Age-related changes in intrinsic function of the superior temporal sulcus in autism spectrum disorders

A multimodal interface for speech perception: the role of the left superior temporal sulcus in social cognition and autism

Multimodal integration is crucial for human interaction, in particular for social communication, which relies on integrating information from various sensory modalities. Recently a third visual pathway specialized in social perception was proposed, which includes the right superior temporal sulcus (STS) playing a key role in processing socially relevant cues and high-level social perception. Importantly, it has also recently been proposed that the left STS contributes to audiovisual integration of speech processing. In this article, we propose that brain areas along the right STS that support multimodal integration for social perception and cognition can be considered homologs to those in the left, language-dominant hemisphere, sustaining multimodal integration of speech and semantic concepts fundamental for social communication. Emphasizing the significance of the left STS in multimodal integration and associated processes such as multimodal attention to socially relevant stimuli, we underscore its potential relevance in comprehending neurodevelopmental conditions characterized by challenges in social communication such as autism spectrum disorder (ASD). Further research into this left lateral processing stream holds the promise of enhancing our understanding of social communication in both typical development and ASD, which may lead to more effective interventions that could improve the quality of life for individuals with atypical neurodevelopment.

A review of the applications of generative adversarial networks to structural and functional MRI based diagnostic classification of brain disorders

Structural and functional MRI (magnetic resonance imaging) based diagnostic classification using machine learning has long held promise, but there are many roadblocks to achieving their potential. While traditional machine learning models suffered from their inability to capture the complex non-linear mapping, deep learning models tend to overfit the model. This is because there is data scarcity and imbalanced classes in neuroimaging; it is expensive to acquire data from human subjects and even more so in clinical populations. Due to their ability to augment data by learning underlying distributions, generative adversarial networks (GAN) provide a potential solution to this problem. Here, we provide a methodological primer on GANs and review the applications of GANs to classification of mental health disorders from neuroimaging data such as functional MRI and showcase the progress made thus far. We also highlight gaps in methodology as well as interpretability that are yet to be addressed. This provides directions about how the field can move forward. We suggest that since there are a range of methodological choices available to users, it is critical for users to interact with method developers so that the latter can tailor their development according to the users' needs. The field can be enriched by such synthesis between method developers and users in neuroimaging.

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.

Abnormal functional connectivity of the reward network is associated with social communication impairments in autism spectrum disorder: A large-scale multi-site resting-state fMRI study

BACKGROUND

The social motivation hypothesis proposes that the social deficits of autism spectrum disorder (ASD) are related to reward system dysfunction. However, functional connectivity (FC) patterns of the reward network in ASD have not been systematically explored yet.

METHODS

The reward network was defined as eight regions of interest (ROIs) per hemisphere, including the nucleus accumbens (NAc), caudate, putamen, anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), amygdala, and insula. We computed both the ROI-wise resting-state FC and seed-based whole-brain FC in 298 ASD participants and 348 typically developing (TD) controls from the Autism Brain Imaging Data Exchange I dataset. Two-sample t-tests were applied to obtain the aberrant FCs. Then, the association between aberrant FCs and clinical symptoms was assessed with Pearson's correlation or Spearman's correlation. In addition, Neurosynth Image Decoder was used to generate word clouds verifying the cognitive functions of the aberrant pathways. Furthermore, a three-way multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, subtype and age on the atypical FCs.

RESULTS

For the within network analysis, the left ACC showed weaker FCs with both the right amygdala and left NAc in ASD compared with TD, which were negatively correlated with the Autism Diagnostic Observation Schedule (ADOS) total scores and Social Responsiveness Scale (SRS) total scores respectively. For the whole-brain analysis, weaker FC (i.e., FC between the left vmPFC and left calcarine gyrus, and between the right vmPFC and left precuneus) accompanied by stronger FC (i.e., FC between the left caudate and right insula) were exhibited in ASD relative to TD, which were positively associated with the SRS motivation scores. Additionally, we detected the main effect of age on FC between the left vmPFC and left calcarine gyrus, of subtype on FC between the right vmPFC and left precuneus, of age and age-by-gender interaction on FC between the left caudate and right insula.

CONCLUSIONS

Our findings highlight the crucial role of abnormal FC patterns of the reward network in the core social deficits of ASD, which have the potential to reveal new biomarkers for ASD.

Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review

The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.

Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.

Altered resting-state functional connectivity of the brain in children with autism spectrum disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders. Brain mapping has shown that functional brain connections are altered in autism. This study investigated the pattern of brain connection changes in autistic people compared to healthy people. This study aimed to analyze functional abnormalities within the brain due to ASD, using resting-state functional magnetic resonance imaging (fMRI). Resting-state functional magnetic resonance images of 26 individuals with ASD and 26 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The DPARSF (data processing assistant for resting-state fMRI) toolbox was used for resting-state functional image processing, and features related to functional connections were extracted from these images. Then, the extracted features from both groups were compared using an Independent Two-Sample T Test, and the features with significant differences between the two groups were identified. Compared with healthy controls, individuals with ASD showed hyper-connectivity in the frontal lobe, anterior cingulum, parahippocampal, left precuneus, angular, caudate, superior temporal, and left pallidum, as well as hypo-connectivity in the precentral, left superior frontal, left middle orbitofrontal, right amygdala, and left posterior cingulum. Our findings show that abnormal functional connectivity exists in patients with ASD. This study makes an important advancement in our understanding of the abnormal neurocircuits causing autism.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P < 0.05 , family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Mapping brain functional and structural abnormities in autism spectrum disorder: moving toward precision treatment

Autism spectrum disorder (ASD) is a formidable challenge for psychiatry and neuroscience because of its high prevalence, lifelong nature, complexity, and substantial heterogeneity. A major goal of neuroimaging studies of ASD is to understand the neurobiological underpinnings of this disorder from multi-dimensional and multi-level perspectives, by investigating how brain anatomy, function, and connectivity are altered in ASD, and how they vary across the population. However, ongoing debate exists within those studies, and neuroimaging findings in ASD are often contradictory. Over the past decade, we have dedicated to delineate a comprehensive and consistent mapping of the abnormal structure and function of the autistic brain, and this review synthesizes the findings across our studies reaching a consensus that the "social brain" are the most affected regions in the autistic brain at different levels and modalities. We suggest that the social brain network can serve as a plausible biomarker and potential target for effective intervention in individuals with ASD.

Dissociation of early and late face-related processes in autism spectrum disorder and Williams syndrome

Background

Williams syndrome (WS) and Autism Spectrum Disorders (ASD) are neurodevelopmental conditions associated with atypical but opposite face-to-face interactions patterns: WS patients overly stare at others, ASD individuals escape eye contact. Whether these behaviors result from dissociable visual processes within the occipito-temporal pathways is unknown.

Using high-density electroencephalography, multivariate signal processing algorithms and a protocol designed to identify and extract evoked activities sensitive to facial cues, we investigated how WS (N = 14), ASD (N = 14) and neurotypical subjects (N = 14) decode the information content of a face stimulus.

Results

We found two neural components in neurotypical participants, both strongest when the eye region was projected onto the subject's fovea, simulating a direct eye contact situation, and weakest over more distant regions, reaching a minimum when the focused region was outside the stimulus face. The first component peaks at 170 ms, an early signal known to be implicated in low-level face features. The second is identified later, 260 ms post-stimulus onset and is implicated in decoding salient face social cues.

Remarkably, both components were found distinctly impaired and preserved in WS and ASD. In WS, we could weakly decode the 170 ms signal based on our regressor relative to facial features, probably due to their relatively poor ability to process faces’ morphology, while the late 260 ms component was highly significant. The reverse pattern was observed in ASD participants who showed neurotypical like early 170 ms evoked activity but impaired late evoked 260 ms signal.

Conclusions

Our study reveals a dissociation between WS and ASD patients and points at different neural origins for their social impairments.

Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI

Brain functional connectivity (FC) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has been widely employed to study neuropsychiatric disorders such as autism spectrum disorder (ASD). Existing studies usually suffer from (1) significant data heterogeneity caused by different scanners or studied populations in multiple sites, (2) curse of dimensionality caused by millions of voxels in each fMRI scan and a very limited number (tens or hundreds) of training samples, and (3) poor interpretability, which hinders the identification of reproducible disease biomarkers. To this end, we propose a Multi-site Clustering and Nested Feature Extraction (MC-NFE) method for fMRI-based ASD detection. Specifically, we first divide multi-site training data into ASD and healthy control (HC) groups. To model inter-site heterogeneity within each category, we use a similarity-driven multiview linear reconstruction model to learn latent representations and perform subject clustering within each group. We then design a nested singular value decomposition (SVD) method to mitigate inter-site heterogeneity and extract FC features by learning both local cluster-shared features across sites within each category and global category-shared features across ASD and HC groups, followed by a linear support vector machine (SVM) for ASD detection. Experimental results on 609 subjects with rs-fMRI from the ABIDE database with 21 imaging sites suggest that the proposed MC-NFE outperforms several state-of-the-art methods in ASD detection. The most discriminative FCs identified by the MC-NFE are mainly located in default mode network, salience network, and cerebellum region, which could be used as potential biomarkers for fMRI-based ASD analysis.

Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder

LAY ABSTRACT

Autism spectrum disorder has long been conceptualized as a disorder of "atypical development of functional brain connectivity (which refers to correlations in activity levels of distant brain regions)." However, most of the research has focused on the connectivity between cortical regions, and much remains unknown about the developmental changes of functional connectivity between subcortical and cortical areas in autism spectrum disorder. We used the technique of resting-state functional magnetic resonance imaging to explore the developmental characteristics of intrinsic functional connectivity (functional brain connectivity when people are asked not to do anything) between subcortical and cortical regions in individuals with and without autism spectrum disorder aged 6-30 years. We focused on one important subcortical structure called striatum, which has roles in motor, cognitive, and affective processes. We found that cortico-striatal intrinsic functional connectivities showed opposite developmental trajectories in autism spectrum disorder and typically developing individuals, with connectivity increasing with age in autism spectrum disorder and decreasing or constant in typically developing individuals. We also found significant negative behavioral correlations between those atypical cortico-striatal intrinsic functional connectivities and autistic symptoms, such as social-communication deficits, and restricted/repetitive behaviors and interests. Taken together, this work highlights that the atypical development of cortico-subcortical functional connectivity might be largely involved in the neuropathological mechanisms of autism spectrum disorder.

Higher VO2max is associated with thicker cortex and lower grey matter blood flow in older adults

VO₂max (maximal oxygen consumption), a validated measure of aerobic fitness, has been associated with better cerebral artery compliance and measures of brain morphology, such as higher cortical thickness (CT) in frontal, temporal and cingular cortices, and larger grey matter volume (GMV) of the middle temporal gyrus, hippocampus, orbitofrontal cortex and cingulate cortex. Single sessions of physical exercise can promptly enhance cognitive performance and brain activity during executive tasks. However, the immediate effects of exercise on macro-scale properties of the brain’s grey matter remain unclear. We investigated the impact of one session of moderate-intensity physical exercise, compared with rest, on grey matter volume, cortical thickness, working memory performance, and task-related brain activity in older adults. Cross-sectional associations between brain measures and VO₂max were also tested. Exercise did not induce statistically significant changes in brain activity, grey matter volume, or cortical thickness. Cardiovascular fitness, measured by VO₂max, was associated with lower grey matter blood flow in the left hippocampus and thicker cortex in the left superior temporal gyrus. Cortical thickness was reduced at post-test independent of exercise/rest. Our findings support that (1) fitter individuals may need lower grey matter blood flow to meet metabolic oxygen demand, and (2) have thicker cortex.

Altered maturation and atypical cortical processing of spoken sentences in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with widespread receptive language impairments, yet the neural mechanisms underlying these deficits are poorly understood. Neuroimaging has shown that processing of socially-relevant sounds, including speech and non-speech, is atypical in ASD. However, it is unclear how the presence of lexical-semantic meaning affects speech processing in ASD. Here, we recorded magnetoencephalography data from individuals with ASD (N = 22, ages 7-17, 4 females) and typically developing (TD) peers (N = 30, ages 7-17, 5 females) during unattended listening to meaningful auditory speech sentences and meaningless jabberwocky sentences. After adjusting for age, ASD individuals showed stronger responses to meaningless jabberwocky sentences than to meaningful speech sentences in the same left temporal and parietal language regions where TD individuals exhibited stronger responses to meaningful speech. Maturational trajectories of meaningful speech responses were atypical in temporal, but not parietal, regions in ASD. Temporal responses were associated with ASD severity, while parietal responses were associated with aberrant involuntary attentional shifting in ASD. Our findings suggest a receptive speech processing dysfunction in ASD, wherein unattended meaningful speech elicits abnormal engagement of the language system, while unattended meaningless speech, filtered out in TD individuals, engages the language system through involuntary attention capture.

Atypical core-periphery brain dynamics in autism

The intrinsic function of the human brain is dynamic, giving rise to numerous behavioral subtypes that fluctuate distinctively at multiple timescales. One of the key dynamical processes that takes place in the brain is the interaction between core-periphery brain regions, which undergoes constant fluctuations associated with developmental time frames. Core-periphery dynamical changes associated with macroscale brain network dynamics span multiple timescales and may lead to atypical behavior and clinical symptoms. For example, recent evidence suggests that brain regions with shorter intrinsic timescales are located at the periphery of brain networks (e.g., sensorimotor hand, face areas) and are implicated in perception and movement. On the contrary, brain regions with longer timescales are core hub regions. These hubs are important for regulating interactions between the brain and the body during self-related cognition and emotion. In this review, we summarize a large body of converging evidence derived from time-resolved fMRI studies in autism to characterize atypical core-periphery brain dynamics and how they relate to core and contextual sensory and cognitive profiles.

Towards robust and replicable sex differences in the intrinsic brain function of autism

BACKGROUND

Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

METHODS

We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research.

RESULTS

Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples-EU-AIMS LEAP.

LIMITATIONS

Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

CONCLUSIONS

Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

Sparse Multiview Task-Centralized Ensemble Learning for ASD Diagnosis Based on Age- and Sex-Related Functional Connectivity Patterns

Autism spectrum disorder (ASD) is an age- and sex-related neurodevelopmental disorder that alters the brain's functional connectivity (FC). The changes caused by ASD are associated with different age- and sex-related patterns in neuroimaging data. However, most contemporary computer-assisted ASD diagnosis methods ignore the aforementioned age-/sex-related patterns. In this paper, we propose a novel sparse multiview task-centralized (Sparse-MVTC) ensemble classification method for image-based ASD diagnosis. Specifically, with the age and sex information of each subject, we formulate the classification as a multitask learning problem, where each task corresponds to learning upon a specific age/sex group. We also extract multiview features per subject to better reveal the FC changes. Then, in Sparse-MVTC learning, we select a certain central task and treat the rest as auxiliary tasks. By considering both task-task and view-view relationships between the central task and each auxiliary task, we can learn better upon the entire dataset. Finally, by selecting the central task, in turn, we are able to derive multiple classifiers for each task/group. An ensemble strategy is further adopted, such that the final diagnosis can be integrated for each subject. Our comprehensive experiments on the ABIDE database demonstrate that our proposed Sparse-MVTC ensemble learning can significantly outperform the state-of-the-art classification methods for ASD diagnosis.

The influence of age and ASD on verbal fluency networks

BACKGROUND

The integrity and connectivity of the frontal lobe, which subserves fluency, may be compromised by both ASD and aging. Alternate networks often integrate to help compensate for compromised functions during aging. We used network analyses to study how compensation may overcome age-related compromised in individuals with ASD.

METHOD

Participants consisted of middle-aged (40-60; n=24) or young (18-25; n=18) right-handed males who have a diagnosis of ASD, and age- and IQ-matched control participants (n=20, 14, respectively). All performed tests of language and executive functioning and a fluency functional MRI task. We first used group individual component analysis (ICA) for each of the 4 groups to determine whether different networks were engaged. An SPM analysis was used to compare activity detected in the network nodes from the ICA analyses.

RESULTS

The individuals with ASD performed more slowly on two cognitive tasks (Stroop word reading and Trailmaking Part A). The 4 groups engaged different networks during the fluency fMRI task despite equivalent performance. Comparisons of specific regions within these networks indicated younger individuals had greater engagement of the thalamus and supplementary speech area, while older adults engaged the superior temporal gyrus. Individuals with ASD did not disengage from the Default Mode Network during word generation.

CONCLUSION

Interactions between diagnosis and aging were not found in this study of young and middle-aged men, but evidence for differential engagement of compensatory networks was observed.

A Review of Functional and Structural Neurobiology of the Action Observation Network in Autism Spectrum Disorder and Developmental Coordination Disorder

Recent research has reported motor impairment similarities between children with developmental coordination disorder (DCD) and a subgroup of individuals with autism spectrum disorder (ASD). However, there is a debate as to whether DCD is a co-occurring diagnosis in individuals with ASD and motor impairments (ASDd), or if motor impairments in ASD are distinct from DCD. However, the etiology of motor impairments is not well understood in either disorder. Clarifying comorbidities in ASD is important to determine different etiopathological phenotyping clusters in ASD and to understand the variety of genetic and environmental factors that contribute to the disorder. Furthermore, this distinction has important therapeutic relevance. Here we explore the current neuroimaging findings in ASD and DCD and discusses possible neural mechanisms that underlie similarities and differences between the disorders.

He said, she said: Autism spectrum diagnosis and gender differentially affect relationships between executive functions and social communication

Autism spectrum disorder is characterized by difficulties with social communication, with a preponderance in males. Evidence supports a relationship between metacognitive executive functions (e.g. planning, working memory) and social communication in autism spectrum disorder, yet relationships with specific metacognitive executive functions and how gender alters the expression of these relationships require further study. We used multiple regression to examine relationships between informant-based measures of metacognitive executive function and social communication in intellectually able (IQ ⩾ 85) female ( n = 111; mean age = 10.2 ± 2.8; 31 autism spectrum disorder) and male youth ( n = 310; mean age = 10.5 ± 1.9; 146 autism spectrum disorder) with and without autism spectrum disorder from the Autism Brain Imaging Data Exchange-II database. Executive function–social communication relationships were different in females and males with autism spectrum disorder. Relationships between the entire metacognitive index and social communication were stronger in males with autism spectrum disorder than without; this pattern was also observed for metacognitive sub-indices ‘monitor’ and ‘working memory’. These patterns were not observed in females. Relationships between executive function and social communication appear different for female and male youth with an autism spectrum disorder diagnosis. To better understand the nature of metacognitive contributions to social communication in autism spectrum disorder, future work should investigate the co-development of monitoring, working memory and social communication, while taking gender into account.

Distinct Patterns of Atypical Functional Connectivity in Lower-Functioning Autism

BACKGROUND

Functional magnetic resonance imaging research on autism spectrum disorders (ASDs) has been largely limited to individuals with near-average intelligence. Although cognitive impairment is common in ASDs, functional network connectivity in this population remains poorly understood. Specifically, it remains unknown whether lower-functioning individuals exhibit exacerbated connectivity abnormalities similar to those previously detected in higher-functioning samples or specific divergent patterns of connectivity.

METHODS

Resting-state functional magnetic resonance imaging data from 88 children (44 ASD, 44 typically developing; average age: 11 years) were included. Based on IQ, individuals with ASDs were assigned to either a lower-functioning group (mean IQ = 77 ± 6) or a higher-functioning group (mean IQ = 123 ± 8). Two typically developing comparison groups were matched to these groups on head motion, handedness, and age. Seeds in the medial prefrontal cortex, posterior cingulate cortex, posterior superior temporal sulcus, insula, and amygdala were used to contrast whole-brain functional connectivity across groups.

RESULTS

Lower-functioning ASD participants (compared with higher-functioning ASD participants) showed significant underconnectivity within the default mode network and the ventral visual stream. Higher-functioning ASD participants (compared with matched typically developing participants) showed significantly decreased anticorrelations among default mode, salience, and task-positive regions. Effect sizes of detected differences were large (Cohen's d > 1.46).

CONCLUSIONS

Lower- and higher-functioning individuals with ASDs demonstrated distinct patterns of atypical connectivity. Findings suggest a gross pattern of predominantly reduced network integration in lower-functioning ASDs (affecting default mode and visual networks) and predominantly reduced network segregation in higher-functioning ASDs. Results indicate the need for stratification by general functional level in studies of functional connectivity in ASDs.

Hypoconnectivity of insular resting-state networks in adolescents with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication. The anterior insula (AI) participates in emotional salience detection; and the posterior insula (PI) participates in sensorimotor integration and response selection. Meta-analyses have noted insula-based aberrant connectivity within ASD. Given the observed social impairments in ASD and the role of the insula in social information processing (SIP), investigating functional organization of this structure in ASD is important. We investigated differences in resting-state functional connectivity (RSFC) using fMRI in male youths with (N=13; mean=14.6 years; range: 10.2-18.0 years) and without ASD (N=17; mean=14.5 years; range: 10.0-17.5 years). With seed-based FC measures, we compared RSFC in insular networks. Hypoconnectivity was observed in ASD (AI-superior frontal gyrus (SFG); AI-thalamus; PI-inferior parietal lobule (IPL); PI-fusiform gyrus (FG); PI-lentiform nucleus/putamen). Using the Social Communication Questionnaire (SCQ) to assess social functioning, regression analyses yielded negative correlations between SCQ scores and RSFC (AI-SFG; AI-thalamus; PI-FG; PI-IPL). Given the insula's connections to limbic regions, and its role in integrating external sensory stimuli with internal states, atypical activity in this structure may be associated with social deficits characterizing ASD. Our results suggest further investigation of the insula's role in SIP across a continuum of social abilities is needed.

Atypical longitudinal development of functional connectivity in adolescents with autism spectrum disorder

Autism spectrum disorder (ASD) is consistently associated with alterations in brain connectivity, but there are conflicting results as to where and when individuals with ASD display increased or reduced functional connectivity. Such inconsistent findings may be driven by atypical neurodevelopmental trajectories in ASD during adolescence, but no longitudinal studies to date have investigated this hypothesis. We thus examined the functional connectivity of three neurocognitive resting-state networks-the default mode network (DMN), salience network, and central executive network (CEN)-in a longitudinal sample of youth with ASD (n = 16) and without ASD (n = 22) studied during early/mid- and late adolescence. Functional connectivity between the CEN and the DMN displayed significantly altered developmental trajectories in ASD: typically developing (TD) controls-but not youth with ASD-exhibited an increase in negative functional connectivity between these two networks with age. This significant interaction was due to the ASD group displaying less negative functional connectivity than the TD group during late adolescence only, with no significant group differences in early/mid-adolescence. These preliminary findings suggest a localized age-dependency of functional connectivity alterations in ASD and underscore the importance of considering age when examining brain connectivity. Autism Research 2019, 12: 53-65. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Brain connectivity may develop differently during adolescence in youth with autism spectrum disorder (ASD). We looked at changes in brain connectivity over time within individuals and found that, for some brain regions, adolescents with ASD did not show the same changes in brain connectivity that typically developing adolescents did. This suggests it is important to consider age when studying brain connectivity in ASD.

Alterations in resting state connectivity along the autism trait continuum: a twin study

Autism spectrum disorder (ASD) has been found to be associated with alterations in resting state (RS) functional connectivity, including areas forming the default mode network (DMN) and salience network (SN). However, insufficient control for confounding genetic and environmental influences and other methodological issues limit the generalizability of previous findings. Moreover, it has been hypothesized that ASD might be marked by early hyper-connectivity followed by later hypo-connectivity. To date, only a few studies have explicitly tested age-related influences on RS connectivity alterations in ASD. Using a within-twin pair design (N=150 twins; 8-23 years), we examined altered RS connectivity between core regions of the DMN and SN in relation to autistic trait severity and age in a sample of monozygotic (MZ) and dizygotic (DZ) twins showing typical development, ASD or other neurodevelopmental conditions. Connectivity between core regions of the SN was stronger in twins with higher autistic traits compared to their co-twins. This effect was significant both in the total sample and in MZ twins alone, highlighting the effect of non-shared environmental factors on the link between SN-connectivity and autistic traits. While this link was strongest in children, we did not identify differences between age groups for the SN. In contrast, connectivity between core hubs of the DMN was negatively correlated with autistic traits in adolescents and showed a similar trend in adults but not in children. The results support hypotheses of age-dependent altered RS connectivity in ASD, making altered SN and DMN connectivity promising candidate biomarkers for ASD.

Maturational trajectories of local and long-range functional connectivity in autism during face processing

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures.

Early human brain development: Starring the subplate

This review summarizes early human brain development on the basis of neuroanatomical data and functional connectomics. It indicates that the most significant changes in the brain occur during the second half of gestation and the first three months post-term, in particular in the cortical subplate and cerebellum. As the transient subplate pairs a high rate of intricate developmental changes and interactions with clear functional activity, two phases of development are distinguished: a) the transient cortical subplate phase, ending at 3 months post-term when the permanent circuitries in the primary motor, somatosensory and visual cortices have replaced the subplate; and subsequently, b) the phase in which the permanent circuitries dominate. In the association areas the subplate dissolves in the remainder of the first postnatal year. During both phases developmental changes are paralleled by continuous reconfigurations in network activity. The reviewed literature also suggests that disruption of subplate development may play a pivotal role in developmental disorders, such as cerebral palsy, autism spectrum disorders, attention deficit hyperactivity disorder and schizophrenia.

A theoretical rut: revisiting and critically evaluating the generalized under/over-connectivity hypothesis of autism

In 2004, two papers proposed that pervasive functional under-connectivity (Just et al., ) or a trade-off between excessive local connectivity at the cost of distal under-connectivity (Belmonte et al., ) characterizes atypical brain organization in autism. Here, we take stock of the most recent and rigorous functional and structural connectivity findings with a careful eye toward evaluating the extent to which they support these original hypotheses. Indeed, the empirical data do not support them. From rsfMRI studies in adolescents and adults, there is an emerging consensus regarding long-range functional connections indicating cortico-cortical under-connectivity, specifically involving the temporal lobes, combined with subcortical-cortical over-connectivity. In contrast, there is little to no consensus regarding local functional connectivity or findings from task-based functional connectivity studies. The structural connectivity data suggest that white matter tracts are pervasively weak, particularly in the temporal lobe. Together, these findings are revealing how deeply complex the story is regarding atypical neural network organization in autism. In other words, distance and strength of connectivity as individual factors or as interacting factors do not consistently explain the patterns of atypical neural connectivity in autism. Therefore, we make several methodological recommendations and highlight developmental considerations that will help researchers in the field cultivate new hypotheses about the nature and mechanisms of potentially aberrant functional and structural connectivity in autism.

Aberrant development of the asymmetry between hemispheric brain white matter networks in autism spectrum disorder

Atypical brain asymmetry/lateralization has long been hypothesized for autism spectrum disorder (ASD), and this model has been repeatedly supported by various neuroimaging studies. Recently, hemispheric network topologies have been found to be asymmetric, thereby providing a new avenue for investigating brain asymmetries under various conditions. To date, however, how network topological asymmetries are altered in ASD remains largely unexplored. To clarify this, the present study included ASD individuals from the newly released Autism Brain Imaging Data Exchange II database (58 right-handed male ASD individuals aged 5 to 26 years and 70 age- and IQ-matched typically developing (TD) individuals). Diffusion and structural magnetic resonance imaging were used to construct hemispheric white matter networks, and graph-theory approaches were applied to quantify topological efficiencies for hemispheric networks. Statistical analyses revealed a decreased rightward asymmetry of network efficiencies with increasing age in the TD group, but not in the ASD group. More specifically, the TD group did not exhibit an age-related increase in network efficiency in the right hemisphere, but the ASD group did. For the left hemisphere, no difference between the groups was observed for the developmental trajectory of network efficiencies. Intriguingly, within the ASD group, more severe restricted and repetitive behavior in ASD was found to be correlated with less rightward asymmetry of network local efficiency. These findings provide suggestive evidence of atypical network topological asymmetries and offer important insights into the abnormal development of ASD brains.

Executive function and functional and structural brain differences in middle-age adults with autism spectrum disorder

There is a rapidly growing group of aging adults with autism spectrum disorder (ASD) who may have unique needs, yet cognitive and brain function in older adults with ASD is understudied. We combined functional and structural neuroimaging and neuropsychological tests to examine differences between middle-aged men with ASD and matched neurotypical (NT) men. Participants (ASD, n = 16; NT, n = 17) aged 40-64 years were well-matched according to age, IQ (range: 83-131), and education (range: 9-20 years). Middle-age adults with ASD made more errors on an executive function task (Wisconsin Card Sorting Test) but performed similarly to NT adults on tests of delayed verbal memory (Rey Auditory Verbal Learning Test) and local visual search (Embedded Figures Task). Independent component analysis of a functional MRI working memory task (n-back) completed by most participants (ASD = 14, NT = 17) showed decreased engagement of a cortico-striatal-thalamic-cortical neural network in older adults with ASD. Structurally, older adults with ASD had reduced bilateral hippocampal volumes, as measured by FreeSurfer. Findings expand our understanding of ASD as a lifelong condition with persistent cognitive and functional and structural brain differences evident at middle-age. Autism Res 2017, 10: 1945-1959. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

We compared cognitive abilities and brain measures between 16 middle-age men with high-functioning autism spectrum disorder (ASD) and 17 typical middle-age men to better understand how aging affects an older group of adults with ASD. Men with ASD made more errors on a test involving flexible thinking, had less activity in a flexible thinking brain network, and had smaller volume of a brain structure related to memory than typical men. We will follow these older adults over time to determine if aging changes are greater for individuals with ASD.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided.

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.

Possible sexually dimorphic role of miRNA and other sncRNA in ASD brain

Background

Autism spectrum disorder (ASD) is sexually dimorphic in brain structure, genetics, and behaviors. In studies of brain tissue, the age of the population is clearly a factor in interpreting study outcome, yet sex is rarely considered. To begin to address this issue, we extend our previously published microarray analyses to examine expression of small noncoding RNAs (sncRNAs), including microRNAs (miRNAs), in ASD and in the control temporal cortex in males and females. Predicted miRNA targets were identified as well as the pathways they overpopulate.

Findings

After considering age, sexual dimorphism in ASD sncRNA expression persists in the temporal cortex and in the patterning that distinguishes regions. Among the sexually dimorphic miRNAs are miR-219 and miR-338, which promote oligodendrocyte differentiation, miR-125, implicated in neuronal differentiation, and miR-488, implicated in anxiety. Putative miRNA targets are significantly over-represented in immune and nervous system pathways in both sexes, consistent with previous mRNA studies. Even for common pathways, the specific target mRNAs are often sexually dimorphic. For example, both male and female target genes significantly populate the Axonal Guidance Signaling pathway, yet less than a third of the targets are common to both sexes.

Conclusions

Our findings of sexual dimorphism in sncRNA levels underscore the importance of considering sex, in addition to age, when interpreting molecular findings on ASD brain.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0117-0) contains supplementary material, which is available to authorized users.

Atypical developmental trajectory of local spontaneous brain activity in autism spectrum disorder

Autism spectrum disorder (ASD) is marked by atypical trajectory of brain maturation, yet the developmental abnormalities in brain function remain unclear. The current study examined the effect of age on amplitude of low-frequency fluctuations (ALFF) in ASD and typical controls (TC) using a cross-sectional design. We classified all the participants into three age cohorts: child (<11 years, 18ASD/20TC), adolescent (11-18 years, 28ASD/26TC) and adult (≥18 years, 18ASD/18TC). Two-way analysis of variance (ANOVA) was performed to ascertain main effects and interaction effects on whole brain ALFF maps. Results exhibited significant main effect of diagnosis in ASD with decreased ALFF in the right precuneus and left middle occipital gyrus during all developmental stages. Significant diagnosis-by-age interaction was observed in the medial prefrontal cortex (mPFC) with ALFF lowered in autistic children but highered in autistic adolescents and adults. Specifically, remarkable quadratic change of ALFF with increasing age in mPFC presented in TC group was absent in ASD. Additionally, abnormal ALFF values in diagnosis-related brain regions predicted the social deficits in ASD. Our findings indicated aberrant developmental patterns of spontaneous brain activity associated with social deficits in ASD and highlight the crucial role of the default mode network in the development of disease.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives.

Functional connectivity differences in autism during face and car recognition: underconnectivity and atypical age-related changes

Face recognition abilities improve between adolescence and adulthood over typical development (TD), but plateau in autism, leading to increasing face recognition deficits in autism later in life. Developmental differences between autism and TD may reflect changes between neural systems involved in the development of face encoding and recognition. Here, we focused on whole-brain connectivity with the fusiform face area (FFA), a well-established face-preferential brain region. Older children, adolescents, and adults with and without autism completed the Cambridge Face Memory Test, and a matched car memory test, during fMRI scanning. We then examined task-based functional connectivity between the FFA and the rest of the brain, comparing autism and TD groups during encoding and recognition of face and car stimuli. The autism group exhibited underconnectivity, relative to the TD group, between the FFA and frontal and primary visual cortices, independent of age. Underconnectivity with the medial and rostral lateral prefrontal cortex was face-specific during encoding and recognition, respectively. Conversely, underconnectivity with the L orbitofrontal cortex was evident for both face and car encoding. Atypical age-related changes in connectivity emerged between the FFA and the R temporoparietal junction, and R dorsal striatum for face stimuli only. Similar differences in age-related changes in autism emerged for FFA connectivity with the amygdala across both face and car recognition. Thus, underconnectivity and atypical development of functional connectivity may lead to a less optimal face-processing network in the context of increasing general and social cognitive deficits in autism.

Patterns of Atypical Functional Connectivity and Behavioral Links in Autism Differ Between Default, Salience, and Executive Networks

Autism spectrum disorder (ASD) is characterized by atypical brain network organization, but findings have been inconsistent. While methodological and maturational factors have been considered, the network specificity of connectivity abnormalities remains incompletely understood. We investigated intrinsic functional connectivity (iFC) for four "core" functional networks-default-mode (DMN), salience (SN), and left (lECN) and right executive control (rECN). Resting-state functional MRI data from 75 children and adolescents (37 ASD, 38 typically developing [TD]) were included. Functional connectivity within and between networks was analyzed for regions of interest (ROIs) and whole brain, compared between groups, and correlated with behavioral scores. ROI analyses showed overconnectivity (ASD > TD), especially between DMN and ECN. Whole-brain results were mixed. While predominant overconnectivity was found for DMN (posterior cingulate seed) and rECN (right inferior parietal seed), predominant underconnectivity was found for SN (right anterior insula seed) and lECN (left inferior parietal seed). In the ASD group, reduced SN integrity was associated with sensory and sociocommunicative symptoms. In conclusion, atypical connectivity in ASD is network-specific, ranging from extensive overconnectivity (DMN, rECN) to extensive underconnectivity (SN, lECN). Links between iFC and behavior differed between groups. Core symptomatology in the ASD group was predominantly related to connectivity within the salience network.

Frequency of Maternal Touch Predicts Resting Activity and Connectivity of the Developing Social Brain

Previous behavioral research points to a positive relationship between maternal touch and early social development. Here, we explored the brain correlates of this relationship. The frequency of maternal touch was recorded for 43 five-year-old children during a 10 min standardized play session. Additionally, all children completed a resting-state functional magnetic resonance imaging session. Investigating the default mode network revealed a positive relation between the frequency of maternal touch and activity in the right posterior superior temporal sulcus (pSTS) extending into the temporo-parietal junction. Using this effect as a seed in a functional connectivity analysis identified a network including extended bilateral regions along the temporal lobe, bilateral frontal cortex, and left insula. Compared with children with low maternal touch, children with high maternal touch showed additional connectivity with the right dorso-medial prefrontal cortex. Together these results support the notion that childhood tactile experiences shape the developing "social brain" with a particular emphasis on a network involved in mentalizing.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect 'neural masculinization', as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD.

Development of a selective left-hemispheric fronto-temporal network for processing syntactic complexity in language comprehension

The development of language comprehension abilities in childhood is closely related to the maturation of the brain, especially the ability to process syntactically complex sentences. Recent studies proposed that the fronto-temporal connection within left perisylvian regions, supporting the processing of syntactically complex sentences, is still immature at preschool age. In the current study, resting state functional magnetic resonance imaging data were acquired from typically developing 5-year-old children and adults to shed further light on the brain functional development. Children additionally performed a behavioral syntactic comprehension test outside the scanner. The amplitude of low-frequency fluctuations was analyzed in order to identify the functional correlation networks of language-relevant brain regions. Results showed an intrahemispheric correlation between left inferior frontal gyrus (IFG) and left posterior superior temporal sulcus (pSTS) in adults, whereas an interhemispheric correlation between left IFG and its right-hemispheric homolog was predominant in children. Correlation analysis between resting-state functional connectivity and sentence processing performance in 5-year-olds revealed that local connectivity within the left IFG is associated with competence of processing syntactically simple canonical sentences, while long-range connectivity between IFG and pSTS in left hemisphere is associated with competence of processing syntactically relatively more complex non-canonical sentences. The present developmental data suggest that a selective left fronto-temporal connectivity network for processing complex syntax is already in functional connection at the age of 5 years when measured in a non-task situation. The correlational findings provide new insight into the relationship between intrinsic functional connectivity and syntactic language abilities in preschool children.

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resting state ALFF correlated in adults between left IFG and left pSTS.

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resting state ALFF correlated in children between left IFG and right homolog area.

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intrahemispheric connectivity co-varies with syntactic processing skills in children.

Inferior frontal oscillations reveal visuo-motor matching for actions and speech: evidence from human intracranial recordings

The neural correspondence between the systems responsible for the execution and recognition of actions has been suggested both in humans and non-human primates. Apart from being a key region of this visuo-motor observation-execution matching (OEM) system, the human inferior frontal gyrus (IFG) is also important for speech production. The functional overlap of visuo-motor OEM and speech, together with the phylogenetic history of the IFG as a motor area, has led to the idea that speech function has evolved from pre-existing motor systems and to the hypothesis that an OEM system may exist also for speech. However, visuo-motor OEM and speech OEM have never been compared directly. We used electrocorticography to analyze oscillations recorded from intracranial electrodes in human fronto-parieto-temporal cortex during visuo-motor (executing or visually observing an action) and speech OEM tasks (verbally describing an action using the first or third person pronoun). The results show that neural activity related to visuo-motor OEM is widespread in the frontal, parietal, and temporal regions. Speech OEM also elicited widespread responses partly overlapping with visuo-motor OEM sites (bilaterally), including frontal, parietal, and temporal regions. Interestingly a more focal region, the inferior frontal gyrus (bilaterally), showed both visuo-motor OEM and speech OEM properties independent of orolingual speech-unrelated movements. Building on the methodological advantages in human invasive electrocorticography, the present findings provide highly precise spatial and temporal information to support the existence of a modality-independent action representation system in the human brain that is shared between systems for performing, interpreting and describing actions.