Autism and abnormal development of brain connectivity

Individuals with high autistic traits exhibit altered interhemispheric brain functional connectivity patterns

Individuals with high autistic traits (AT) encounter challenges in social interaction, similar to autistic persons. Precise screening and focused interventions positively contribute to improving this situation. Functional connectivity analyses can measure information transmission and integration between brain regions, providing neurophysiological insights into these challenges. This study aimed to investigate the patterns of brain networks in high AT individuals to offer theoretical support for screening and intervention decisions. EEG data were collected during a 4-min resting state session with eyes open and closed from 48 participants. Using the Autism Spectrum Quotient (AQ) scale, participants were categorized into the high AT group (HAT, n = 15) and low AT groups (LAT, n = 15). We computed the interhemispheric and intrahemispheric alpha coherence in two groups. The correlation between physiological indices and AQ scores was also examined. Results revealed that HAT exhibited significantly lower alpha coherence in the homologous hemispheres of the occipital cortex compared to LAT during the eyes-closed resting state. Additionally, significant negative correlations were observed between the degree of AT (AQ scores) and the alpha coherence in the occipital cortex, as well as in the right frontal and left occipital regions. The findings indicated that high AT individuals exhibit decreased connectivity in the occipital region, potentially resulting in diminished ability to process social information from visual inputs. Our discovery contributes to a deeper comprehension of the neural underpinnings of social challenges in high AT individuals, providing neurophysiological signatures for screening and intervention strategies for this population.

WDR62 controls cortical radial migration and callosal projection of neurons in the developing cerebral cortex

WD repeat domain 62 (WDR62) was identified as the second most causative gene of autosomal recessive primary microcephaly (MCPH) frequently associated structural abnormalities such as lissencephaly, polymicrogyria as well as hypoplasia of the corpus callosum, however, underlining mechanism behind these abnormality remains unknown. Here we show that either ablation of WDR62 in neural progenitor cells (NPCs) or post-mitotic neurons both impedes cortical neuronal radial migration in the developing brain. WDR62 modulates the transition from multipolar to bipolar states in migrating neurons and ensures the accurate formation of contralateral projections of callosal neurons. Our results further indicated that ASD-related mutations in WDR62 are associated with a reduced capacity for neuronal migration in the developing brain. Finally, we provide the molecular evidence that the levels of Reelin, a key modulator of neuronal migration and high confidence ASD candidate gene, were significantly reduced in the brains of Wdr62 deficient mice. These finding define critical roles for WDR62 in cortical neuronal radial migration and callosal projection which provides insights into the pathogenesis of WDR62 deficiency-related brain dysplasia.

Electrophysiological Abnormalities Associated With Sustained Attention in Children With Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder

This study investigates electrophysio- logical abnormalities in children with Attention-Deficit/ Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) during sustained attention tasks, focusing on vigilance and inhibitory control, and explores associations between neural markers and attentional performance.Children with ADHD (n = 30), ASD (n = 23), and typically developing (TD) children (n = 31) completed a Test of Variables of Attention (TOVA) task while electroencephalography (EEG) was recorded. Event-related potentials (ERPs: P1, N2, P3) and event-related desynchronization/synchronization (ERD/ERS: theta ERS, alpha ERD, beta ERS) were measured and compared across groups. Correlations between electrophysiological features and behavioral performance were analyzedBoth ADHD and ASD groups demonstrated attenuated P1 amplitudes during vigilance task and reduced prefrontal theta ERS during inhibitory control. The ASD group exhibited additional impairments, including attenuated N2 amplitudes in inhibitory control, reduced P3 amplitudes, and weaker alpha ERD across conditions. The ADHD group showed additional deficits in theta ERS. Notably, N2 amplitude and theta ERS during vigilance state significantly correlated with response time measures. Children with ADHD and ASD share deficits in primary visual stimulus processing and inhibitory attention allocation. ASD-specific impairments involve top-down processing and inhibition, while ADHD-specific challenges involve attentional allocation and modulation. These findings enhance the electrophysiological understanding of sustained attention in ADHD and ASD, offering insights that may inform future diagnostic and intervention strategies.

Large-scale EM data reveals myelinated axonal changes and altered connectivity in the corpus callosum of an autism mouse model

Introduction

Autism spectrum disorder (ASD) encompasses a diverse range of neurodevelopmental disorders with complex etiologies, including genetic, environmental, and neuroanatomical factors. While the exact mechanisms underlying ASD remain unclear, structural abnormalities in the brain offer valuable insights into its pathophysiology. The corpus callosum, the largest white matter tract in the brain, plays a crucial role in interhemispheric communication, and its structural abnormalities may contribute to ASD-related phenotypes.

Methods

To investigate the ultrastructural alterations in the corpus callosum associated with ASD, we utilized serial scanning electron microscopy (sSEM) in mice. A dataset of the entire sagittal sections of the corpus callosum from wild-type and Shank3B mutant mice was acquired at 4 nm resolution, enabling precise comparisons of myelinated axon properties. Leveraging a fine-tuned EM-SAM model for automated segmentation, we quantitatively analyzed key metrics, including G-ratio, myelin thickness, and axonal density.

Results

In the corpus callosum of Shank3B autism model mouse, we observed a significant increase in myelinated axon density, accompanied by thinner myelin sheaths compared to wild-type. Additionally, we identified abnormalities in the diameter distribution of myelinated axons and deviations in G-ratio. Notably, these ultrastructural alterations were widespread across the corpus callosum, suggesting a global disruption of myelinated axon integrity.

Discussion

This study provides novel insights into the microstructural abnormalities of the corpus callosum in ASD mouse, supporting the hypothesis that myelination deficits contribute to ASD-related communication impairments between brain hemispheres. However, given the structural focus of this study, further research integrating functional assessments is necessary to establish a direct link between these morphological changes and ASD-related neural dysfunction.

A functional parcellation of the whole brain in high-functioning individuals with autism spectrum disorder reveals atypical patterns of network organization

Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy high-functioning individuals with ASD and a group of seventy typically developing (TD) individuals. The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates internal consistency and repeatability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: (1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, (2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and (3) subcortical structures and the hippocampus are atypically integrated with the neocortex. These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

Atypical Developmental Patterns of Sensorimotor-Related Networks in Autism Spectrum Disorder: A BrainAGE Study Based on Resting-State fMRI

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder characterized by atypical brain development. Previous whole-brain BrainAGE studies have unveiled the presence of accelerated or delayed brain function developmental patterns in individuals with ASD. However, it remains unclear whether these patterns manifest at a global level throughout the entire brain or are specific to certain functional sub-networks. The study included resting-state functional magnetic resonance imaging (fMRI) data from 127 individuals with ASD and 135 healthy controls (aged between 5 and 40 years). ALFF maps were measured for each participant. Then, sub-network-level BrainAGE analyses were conducted across 10 sub-networks using the Individual-weighted Multilayer Perceptron Network (ILWMLP) regression method. The BrainAGE analyses revealed atypical developmental trajectories in sensorimotor-related sub-networks, encompassing auditory, motor, and sensorimotor sub-networks. In individuals with ASD, delayed brain function development was observed in the auditory and sensorimotor networks, with a more pronounced delay observed in older individuals. Conversely, the motor network exhibited accelerated development in younger individuals but delayed development in older individuals. Our findings unveiled aberrant developmental patterns in sensorimotor-related sub-networks among individuals with ASD, exhibiting distinct atypical profiles across different sub-networks. These results might contribute to a deeper understanding of the deviant brain development observed in ASD.

Transcallosal white matter and cortical gray matter variations in autistic adults aged 30-73 years

BACKGROUND

Autism spectrum disorder (ASD) is a lifelong condition that profoundly impacts health, independence, and quality of life. However, research on brain aging in autistic adults is limited, and microstructural variations in white and gray matter remain poorly understood. To address this critical gap, we assessed novel diffusion MRI (dMRI) biomarkers, free water, and free water corrected fractional anisotropy (fwcFA), and mean diffusivity (fwcMD) across 32 transcallosal tracts and their corresponding homotopic grey matter origin/endpoint regions of interest (ROIs) in middle and old aged autistic adults.

METHODS

Forty-three autistic adults aged 30-73 and 43 age-, sex-, and IQ-matched neurotypical controls underwent dMRI scans. We examined free water, fwcFA, fwcMD differences between the two groups and age-related pattern of each dMRI metric across the whole brain for each group. The relationships between clinical measures of ASD and free water in regions that significantly differentiated autistic adults from neurotypical controls were also explored. In supplementary analyses, we also assessed free water uncorrected FA and MD using conventional single tensor modeling.

RESULTS

Autistic adults exhibited significantly elevated free water in seven frontal transcallosal tracts compared to controls. In controls, age-related increases in free water and decreases in fwcFA were observed across most transcallosal tracts. However, these age-associated patterns were entirely absent in autistic adults. In gray matter, autistic adults showed elevated free water in the calcarine cortices and lower fwcMD in the dorsal premotor cortices compared to controls. Lastly, age-related increases in free water were found across all white matter and gray matter ROIs in neurotypical controls, whereas no age-related associations were detected in any dMRI metrics for autistic adults.

LIMITATIONS

We only recruited cognitively capable autistic adults, which limits the generalizability of our findings across the full autism spectrum. The cross-sectional design precludes inferences about microstructural changes over time in middle and old aged autistic adults.

CONCLUSIONS

Our findings revealed increased free water load in frontal white matter in autistic adults and identified distinct age-associated microstructural variations between the two groups. These findings highlight more heterogeneous brain aging profiles in autistic adults. Our study also demonstrated the importance of quantifying free water in dMRI studies of ASD.

Canalization of circuit assembly by δ-protocadherins in the zebrafish optic tectum

Neurons are precisely and reproducibly assembled into complex networks during development. How genes collaborate to guide this assembly remains an enduring mystery. In humans, large numbers of genes have been implicated in neurodevelopmental disorders that are characterized by variable and overlapping phenotypes. The complexity of the brain, the large number of genes involved and the heterogeneity of the disorders makes understanding the relationships between genes, development and neural function challenging. Waddington suggested the concept of canalization to describe the role of genes in shaping developmental trajectories that lead to precise outcomes1. Here, we show that members of the δ-protocadherin family of homophilic adhesion molecules, Protocadherin-19 and Protocadherin-17, contribute to developmental canalization of visual circuit assembly in the zebrafish. We provided oriented visual stimuli to zebrafish larvae and performed in vivo 2-photon calcium imaging in the optic tectum. The latent dynamics resulting from the population activity were confined to a conserved manifold. Among different wild type larvae, these dynamics were remarkably similar, allowing quantitative comparisons within and among genotypes. In both Protocadherin-19 and Protocadherin-17 mutants, the latent dynamics diverged from wild type. Importantly, these deviations could be averaged away, suggesting that the loss of these adhesion molecules leads to stochastic phenotypic variability and introduced disruptions of circuit organization that varied among individual mutants. These results provide a specific, quantitative example of canalization in the development of a vertebrate neural circuit, and suggest a framework for understanding the observed variability in complex brain disorders.

Cortical Response to Acute Implantation of the Utah Optrode Array in Macaque Cortex

Optogenetics has transformed the study of neural circuit function, but limitations in its application to species with large brains, such as non-human primates (NHPs), remain. A major challenge in NHP optogenetics is delivering light to sufficiently large volumes of deep neural tissue with high spatiotemporal precision, without simultaneously affecting superficial tissue. To overcome these limitations, we recently developed and tested in vivo in NHP cortex, the Utah Optrode Array (UOA). This is a 10×10 array of penetrating glass shanks, tiling a 4×4mm 2 area, bonded to interleaved needle-aligned and interstitial µLED arrays, which allows for independent photostimulation of deep and superficial brain tissue. Here, we investigate the acute biological response to UOA implantation in NHP cortex, with the goal of optimizing device design for reduced insertion trauma and subsequent chronic response. To this goal, we systematically vary UOA shank diameter, surface texture, tip geometry, and insertion pressure, and assess their effects on astrocytes, microglia, and neuronal viability, following acute implantation. We find that UOAs with shanks of smaller diameter, smooth surface texture and round tips cause the least damage. Higher insertion pressures have limited effects on the inflammatory response, but lead to greater tissue compression. Our results highlight the importance of balancing shank diameter, tip geometry, and insertion pressure in UOA design for preserving tissue integrity and improving long-term UOA performance and biocompatibility.

EEG Abnormalities and Phenotypic Correlates in Preschoolers with Autism Spectrum Disorder: A Single-Center Study

Background: The literature suggests the existence of an association between autism spectrum disorders (ASDs) and subclinical electroencephalographic abnormalities (SEAs), which show a heterogeneous prevalence rate (12.5-60.7%) within the pediatric ASD population. The aim of this study was to investigate the EEG findings in a cohort of ASD preschoolers and their correlation with the phenotypic characteristics. Methods: We retrospectively reviewed data on 141 ASD preschoolers evaluated in a tertiary care university hospital over the period 2008-2018. All participants underwent at least one standard polygraphic electroencephalogram (EEG) and a clinical multidisciplinary assessment with standardized instruments. Results: 77 patients (55%) showed SEAs, which were mainly represented by epileptiform discharges (p < 0.00001), especially focal and multifocal (p = 0.010). Abnormal EEG (p = 0.035) and epileptiform discharges (p = 0.014) were associated with seizure onset and were predominant in sleep (p < 0.00001). Patients with abnormal tracing (p = 0.031) and slow abnormalities (p < 0.001) were significantly younger. ASD severity was not found to be correlated with EEG results, which showed a potential, albeit non-significant, association with some psychometric parameters. Very similar results were found when patients were divided according to sex. Conclusions: EEG abnormalities appear to correlate more with ASD internalizing, externalizing and emotional comorbidities, rather than with ASD core symptoms; larger samples are needed to further investigate this association.

The pediatric psychopharmacology of autism spectrum disorder: A systematic review - Part II: The future

Part I of this systematic review summarized the state-of-the-art of pediatric psychopharmacology for Autism Spectrum Disorder (ASD), a severe and lifelong neurodevelopmental disorder. The purpose of this Part II follow-up article is to provide a systematic overview of the experimental psychopharmacology of ASD. To this aim, we have first identified in the Clinicaltrials.gov website all the 157 pharmacological and nutraceutical compounds which have been experimentally tested in children and adolescents with ASD using the randomized placebo-controlled trial (RCT) design. After excluding 24 drugs already presented in Part I, a systematic review spanning each of the remaining 133 compounds was registered on Prospero (ID: CRD42023476555), performed on PubMed (August 8, 2024), and completed with EBSCO, PsycINFO (psychology and psychiatry literature) and the Cochrane Database of Systematic reviews, yielding a total of 115 published RCTs, including 57 trials for 23 pharmacological compounds and 48 trials for 17 nutraceuticals/supplements. Melatonin and oxytocin were not included, because recent systematic reviews have been already published for both these compounds. RCTs of drugs with the strongest foundation in preclinical research, namely arbaclofen, balovaptan and bumetanide have all failed to reach their primary end-points, although efforts to target specific patient subgroups do warrant further investigation. For the vast majority of compounds, including cannabidiol, vasopressin, and probiotics, insufficient evidence of efficacy and safety is available. However, a small subset of compounds, including N-acetylcysteine, folinic acid, l-carnitine, coenzyme Q10, sulforaphane, and metformin may already be considered, with due caution, for clinical use, because there is promising evidence of efficacy and a high safety profile. For several other compounds, such as secretin, efficacy can be confidently excluded, and/or the data discourage undertaking new RCTs. Part I and Part II summarize "drug-based" information, which will be ultimately merged to provide clinicians with a "symptom-based" consensus statement in a conclusive Part III, with the overarching aim to foster evidence-based clinical practices and to organize new strategies for future clinical trials.

Knowledge-driven multi-graph convolutional network for brain network analysis and potential biomarker discovery

In brain network analysis, individual-level data can provide biological features of individuals, while population-level data can provide demographic information of populations. However, existing methods mostly utilize either individual- or population-level features separately, inevitably neglecting the multi-level characteristics of brain disorders. To address this issue, we propose an end-to-end multi-graph neural network model called KMGCN. This model simultaneously leverages individual- and population-level features for brain network analysis. At the individual level, we construct multi-graph using both knowledge-driven and data-driven approaches. Knowledge-driven refers to constructing a knowledge graph based on prior knowledge, while data-driven involves learning a data graph from the data itself. At the population level, we construct multi-graph using both imaging and phenotypic data. Additionally, we devise a pooling method tailored for brain networks, capable of selecting brain regions that impact brain disorders. We evaluate the performance of our model on two large datasets, ADNI and ABIDE, and experimental results demonstrate that it achieves state-of-the-art performance, with 86.87% classification accuracy for ADNI and 86.40% for ABIDE, accompanied by around 10% improvements in all evaluation metrics compared to the state-of-the-art models. Additionally, the biomarkers identified by our model align well with recent neuroscience research, indicating the effectiveness of our model in brain network analysis and potential biomarker discovery. The code is available at https://github.com/GN-gjh/KMGCN.

The "Reading the Mind in Films" Task: A Pilot Study on Complex Emotion and Mental State Recognition for the Italian Adaptation in Adults with and Without Autism Spectrum Conditions

Background/Objectives: The present pilot study tested and reports the Italian adaptation of the Reading the Mind in Film test (RMF), an ecological test for assessing, in Italian adults with and without Autism Spectrum Condition (ASC), complex emotion and mental state recognition in natural settings and everyday situations. Method: A sample of young adults with Autism Spectrum Condition (with ASC; n = 22), attending a filmmaking course at a post-diploma school (Scuola Futuro Lavoro) took part in the study and was compared with a control group of neurotypical university students (without ASC; n = 22). All participants underwent individual testing and completed the Italian version of the Autism Questionnaire before performing the Italian version of both the RMF task and the Reading the Mind in the Eyes Test (RMET). The latter, widely used to evaluate the ability to detect what someone else is thinking or feeling from the eye region. Results: The findings of the control group were in line with the original study, demonstrating the validity and reliability of the translation and the dubbing procedure of the RMF test. However, no main significant differences in performance were found between the two groups. Conclusions: Such results suggest that taking a course in film and video making may have helped the autistic students learn how to recognize mental states.

How auditory processing influences the autistic profile: A review

We need to combine sensory data from various sources to make sense of the world around us. This sensory data helps us understand our surroundings, influencing our experiences and interactions within our everyday environments. Recent interest in sensory-focused approaches to supporting autistic people has fixed on auditory processing-the sense of hearing and the act of listening-and its crucial role in language, communications, and social domains, as well as non-social autism-specific attributes, to understand better how sensory processing might differ in autistic people. In this narrative review, we synthesize published research into auditory processing in autistic people and the relationship between auditory processing and autistic attributes in a contextually novel way. The purpose is to understand the relationship between these domains more fully, drawing on evidence gleaned from experiential perspectives through to neurological investigations. We also examine the relationship between auditory processing and diagnosable auditory conditions, such as hyperacusis, misophonia, phonophobia, and intolerance to loud sounds, as well as its relation to sleep, anxiety, and sensory overload. Through reviewing experiential, behavioral and neurological literature, we demonstrate that auditory processes interact with and shape the broader autistic profile-something not previously considered. Through a better understanding of the potential impact of auditory experiences, our review aims to inform future research on investigating the relationship between auditory processing and autistic traits through quantitative measures or using qualitative experiential inquiry to examine this relationship more holistically.

Visual attention modulates mu suppression during biological motion perception in autistic individuals

There has been a lot of controversy regarding mirror neuron function in autism spectrum disorder (ASD), in particular during the observation of biological motions (BM). Here, we directly explored the link between visual attention and brain activity in terms of mu suppression, by simultaneously recording eye-tracking and EEGs during BM tasks. Nineteen autistic children (15 boys, mean age = 11.57 ± 4.28 years) and 19 age-matched neurotypical (NT) children (15 boys, mean age = 11.68 ± 5.22 years) participated in the study. Each participant's eye movement and EEG were simultaneously recorded while watching four BM stimuli (walking, cartwheeling, free-throwing and underarm throwing) and a scrambled condition. Mu (8-13 Hz) suppression index (SI) for central regions was calculated. Fixation counts and percent of fixation time were calculated as indices of eye movements. EEG results revealed significant mu suppressions in the central region in both groups for all BM actions. Eye-tracking results showed that NT children had greater fixation counts and a higher percentage of fixation time than autistic children, indicating greater overall visual attention to BM. Notably, correlational analyses for both groups further revealed that individuals' fixation time and fixation counts were negatively correlated with the mu suppression index for all actions, indicating a strong association between visual attention and mu SI in the central region. Our findings suggest a critical role of visual attention in interpreting mu suppression during action perception in autism.

Enhancing Autism Spectrum Disorder identification in multi-site MRI imaging: A multi-head cross-attention and multi-context approach for addressing variability in un-harmonized data

Multi-site MRI imaging poses a significant challenge due to the potential variations in images across different scanners at different sites. This variability can introduce ambiguity in further image analysis. Consequently, the image analysis techniques become site-dependent and scanner-dependent, implying that adjustments in the analysis methodologies are necessary for each scanner configuration. Further, implementing real-time modifications becomes intricate, particularly when incorporating a new type of scanner, as it requires adapting the analysis methods accordingly. Taking into account the aforementioned challenge, we have considered its implications for an Autism spectrum disorder (ASD) application. Our objective is to minimize the impact of site and scanner variability in the analysis, aiming to develop a model that remains effective across different scanners and sites. This entails devising a methodology that allows the same model to function seamlessly across multiple scanner configurations and sites. ASD, a behavioral disorder affecting child development, requires early detection. Clinical observation is time-consuming, prompting the use of fMRI with machine/deep learning for expedited diagnosis. Previous methods leverage fMRI's functional connectivity but often rely on less generalized feature extractors and classifiers. Hence, there is significant room for improvement in the generalizability of detection methods across multi-site data, which is acquired from multiple scanners with different settings. In this study, we propose a Cross-Combination Multi-Scale Multi-Context Framework (CCMSMCF) capable of performing neuroimaging-based diagnostic classification of mental disorders for a multi-site dataset. Thus, this framework attains a degree of internal data harmonization, rendering it to some extent site and scanner-agnostic. Our proposed network, CCMSMCF, is constructed by integrating two sub-modules: the Multi-Head Attention Cross-Scale Module (MHACSM) and the Residual Multi-Context Module (RMCN). We also employ multiple loss functions in a novel manner for training the model, which includes Binary Cross Entropy, Dice loss, and Embedding Coupling loss. The model is validated on the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset, which includes data from multiple scanners across different sites, and achieves promising results.

Acquisition Time for Resting-State HbO/Hb Coupling Measured by Functional Near-Infrared Spectroscopy in Assessing Autism

Functional near-infrared spectroscopy was used to record spontaneous hemodynamic fluctuations form the bilateral temporal lobes in 25 children with autism spectrum disorder (ASD) and 22 typically developing (TD) children. The coupling between oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) was calculated by Pearson correlation coefficient, showing significant difference between ASD and TD, thus the coupling could be a characteristic feature for ASD. To evaluate the discrimination ability of the feature obtained in different acquisition times, the receiver operating characteristic curve (ROC) was constructed and the area under curve (AUC) was calculated. The results showed AUC > 0.8 when the time duration was longer than 1.5 min, but longer than 4 min, AUC value (~0.87) hardly varied, implying the maximal discrimination ability reached. This study demonstrated the coupling could be one of characteristic features for ASD even acquired in a short measurement time.

Adaptive rewiring: a general principle for neural network development

The nervous system, especially the human brain, is characterized by its highly complex network topology. The neurodevelopment of some of its features has been described in terms of dynamic optimization rules. We discuss the principle of adaptive rewiring, i.e., the dynamic reorganization of a network according to the intensity of internal signal communication as measured by synchronization or diffusion, and its recent generalization for applications in directed networks. These have extended the principle of adaptive rewiring from highly oversimplified networks to more neurally plausible ones. Adaptive rewiring captures all the key features of the complex brain topology: it transforms initially random or regular networks into networks with a modular small-world structure and a rich-club core. This effect is specific in the sense that it can be tailored to computational needs, robust in the sense that it does not depend on a critical regime, and flexible in the sense that parametric variation generates a range of variant network configurations. Extreme variant networks can be associated at macroscopic level with disorders such as schizophrenia, autism, and dyslexia, and suggest a relationship between dyslexia and creativity. Adaptive rewiring cooperates with network growth and interacts constructively with spatial organization principles in the formation of topographically distinct modules and structures such as ganglia and chains. At the mesoscopic level, adaptive rewiring enables the development of functional architectures, such as convergent-divergent units, and sheds light on the early development of divergence and convergence in, for example, the visual system. Finally, we discuss future prospects for the principle of adaptive rewiring.

MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning

Prompt learning has demonstrated impressive efficacy in the fine-tuning of multimodal large models to a wide range of downstream tasks. Nonetheless, applying existing prompt learning methods for the diagnosis of neurological disorder still suffers from two issues: (i) existing methods typically treat all patches equally, despite the fact that only a small number of patches in neuroimaging are relevant to the disease, and (ii) they ignore the structural information inherent in the brain connection network which is crucial for understanding and diagnosing neurological disorders. To tackle these issues, we introduce a novel prompt learning model by learning graph prompts during the fine-tuning process of multimodal models for diagnosing neurological disorders. Specifically, we first leverage GPT-4 to obtain relevant disease concepts and compute semantic similarity between these concepts and all patches. Secondly, we reduce the weight of irrelevant patches according to the semantic similarity between each patch and disease-related concepts. Moreover, we construct a graph among tokens based on these concepts and employ a graph convolutional network layer to extract the structural information of the graph, which is used to prompt the pre-trained multimodal models for diagnosing neurological disorders. Extensive experiments demonstrate that our method achieves superior performance for neurological disorder diagnosis compared with state-of-the-art methods and validated by clinicians.

A QR Code for the Brain: A dynamical systems framework for computing neurophysiological biomarkers

Neural circuits are often considered the bridge connecting genetic causes and behavior. Whereas prenatal neural circuits are believed to be derived from a combination of genetic and intrinsic activity, postnatal circuits are largely influenced by exogenous activity and experience. A dynamical neuroelectric field maintained by neural activity is proposed as the fundamental information processing substrate of cognitive function. Time series measurements of the neuroelectric field can be collected by scalp sensors and used to mathematically quantify the essential dynamical features of the neuroelectric field by constructing a digital twin of the dynamical system phase space. The multiscale nonlinear values that result can be organized into tensor data structures, from which latent features can be extracted using tensor factorization. These latent features can be mapped to behavioral constructs to derive digital biomarkers. This computational framework provides a robust method for incorporating neurodynamical measures into neuropsychiatric biomarker discovery.

Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study

BACKGROUND

Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features.

METHODS

The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years.

RESULTS

A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects.

CONCLUSIONS

The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.

Transcallosal white matter and cortical gray matter variations in autistic adults ages 30-73 years: A bi-tensor free water imaging approach

Background: Autism spectrum disorder (ASD) has long been recognized as a lifelong condition, but brain aging studies in autistic adults aged >30 years are limited. Free water, a novel brain imaging marker derived from diffusion MRI (dMRI), has shown promise in differentiating typical and pathological aging and monitoring brain degeneration. We aimed to examine free water and free water corrected dMRI measures to assess white and gray matter microstructure and their associations with age in autistic adults. Methods: Forty-three autistic adults ages 30-73 years and 43 age, sex, and IQ matched neurotypical controls participated in this cross-sectional study. We quantified fractional anisotropy (FA), free water, and free water-corrected FA (fwcFA) across 32 transcallosal white matter tracts and 94 gray matter areas in autistic adults and neurotypical controls. Follow-up analyses assessed age effect on dMRI metrics of the whole brain for both groups and the relationship between dMRI metrics and clinical measures of ASD in regions that significantly differentiated autistic adults from controls. Results: We found globally elevated free water in 24 transcallosal tracts in autistic adults. We identified negligible differences in dMRI metrics in gray matter between the two groups. Age-associated FA reductions and free water increases were featured in neurotypical controls; however, this brain aging profile was largely absent in autistic adults. Additionally, greater autism quotient (AQ) total raw score was associated with increased free water in the inferior frontal gyrus pars orbitalis and lateral orbital gyrus in autistic adults. Limitations: All autistic adults were cognitively capable individuals, minimizing the generalizability of the research findings across the spectrum. This study also involved a cross-sectional design, which limited inferences about the longitudinal microstructural changes of white and gray matter in ASD. Conclusions: We identified differential microstructural configurations between white and gray matter in autistic adults and that autistic individuals present more heterogeneous brain aging profiles compared to controls. Our clinical correlation analysis offered new evidence that elevated free water in some localized white matter tracts may critically contribute to autistic traits in ASD. Our findings underscored the importance of quantifying free water in dMRI studies of ASD.

The dissociating effects of fear and disgust on multisensory integration in autism: evidence from evoked potentials

Background

Deficits in Multisensory Integration (MSI) in ASD have been reported repeatedly and have been suggested to be caused by altered long-range connectivity. Here we investigate behavioral and ERP correlates of MSI in ASD using ecologically valid videos of emotional expressions.

Methods

In the present study, we set out to investigate the electrophysiological correlates of audiovisual MSI in young autistic and neurotypical adolescents. We employed dynamic stimuli of high ecological validity (500 ms clips produced by actors) that depicted fear or disgust in unimodal (visual and auditory), and bimodal (audiovisual) conditions.

Results

We report robust MSI effects at both the behavioral and electrophysiological levels and pronounced differences between autistic and neurotypical participants. Specifically, neurotypical controls showed robust behavioral MSI for both emotions as seen through a significant speed-up of bimodal response time (RT), confirmed by Miller's Race Model Inequality (RMI), with greater MSI effects for fear than disgust. Adolescents with ASD, by contrast, showed behavioral MSI only for fear. At the electrophysiological level, the bimodal condition as compared to the unimodal conditions reduced the amplitudes of the visual P100 and auditory P200 and increased the amplitude of the visual N170 regardless of group. Furthermore, a cluster-based analysis across all electrodes revealed that adolescents with ASD showed an overall delayed and spatially constrained MSI effect compared to controls.

Conclusion

Given that the variables we measured reflect attention, our findings suggest that MSI can be modulated by the differential effects on attention that fear and disgust produce. We also argue that the MSI deficits seen in autistic individuals can be compensated for at later processing stages by (a) the attention-orienting effects of fear, at the behavioral level, and (b) at the electrophysiological level via increased attentional effort.

Therapeutic effects of nanosilibinin in valproic acid-zebrafish model of autism spectrum disorder: Focusing on Wnt signaling pathway and autism spectrum disorder-related cytokines

In this study, we delved into the intricate world of autism spectrum disorder (ASD) and its connection to the disturbance in the Wnt signaling pathway and immunological abnormalities. Our aim was to evaluate the impact of silibinin, a remarkable modulator of both the Wnt signaling pathway and the immune system, on the neurobehavioral and molecular patterns observed in a zebrafish model of ASD induced by valproic acid (VPA). Because silibinin is a hydrophobic molecule and highly insoluble in water, it was used in the form of silibinin nanoparticles (nanosilibinin, NS). After assessing survival, hatching rate, and morphology of zebrafish larvae exposed to different concentrations of NS, the appropriate concentrations were chosen. Then, zebrafish embryos were exposed to VPA (1 μM) and NS (100 and 200 μM) at the same time for 120 h. Next, anxiety and inattentive behaviors and the expression of CHD8, CTNNB, GSK3beta, LRP6, TNFalpha, IL1beta, and BDNF genes were assessed 7 days post fertilization. The results indicated that higher concentrations of NS had adverse effects on survival, hatching, and morphological development. The concentrations of 100 and 200 μM of NS could ameliorate the anxiety-like behavior and learning deficit and decrease ASD-related cytokines (IL1beta and TNFalpha) in VPA-treated larvae. In addition, only 100 μM of NS prevented raising the gene expression of Wnt signaling-related factors (CHD8, CTNNB, GSK3beta, and LRP6). In conclusion, NS treatment for the first 120 h showed therapeutic effect on an autism-like phenotype probably via reducing the expression of pro-inflammatory cytokines genes and changing the expression of Wnt signaling components genes.

Impaired Experience-Dependent Theta Oscillation Synchronization and Inter-Areal Synaptic Connectivity in the Visual Cortex of Fmr1 KO Mice

Fragile X syndrome (FX) is the most prevalent inheritable form of autism spectrum disorder (ASD), characterized by hypersensitivity, difficulty in habituating to new sensory stimuli, and intellectual disability. Individuals with FX often experience visual perception and learning deficits. Visual experience leads to the emergence of the familiarity-evoked theta band oscillations in the primary visual cortex (V1) and the lateromedial area (LM) of mice. These theta oscillations in V1 and LM are synchronized with each other, providing a mechanism of sensory multi-areal binding. However, how this multi-areal binding and the corresponding theta oscillations are altered in FX is not known. Using iDISCO whole brain clearing with light-sheet microscopy, we quantified immediate early gene Fos expression in V1 and LM, identifying deficits in experience-dependent neural activity in FX mice. We performed simultaneous in vivo recordings with silicon probes in V1 and LM of awake mice and channelrhodopsin-2-assisted circuit mapping (CRACM) in acute brain slices to examine the neural activity and strength of long-range synaptic connections between V1 and LM in both wildtype (WT) and Fmr1 knockout (KO) mice, the model of FX, before and after visual experience. Our findings reveal synchronized familiarity-evoked theta oscillations in V1 and LM, the increased strength of V1→LM functional and synaptic connections, which correlated with the corresponding changes of presynaptic short-term plasticity in WT mice. The LM oscillations were attenuated in FX mice and correlated with impaired functional and synaptic connectivity and short-term plasticity in the feedforward (FF) V1→LM and feedback (FB) LM→V1 pathways. Finally, using 4Pi single-molecule localization microscopy (SMLM) in thick brain tissue, we identified experience-dependent changes in the density and shape of dendritic spines in layer 5 pyramidal cells of WT mice, which correlated with the functional synaptic measurements. Interestingly, there was an increased dendritic spine density and length in naïve FX mice that failed to respond to experience. Our study provides the first comprehensive characterization of the role of visual experience in triggering inter-areal neural synchrony and shaping synaptic connectivity in WT and FX mice.

Altered intra- and inter-network connectivity in autism spectrum disorder

OBJECTIVE

A neurodevelopmental illness termed as the autism spectrum disorder (ASD) is described by social interaction impairments. Previous studies employing resting-state functional imaging (rs-fMRI) identified both hyperconnectivity and hypoconnectivity patterns in ASD people. However, specific patterns of connectivity within and between networks linked to ASD remain largely unexplored.

METHODS

We utilized a meticulously selected subset of high-quality data, comprising 45 individuals diagnosed with ASD and 47 HCs, obtained from the ABIDE dataset. The pre-processed rs-fMRI time series signals were partitioned into ninety regions of interest. We focused on eight intrinsic connectivity networks and further performed intra- and inter-network analysis. Finally, support vector machine was used to discriminate ASD from HC.

RESULTS

Through different sparsities, ASD exhibited significantly decreased intra-network connectivity within default mode network and dorsal attention network, increased connectivity between limbic network and subcortical network, and decreased connectivity between default mode network and limbic network. Using the classifier trained on altered intra- and inter-network connectivity, multivariate pattern analyses classified the ASD from HC with 71.74% accuracy, 70.21% specificity and 75.56% sensitivity in 10% sparsity of functional connectivity.

CONCLUSIONS

ASD showed characteristic reorganization of the brain networks and this provided new insight into the underlying process of the functional connectome dysfunction in ASD.

Shared behavioural impairments in visual perception and place avoidance across different autism models are driven by periaqueductal grey hypoexcitability in Setd5 haploinsufficient mice

Despite the diverse genetic origins of autism spectrum disorders (ASDs), affected individuals share strikingly similar and correlated behavioural traits that include perceptual and sensory processing challenges. Notably, the severity of these sensory symptoms is often predictive of the expression of other autistic traits. However, the origin of these perceptual deficits remains largely elusive. Here, we show a recurrent impairment in visual threat perception that is similarly impaired in 3 independent mouse models of ASD with different molecular aetiologies. Interestingly, this deficit is associated with reduced avoidance of threatening environments-a nonperceptual trait. Focusing on a common cause of ASDs, the Setd5 gene mutation, we define the molecular mechanism. We show that the perceptual impairment is caused by a potassium channel (Kv1)-mediated hypoexcitability in a subcortical node essential for the initiation of escape responses, the dorsal periaqueductal grey (dPAG). Targeted pharmacological Kv1 blockade rescued both perceptual and place avoidance deficits, causally linking seemingly unrelated trait deficits to the dPAG. Furthermore, we show that different molecular mechanisms converge on similar behavioural phenotypes by demonstrating that the autism models Cul3 and Ptchd1, despite having similar behavioural phenotypes, differ in their functional and molecular alteration. Our findings reveal a link between rapid perception controlled by subcortical pathways and appropriate learned interactions with the environment and define a nondevelopmental source of such deficits in ASD.

A de novo missense mutation in synaptotagmin-1 associated with neurodevelopmental disorder desynchronizes neurotransmitter release

Synaptotagmin-1 (Syt1) is a presynaptic calcium sensor with two calcium binding domains, C2A and C2B, that triggers action potential-induced synchronous neurotransmitter release, while suppressing asynchronous and spontaneous release. We identified a de novo missense mutation (P401L) in the C2B domain in a patient with developmental delay and autistic symptoms. Expressing the orthologous mouse mutant (P400L) in cultured Syt1 null mutant neurons revealed a reduction in dendrite outgrowth with a proportional reduction in synapses. This was not observed in single Syt1PL-rescued neurons that received normal synaptic input when cultured in a control network. Patch-clamp recordings showed that spontaneous miniature release events per synapse were increased more than 500% in Syt1PL-rescued neurons, even beyond the increased rates in Syt1 KO neurons. Furthermore, action potential-induced asynchronous release was increased more than 100%, while synchronous release was unaffected. A similar shift to more asynchronous release was observed during train stimulations. These cellular phenotypes were also observed when Syt1PL was overexpressed in wild type neurons. Our findings show that Syt1PL desynchronizes neurotransmission by increasing the readily releasable pool for asynchronous release and reducing the suppression of spontaneous and asynchronous release. Neurons respond to this by shortening their dendrites, possibly to counteract the increased synaptic input. Syt1PL acts in a dominant-negative manner supporting a causative role for the mutation in the heterozygous patient. We propose that the substitution of a rigid proline to a more flexible leucine at the bottom of the C2B domain impairs clamping of release by interfering with Syt1's primary interface with the SNARE complex. This is a novel cellular phenotype, distinct from what was previously found for other SYT1 disease variants, and points to a role for spontaneous and asynchronous release in SYT1-associated neurodevelopmental disorder.

Abnormal Development of the Corpus Callosum in Autism Spectrum Disorder: An MRI Study

BACKGROUND

Altered size in the corpus callosum (CC) has been reported in individuals with autism spectrum disorder (ASD), but few studies have investigated younger children. Moreover, knowledge about the age-related changes in CC size in individuals with ASD is limited.

OBJECTIVES

Our objective was to investigate the age-related size of the CC and compare them with age-matched healthy controls between the ages of 2 and 18 years.

METHODS

Structural-weighted images were acquired in 97 male patients diagnosed with ASD; published data were used for the control group. The CC was segmented into 7 distinct subregions (rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium) as per Witelson's technique using ITK-SNAP software. We calculated both the total length and volume of the CC as well as the length and height of its 7 subregions. The length of the CC measures was studied as both continuous and categorical forms. For the continuous form, Pearson's correlation was used, while categorical forms were based on age ranges reflecting brain expansion during early postnatal years. Differences in CC measures between adjacent age groups in individuals with ASD were assessed using a Student t-test. Mean and standard deviation scores were compared between ASD and control groups using the Welch t-test.

RESULTS

Age showed a moderate positive association with the total length of the CC (r = 0.43; Padj = 0.003) among individuals with ASD. Among the subregions, a positive association was observed only in the anterior midbody of the CC (r = 0.41; Padj = 0.01). No association was found between the age and the height of individual subregions or with the total volume of the CC. In comparison with healthy controls, individuals with ASD exhibited shorter lengths and heights of the genu and splenium of the CC across wide age ranges.

CONCLUSION

Overall, our results highlight a distinct abnormal developmental trajectory of CC in ASD, particularly in the genu and splenium structures, potentially reflecting underlying pathophysiological mechanisms that warrant further investigation.

Altered projection-specific synaptic remodeling and its modification by oxytocin in an idiopathic autism marmoset model

Alterations in the experience-dependent and autonomous elaboration of neural circuits are assumed to underlie autism spectrum disorder (ASD), though it is unclear what synaptic traits are responsible. Here, utilizing a valproic acid-induced ASD marmoset model, which shares common molecular features with idiopathic ASD, we investigate changes in the structural dynamics of tuft dendrites of upper-layer pyramidal neurons and adjacent axons in the dorsomedial prefrontal cortex through two-photon microscopy. In model marmosets, dendritic spine turnover is upregulated, and spines are generated in clusters and survived more often than in control marmosets. Presynaptic boutons in local axons, but not in commissural long-range axons, demonstrate hyperdynamic turnover in model marmosets, suggesting alterations in projection-specific plasticity. Intriguingly, nasal oxytocin administration attenuates clustered spine emergence in model marmosets. Enhanced clustered spine generation, possibly unique to certain presynaptic partners, may be associated with ASD and be a potential therapeutic target.

Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI

We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.

Differential neural correlates underlying visuospatial versus semantic reasoning in autistic children

While fronto-posterior underconnectivity has often been reported in autism, it was shown that different contexts may modulate between-group differences in functional connectivity. Here, we assessed how different task paradigms modulate functional connectivity differences in a young autistic sample relative to typically developing children. Twenty-three autistic and 23 typically developing children aged 6 to 15 years underwent functional magnetic resonance imaging (fMRI) scanning while completing a reasoning task with visuospatial versus semantic content. We observed distinct connectivity patterns in autistic versus typical children as a function of task type (visuospatial vs. semantic) and problem complexity (visual matching vs. reasoning), despite similar performance. For semantic reasoning problems, there was no significant between-group differences in connectivity. However, during visuospatial reasoning problems, we observed occipital-occipital, occipital-temporal, and occipital-frontal over-connectivity in autistic children relative to typical children. Also, increasing the complexity of visuospatial problems resulted in increased functional connectivity between occipital, posterior (temporal), and anterior (frontal) brain regions in autistic participants, more so than in typical children. Our results add to several studies now demonstrating that the connectivity alterations in autistic relative to neurotypical individuals are much more complex than previously thought and depend on both task type and task complexity and their respective underlying cognitive processes.

Central Executive and Default Mode Networks: An Appraisal of Executive Function and Social Skill Brain-Behavior Correlates in Youth with Autism Spectrum Disorder

Atypical connectivity patterns have been observed for individuals with autism spectrum disorders (ASD), particularly across the triple-network model. The current study investigated brain-behavior relationships in the context of social skills and executive function profiles for ASD youth. We calculated connectivity measures from diffusion tensor imaging using Bayesian estimation and probabilistic tractography. We replicated prior structural equation modeling of behavioral measures with total default mode network (DMN) connectivity to include comparisons with central executive network (CEN) connectivity and CEN-DMN connectivity. Increased within-CEN connectivity was related to metacognitive strengths. Our findings indicate behavior regulation difficulties in youth with ASD may be attributable to impaired connectivity between the CEN and DMN and social skill difficulties may be exacerbated by impaired within-DMN connectivity.

Central Causation of Autism/ASDs via Excessive [Ca2+]i Impacting Six Mechanisms Controlling Synaptogenesis during the Perinatal Period: The Role of Electromagnetic Fields and Chemicals and the NO/ONOO(-) Cycle, as Well as Specific Mutations

The roles of perinatal development, intracellular calcium [Ca2+]i, and synaptogenesis disruption are not novel in the autism/ASD literature. The focus on six mechanisms controlling synaptogenesis, each regulated by [Ca2+]i, and each aberrant in ASDs is novel. The model presented here predicts that autism epidemic causation involves central roles of both electromagnetic fields (EMFs) and chemicals. EMFs act via voltage-gated calcium channel (VGCC) activation and [Ca2+]i elevation. A total of 15 autism-implicated chemical classes each act to produce [Ca2+]i elevation, 12 acting via NMDA receptor activation, and three acting via other mechanisms. The chronic nature of ASDs is explained via NO/ONOO(-) vicious cycle elevation and MeCP2 epigenetic dysfunction. Genetic causation often also involves [Ca2+]i elevation or other impacts on synaptogenesis. The literature examining each of these steps is systematically examined and found to be consistent with predictions. Approaches that may be sed for ASD prevention or treatment are discussed in connection with this special issue: The current situation and prospects for children with ASDs. Such approaches include EMF, chemical avoidance, and using nutrients and other agents to raise the levels of Nrf2. An enriched environment, vitamin D, magnesium, and omega-3s in fish oil may also be helpful.

The autism susceptibility kinase, TAOK2, phosphorylates eEF2 and modulates translation

Genes implicated in translation control have been associated with autism spectrum disorders (ASDs). However, some important genetic causes of autism, including the 16p11.2 microdeletion, bear no obvious connection to translation. Here, we use proteomics, genetics, and translation assays in cultured cells and mouse brain to reveal altered translation mediated by loss of the kinase TAOK2 in 16p11.2 deletion models. We show that TAOK2 associates with the translational machinery and functions as a translational brake by phosphorylating eukaryotic elongation factor 2 (eEF2). Previously, all signal-mediated regulation of translation elongation via eEF2 phosphorylation was believed to be mediated by a single kinase, eEF2K. However, we show that TAOK2 can directly phosphorylate eEF2 on the same regulatory site, but functions independently of eEF2K signaling. Collectively, our results reveal an eEF2K-independent signaling pathway for control of translation elongation and suggest altered translation as a molecular component in the etiology of some forms of ASD.

Annual Research Review: Early intervention viewed through the lens of developmental neuroscience

The overarching goal of this paper is to examine the efficacy of early intervention when viewed through the lens of developmental neuroscience. We begin by briefly summarizing neural development from conception through the first few postnatal years. We emphasize the role of experience during the postnatal period, and consistent with decades of research on critical periods, we argue that experience can represent both a period of opportunity and a period of vulnerability. Because plasticity is at the heart of early intervention, we next turn our attention to the efficacy of early intervention drawing from two distinct literatures: early intervention services for children growing up in disadvantaged environments, and children at elevated likelihood of developing a neurodevelopmental delay or disorder. In the case of the former, we single out interventions that target caregiving and in the case of the latter, we highlight recent work on autism. A consistent theme throughout our review is a discussion of how early intervention is embedded in the developing brain. We conclude our article by discussing the implications our review has for policy, and we then offer recommendations for future research.

Community detection in the human connectome: Method types, differences and their impact on inference

Community structure is a fundamental topological characteristic of optimally organized brain networks. Currently, there is no clear standard or systematic approach for selecting the most appropriate community detection method. Furthermore, the impact of method choice on the accuracy and robustness of estimated communities (and network modularity), as well as method-dependent relationships between network communities and cognitive and other individual measures, are not well understood. This study analyzed large datasets of real brain networks (estimated from resting-state fMRI fromn $$ n $$ = 5251 pre/early adolescents in the adolescent brain cognitive development [ABCD] study), andn $$ n $$ = 5338 synthetic networks with heterogeneous, data-inspired topologies, with the goal to investigate and compare three classes of community detection methods: (i) modularity maximization-based (Newman and Louvain), (ii) probabilistic (Bayesian inference within the framework of stochastic block modeling (SBM)), and (iii) geometric (based on graph Ricci flow). Extensive comparisons between methods and their individual accuracy (relative to the ground truth in synthetic networks), and reliability (when applied to multiple fMRI runs from the same brains) suggest that the underlying brain network topology plays a critical role in the accuracy, reliability and agreement of community detection methods. Consistent method (dis)similarities, and their correlations with topological properties, were estimated across fMRI runs. Based on synthetic graphs, most methods performed similarly and had comparable high accuracy only in some topological regimes, specifically those corresponding to developed connectomes with at least quasi-optimal community organization. In contrast, in densely and/or weakly connected networks with difficult to detect communities, the methods yielded highly dissimilar results, with Bayesian inference within SBM having significantly higher accuracy compared to all others. Associations between method-specific modularity and demographic, anthropometric, physiological and cognitive parameters showed mostly method invariance but some method dependence as well. Although method sensitivity to different levels of community structure may in part explain method-dependent associations between modularity estimates and parameters of interest, method dependence also highlights potential issues of reliability and reproducibility. These findings suggest that a probabilistic approach, such as Bayesian inference in the framework of SBM, may provide consistently reliable estimates of community structure across network topologies. In addition, to maximize robustness of biological inferences, identified network communities and their cognitive, behavioral and other correlates should be confirmed with multiple reliable detection methods.

An optrode array for spatiotemporally-precise large-scale optogenetic stimulation of deep cortical layers in non-human primates

Optogenetics has transformed studies of neural circuit function, but remains challenging to apply to non-human primates (NHPs). A major challenge is delivering intense, spatiotemporally-precise, patterned photostimulation across large volumes in deep tissue. Such stimulation is critical, for example, to modulate selectively deep-layer corticocortical feedback circuits. To address this need, we have developed the Utah Optrode Array (UOA), a 10×10 glass needle waveguide array fabricated atop a novel opaque optical interposer, and bonded to an electrically addressable µLED array. In vivo experiments with the UOA demonstrated large-scale, spatiotemporally precise, activation of deep circuits in NHP cortex. Specifically, the UOA permitted both focal (confined to single layers/columns), and widespread (multiple layers/columns) optogenetic activation of deep layer neurons, as assessed with multi-channel laminar electrode arrays, simply by varying the number of activated µLEDs and/or the irradiance. Thus, the UOA represents a powerful optoelectronic device for targeted manipulation of deep-layer circuits in NHP models.

Functional labeling of individualized postsynaptic neurons using optogenetics and trans-Tango in Drosophila (FLIPSOT)

A population of neurons interconnected by synapses constitutes a neural circuit, which performs specific functions upon activation. It is essential to identify both anatomical and functional entities of neural circuits to comprehend the components and processes necessary for healthy brain function and the changes that characterize brain disorders. To date, few methods are available to study these two aspects of a neural circuit simultaneously. In this study, we developed FLIPSOT, or functional labeling of individualized postsynaptic neurons using optogenetics and trans-Tango. FLIPSOT uses (1) trans-Tango to access postsynaptic neurons genetically, (2) optogenetic approaches to activate (FLIPSOTa) or inhibit (FLIPSOTi) postsynaptic neurons in a random and sparse manner, and (3) fluorescence markers tagged with optogenetic genes to visualize these neurons. Therefore, FLIPSOT allows using a presynaptic driver to identify the behavioral function of individual postsynaptic neurons. It is readily applied to identify functions of individual postsynaptic neurons and has the potential to be adapted for use in mammalian circuits.

Design and methodology for a proof of mechanism study of individualized neuronavigated continuous Theta burst stimulation for auditory processing in adolescents with autism spectrum disorder

It has been suggested that aberrant excitation/inhibition (E/I) balance and dysfunctional structure and function of relevant brain networks may underlie the symptoms of autism spectrum disorder (ASD). However, the nomological network linking these constructs to quantifiable measures and mechanistically relating these constructs to behavioral symptoms of ASD is lacking. Herein we describe a within-subject, controlled, proof-of-mechanism study investigating the pathophysiology of auditory/language processing in adolescents with ASD. We utilize neurophysiological and neuroimaging techniques including magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) metrics of language network structure and function. Additionally, we apply a single, individually targeted session of continuous theta burst stimulation (cTBS) as an experimental probe of the impact of perturbation of the system on these neurophysiological and neuroimaging outcomes. MRS, fMRI, and MEG measures are evaluated at baseline and immediately prior to and following cTBS over the posterior superior temporal cortex (pSTC), a region involved in auditory and language processing deficits in ASD. Also, behavioral measures of ASD and language processing and DWI measures of auditory/language network structures are obtained at baseline to characterize the relationship between the neuroimaging and neurophysiological measures and baseline symptom presentation. We hypothesize that local gamma-aminobutyric acid (GABA) and glutamate concentrations (measured with MRS), and structural and functional activity and network connectivity (measured with DWI and fMRI), will significantly predict MEG indices of auditory/language processing and behavioral deficits in ASD. Furthermore, a single session of cTBS over left pSTC is hypothesized to lead to significant, acute changes in local glutamate and GABA concentration, functional activity and network connectivity, and MEG indices of auditory/language processing. We have completed the pilot phase of the study (n=20 Healthy Volunteer adults) and have begun enrollment for the main phase with adolescents with ASD (n=86; age 14-17). If successful, this study will establish a nomological network linking local E/I balance measures to functional and structural connectivity within relevant brain networks, ultimately connecting them to ASD symptoms. Furthermore, this study will inform future therapeutic trials using cTBS to treat the symptoms of ASD.

Atypical local brain connectivity in pediatric autism spectrum disorder? A coordinate-based meta-analysis of regional homogeneity studies

Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age [Formula: see text] 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology.

Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders

BACKGROUND

The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and functional MRI might improve the performances of a deep learning (DL) model trained to discriminate subjects with Autism Spectrum Disorders (ASD) with respect to typically developing controls (TD).

MATERIAL AND METHODS

We analyzed both structural and functional MRI brain scans publicly available within the ABIDE I and II data collections. We considered 1383 male subjects with age between 5 and 40 years, including 680 subjects with ASD and 703 TD from 35 different acquisition sites. We extracted morphometric and functional brain features from MRI scans with the Freesurfer and the CPAC analysis packages, respectively. Then, due to the multisite nature of the dataset, we implemented a data harmonization protocol. The ASD vs. TD classification was carried out with a multiple-input DL model, consisting in a neural network which generates a fixed-length feature representation of the data of each modality (FR-NN), and a Dense Neural Network for classification (C-NN). Specifically, we implemented a joint fusion approach to multiple source data integration. The main advantage of the latter is that the loss is propagated back to the FR-NN during the training, thus creating informative feature representations for each data modality. Then, a C-NN, with a number of layers and neurons per layer to be optimized during the model training, performs the ASD-TD discrimination. The performance was evaluated by computing the Area under the Receiver Operating Characteristic curve within a nested 10-fold cross-validation. The brain features that drive the DL classification were identified by the SHAP explainability framework.

RESULTS

The AUC values of 0.66±0.05 and of 0.76±0.04 were obtained in the ASD vs. TD discrimination when only structural or functional features are considered, respectively. The joint fusion approach led to an AUC of 0.78±0.04. The set of structural and functional connectivity features identified as the most important for the two-class discrimination supports the idea that brain changes tend to occur in individuals with ASD in regions belonging to the Default Mode Network and to the Social Brain.

CONCLUSIONS

Our results demonstrate that the multimodal joint fusion approach outperforms the classification results obtained with data acquired by a single MRI modality as it efficiently exploits the complementarity of structural and functional brain information.

Children with Autism Spectrum Disorder and Abnormalities of Clinical EEG: A Qualitative Review

Over the last decade, the comorbidity between Autism Spectrum Disorder (ASD) and epilepsy has been widely demonstrated, and many hypotheses regarding the common neurobiological bases of these disorders have been put forward. A variable, but significant, prevalence of abnormalities on electroencephalogram (EEG) has been documented in non-epileptic children with ASD; therefore, several scientific studies have recently tried to demonstrate the role of these abnormalities as a possible biomarker of altered neural connectivity in ASD individuals. This narrative review intends to summarize the main findings of the recent scientific literature regarding abnormalities detected with standard EEG in children/adolescents with idiopathic ASD. Research using three different databases (PubMed, Scopus and Google Scholar) was conducted, resulting in the selection of 10 original articles. Despite an important lack of studies on preschoolers and a deep heterogeneity in results, some authors speculated on a possible association between EEG abnormalities and ASD characteristics, in particular, the severity of symptoms. Although this correlation needs to be more strongly elucidated, these findings may encourage future studies aimed at demonstrating the role of electrical brain abnormalities as an early biomarker of neural circuit alterations in ASD, highlighting the potential diagnostic, prognostic and therapeutic value of EEG in this field.

A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization

BACKGROUND

Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals.

METHODS

The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ.

RESULTS

We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex.

CONCLUSIONS

These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

Differences in Brain Network Topology Based on Alcohol Use History in Adolescents

Approximately 6 million youth aged 12 to 20 consume alcohol monthly in the United States. The effect of alcohol consumption in adolescence on behavior and cognition is heavily researched; however, little is known about how alcohol consumption in adolescence may alter brain function, leading to long-term developmental detriments. In order to investigate differences in brain connectivity associated with alcohol use in adolescents, brain networks were constructed using resting-state functional magnetic resonance imaging data collected by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) from 698 youth (12-21 years; 117 hazardous drinkers and 581 no/low drinkers). Analyses assessed differences in brain network topology based on alcohol consumption in eight predefined brain networks, as well as in whole-brain connectivity. Within the central executive network (CEN), basal ganglia network (BGN), and sensorimotor network (SMN), no/low drinkers demonstrated stronger and more frequent connections between highly globally efficient nodes, with fewer and weaker connections between highly clustered nodes. Inverse results were observed within the dorsal attention network (DAN), visual network (VN), and frontotemporal network (FTN), with no/low drinkers demonstrating weaker connections between nodes with high efficiency and increased frequency of clustered nodes compared to hazardous drinkers. Cross-sectional results from this study show clear organizational differences between adolescents with no/low or hazardous alcohol use, suggesting that aberrant connectivity in these brain networks is associated with risky drinking behaviors.

Abnormal Microglial Density and Morphology in the Brain of Cyclooxygenase 2 Knockin Mice

Prostaglandin E2 (PGE2) is a signaling molecule produced by cyclooxygenase-2 (COX-2) that is important in healthy brain development. Anomalies in the COX-2/PGE2 pathway due to genetic or environmental factors have been linked to Autism Spectrum Disorders (ASD). Our previous studies showed that COX-2 deficient (COX-2-KI) mice exhibit sex-dependent molecular changes in the brain and associated autism-related behaviors. Here, we aim to determine the effect of COX-2-KI on microglial density and morphology in the developing brain. Microglia normally transition between an amoeboid or ramified morphology depending on their surroundings and are important for the development of the healthy brain, assisting with synaptogenesis, synaptic pruning, and phagocytosis. We use COX-2-KI male and female mice to evaluate microglia density, morphology, and branch length and number in five brain regions (cerebellum, hippocampus, olfactory bulb, prefrontal cortex, and thalamus) at the gestational day 19 (G19) and postnatal day 25 (PN25). We discovered that COX2-KI females were affected at G19 with increased microglial density, altered percentage of amoeboid and ramified microglia, affected branch length, and decreased branching networks in a region-specific manner; these effects persisted to PN25 in select regions. Interestingly, while limited changes were found in G19 COX-2-KI males, at PN25 we found increased microglial density, higher percentages of ramified microglia, and increased branch counts, and length observed in nearly all brain regions tested. Overall, we show for the first time that the COX-2 deficiency in our ASD mouse model influences microglia morphology in a sex- and region- and stage-dependent manner.

Fundamental behavioral and neurophysiologic relationships between sensory processing, intolerance of uncertainty, and autistic traits in children: A hybrid approach

Sensory differences are common and often challenging for autistic children. Furthermore, atypical sensory processing is associated with autistic traits and other autism-related behaviors, such as intolerance of uncertainty (IU). Such traits and their relatedness vary continuously across autistic and non-autistic children alike. However, the underlying neural correlates of these continuous variables, and their associations, are not well understood. Therefore, this study examined relationships between sensory processing, IU, autistic traits, and associated resting state brain connectivity, across a sample of both autistic (n = 30) and non-autistic (n = 26) children. In addition to computing behavioral correlations between these factors, we carried out independent component network functional connectivity analysis to investigate associations between cortical and cerebellar networks and behavioral results between groups and across our entire sample. Across-group correlations between sensory processing, autistic traits, and IU were significant. In addition, data demonstrated overlapping sensory processing and intolerance of uncertainty scores, spanning the groups. Brain (rs-fMRI)-behavioral relationships revealed strong associations between sensory, large-scale resting state, and cerebellar networks and behavioral scores. Overall, our findings suggest that sensory differences are related to IU and autistic traits across the population. Neurophysiologic data pointed to functional connectivity between sensory cortices and supramodal brain networks. These findings provide evidence for the continuous variation of behaviors common to autism throughout the entire population and their neurobiological correlates.

Potential mechanisms of action of resveratrol in prevention and therapy for mental disorders

There is a growing body of evidence about the potential of diet and nutrients to improve the population's mental health and the treatment of psychiatric disorders. Some studies have suggested that resveratrol has therapeutic properties in mental disorders, such as major depressive disorder, bipolar disorder, Alzheimer's disease, and autism. In addition, resveratrol is known to induce several benefits modulated by multiple synergistic pathways, which control oxidative stress, inflammation, and cell death. This review collects the currently available data from animal and human studies and discusses the potential mechanisms of action of resveratrol in prevention and therapy for psychiatric disorders.

Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking

Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.

The Prevalence of Attention Deficit/Hyperactivity Disorder Symptoms in Children and Adolescents With Autism Spectrum Disorder Without Intellectual Disability: A Systematic Review

OBJECTIVE

ADHD commonly co-occurs with ASD without ID in young people. It has been difficult to obtain accurate prevalence estimates of ADHD in this population, as a dual-diagnosis was not permitted until DSM-V. We systematically reviewed the literature on the prevalence of ADHD symptoms in young people with ASD without ID.

METHOD

9,050 articles were identified through six databases. Articles were reviewed against inclusion and exclusion criteria and 23 studies were included.

RESULTS

ADHD symptom prevalence varied from 2.6% to 95.5%. We discuss these findings according to the ADHD assessment measure, informant, diagnostic criteria, risk of bias rating and recruitment pool.

CONCLUSION

ADHD symptoms are common in young people with ASD without ID, but there is substantial variance in study reporting. Future studies should recruit participants from community sources, provide information on key sociodemographic sample characteristics and assess ADHD with standardized diagnostic criteria, using both parent/carer and teacher report.