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

Brain connectivity and transcriptional changes induced by rTMS in first-episode major depressive disorder

Repetitive transcranial magnetic stimulation (rTMS) is a widely utilized non-invasive brain stimulation technique with demonstrated efficacy in treating major depressive disorder (MDD). However, the mechanisms underlying its therapeutic effects, particularly in modulating neural connectivity and influencing gene expression, remain incompletely understood. In this study, we investigated the voxel-wise degree centrality (DC) induced by 10 Hz rTMS targeting the left dorsolateral prefrontal cortex, as well as their associations with transcriptomic data from the Allen Human Brain Atlas. The results indicated that the active treatment significantly reduced clinical symptoms and increased DC in the left superior medial frontal gyrus, left middle occipital gyrus, and right anterior cingulate cortex. Partial least squares regression analysis revealed that genes associated with DC alternations were enriched biological processes related to neural plasticity and synaptic connectivity. Furthermore, protein-protein interaction (PPI) analysis identified key hub genes, including SCN1A, SNAP25, and PVALB, whose expression levels were positively correlated with DC changes. Notably, SCN1A emerged as a significant predictor on DC changes. These findings suggest that rTMS may exert its therapeutic effects in MDD by modulating specific molecular pathways and neural networks, providing valuable insights into its mechanisms of action.

The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders

Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of functional alterations suffered from low replicability and high variability. This is partly because of differences in the atlas and delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated the impact of the brain parcellation approach on the FC-based brain network analysis. We focused on identifying the replicable FCs using three structural brain atlases, including Automated Anatomical Labeling (AAL), Brainnetome atlas (BNA) and HCP_MMP_1.0, and four functional brain parcellation approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) and two Schaefer parcelletions, among correlation, group difference, and classification tasks in six neuropsychiatric disorders: attention deficit and hyperactivity disorder (ADHD, n = 340), autism spectrum disorder (ASD, n = 513), schizophrenia (SZ, n = 200), schizoaffective disorder (SAD, n = 142), bipolar disorder (BP, n = 172), and major depression disorder (MDD, n = 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC deficits were reproducible in all disorders, independent of the atlasing approach; however, replicable FC extraction in other areas and the classification accuracy were affected by the parcellation schema. Overall, functional atlases with finer granularity performed better in classification tasks. Specifically, the Schaefer atlases generated the most repeatable FC deficit patterns across six illnesses. These results indicate that frontal-related FCs may serve as potential common and robust neuro-abnormalities across 6 psychiatric disorders. Furthermore, in order to improve the replicability of rsfMRI-based FC analyses, this study suggests the use of functional templates at larger granularity.

Differentiating Functional Connectivity Patterns in ADHD and Autism Among the Young People: A Machine Learning Solution

OBJECTIVE

ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning approaches. We had two key objectives: (a) to determine the extent to which ADHD and autism could be effectively distinguished via machine learning from one another on this basis and (b) to identify the brain networks differentially implicated in the two conditions.

METHOD

Data from two publicly available resting-state functional magnetic resonance imaging (fMRI) resources-Autism Brain Imaging Data Exchange (ABIDE) and the ADHD-200 Consortium-were analyzed. A total of 330 participants (65 females and 265 males; mean age = 11.6 years), comprising equal subgroups of 110 participants each for ADHD, autism, and healthy controls (HC), were selected from the data sets ensuring data quality and the exclusion of comorbidities. We identified region-to-region connectivity values, which were subsequently employed as inputs to the linear discriminant analysis algorithm.

RESULTS

Machine learning models provided strong differentiation between connectivity patterns in participants with ADHD and autism-with the highest accuracy of 85%. Predominantly frontoparietal network alterations in connectivity discriminate ADHD individuals from autism and neurotypical group. Networks contributing to discrimination of autistic individuals from neurotypical group were more heterogeneous. These included language, salience, and frontoparietal networks.

CONCLUSION

These results contribute to our understanding of the distinct neural signatures underlying ADHD and autism in terms of intrinsic patterns of brain connectivity. The high level of discriminability between ADHD and autism, highlights the potential role of brain based metrics in supporting differential diagnostics.

Real-world goal-directed behavior reveals aberrant functional brain connectivity in children with ADHD

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

Altered coupling relationships across resting-state functional connectivity measures in schizophrenia, bipolar disorder, and attention deficit/hyperactivity disorder

Resting-state functional connectivity (rsFC) measures have enjoyed significant success in discovering the neuropathological characteristics of schizophrenia (SZ), bipolar disorder (BD), and attention deficit/hyperactivity disorder (ADHD). However, it is unknown whether and how the spatial and temporal coupling relationships across rsFC measures would be altered in these psychiatric disorders. Here, resting-state fMRI data were obtained from a transdiagnostic sample of healthy controls (HC) and individuals with SZ, BD, and ADHD. We used Kendall's W to compute volume-wise and voxel-wise concordance across rsFC measures, followed by group comparisons. In terms of the spatial coupling, both SZ and BD individuals exhibited decreased volume-wise concordance compared with HC. Regarding the temporal coupling, SZ individuals showed decreased voxel-wise concordance in the right lateral occipital cortex relative to HC. BD individuals exhibited decreased voxel-wise concordance in the bilateral basal forebrain and bilateral superior/middle temporal gyrus compared to HC. Additionally, correlation analyses demonstrated positive associations of voxel-wise concordance in the left basal forebrain with negative symptoms including alogia and affective flattening in pooled SZ and BD individuals. Our findings of distinct patterns of spatial and temporal decoupling across rsFC measures among SZ, BD, and ADHD may provide unique insights into the neuropathological mechanisms of these psychiatric disorders.

Language networks in Autism Spectrum Disorder: A systematic review of connectivity-based fMRI studies

Autism Spectrum Disorder (ASD) is a heterogeneous condition associated with differences in functional neural connectivity relative to neurotypical (NT) peers. Language-based functional connectivity represents an ideal context in which to characterize connectivity because language is heterogeneous and linked to core features in ASD, and NT language networks are well-defined. We conducted a systematic review of language-related functional connectivity literature on individuals with ASD using PubMed, PsychInfo, Scopus, ProQuest, and Google Scholar, yielding 96 studies. Language-task studies indicated local over-connectivity within the language network and global under-connectivity of language with out-of-network regions in ASD. Resting-state studies showed mixed patterns, and connectivity was associated ASD symptomology and language skills. This evidence indicates language-task elicited local over-connectivity and global under-connectivity in ASD, but not a local versus global distinction of resting-state language-related connectivity. Associations with behavior suggest that local over-connectivity and global under-connectivity characterize ASD, and heightened language-related connectivity may support social function.

Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology

BACKGROUND

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together and sex differences are often overlooked. Population modeling, often referred to as normative modeling, provides a unified framework for studying age-specific and sex-specific divergences in brain development.

METHODS

Here, we used population modeling and a large, multisite neuroimaging dataset (N = 4255 after quality control) to characterize cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of more than 75,000 individuals. We also examined sex and age differences and relationship with autistic traits and explored the co-occurrence of autism and ADHD.

RESULTS

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume that was localized to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness but lower cortical volume and surface area across much of the cortex. The co-occurring autism+ADHD group showed a unique pattern of widespread increases in cortical thickness and certain decreases in surface area. We also found that sex modulated the neuroanatomy of autism but not ADHD, and there was an age-by-diagnosis interaction for ADHD only.

CONCLUSIONS

These results indicate distinct cortical differences in autism and ADHD that are differentially affected by age and sex as well as potentially unique patterns related to their co-occurrence.

Changes in degree centrality and its associated genes: A longitudinal study of patients with schizophrenia undergoing pharmacological treatment

BACKGROUND

The role of degree centrality (DC) in schizophrenia (SCZ), its trajectory following pharmacological treatment, and its potential as a prognostic biomarker and genetic mechanism remain unclear.

METHODS

We recruited 51 healthy controls (HC) and 56 patients with SCZ. Additionally, the SCZ patients underwent three months of antipsychotic medication treatment. We collected resting-state functional magnetic resonance imaging data, clinical variables, and conducted analyses using support vector machines, support vector regression, and gene expression correlation analysis.

RESULTS

Our study revealed that SCZ patients had generally reduced DC values in the cerebral cortex compared to HC at baseline, with increased DC values observed in the left occipital gyrus. After three months of treatment, SCZ patients exhibited a significant decrease in DC values in the left fusiform gyrus and an increase in the left inferior parietal gyrus. Variations in DC values in SCZ patients were associated with multiple genes, primarily enriched in molecular functions.

CONCLUSION

Changes in DC values in the right inferior occipital/fusiform gyrus and right calcarine/middle occipital gyrus may serve as neuroimaging markers to differentiate between HC and SCZ patients. Additionally, DC values in the left middle/postcentral gyrus could be used to predict treatment outcomes. Transcriptome-neuroimaging spatial correlation analysis provides valuable insights into the neurobiological mechanisms underlying SCZ pathology.

Effective connectivity alterations of the triple network model in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are both highly prevalent disorders and frequently co-occur. The underlying neurological mechanisms of the co-occurrence of ASD and ADHD (ASD + ADHD) remain unknown. This study focuses on investigating the effective connectivity (EC) alterations within the triple network model in individuals with ASD + ADHD. Resting-state functional magnetic resonance imaging data were obtained from 44 individuals with ASD + ADHD, 60 individuals with ASD without ADHD (ASD-only), 35 individuals with ADHD without ASD (ADHD-only), and 81 healthy controls (HC) from the Autism Brain Imaging Data Exchange II and the ADHD-200 Sample database. Spectral dynamic causal modeling was employed to explore the EC alterations within and between the default mode network, salience network, and central executive network. Our analysis showed that compared to HC, ASD + ADHD, ASD-only, and ADHD-only exhibited both shared and disorder-specific EC alterations within the triple-network model. These results have potential clinical implications for identifying ASD + ADHD, facilitating diagnostic accuracy, guiding targeted treatment approaches, and informing etiological studies.

Developmental functional brain network abnormalities in autism spectrum disorder comorbid with attention deficit hyperactivity disorder

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) often co-occur. Developmental stages significantly influence the variations in brain alterations. However, whether ASD comorbid with ADHD (ASD + ADHD) represents a unique neural characteristic from ASD without comorbid ADHD (ASD-alone), or instead manifests a shared neural correlate associated with ASD across diverse age cohorts remain unclear. This study examined topological properties and functional connectivity (FC) patterns through resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange II. Participants were divided into two age cohorts: childhood (under 12 years) and adolescence (12-18 years), consisting of 171 ASD pediatric patients and 111 typically developing (TD) controls. These cohorts were further classified into subgroups of ASD + ADHD, ASD-alone, and TD controls to compare across the age categories. The age, intelligence quotient, and gender of participants across three groups were matched within childhood and adolescence stages. We constructed functional brain networks, conducted graph-theory analysis, and analysed FC for both age cohorts. The findings revealed that both ASD + ADHD and ASD-alone shared some FC dysfunctions in the Default Mode Network (DMN) and atypical global metrics. Additionally, each group demonstrated unique neural FC and topological profiles that evolved with development.

CONCLUSIONS

This study highlights the neural profiles of ASD + ADHD from a developmental perspective and suggests age-considerate approaches in clinical treatments.

WHAT IS KNOWN

• ASD + ADHD shared some neural correlate associated with ASD-alone and also had specific neurobiological mechanisms which were different from ASD-alone. • Developmental stages significantly influence the variations in brain alterations observed in ASD or ADHD.

WHAT IS NEW

• Both ASD + ADHD and ASD-alone shared some FC dysfunctions in the Default Mode Network and atypical global metrics. • ASD + ADHD and ASD-alone demonstrated unique neural FC and topological profiles that evolved with development.

What is the best brain state to predict autistic traits?

Autism is a heterogeneous condition, and functional magnetic resonance imaging-based studies have advanced understanding of neurobiological correlates of autistic features. Nevertheless, little work has focused on the optimal brain states to reveal brain-phenotype relationships. In addition, there is a need to better understand the relevance of attentional abilities in mediating autistic features. Using connectome-based predictive modelling, we interrogate three datasets to determine scanning conditions that can boost prediction of clinically relevant phenotypes and assess generalizability. In dataset one, a sample of youth with autism and neurotypical participants, we find that a sustained attention task (the gradual onset continuous performance task) results in high prediction performance of autistic traits compared to a free-viewing social attention task and a resting-state condition. In dataset two, we observe the predictive network model of autistic traits generated from the sustained attention task generalizes to predict measures of attention in neurotypical adults. In dataset three, we show the same predictive network model of autistic traits from dataset one further generalizes to predict measures of social responsiveness in data from the Autism Brain Imaging Data Exchange. In sum, our data suggest that an in-scanner sustained attention challenge can help delineate robust markers of autistic traits and support the continued investigation of the optimal brain states under which to predict phenotypes in psychiatric conditions.

Sensory and motor cortices parcellations estimated via distance-weighted sparse representation with application to autism spectrum disorder

BACKGROUND

Motor impairments and sensory processing abnormalities are prevalent in autism spectrum disorder (ASD), closely related to the core functions of the primary motor cortex (M1) and the primary somatosensory cortex (S1). Currently, there is limited knowledge about potential therapeutic targets in the subregions of M1 and S1 in ASD patients. This study aims to map clinically significant functional subregions of M1 and S1.

METHODS

Resting-state functional magnetic resonance imaging data (NTD = 266) from Autism Brain Imaging Data Exchange (ABIDE) were used for subregion modeling. We proposed a distance-weighted sparse representation algorithm to construct brain functional networks. Functional subregions of M1 and S1 were identified through consensus clustering at the group level. Differences in the characteristics of functional subregions were analyzed, along with their correlation with clinical scores.

RESULTS

We observed symmetrical and continuous subregion organization from dorsal to ventral aspects in M1 and S1, with M1 subregions conforming to the functional pattern of the motor homunculus. Significant intergroup differences and clinical correlations were found in the dorsal and ventral aspects of M1 (p < 0.05/3, Bonferroni correction) and the ventromedial BA3 of S1 (p < 0.05/5). These functional characteristics were positively correlated with autism severity. All subregions showed significant results in the ROI-to-ROI intergroup differential analysis (p < 0.05/80).

LIMITATIONS

The generalizability of the segmentation model requires further evaluation.

CONCLUSIONS

This study highlights the significance of M1 and S1 in ASD treatment and may provide new insights into brain parcellation and the identification of therapeutic targets for ASD.

Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder

Clinical, neuroimaging and genomics evidence have increasingly underscored a degree of overlap between autism and attention-deficit/hyperactivity disorder (ADHD). This study explores the specific contribution of their core symptoms to shared biology in a sample of N=166 verbal children (6-12 years) with rigorously-established primary diagnoses of either autism or ADHD (without autism). We investigated the associations between inter-individual differences in clinician-based dimensional measures of autism and ADHD symptoms and whole-brain low motion intrinsic functional connectivity (iFC). Additionally, we explored their linked gene expression patterns in silico. Whole-brain multivariate distance matrix regression revealed a transdiagnostic association between autism severity and iFC of two nodes: the middle frontal gyrus of the frontoparietal network and posterior cingulate cortex of the default mode network. Across children, the greater the iFC between these nodes, the more severe the autism symptoms, even after controlling for ADHD symptoms. Results from segregation analyses were consistent with primary findings, underscoring the significance of internetwork iFC interactions for autism symptom severity across diagnoses. No statistically significant brain-behavior relationships were observed for ADHD symptoms. Genetic enrichment analyses of the iFC maps associated with autism symptoms implicated genes known to: (i) have greater rate of variance in autism and ADHD, and (ii) be involved in neuron projection, suggesting shared genetic mechanisms for this specific brain-clinical phenotype. Overall, these findings underscore the relevance of transdiagnostic dimensional approaches in linking clinically-defined phenomena to shared presentations at the macroscale circuit- and genomic-levels among children with diagnoses of autism and ADHD.

Landscape of intrinsically disordered proteins in mental disorder diseases

Disrupted genes linked to mental disorders sometimes exhibit characteristics of Intrinsically Disordered Proteins (IDPs). However, few studies have comprehensively explored the functional associations between protein disorder properties and different psychiatric disorders. In this study, we collected disrupted proteins for seven mental diseases (MDD, SCZ, BP, ID, AD, ADHD, ASD) and a control dataset from normal brains. After calculating the disorder scores for each protein, we thoroughly compared the proportions and functions of IDPs between differentially expressed proteins in each disease and healthy controls. Our findings revealed that disrupted proteins, particularly in ASD and ADHD, contain more IDPs than controls from normal brains. Distinct patterns in disorder properties were observed among different mental disorders. Functional enrichment analysis indicated that IDPs in mental disorders were associated with neurodevelopment, synaptic signaling, and gene expression regulatory pathways. In addition, we analyzed the proportion and function of liquid-phase-separated proteins (LLPS) in psychiatric disorders, finding that LLPS proteins are mainly enriched in pathways related to neurodevelopment and inter-synaptic signaling. Furthermore, to validate our findings, we conducted an analysis of differentially expressed genes in an ASD cohort, revealing that the encoded proteins also exhibit a higher proportion of IDPs. Notably, these IDPs were particularly enriched in pathways related to neurodevelopment, including head development, a process known to be disrupted in ASD. Our study sheds light on the crucial role of IDPs in psychiatric disorders, enhancing our understanding of their molecular mechanisms.

The surface-based degree centrality of patients with lifelong premature ejaculation: A resting-state fMRI study

The aim of this study was to investigate alterations in the resting-state brain functional network characteristics of lifelong premature ejaculation (PE) patients using surface-based degree centrality (DC), and to analyze the correlation between these alterations and clinical symptoms in PE patients. The study included individuals with lifelong PE (patient group, n = 36) and a control group matched by age and education level (control group, n = 22). Resting-state functional magnetic resonance imaging (fMRI) scans were performed on all participants. Surface-based degree centrality analysis was conducted and the differences between the two groups were compared using t-tests. Further, the DC values of brain regions showing significant differences were correlated with clinical symptoms. Compared to the control group, the patient group exhibited significantly reduced degree centrality (DC) values in the left precuneus and significantly increased DC values in the right supplementary motor area (SMA). Furthermore, intravaginal ejaculatory latency time (IELT) and Chinese Index of Premature Ejaculation (CIPE) values were positively correlated with left precuneus DC values and negatively correlated with right SMA DC values. Patients with primary lifelong ejaculation demonstrate abnormalities in key brain network nodes and their connections with relevant brain regions, which are strongly associate with clinical symptoms. These findings enhance our understanding of the neuronal pathological changes in PE patients.

Change in striatal functional connectivity networks across 2 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.

Autism is associated with in vivo changes in gray matter neurite architecture

Postmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) make in vivo characterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Developmentsm (ABCD®) study 142 individuals with an autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in autism in the right cerebellar cortex (β = -0.005, SE =0.0015, p = 0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant in post-hoc analysis when the autism sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in autism and the significance of their incorporation as physiological covariates in future studies.

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.

Multiclass classification of Autism Spectrum Disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis

Neurodevelopmental conditions, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), present unique challenges due to overlapping symptoms, making an accurate diagnosis and targeted intervention difficult. Our study employs advanced machine learning techniques to analyze functional magnetic resonance imaging (fMRI) data from individuals with ASD, ADHD, and typically developed (TD) controls, totaling 120 subjects in the study. Leveraging multiclass classification (ML) algorithms, we achieve superior accuracy in distinguishing between ASD, ADHD, and TD groups, surpassing existing benchmarks with an area under the ROC curve near 98%. Our analysis reveals distinct neural signatures associated with ASD and ADHD: individuals with ADHD exhibit altered connectivity patterns of regions involved in attention and impulse control, whereas those with ASD show disruptions in brain regions critical for social and cognitive functions. The observed connectivity patterns, on which the ML classification rests, agree with established diagnostic approaches based on clinical symptoms. Furthermore, complex network analyses highlight differences in brain network integration and segregation among the three groups. Our findings pave the way for refined, ML-enhanced diagnostics in accordance with established practices, offering a promising avenue for developing trustworthy clinical decision-support systems.

Heterogeneity and convergence across seven neuroimaging modalities: a review of the autism spectrum disorder literature

Background

A growing body of literature classifies autism spectrum disorder (ASD) as a heterogeneous, complex neurodevelopmental disorder that often is identified prior to three years of age. We aim to provide a narrative review of key structural and functional properties that differentiate the neuroimaging profile of autistic youth from their typically developing (TD) peers across different neuroimaging modalities.

Methods

Relevant studies were identified by searching for key terms in PubMed, with the most recent search conducted on September 1, 2023. Original research papers were included if they applied at least one of seven neuroimaging modalities (structural MRI, functional MRI, DTI, MRS, fNIRS, MEG, EEG) to compare autistic children or those with a family history of ASD to TD youth or those without ASD family history; included only participants <18 years; and were published from 2013 to 2023.

Results

In total, 172 papers were considered for qualitative synthesis. When comparing ASD to TD groups, structural MRI-based papers (n = 26) indicated larger subcortical gray matter volume in ASD groups. DTI-based papers (n = 14) reported higher mean and radial diffusivity in ASD participants. Functional MRI-based papers (n = 41) reported a substantial number of between-network functional connectivity findings in both directions. MRS-based papers (n = 19) demonstrated higher metabolite markers of excitatory neurotransmission and lower inhibitory markers in ASD groups. fNIRS-based papers (n = 20) reported lower oxygenated hemoglobin signals in ASD. Converging findings in MEG- (n = 20) and EEG-based (n = 32) papers indicated lower event-related potential and field amplitudes in ASD groups. Findings in the anterior cingulate cortex, insula, prefrontal cortex, amygdala, thalamus, cerebellum, corpus callosum, and default mode network appeared numerous times across modalities and provided opportunities for multimodal qualitative analysis.

Conclusions

Comparing across neuroimaging modalities, we found significant differences between the ASD and TD neuroimaging profile in addition to substantial heterogeneity. Inconsistent results are frequently seen within imaging modalities, comparable study populations and research designs. Still, converging patterns across imaging modalities support various existing theories on ASD.

Motor versus Psychomotor? Deciphering the Neural Source of Psychomotor Retardation in Depression

Major depressive disorder (MDD) is characterized by psychomotor retardation whose underlying neural source remains unclear. Psychomotor retardation may either be related to a motor source like the motor cortex or, alternatively, to a psychomotor source with neural changes outside motor regions, like input regions such as visual cortex. These two alternative hypotheses in main (n = 41) and replication (n = 18) MDD samples using 7 Tesla MRI are investigated. Analyzing both global and local connectivity in primary motor cortex (BA4), motor network and middle temporal visual cortex complex (MT+), the main findings in MDD are: 1) Reduced local and global synchronization and increased local-to-global output in motor regions, which do not correlate with psychomotor retardation, though. 2) Reduced local-to-local BA4 - MT+ functional connectivity (FC) which correlates with psychomotor retardation. 3) Reduced global synchronization and increased local-to-global output in MT+ which relate to psychomotor retardation. 4) Reduced variability in the psychophysical measures of MT+ based motion perception which relates to psychomotor retardation. Together, it is shown that visual cortex MT+ and its relation to motor cortex play a key role in mediating psychomotor retardation. This supports psychomotor over motor hypothesis about the neural source of psychomotor retardation in MDD.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

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.

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.

Abnormal functional hubs in migraine patients: a resting-state MRI analysis about voxel-wise degree centrality

The purpose was to explore the spatial centrality of the whole brain functional network related to migraine and to investigate the potential functional hubs associated with migraine. 32 migraine patients and 55 healthy controls were recruited and they received resting-state functional magnetic resonance imaging voluntarily. Voxel-wise Degree Centrality (DC) was measured across the whole brain, and group differences in DC were compared. False Discovery Rate and permutation test (5000 times) were used for multiple comparisons. Finally, significant differences in functional connectivity (FC) between seeds and other brain regions were further researched by the seed-based approach. The correlation analyses between the changes in the brain function and clinical features were also performed. The results showed that, compared to healthy controls, migraine patients exhibited significantly increased DC in the left anterior cingulate cortex (ACC), slightly increased DC in the right ACC and the right medial superior frontal gyrus (SFG). No significant correlation was found between DC and clinical variables. The seed-based analyses showed that migraine patients showed increased FC between the right SFG and left ACC, decreased FC between the left ACC and left superior temporal gyrus (STG). FC value of the right SFG was positively correlated with the score of migraine-specific quality-of-life questionnaire about role in function-preventive in migraine patients. According to relatively changed DC, we found that migraine patients exhibited specific abnormal intrinsic functional hubs. These findings expand our understanding of functional characteristics of migraine, and may provide new insights into understanding the dysfunction and pathophysiology of migraine patients.

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.