivity (FC) into 10 communities. And we adopted core score to define the core-periphery structure of FC. Finally, connectivity strength (CS) and disruption index (DI) were used to evaluate the changes of core-periphery structure in ADHD.

RESULTS

The core community of visual network showed reduced CS and a positive value of DI, while the CS of periphery community was enhanced. In addition, the interaction between core communities (involving the sensorimotor and visual network) and periphery community of attention network showed increased CS and a negative valve of DI.

CONCLUSION

Anomalies in core-periphery community structure provide a new perspective for understanding the community structure of ADHD.

Enhanced group-level dorsolateral prefrontal cortex subregion parcellation through functional connectivity-based distance-constrained spectral clustering with application to autism spectrum disorder

The dorsolateral prefrontal cortex (DLPFC) assumes a central role in cognitive and behavioral control, emerging as a crucial target region for interventions in autism spectrum disorder neuroregulation. Consequently, we endeavor to unravel the functional subregions within the DLPFC to shed light on the intricate functions of the brain. We introduce a distance-constrained spectral clustering (SC-DW) methodology that leverages functional connection to identify distinctive functional subregions within the DLPFC. Furthermore, we verify the relationship between the functional characteristics of these subregions and their clinical implications. Our methodology begins with principal component analysis to extract the salient features. Subsequently, we construct an adjacency matrix, which is constrained by the spatial properties of the brain, by linearly combining the distance matrix and a similarity matrix. The quality of spectral clustering is further optimized through multiple cluster evaluation coefficient. The results from SC-DW revealed four uniform and contiguous subregions within the bilateral DLPFC. Notably, we observe a substantial positive correlation between the functional characteristics of the third and fourth subregions in the left DLPFC with clinical manifestations. These findings underscore the unique insights offered by our proposed methodology in the realms of brain subregion delineation and therapeutic targeting.

Altered brain network centrality in patients with orbital fracture: A resting‑state functional MRI study

The present study aimed to investigate potential functional network brain-activity abnormalities in individuals with orbital fracture (OF) using the voxel-wise degree centrality (DC) technique. The present study included 20 patients with OF (12 males and 8 females) and 20 healthy controls (HC; 12 males and 8 females), who were matched for gender, age and educational attainment. Functional magnetic resonance imaging (fMRI) in the resting state has been widely applied in several fields. Receiver operating characteristic (ROC) curves were calculated to distinguish between patients with OF and HCs. In addition, correlation analyses were performed between behavioral performance and average DC values in various locations. The DC technique was used to assess unprompted brain activity. Right cerebellum 9 region (Cerebelum_9_R) and left cerebellar peduncle 2 area (Cerebelum_Crus2_L) DC values of patients with OF were increased compared with those in HCs. Cerebelum_9_R and Cerebelum_Crus2_L had area under the ROC curve values of 0.983 and 1.000, respectively. Patients with OF appear to have several brain regions that exhibited aberrant brain network characteristics, which raises the possibility of neuropathic causes and offers novel therapeutic options.

Specific brain imaging alterations underlying autistic traits in children with attention-deficit/hyperactivity disorder

BACKGROUND

Autistic traits (ATs) are frequently reported in children with Attention-Deficit/Hyperactivity Disorder (ADHD). This study aimed to examine ATs in children with ADHD from both behavioral and neuroimaging perspectives.

METHODS

We used the Autism Spectrum Screening Questionnaire (ASSQ) to assess and define subjects with and without ATs. For behavioral analyses, 67 children with ADHD and ATs (ADHD + ATs), 105 children with ADHD but without ATs (ADHD - ATs), and 44 typically developing healthy controls without ATs (HC - ATs) were recruited. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data and analyzed the mean amplitude of low-frequency fluctuation (mALFF) values (an approach used to depict different spontaneous brain activities) in a sub-sample. The imaging features that were shared between ATs and ADHD symptoms or that were unique to one or the other set of symptoms were illustrated as a way to explore the "brain-behavior" relationship.

RESULTS

Compared to ADHD-ATs, the ADHD + ATs group showed more global impairment in all aspects of autistic symptoms and higher hyperactivity/impulsivity (HI). Partial-correlation analysis indicated that HI was significantly positively correlated with all aspects of ATs in ADHD. Imaging analyses indicated that mALFF values in the left middle occipital gyrus (MOG), left parietal lobe (PL)/precuneus, and left middle temporal gyrus (MTG) might be specifically related to ADHD, while those in the right MTG might be more closely associated with ATs. Furthermore, altered mALFF in the right PL/precuneus correlated with both ADHD and ATs, albeit in diverse directions.

CONCLUSIONS

The co-occurrence of ATs in children with ADHD manifested as different behavioral characteristics and specific brain functional alterations. Assessing ATs in children with ADHD could help us understand the heterogeneity of ADHD, further explore its pathogenesis, and promote clinical interventions.

Probing the overarching continuum theory: data-driven phenotypic clustering of children with ASD or ADHD

The clinical validity of the distinction between ADHD and ASD is a longstanding discussion. Recent advances in the realm of data-driven analytic techniques now enable us to formally investigate theories aiming to explain the frequent co-occurrence of these neurodevelopmental conditions. In this study, we probe different theoretical positions by means of a pre-registered integrative approach of novel classification, subgrouping, and taxometric techniques in a representative sample (N = 434), and replicate the results in an independent sample (N = 219) of children (ADHD, ASD, and typically developing) aged 7-14 years. First, Random Forest Classification could predict diagnostic groups based on questionnaire data with limited accuracy-suggesting some remaining overlap in behavioral symptoms between them. Second, community detection identified four distinct groups, but none of them showed a symptom profile clearly related to either ADHD or ASD in neither the original sample nor the replication sample. Third, taxometric analyses showed evidence for a categorical distinction between ASD and typically developing children, a dimensional characterization of the difference between ADHD and typically developing children, and mixed results for the distinction between the diagnostic groups. We present a novel framework of cutting-edge statistical techniques which represent recent advances in both the models and the data used for research in psychiatric nosology. Our results suggest that ASD and ADHD cannot be unambiguously characterized as either two separate clinical entities or opposite ends of a spectrum, and highlight the need to study ADHD and ASD traits in tandem.

A systematic review of cannabidiol trials in neurodevelopmental disorders

Cannabis-derived compounds, such as cannabidiol (CBD) and delta-9-trans-tetrahydrocannabinol (THC), are increasingly prescribed for a range of clinical indications. These phyto-cannabinoids have multiple biological targets, including the body's endocannabinoid system. There is growing scientific interest in the use of CBD, a non-intoxicating compound, to ameliorate symptoms associated with neurodevelopmental disorders. However, its suitability as a pharmaceutical intervention has not been reliably established in these clinical populations. This systematic review examines the nine published randomised controlled trials (RCTs) that have probed the safety and efficacy of CBD in individuals diagnosed with attention deficit hyperactivity disorder, autism spectrum disorder, intellectual disability, Tourette Syndrome, and complex motor disorders. Studies were identified systematically through searching four databases: Medline, CINAHL complete, PsycINFO, and EMBASE. Inclusion criteria were randomised controlled trials involving CBD and participants with neurodevelopmental disorders. No publication year or language restrictions were applied. Relevant data were extracted from the identified list of eligible articles. After extraction, data were cross-checked between the authors to ensure consistency. Several trials indicate potential efficacy, although this possibility is currently too inconsistent across RCTs to confidently guide clinical usage. Study characteristics, treatment properties, and outcomes varied greatly across the included trials. The material lack of comparable RCTs leaves CBD's suitability as a pharmacological treatment for neurodevelopmental disorders largely undetermined. A stronger evidence base is urgently required to establish safety and efficacy profiles and guide the ever-expanding clinical uptake of cannabis-derived compounds in neurodevelopmental disorders. Prospero registration number: CRD42021267839.

Abnormal voxel-wise whole-brain functional connectivity in first-episode, drug-naïve adolescents with major depression disorder

Major depression disorder (MDD) is one of the most common psychiatric disorders. Previous studies have demonstrated structural and functional abnormalities in adult depression. However, the neurobiology of adolescent depression has not been fully understood. The aim of this study was to investigate the intrinsic dysconnectivity pattern of voxel-level whole-brain functional networks in first-episode, drug-naïve adolescents with MDD. Resting-state functional magnetic resonance imaging data were acquired from 66 depressed adolescents and 47 matched healthy controls. Voxel-wise degree centrality (DC) analysis was performed to identify voxels that showed altered whole-brain functional connectivity (FC) with other voxels. We further conducted seed-based FC analysis to investigate in more detail the connectivity patterns of the identified DC changes. The relationship between altered DC and clinical variables in depressed adolescents was also analyzed. Compared with controls, depressed adolescents showed lower DC in the bilateral hippocampus, left superior temporal gyrus and right insula. Seed-based analysis revealed that depressed adolescents, relative to controls, showed hypoconnectivity between the hippocampus to the medial prefrontal regions and right precuneus. Furthermore, the DC values in the bilateral hippocampus were correlated with the Hamilton Depression Rating Scale score and duration of disease (all P < 0.05, false discovery rate corrected). Our study indicates abnormal intrinsic dysconnectivity patterns of whole-brain functional networks in drug-naïve, first-episode adolescents with MDD, and abnormal DC in the hippocampus may affect the association of prefrontal-hippocampus circuit. These findings may provide new insights into the pathophysiology of adolescent-onset MDD.

Child Developmental MRI (CDM) project: protocol for a multi-centre, cross-sectional study on elucidating the pathophysiology of attention-deficit/hyperactivity disorder and autism spectrum disorder through a multi-dimensional approach

INTRODUCTION

Neuroimaging studies on attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have demonstrated differences in extensive brain structure, activity and network. However, there remains heterogeneity and inconsistency across these findings, presumably because of the diversity of the disorders themselves, small sample sizes, and site and parameter differences in MRI scanners, and their overall pathogenesis remains unclear. To address these gaps in the literature, we will apply the travelling-subject approach to correct site differences in MRI scanners and clarify brain structure and network characteristics of children with ADHD and ASD using large samples collected in a multi-centre collaboration. In addition, we will investigate the relationship between these characteristics and genetic, epigenetic, biochemical markers, and behavioural and psychological measures.

METHODS AND ANALYSIS

We will collect resting-state functional MRI (fMRI) and T1-weighted and diffusion-weighted MRI data from 15 healthy adults as travelling subjects and 300 children (ADHD, n=100; ASD, n=100; and typical development, n=100) with multi-dimensional assessments. We will also apply data from more than 1000 samples acquired in our previous neuroimaging studies on ADHD and ASD.

ETHICS AND DISSEMINATION

The study protocol has been approved by the Research Ethics Committee of the University of Fukui Hospital (approval no: 20220601). Our study findings will be submitted to scientific peer-reviewed journals and conferences.

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Relapse risk revealed by degree centrality and cluster analysis in heroin addicts undergoing methadone maintenance treatment

BACKGROUND

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

METHODS

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

RESULTS

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical-striatal-thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

CONCLUSION

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients’ cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and identified 3 genes of particular importance within the deleted region: thousand and one amino acid protein kinase 2 (Taok2), seizure-related 6 homolog-like 2 (Sez6l2), and major vault protein (Mvp). Using the CRISPR/Cas9 technique, we generated 3 gene hemi-deletion (3g del/+) mice carrying null mutations in Taok2, Sez6l2, and Mvp. We assessed striatum-dependent phenotypes of these 3g del/+ mice in behavioral, molecular, and imaging studies. Hemi-deletion of Taok2, Sez6l2, and Mvp induces sex-specific behavioral alterations in striatum-dependent behavioral tasks, specifically male-specific hyperactivity and impaired motivation for reward seeking, resembling behavioral phenotypes of 16p11.2 del/+ mice. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice, but only in males. Pathway analysis identified ribosomal dysfunction and translation dysregulation as molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice, unlike single gene mutation studies. These results support the importance of a polygenic approach to study NDDs and our novel strategy to identify genes of interest using gene expression patterns in brain regions, such as the striatum, which are impacted in these disorders.

Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and identified 3 genes of particular importance within the deleted region: thousand and one amino acid protein kinase 2 ( Taok2 ), seizure-related 6 homolog-like 2 ( Sez6l2 ), and major vault protein ( Mvp ). Using the CRISPR/Cas9 technique, we generated 3 gene hemi-deletion (3g del/+) mice carrying null mutations in Taok2, Sez6l2 , and Mvp . We assessed striatum-dependent phenotypes of these 3g del/+ mice in behavioral, molecular, and imaging studies. Hemi-deletion of Taok2, Sez6l2 , and Mvp induces sex-specific behavioral alterations in striatum-dependent behavioral tasks, specifically male-specific hyperactivity and impaired motivation for reward seeking, resembling behavioral phenotypes of 16p11.2 del/+ mice. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice, but only in males. Pathway analysis identified ribosomal dysfunction and translation dysregulation as molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice, unlike single gene mutation studies. These results support the importance of a polygenic approach to study NDDs and our novel strategy to identify genes of interest using gene expression patterns in brain regions, such as the striatum, which are impacted in these disorders.

Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study

Attention deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder, is the most frequent comorbid condition seen in children with autism spectrum disorder (ASD). This high comorbidity between ADHD and ASD worsens symptom manifestations and complicates disease treatment and prognosis. It remains unclear whether individuals suffering with both ADHD and ASD, compared to individuals with ADHD only, share overlapping neural correlates associated with ADHD neuropathology, or exhibit a distinct neuropathological profile. Answering this question is critical to the understanding of treatment outcomes for the challenging comorbid ADHD symptoms. To identify the shared and the differentiated neural correlates of the comorbidity mechanisms of ADHD with ASD, we use diffusion tensor imaging (DTI) to characterize white-matter microstructure integrity in youth diagnosed with ADHD+ASD and youth with ADHD-only (excluding both the diagnosis and symptoms of ASD) compared with a healthy control group. Results show that the ADHD-only cohort exhibits impaired microstructural integrity (lower fractional anisotropy, FA) in the callosal-cingulum (CC-CG) tracts compared to the control cohort. The ADHD+ASD comorbid cohort shows impaired FA in an overlapping region within the CC-CG tracts and, additionally, shows impaired FA in the frontolimbic tracts including the uncinate fasciculus and anterior thalamic radiation. Across all participants, FA in the CC-CG showed a significantly negative relationship with the degree of ADHD symptom severity. Findings of this study suggest a specific role of CC-CG underlying ADHD neuropathology and symptom manifestations, and when comorbid with ASD a shared ADHD profile with a shift toward an anterior-brain, frontal impact. Results of this study may facilitate future targeted therapeutics and assist in diagnostic precision for individuals suffering with differing levels of comorbid ADHD with ASD, and ultimately contribute to improve prognostication and outcomes for these two highly prevalent and comorbid neurodevelopmental disorders.

Alteration of resting-state network dynamics in autism spectrum disorder based on leading eigenvector dynamics analysis

Background

Neurobiological models to explain the vulnerability of autism spectrum disorders (ASDs) are scarce, and previous resting-state functional magnetic resonance imaging (rs-fMRI) studies mostly examined static functional connectivity (FC). Given that FC constantly evolves, it is critical to probe FC dynamic differences in ASD patients.

Methods

We characterized recurring phase-locking (PL) states during rest in 45 ASD patients and 47 age- and sex-matched healthy controls (HCs) using Leading Eigenvector Dynamics Analysis (LEiDA) and probed the organization of PL states across different fine grain sizes.

Results

Our results identified five different groups of discrete resting-state functional networks, which can be defined as recurrent PL state overtimes. Specifically, ASD patients showed an increased probability of three PL states, consisting of the visual network (VIS), frontoparietal control network (FPN), default mode network (DMN), and ventral attention network (VAN). Correspondingly, ASD patients also showed a decreased probability of two PL states, consisting of the subcortical network (SUB), somatomotor network (SMN), FPN, and VAN.

Conclusion

Our findings suggested that the temporal reorganization of brain discrete networks was closely linked to sensory to cognitive systems of the brain. Our study provides new insights into the dynamics of brain networks and contributes to a deeper understanding of the neurological mechanisms of ASD.

Structural filtering of functional data offered discriminative features for autism spectrum disorder

This study attempted to answer the question, "Can filtering the functional data through the frequency bands of the structural graph provide data with valuable features which are not valuable in unfiltered data"?. The valuable features discriminate between autism spectrum disorder (ASD) and typically control (TC) groups. The resting-state fMRI data was passed through the structural graph's low, middle, and high-frequency band (LFB, MFB, and HFB) filters to answer the posed question. The structural graph was computed using the diffusion tensor imaging data. Then, the global metrics of functional graphs and metrics of functional triadic interactions were computed for filtered and unfiltered rfMRI data. Compared to TCs, ASDs had significantly higher clustering coefficients in the MFB, higher efficiencies and strengths in the MFB and HFB, and lower small-world propensity in the HFB. These results show over-connectivity, more global integration, and decreased local specialization in ASDs compared to TCs. Triadic analysis showed that the numbers of unbalanced triads were significantly lower for ASDs in the MFB. This finding may indicate the reason for restricted and repetitive behavior in ASDs. Also, in the MFB and HFB, the numbers of balanced triads and the energies of triadic interactions were significantly higher and lower for ASDs, respectively. These findings may reflect the disruption of the optimum balance between functional integration and specialization. There was no significant difference between ASDs and TCs when using the unfiltered data. All of these results demonstrated that significant differences between ASDs and TCs existed in the MFB and HFB of the structural graph when analyzing the global metrics of the functional graph and triadic interaction metrics. Also, these results demonstrated that frequency bands of the structural graph could offer significant findings which were not found in the unfiltered data. In conclusion, the results demonstrated the promising perspective of using structural graph frequency bands for attaining discriminative features and new knowledge, especially in the case of ASD.

The brain correlates of hostile attribution bias and their relation to the displaced aggression

BACKGROUND

Hostile attribution bias (HAB) has been considered as a risk factor of various types of psychosocial adjustment problem, and contributes to displaced aggression (DA). The neural basis of HAB and the underlying mechanisms of how HAB predicts DA remain unclear.

METHODS

The current study used degree centrality (DC) and resting-sate functional connectivity (RSFC) to investigate the functional connection pattern related to HAB in 503 undergraduate students. Furthermore, the "Decoding" was used to investigate which psychological components the maps of the RSFC-behavior may be related to. Finally, to investigate whether and how the RSFC pattern, HAB predicts DA, we performed mediation analyses.

RESULTS

We found that HAB was negatively associated with DC in bilateral temporal poles (TP) and positively correlated with DC in the putamen and thalamus; Moreover, HAB was negatively associated with the strength of functional connectivity between TP and brain regions in the theory of mind network (ToM), and positively related to the strength of functional connectivity between the thalamus and regions in the ToM network. The "Decoding" showed the maps of the RSFC-behavior may involve the theory mind, autobiographic, language, comprehension and working memory. Mediation analysis further showed that HAB mediated the relationship between some neural correlates of the HAB and DA.

LIMITATIONS

The current results need to be further tested by experimental methods or longitudinal design in further studies.

CONCLUSIONS

These findings shed light on the neural underpinnings of HAB and provide a possible mediation model regarding the relationships among RSFC pattern, HAB, and displaced aggression.

Topological analysis of brain dynamics in autism based on graph and persistent homology

Autism spectrum disorder (ASD) is a heterogeneous disorder with a rapidly growing prevalence. In recent years, the dynamic functional connectivity (DFC) technique has been used to reveal the transient connectivity behavior of ASDs' brains by clustering connectivity matrices in different states. However, the states of DFC have not been yet studied from a topological point of view. In this paper, this study was performed using global metrics of the graph and persistent homology (PH) and resting-state functional magnetic resonance imaging (fMRI) data. The PH has been recently developed in topological data analysis and deals with persistent structures of data. The structural connectivity (SC) and static FC (SFC) were also studied to know which one of the SC, SFC, and DFC could provide more discriminative topological features when comparing ASDs with typical controls (TCs). Significant discriminative features were only found in states of DFC. Moreover, the best classification performance was offered by persistent homology-based metrics and in two out of four states. In these two states, some networks of ASDs compared to TCs were more segregated and isolated (showing the disruption of network integration in ASDs). The results of this study demonstrated that topological analysis of DFC states could offer discriminative features which were not discriminative in SFC and SC. Also, PH metrics can provide a promising perspective for studying ASD and finding candidate biomarkers.

Robust, Generalizable, and Interpretable Artificial Intelligence-Derived Brain Fingerprints of Autism and Social Communication Symptom Severity

BACKGROUND

Autism spectrum disorder (ASD) is among the most pervasive neurodevelopmental disorders, yet the neurobiology of ASD is still poorly understood because inconsistent findings from underpowered individual studies preclude the identification of robust and interpretable neurobiological markers and predictors of clinical symptoms.

METHODS

We leverage multiple brain imaging cohorts and exciting recent advances in explainable artificial intelligence to develop a novel spatiotemporal deep neural network (stDNN) model, which identifies robust and interpretable dynamic brain markers that distinguish ASD from neurotypical control subjects and predict clinical symptom severity.

RESULTS

stDNN achieved consistently high classification accuracies in cross-validation analysis of data from the multisite ABIDE (Autism Brain Imaging Data Exchange) cohort (n = 834). Crucially, stDNN also accurately classified data from independent Stanford (n = 202) and GENDAAR (Gender Exploration of Neurogenetics and Development to Advanced Autism Research) (n = 90) cohorts without additional training. stDNN could not distinguish attention-deficit/hyperactivity disorder from neurotypical control subjects, highlighting the model's specificity. Explainable artificial intelligence revealed that brain features associated with the posterior cingulate cortex and precuneus, dorsolateral and ventrolateral prefrontal cortex, and superior temporal sulcus, which anchor the default mode network, cognitive control, and human voice processing systems, respectively, most clearly distinguished ASD from neurotypical control subjects in the three cohorts. Furthermore, features associated with the posterior cingulate cortex and precuneus nodes of the default mode network emerged as robust predictors of the severity of core social and communication deficits but not restricted/repetitive behaviors in ASD.

CONCLUSIONS

Our findings, replicated across independent cohorts, reveal robust individualized functional brain fingerprints of ASD psychopathology, which could lead to more objective and precise phenotypic characterization and targeted treatments.

Cognitive theories of autism based on the interactions between brain functional networks

Cognitive functions are directly related to interactions between the brain's functional networks. This functional organization changes in the autism spectrum disorder (ASD). However, the heterogeneous nature of autism brings inconsistency in the findings, and specific pattern of changes based on the cognitive theories of ASD still requires to be well-understood. In this study, we hypothesized that the theory of mind (ToM), and the weak central coherence theory must follow an alteration pattern in the network level of functional interactions. The main aim is to understand this pattern by evaluating interactions between all the brain functional networks. Moreover, the association between the significantly altered interactions and cognitive dysfunctions in autism is also investigated. We used resting-state fMRI data of 106 subjects (5–14 years, 46 ASD: five female, 60 HC: 18 female) to define the brain functional networks. Functional networks were calculated by applying four parcellation masks and their interactions were estimated using Pearson's correlation between pairs of them. Subsequently, for each mask, a graph was formed based on the connectome of interactions. Then, the local and global parameters of the graph were calculated. Finally, statistical analysis was performed using a two-sample t-test to highlight the significant differences between autistic and healthy control groups. Our corrected results show significant changes in the interaction of default mode, sensorimotor, visuospatial, visual, and language networks with other functional networks that can support the main cognitive theories of autism. We hope this finding sheds light on a better understanding of the neural underpinning of autism.

How does brain structure and function on MRI differ in children with autism spectrum disorder, developmental coordination disorder, and/or attention deficit hyperactivity disorder?

AIM

The purpose of this study was to systematically review the neural similarities and differences in brain structure and function, measured by magnetic resonance imaging (MRI), in children with neurodevelopmental disorders that commonly co-occur to understand if and how they have shared neuronal characteristics.

METHOD

Using systematic review methodology, the following databases were comprehensively searched: MEDLINE, EMBASE, CINAHL, CENTRAL, PsycINFO, and ProQuest from the earliest record up to December 2021. Inclusion criteria were: (1) peer-reviewed studies, case reports, or theses; (2) children under 18 years of age with at least one of the following neurodevelopmental disorders: autism spectrum disorder (ASD), attention hyperactivity deficit disorder (ADHD), developmental coordination disorder (DCD), and their co-occurrence; (3) studies based on MRI modalities (i.e., structural MRI, diffusion tensor imaging (DTI), and resting-state fMRI). Thirty-one studies that met the inclusion criteria were included for quality assessment by two independent reviewers using the Appraisal tool for Cross-Sectional Studies (AXIS).

RESULTS

Studies compared brain structure and function of children with DCD and ADHD (n=6), DCD and ASD (n=1), ASD and ADHD (n=17), and various combinations of these co-occurring conditions (n=7). Structural neuroimaging (n=15) was the most commonly reported modality, followed by resting-state (n=8), DTI (n=5), and multi-modalities (n=3).

INTERPRETATION

Evidence indicated that the neural correlates of the co-occurring conditions were more widespread and distinct compared to a single diagnosis. The majority of findings (77%) suggested that each neurodevelopmental disorder had more distinct neural correlates than shared neural features, suggesting that each disorder is distinct despite commonly co-occurring with each other. As the number of papers examining the co-occurrence of ASD, DCD, and/or ADHD was limited and most findings were not corrected for multiple comparisons, these results must be interpreted with caution.

Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder

Background

Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder (ADHD). Recently, white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain-behavior relationships. However, disorder-specific features of white matter functional networks (WMFNs) are less well understood than those of gray matter functional networks. In the current study, we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD.

Methods

We recruited 46 drug-naïve boys with ADHD and 46 typically developing (TD) boys, and used clustering analysis on resting-state functional magnetic resonance imaging data to generate WMFNs in each group. Intrinsic activity within each network was extracted, and the associations between network activity and behavior measures were assessed using correlation analysis.

Results

Nine WMFNs were identified for both ADHD and TD participants. However, boys with ADHD showed a splitting of the inferior corticospinal-cerebellar network and lacked a cognitive control network. In addition, boys with ADHD showed increased activity in the dorsal attention network and somatomotor network, which correlated positively with attention problems and hyperactivity symptom scores, respectively, while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition, working memory, and verbal fluency.

Conclusions

We discovered a dual pattern of white matter network activity in drug-naïve ADHD boys, with hyperactive symptom-related networks and hypoactive cognitive networks. These findings characterize two distinct types of WMFN in ADHD psychopathology.

Excessive Functional Coupling With Less Variability Between Salience and Default Mode Networks in Autism Spectrum Disorder

BACKGROUND

Atypical activity in the salience network (SN) and default mode network (DMN) has been previously reported in individuals with autism spectrum disorder (ASD). However, no study to date has investigated the nature and dynamics of the interaction between these two networks in ASD.

METHODS

Here, we aimed to characterize the functional connectivity between the SN and the DMN by using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange and comparing individuals with ASD (n = 325) to a typically developing group (n = 356). We examined static and dynamic levels of functional connectivity using the medial prefrontal cortex (mPFC) seed as a core region of the DMN.

RESULTS

We found that individuals with ASD have higher mPFC connectivity with the insula, a core region of the SN, when compared with the typical development group. Moreover, the mPFC-insula coupling showed less variability in ASD compared with the typical development group. A novel semblance-based network dynamic analysis further confirmed that the strong mPFC-insula coupling in the ASD group reduced spontaneous attentional shift for possible external elements of the environment. Indeed, we found that excessive mPFC-insula coupling was significantly associated with a tendency for reduced social responsiveness.

CONCLUSIONS

These findings suggest that the internally oriented cognition in individuals with ASD may be due to excessive coupling between the DMN and the SN.

Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study

Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.

Altered Brain Connectivity Patterns of Individual Differences in Insightful Problem Solving

Insightful problem solving (IPS) attracts widespread attention in creative thinking domains. However, the neural underpinnings of individual differences in IPS are still unclear. The purpose of this research was to investigate inherent full-brain connectivity patterns at voxel-level in IPS. Sixty-two healthy participants were enrolled in the study. We used a voxelwise full-brain network measurement, degree centrality (DC), to depict the characteristics of cerebral network involved in individual differences in IPS. For each participant, we employed a chunk decomposition paradigm, using Mandarin characters as stimuli, to estimate the individual differences in IPS. Results showed that DC in the inferior frontal gyrus, and the middle frontal gyrus/precentral gyrus positively correlated with IPS, while the anterior cingulate cortex, and the brainstern/cerebellum/thalamus exhibited negative correlations with IPS. Using each cluster above as a seed, we performed seed-based functional connectivity analysis further. Results showed that IPS was mainly involved in the default mode network, containing the key regions of precuneus and medial prefrontal cortex. All in all, this research may shed new lights on understanding the neural underpinnings of individual differences in IPS.

Path Analysis: A Method to Estimate Altered Pathways in Time-varying Graphs of Neuroimaging Data

Graph-theoretical methods have been widely used to study human brain networks in psychiatric disorders. However, the focus has primarily been on global graphic metrics with little attention to the information contained in paths connecting brain regions. Details of disruption of these paths may be highly informative for understanding disease mechanisms. To detect the absence or addition of multistep paths in the patient group, we provide an algorithm estimating edges that contribute to these paths with reference to the control group. We next examine where pairs of nodes were connected through paths in both groups by using a covariance decomposition method. We apply our method to study resting-state fMRI data in schizophrenia versus controls. Results show several disconnectors in schizophrenia within and between functional domains, particularly within the default mode and cognitive control networks. Additionally, we identify new edges generating additional paths. Moreover, although paths exist in both groups, these paths take unique trajectories and have a significant contribution to the decomposition. The proposed path analysis provides a way to characterize individuals by evaluating changes in paths, rather than just focusing on the pairwise relationships. Our results show promise for identifying path-based metrics in neuroimaging data.

Transdiagnostic and sex differences in cognitive profiles of autism spectrum disorder and attention-deficit/hyperactivity disorder

An increasing number of studies have shown that autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share symptoms and aetiologies. However, transdiagnostic comparisons between ASD and ADHD is complicated due to the sex differences within each condition. To clarify the similarities and differences in the cognitive functioning between ASD and ADHD, while considering potential sex differences, this study compared cognitive profiles assessed by the WAIS-III between the four groups created by orthogonally combining diagnosis and sex based on the data from 277 ASD males, 86 ASD females, 99 ADHD males and 64 ADHD females. The analysis revealed three major findings. First, performance IQ and perceptual organization index were higher in ADHD males than in ASD males and ADHD females. Second, Gaussian mixture model fitting revealed two clusters underlying the distribution of subindex scores. The percentage of being classified into the cluster that scored lower in all the subindices was higher in females than in males irrespective of diagnosis. Third, feature importance for classification of ASD and ADHD yielded by random forest classifier, a supervised machine learning algorithm, revealed that autism quotient was most informative feature in classifying ASD and ADHD in males, while the discrepancy between verbal and performance intelligence quotient was in females, indicating that the set of behavioral features contributing to classification differs between males and females. Thus, these findings indicate that sex as well as diagnosis is critical in determining the cognitive profiles of people with ASD and ADHD. LAY SUMMARY: The present study compared profiles of cognitive functions measured by Wechsler Adult Intelligence Scale between males and females with ASD and ADHD. The analyses revealed clear sex differences in cognitive functions in both ASD and ADHD and that the set of cognitive functions useful in classifying ASD and ADHD differed between males and females. Thus, biological sex seems to be a critical factor in determining the cognitive profiles of people with ASD and ADHD.

Frontal corticostriatal functional connectivity reveals task positive and negative network dysregulation in relation to ADHD, sex, and inhibitory control

Frontal corticostriatal circuits (FCSC) are involved in self-regulation of cognition, emotion, and motor function. While these circuits are implicated in attention-deficit/hyperactivity disorder (ADHD), the literature establishing FCSC associations with ADHD is inconsistent. This may be due to study variability in considerations of how fMRI motion regression was handled between groups, or study specific differences in age, sex, or the striatal subregions under investigation. Given the importance of these domains in ADHD it is crucial to consider the complex interactions of age, sex, striatal subregions and FCSC in ADHD presentation and diagnosis. In this large-scale study of 362 8-12 year-old children with ADHD (n = 165) and typically developing (TD; n = 197) children, we investigate associations between FCSC with ADHD diagnosis and symptoms, sex, and go/no-go (GNG) task performance. Results include: (1) increased striatal connectivity with age across striatal subregions with most of the frontal cortex, (2) increased frontal-limbic striatum connectivity among boys with ADHD only, mostly in default mode network (DMN) regions not associated with age, and (3) increased frontal-motor striatum connectivity to regions of the DMN were associated with greater parent-rated inattention problems, particularly among the ADHD group. Although diagnostic group differences were no longer significant when strictly controlling for head motion, with motion possibly reflecting the phenotypic variance of ADHD itself, the spatial distribution of all symptom, age, sex, and other ADHD group effects were nearly identical to the initial results. These results demonstrate differential associations of FCSC between striatal subregions with the DMN and FPN in relation to age, ADHD, sex, and inhibitory control.

Altered static and dynamic voxel-mirrored homotopic connectivity in patients with frontal glioma

Contralateral regions play critical role in functional compensation in glioma patients. Voxel-mirrored homotopic connectivity (VMHC) characterizes the intrinsic functional connectivity (FC) of the brain, considered to have a regional functional basis. We aimed to investigate the alterations of brain regional function and VMHC in patients with frontal glioma, and further investigated the correlation between these alterations and cognition. We enrolled patients with frontal glioma and matched healthy controls (HC). We chose degree centrality (DC), regional homogeneity (ReHo), and VMHC to investigate the alterations of regional function and intrinsic FC in patients. Furthermore, partial correlation analyses were conducted to explore the relationship between imaging functional indicators and cognitions. Compared with HC, patients showed decreased static VMHC within right and left middle frontal gyrus (MFG.R, MFG.L), left superior frontal gyrus (SFG.L), right precuneus (PCUN.R), and left precuneus (PCUN.L), decreased static DC within left cingulate gyrus (CG.L), right superior frontal gyrus (SFG.R), and right postcentral gyrus (POCG.R), decreased static ReHo within CG.L, decreased dynamic ReHo within right inferior parietal lobule (IPL.R), but increased dynamic VMHC (dVMHC) within PCUN.R and PCUN.L. Furthermore, values of decreased VMHC within MFG.R, decreased DC within CG.L, decreased ReHo within CG.L, and increased dVMHC within PCUN.R were significantly positively correlated with cognitive functions. We preliminarily confirmed glioma causes regional dysfunction and disturbs long-distance FC, and long-distance FC showed strong instability in patients with frontal glioma. Meanwhile, the correlation analyses indicated directions for cognitive protection in patients with frontal glioma.

Abnormal Intrinsic Functional Hubs in Corneal Ulcer: Evidence from a Voxel-Wise Degree Centrality Analysis

BACKGROUND

Numerous anterior neuroimaging researches have revealed that corneal ulcers (CU) are related to changes in cerebral anatomic structure and functional area. Nonetheless, functional characteristics of the brain's network organization still show no definite research results. The study was designed to confirm CU-associated spatial centrality distribution functional network of the whole cerebrum and explore the mechanism through which the larvaceous changed the intrinsic functional hubs.

MATERIAL AND METHODS

In this study, 40 patients with CU and 40 normal controls (matched in sex, age, and education level) were enrolled in this study to undergo resting-state functional magnetic resonance imaging (fMRI) scans. The differences between the groups were determined by measuring the voxel-wise degree centrality (DC) throughout the whole cerebrum. For the purpose of assessing the correlation between abnormal DC value and clinical variables, the Linear correlation analysis was used.

RESULTS

Compared with normal controls (NCs), CU patients revealed high DC values in the frontal lobe, precuneus, inferior parietal lobule, posterior cingulate, occipital lobe, and temporal lobe in the brain functional connectivity maps throughout the brain. The intergroup differences also had high similarity on account of different thresholds. In addition, DC values were positively related to the duration of CU in the left middle frontal gyrus.

CONCLUSIONS

The experimental results revealed that patients with CU showed spatially unnatural intrinsic functional hubs whether DC values increased or decreased. This brings us to a new level of comprehending the functional features of CU and may offer useful information to make us obtain a clear understanding of the dysfunction of CU.

Biomarkers Obtained by Transcranial Magnetic Stimulation in Neurodevelopmental Disorders

SUMMARY

Transcranial magnetic stimulation (TMS) is a method for focal brain stimulation that is based on the principle of electromagnetic induction where small intracranial electric currents are generated by a powerful fluctuating magnetic field. Over the past three decades, TMS has shown promise in the diagnosis, monitoring, and treatment of neurological and psychiatric disorders in adults. However, the use of TMS in children has been more limited. We provide a brief introduction to the TMS technique; common TMS protocols including single-pulse TMS, paired-pulse TMS, paired associative stimulation, and repetitive TMS; and relevant TMS-derived neurophysiological measurements including resting and active motor threshold, cortical silent period, paired-pulse TMS measures of intracortical inhibition and facilitation, and plasticity metrics after repetitive TMS. We then discuss the biomarker applications of TMS in a few representative neurodevelopmental disorders including autism spectrum disorder, fragile X syndrome, attention-deficit hyperactivity disorder, Tourette syndrome, and developmental stuttering.

An examination of the relationships between attention/deficit hyperactivity disorder symptoms and functional connectivity over time

Previous cross-sectional work has demonstrated resting-state connectivity abnormalities in children and adolescents with attention/deficit hyperactivity disorder (ADHD) relative to typically developing controls. However, it is unclear to what extent these neural abnormalities confer risk for later symptoms of the disorder, or represent the downstream effects of symptoms on functional connectivity. Here, we studied 167 children and adolescents (mean age at baseline = 10.74 years (SD = 2.54); mean age at follow-up = 13.3 years (SD = 2.48); 56 females) with varying levels of ADHD symptoms, all of whom underwent resting-state functional magnetic resonance imaging and ADHD symptom assessments on two occasions during development. Resting-state functional connectivity was quantified using eigenvector centrality mapping. Using voxelwise cross-lag modeling, we found that less connectivity at baseline within right inferior frontal gyrus was associated with more follow-up symptoms of inattention (significant at an uncorrected cluster-forming threshold of p ≤ 0.001 and a cluster-level familywise error corrected threshold of p < 0.05). Findings suggest that previously reported cross-sectional abnormalities in functional connectivity within inferior frontal gyrus in patients with ADHD may represent a longitudinal risk factor for the disorder, in line with efforts to target this region with novel therapeutic methods.

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Alteration of whole-brain amplitude of low-frequency fluctuation and degree centrality in patients with mild to moderate depression: A resting-state functional magnetic resonance imaging study

BACKGROUND

Mild to moderate depressive disorder has a high risk of progressing to major depressive disorder.

METHODS

Low-frequency amplitude and degree centrality were calculated to compare 49 patients with mild to moderate depression and 21 matched healthy controls. Correlation analysis was conducted to explore the correlation between the amplitude of low-frequency fluctuation (ALFF) and the degree centrality (DC) of altered brain region and the scores of clinical scale. Receiver operating characteristic (ROC) curves were further analyzed to evaluate the predictive value of above altered ALFF and DC areas as image markers for mild to moderate depression.

RESULTS

Compared with healthy controls, patients with mild to moderate depression had lower ALFF values in the left precuneus and posterior cingulate gyrus [voxel p < 0.005, cluster p < 0.05, Gaussian random field correction (GRF) corrected] and lower DC values in the left insula (voxel p < 0.005, cluster p < 0.05, GRF corrected). There was a significant negative correlation between DC in the left insula and scale scores of Zung's Depression Scale (ZungSDS), Beck Self-Rating Depression Scale (BDI), Toronto Alexithymia Scale (TAS26), and Ruminative Thinking Response Scale (RRS_SUM, RRS_REFLECTION, RRS_DEPR). Finally, ROC analysis showed that the ALFF of the left precuneus and posterior cingulate gyrus had a sensitivity of 61.9% and a specificity of 79.6%, and the DC of the left insula had a sensitivity of 81% and a specificity of 85.7% in differentiating mild to moderate depression from healthy controls.

CONCLUSION

Intrinsic abnormality of the brain was mainly located in the precuneus and insular in patients with mild to moderate depression, which provides insight into potential neurological mechanisms.

Abnormal Degree Centrality in Children with Low-Function Autism Spectrum Disorders: A Sleeping-State Functional Magnetic Resonance Imaging Study

PURPOSE

This study used the graph-theory approach, degree centrality (DC) to analyze whole-brain functional networks at the voxel level in children with ASD, and investigated whether DC changes were correlated with any clinical variables in ASD children.

METHODS

The current study included 86 children with ASD and 54 matched healthy subjects Aged 2-5.5 years. Next, chloral hydrate induced sleeping-state functional magnetic resonance imaging (ss-fMRI) datasets were acquired from these ASD and healthy subjects. For a given voxel, the DC was calculated by calculating the number of functional connections with significantly positive correlations at the individual level. Group differences were tested using two-sample t-tests (p < 0.01, AlphaSim corrected). Finally, relationships between abnormal DCs and clinical variables were investigated via Pearson's correlation analysis.

RESULTS

Children with ASD exhibited low DC values in the right middle frontal gyrus (MFG) (p < 0.01, AlphaSim corrected). Furthermore, significantly negative correlations were established between the decreased average DC values within the right MFG in ASD children and the total ABC scores, as well as with two ABC subscales measuring highly relevant impairments in ASD (ie, stereotypes and object-use behaviors and difficulties in language).

CONCLUSION

Taken together, the results of our ss-fMRI study suggest that abnormal DC may represent an important contribution to elucidation of the neuropathophysiological mechanisms of preschoolers with ASD.