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Autism spectrum disorder (ASD) is a neurodevelopmental disability with global implication. Altered brain connectivity in the language network has frequently been reported in ASD patients using task-based functional magnetic resonance imaging (fMRI) compared to typically developing (TD) participants. Most of these studies have focused on a specific...
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Purpose:
We investigated the hypothesis that increasing fMRI temporal resolution using a multiband (MB) gradient echo-echo planar imaging (GRE-EPI) pulse sequence provides fMRI language maps of higher statistical quality than those acquired with a traditional GRE-EPI sequence.
Methods:
This prospective study enrolled 29 consecutive patients rece...
Citations
... If we start to explore the research done in this field, we can aim to not only get a greater understanding of the role of attachment in EMS development, and its association with mental health challenges, but create greater levels of awareness around factors for clinicians to be mindful of when using Schema Therapy interventions with this population. Lee et al. (2017) suggest Autistic children have differences regarding social processing and communication, potentially hindering the formation of secure attachments if parents are not understanding and receptive to meeting their specific needs in an attuned way. The development and experience of attachment in individuals that are Autistic and/or ADHD reveal the intricate and multi-faceted nature of meeting an individual's core needs. ...
Autistic/ADHD individuals are increasingly recognised as a valid minority group, with consistent research demonstrating a higher prevalence of co-occurring mental health conditions such as PTSD, anxiety, depression, substance use, and eating disorders among other mental health challenges. Due to this, there is increasing focus on the adaptations required for Autistic and ADHD individuals of current therapeutic approaches such as Schema Therapy. Particular emphasis when creating these adaptations needs to include looking at the developmental experiences, social influences, and continued adversity faced by Autistic and ADHD individuals across the lifespan, and how the narrative around Autism and ADHD within psychotherapy in general needs to change. This paper critically examines the role of attachment, unmet needs, and adverse childhood experiences in Autistic and ADHD individuals and the subsequent impact on schema development and maintenance and mental health. This will include an overview of the current literature in this area, reconsideration of understandings of Autism and ADHD, particular therapeutic considerations and adjustments and importantly discussion around the wider societal changes that need to occur to prevent schema development and reinforcement across the lifespan.
... Autism is a neurodevelopmental condition that impacts a person's cognitive, language, sensory perceptions and social abilities (Lee et al., 2017). Worldwide, approximately 1 in 59 children is autistic (Baio et al., 2018). ...
The quality of life of autistic children and their parents is impacted by the stress they experience, their coping strategies
and the availability of professional health, social and educational support services. Recent changes in the structural
organisation of child disability professional supports in Ireland mean that in-depth knowledge about current experiences
of parenting autistic children is necessary. This qualitative study explored parents’ perceptions and experiences regarding
their challenges, stress levels, coping strategies and professional support services. Semi-structured in-depth interviews
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the system to access services is experienced as difficult and parents consider it is operating inadequately. This reveals
a pressing need to improve systems that provide professional support services to autistic children and their families.
... Functional magnetic resonance imaging (fMRI) has been widely used in clinical studies, as a non-invasive and convenient method, to investigate the neural mechanisms underlying many common mental disorders (e.g., major depressive disorder and schizophrenia) [5][6][7]. Past fMRI studies have demonstrated that ASD is associated with aberrant brain functions such as significantly decreased/increased functional connectivity (FC) within the visual, frontoparietal (cognition), and language-related subnetworks in the brain [8][9][10][11]. These studies have significantly improved our understanding of the complex pathobiology of ASD. ...
Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders whose pathobiology remains elusive. This study aimed to investigate the possible neural mechanisms underlying ASD using a dynamic brain network model and a relatively large-sample, multi-site dataset. Resting-state functional magnetic resonance imaging data were acquired from 208 ASD patients and 227 typical development (TD) controls, who were drawn from the multi-site Autism Brain Imaging Data Exchange (ABIDE) database. Brain network flexibilities were estimated and compared between the ASD and TD groups at both global and local levels, after adjusting for sex, age, head motion, and site effects. The results revealed significantly increased brain network flexibilities (indicating a decreased stability) at the global level, as well as at the local level within the default mode and sensorimotor areas in ASD patients than TD participants. Additionally, significant ASD-related decreases in flexibilities were also observed in several occipital regions at the nodal level. Most of these changes were significantly correlated with the Autism Diagnostic Observation Schedule (ADOS) total score in the entire sample. These results suggested that ASD is characterized by significant changes in temporal stabilities of the functional brain network, which can further strengthen our understanding of the pathobiology of ASD.
... Among them, language development impairment caused by autism is one of the common types (Taghva and Mahabadi, 2013). Compared to typically developing children, children with autism have differences in brain connectivity, which may lead to language and communication difficulties (Lee et al., 2017). In addition, there is only a single channel to receive external information, which makes it difficult for autistic children to obtain the same learning and communication opportunities as typically developing child. ...
Background
Studies have shown that music therapy can be used as a therapeutic aid for clinical disorders. To evaluate the effects of music therapy (MT) on language communication and social skills in children with autism spectrum disorder (ASD), a meta-analysis was performed on eligible studies in this field.
Methods
A systematic search was conducted in eight databases: PubMed, Embase, Web of Science, Cochrane Library databases, the China National Knowledge Infrastructure (CNKI), Wanfang Data, the Chinese Biomedical Literature (CBM) Database, and the VIP Chinese Science and Technology Periodicals Database. The standard mean difference (SMD) values were used to evaluate outcomes, and the pooled proportions and SMD with their 95% confidence intervals (CIs) were also calculated.
Results
Eighteen randomized controlled trial (RCT) studies were included, with a total of 1,457 children with ASD. This meta-analysis revealed that music therapy improved their language communication [SMD = −1.20; 95%CI –1.45, −0.94; χ² (17) = 84.17, I² = 80%, p < 0.001] and social skills [SMD = −1. 13; 95%CI –1.49, −0.78; χ² (17) = 162.53, I² = 90%, p < 0.001]. In addition, behavior [SMD = −1.92; 94%CI –2.56, −1.28; χ² (13) = 235.08, I² = 95%, p < 0.001], sensory perception [SMD = −1.62; 95%CI –2.17, −1.08; χ² (16) = 303.80, I² = 95%, p < 0.001], self-help [SMD = −2. 14; 95%CI –3.17, −1.10; χ² (6) = 173.07, I² = 97%, p < 0.001] were all improved.
Conclusion
Music therapy has a positive effect on the improvement of symptoms in children with ASD.
Systematic review registration
https://www.crd.york.ac.uk/PROSPERO/.
... Autism spectrum conditions (ASC) 2 , also known as Autism spectrum disorders (ASD), are a series of heterogeneous neurodevelopmental conditions [1][2][3], and severely impact people's social communication and interaction [4][5][6], contributing to autism-specific language profiles [7] and language regression [8]. Recent neuroimaging studies attribute ASC's language deficiency to the damage to the brain language network which supports the idea that the communication dysfunction resulting from deviant neural activity of the language network will affect individuals with ASC's language ability greatly [5,[9][10][11]. Hence, detecting atypical brain activity from the perspective of language is of great importance to the neural and pathophysiological studies of ASC. As one of the classical and essential language regions [12][13][14], Wernicke's area has been proven to be responsible for language comprehension [15] and involved in many language-related tasks, such as interactive verbal communication [16]. ...
... Collecting over 2000 participants from more than 30 sites, a well-formed public dataset named Autism Brain Image Data Exchange (ABIDE) has been established to detect neurophysiological patterns of ASC [9,35,36] and has the potential to demonstrate novel discovery and reproductive results [37,38]. Furthermore, calculations of data from the multicenter call for large-scale integration methods, such as mega-analysis, to reduce the heterogeneity that results from the scanning parameters or instruments utilized in various cohorts [39]. ...
Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01–0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01–0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.
... It is also important to note a degree of overlap between the structural and functional findings of the current study: indeed, the left superior temporal gyrus (a crucial structure implicated in language and social cognition frequently impaired in ASD subjects [12,13,47]) is both increased in thickness and altered as far as FC is concerned in ASD individuals compared with control participants. This result support the notion that brain changes in ASD, even if subtle and diffuse, converge into specific, close localized areas of structural and functional alterations [58,63,69]. ...
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.
... We speculate that the relationship between Wernicke's area and autism is highly relevant to the temporal lobe [54]. The accuracy of the parietal lobe, where Broca's area [55] is located, is higher than that of the occipital lobe, which is responsible for visual perception. In particular, experiments that use only temporal lobe data have significantly higher accuracy compared to those that use only left-brain or right-brain data. ...
Currently, resting-state electroencephalography (rs-EEG) has become an effective and low-cost evaluation way to identify autism spectrum disorders (ASD) in children. However, it is of great challenge to extract useful features from raw rs-EEG data to improve diagnosis performance. Traditional methods mainly rely on the design of manual feature extractors and classifiers, which are separately performed and cannot be optimized simultaneously. To this end, this paper proposes a new end-to-end diagnostic method based on a recently emerged graph convolutional neural network for the diagnosis of ASD in children. Inspired by related neuroscience findings on the abnormal brain functional connectivity and hemispheric asymmetry characteristics observed in autism patients, we design a new Regional-asymmetric Adaptive Graph Convolutional Neural Network (RAGNN). It utilizes a hierarchical feature extraction and fusion process to learn separable spatiotemporal EEG features from different brain regions, two hemispheres, and a global brain. In the temporal feature extraction section, we utilize a convolutional layer that spans from the brain area to the hemisphere. This allows for effectively capturing temporal features both within and between brain areas. To better capture spatial characteristics of multi-channel EEG signals, we employ adaptive graph convolutional learning to capture non-Euclidean features within the brain’s hemispheres. Additionally, an attention layer is introduced to highlight different contributions of the left and right hemispheres, and the fused features are used for classification. We conducted a subject-independent cross-validation experiment on rs-EEG data from 45 children with ASD and 45 typically developing (TD) children. Experimental results have shown that our proposed RAGNN model outperformed several existing deep learning-based methods (ShaollowNet, EEGNet, TSception, ST-GCN, and CGRU-MDGN).
... The limited number of experiments might have led us to miss small or medium effect size differences between the autism and non-autism groups. The limited number of articles included in our study might be because conducting fMRI studies in awake children/adolescents with autism has been challenging (Jassim et al., 2021;Lee et al., 2017) given the susceptibility of this technique to movement-related artifacts (Patriquin et al., 2013;Tyszka et al., 2013). Due to the potential sensory discomfort fMRI exams might induce (e.g., exposure to acoustic noise; McJury & Shellock, 2000), some participants may have difficulty remaining still in the scanner, leading to the removal of their data during subsequent analysis. ...
Difficulties in auditory language comprehension are common among children and adolescents with autism spectrum disorder. However, findings regarding the underlying neural mechanisms remain mixed, and few studies have systematically explored the overall patterns of these findings. Therefore, this study aims to systematically review and meta‐analyze the functional magnetic resonance imaging evidence of neural activation patterns while engaging in auditory language comprehension tasks among children and adolescents with autism. Using activation likelihood estimation, we conducted a series of meta‐analyses to investigate neural activation patterns during auditory language comprehension tasks compared to baseline conditions in autism and non‐autism groups and compared the activation patterns of the groups, respectively. Eight studies were included in the within‐group analyses, and seven were included in the between‐group analysis. The within‐group analyses revealed that the bilateral superior temporal gyrus was activated during auditory language comprehension tasks in both groups, whereas the left superior frontal gyrus and dorsal medial prefrontal cortex were activated only in the non‐autism group. Furthermore, the between‐group analysis showed that children and adolescents with autism, compared to those without autism, showed reduced activation in the right superior temporal gyrus, left middle temporal gyrus, and insula, whereas the autism group did not show increased activation in any of the regions relative to the non‐autism group. Overall, these findings contribute to our understanding of the potential neural mechanisms underlying difficulties in auditory language comprehension in children and adolescents with autism and provide practical implications for early screening and language‐related interventions for children and adolescents with autism.
... Then, the dorsal pathway plays a dominant role in language production, including the inferior frontal gyri (opercular and triangular) and supplementary motor area. [5][6][7][8] A systematic review examined structural magnetic resonance imaging (MRI) measurements, including brain volumetry, and associations with language outcomes in children aged 6-19 born very preterm, defined as less than 32 weeks GA. 2 The authors concluded that the results of the studies were inconsistent, mainly because they used diverse methods and studied different GAs and morbidities. 2 Other studies have shown that decreased total gray matter (GM), total white matter (WM), and intracranial volume (ICV) were associated with language outcomes in children born very preterm. ...
... Language-related regions were pre-defined and selected based on previous studies. [5][6][7] We included the canonical language regions described as Broca's area, namely the triangular and opercular part of the inferior frontal gyri, and Wernicke's area, within the superior temporal gyri. 4 We also included the middle and inferior temporal gyri, the inferior parietal gyri, namely angular and supramarginal gyri, Heschl's gyrus, and the supplementary motor area. ...
Background
Children born preterm are more prone to have language difficulties. Few studies focus on children born extremely preterm (EPT) and the structural differences in language-related regions between these children and children born at term.
Methods
Our study used T1-weighted magnetic resonance imaging (MRI) scans to calculate the brain volumetry, brain asymmetry, and cortical thickness of language-related regions in 50 children born EPT and 37 term-born controls at 10 years of age. The language abilities of 41 of the children born EPT and 29 term-born controls were then assessed at 12 years of age, using the Wechsler Intelligence Scale for Children, Fifth Edition and the Clinical Evaluations of Language Fundamentals, Fourth Edition. The differences between MRI parameters and their associations with language outcomes were compared in the two groups.
Results
Brain volume and cortical thickness of language-related regions were reduced in children born EPT, but volumetric asymmetry was not different between children born EPT and at term. In children born EPT the brain volume was related to language outcomes, prior to adjustments for full-scale IQ.
Conclusions
These findings expand our understanding of the structural correlates underlying impaired language performance in children born with EPT.
Impact
The article expands understanding of the structure-function relationship between magnetic resonance imaging measurements of language-related regions and language outcomes for children born extremely preterm beyond infancy.
Most literature to date has focused on very preterm children, but the focus in this paper is on extreme prematurity and language outcomes.
While the brain volume and cortical thickness of language-related regions were reduced in children born EPT only the volume, prior to adjustment for full-scale IQ, was associated with language outcomes.
We found no differences in volumetric asymmetry between children born EPT and at term.
... The development and existence of such dynamic adaptation and reorganization of neural connectivity underscores the importance of studying neurodevelopmental disorders with different age groups and properly accounting for age and brain maturity during the study. For example, adolescents and adults with ASD may demonstrate different levels of functional connectivity alterations during a language task compared with controls of the same age group [94]. This could be because the compensatory networks are at different stages of development, which would also explain how ASD individuals of different age groups may have different levels of adaptation to their social environments. ...
Autism Spectrum Disorder (ASD) is characterized by both atypical functional brain connectivity and cognitive challenges across multiple cognitive domains. The relationship between task-dependent brain connectivity and cognitive abilities, however, remains poorly understood. In this study, children with ASD and their typically developing (TD) peers engaged in semantic and pragmatic language tasks while their task-dependent brain connectivity was mapped and compared. A multivariate statistical approach revealed associations between connectivity and psychometric assessments of relevant cognitive abilities. While both groups exhibited brain–behavior correlations, the nature of these associations diverged, particularly in the directionality of overall correlations across various psychometric categories. Specifically, greater disparities in functional connectivity between the groups were linked to larger differences in Autism Questionnaire, BRIEF, MSCS, and SRS-2 scores but smaller differences in WASI, pragmatic language, and Theory of Mind scores. Our findings suggest that children with ASD utilize distinct neural communication patterns for language processing. Although networks recruited by children with ASD may appear less efficient than those typically engaged, they could serve as compensatory mechanisms for potential disruptions in conventional brain networks.
