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Decreased Functional and Structural Connectivity Is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder after Mini-Basketball Training Program

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Title: Decreased Functional and Structural Connectivity Is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder after Mini-Basketball Training Program
Language: English
Authors: Dongyue Zhou, Zhimei Liu, Guanyu Gong, Yunge Zhang, Lin Lin, Kelong Cai, Huashuai Xu, Fengyu Cong, Huanjie Li (ORCID 0000-0002-1056-1579), Aiguo Chen
Source: Journal of Autism and Developmental Disorders. 2024 54(12):4515-4528.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 14
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Exercise, Intervention, Symptoms (Individual Disorders), Autism Spectrum Disorders, Team Sports, Children, Brain Hemisphere Functions, Program Effectiveness, Preadolescents
DOI: 10.1007/s10803-023-06160-x
ISSN: 0162-3257
1573-3432
Abstract: Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention. We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3-12 years (experiment group: n = 32, control group: n = 26). ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical--cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD. Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1447762
Database: ERIC
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  Value: <anid>AN0180804672;aut01dec.24;2024Nov13.05:17;v2.2.500</anid> <title id="AN0180804672-1">Decreased Functional and Structural Connectivity is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder After Mini-basketball Training Program </title> <p>Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention. We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3–12 years (experiment group: n = 32, control group: n = 26). ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical–cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD. Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.</p> <p>Keywords: Autism spectrum disorder (ASD); Exercise intervention; Functional connectivity; Morphological brain network; K-means</p> <p>Dongyue Zhou and Zhimei Liu have contributed equally to this work.</p> <hd id="AN0180804672-2">Introduction</hd> <p>Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized with social interaction deficits as well as repetitive and stereotyped behavior (American Psychiatric Association, [<reflink idref="bib2" id="ref1">2</reflink>]). Despite of the high prevalence, the exact etiology of ASD is still unclear. One primary therapeutic approach is behavior intervention, including behavior management therapy, social skill training, and cognitive behavior therapy, which have been proven effective to ameliorate ASD-related symptoms in several studies (Hynes & Block, [<reflink idref="bib22" id="ref2">22</reflink>]).</p> <p>Physical exercise, as a complementary approach, could be added to the conventional ASD treatments and various studies have suggested that the combination therapy may achieve maximal therapeutic effect (Hynes & Block, [<reflink idref="bib22" id="ref3">22</reflink>]). For example, physical exercises such as swimming, cycling and jogging, have been shown to be helpful for improving social skills and social communication (Howells et al., [<reflink idref="bib20" id="ref4">20</reflink>]; Healy et al., [<reflink idref="bib18" id="ref5">18</reflink>]; Pan, [<reflink idref="bib33" id="ref6">33</reflink>]; Cai et al., [<reflink idref="bib6" id="ref7">6</reflink>]). However, certain types of physical exercise such as jogging and swimming tend to be individual-based and rarely involve peer-to-peer interactions.</p> <p>In contrast, team-based activities like basketball training, could provide more beneficial effects due to team participation (Howells et al., [<reflink idref="bib21" id="ref8">21</reflink>]). Besides, although theoretically physical exercise should benefit ASD in all age groups, early intervention in younger children, whose nervous systems remain under development (myelination and synapse formation) could crucially result in more obvious symptomatic improvement (Khundrakpam et al., [<reflink idref="bib23" id="ref9">23</reflink>]). Hence, the present study was designed to carry out a 12-week mini-basketball training program (MBTP) in ASD children aging 3–12 years old.</p> <p>Most previous studies revealed the effect of physical exercise based on behavior analyses (e.g. improvement in social deficits and execution function) (Healy et al., [<reflink idref="bib18" id="ref10">18</reflink>]; Hynes & Block, [<reflink idref="bib22" id="ref11">22</reflink>]), and only a few provided further explanation about underlying neurological mechanisms. For example, one study revealed that significant change (higher fractional anisotropy (FA) in the body of corpus callosum identified in children with ASD after MBTP, suggesting increased white matter integrity and that change was associated with improved social communication (Cai et al., [<reflink idref="bib6" id="ref12">6</reflink>]). Another study showed that increased effective connectivity in the medial prefrontal cortex occurred after MBTP, along with improved social responsiveness scale-2 score (Yu et al., [<reflink idref="bib48" id="ref13">48</reflink>]).</p> <p>Yet, these previous studies are limited, focusing only on the single brain region and using single-modality analysis. Increasing evidences have suggested that the development of ASD symptom involves atypical changes in multiple brain regions with structural and functional networks rather than a single brain region (Cardon et al., [<reflink idref="bib7" id="ref14">7</reflink>]; Green et al., [<reflink idref="bib15" id="ref15">15</reflink>]). For example, hyperconnectivity between salience network and motor network was found in ASD, and the salience network was reported to be related to restricted and repetitive behaviors (Uddin et al., [<reflink idref="bib39" id="ref16">39</reflink>]). Several other studies reported atypical functional connectivity between sensorimotor networks and various other networks in children with ASD and their associations with social impairment symptoms in ASD (Supekar et al., [<reflink idref="bib36" id="ref17">36</reflink>]; Wang et al., [<reflink idref="bib45" id="ref18">45</reflink>]). An abnormal structural covariance network among subcortical regions in ASD was also reported, showing the crucial role of subcortical regions in ASD social cognition (Duan et al., [<reflink idref="bib12" id="ref19">12</reflink>]). Inspired by these observations, our study hypothesized that the improvement of core symptoms after physical exercise in ASD could be related with changes in functional and structural networks.</p> <p>To test our hypothesis, we applied advanced individual-based methods to reveal the neural mechanisms of MBTP intervention, mainly on functional and structural networks, and we analyzed the potential association between brain metrics changes and core symptoms of ASD children. We used individual-specific parcellation developed by Wang et al. ([<reflink idref="bib40" id="ref20">40</reflink>]) and similarity calculation in regional morphology developed by Kong et al. ([<reflink idref="bib25" id="ref21">25</reflink>]) to construct individual-based functional networks and structural morphological networks. Functional connectivity was calculated using individual-specific parcellation, taking the variability of functional brain organization across individuals into account. The individual-specific functional connectome has been proven to have a more robust performance in predicting symptom scores in psychiatric disorders (Fan et al., [<reflink idref="bib13" id="ref22">13</reflink>]; Wang et al., [<reflink idref="bib41" id="ref23">41</reflink>]). Individual-based structural brain network was constructed by calculating interregional morphological connectivity among brain regions, which preserves the individual specificity compared with structural covariance networks at the group level (Alexander-Bloch et al., [<reflink idref="bib1" id="ref24">1</reflink>]). We speculated that combined functional and structural methods can comprehensively explain the underlying mechanisms by which MBTP led to the improvement of ASD core symptoms.</p> <hd id="AN0180804672-3">Methods</hd> <p></p> <hd id="AN0180804672-4">Participants</hd> <p>We included 58 ASD children (32 children in the experiment group (EXP) (age: 6.40 ± 2.07, male/female: 28/4) and 26 children in the control group (CON) (age: 5.94 ± 1.79, male/female: 22/4) diagnosed with ASD by experienced psychiatrists based on DSM-5 criteria (Association American Psychiatric, [<reflink idref="bib2" id="ref25">2</reflink>]). Participants were excluded if they: (<reflink idref="bib1" id="ref26">1</reflink>) were involved in a structured exercise program in the past six months; (<reflink idref="bib2" id="ref27">2</reflink>) had co-morbid psychiatric or neurological disorders; (<reflink idref="bib3" id="ref28">3</reflink>) had current medication with psychoactive drugs; (<reflink idref="bib4" id="ref29">4</reflink>) had impaired visual or auditory function; (<reflink idref="bib5" id="ref30">5</reflink>) had a history of head trauma; (<reflink idref="bib6" id="ref31">6</reflink>) had medical contraindications to exercise. We conducted a quasi-experimental design to control the matched age, gender as well as symptom severity evaluated by the Childhood Autism Rating Scale (CARS) in two groups at baseline. CARS includes 15 items, and each item scores from one to four, with higher scores indicating more severe symptoms. ASD children in our study were from mild to moderate levels and severe levels. Verbal and non-verbal participants in the two groups were also matched. Subjects were recruited from Chuying Child Development Center and Starssailor Education Institution in Yangzhou, China. The study was approved by the Ethics and Human Protection Committee of the Affiliated Hospital of Yangzhou University, and complied with the ethical standards of the Helsinki declaration.</p> <hd id="AN0180804672-5">Mini-basketball Training Program and Behavioral Measurements</hd> <p>Children in the control group maintained standard behavior rehabilitation program set by institutions and did not participate in any specific sport-related programs. Children in the experiment group received both rehabilitation program and also an additional 12-week mini-basketball training program (MBTP).</p> <p>MBTP was conducted by two certified physical educators and encouraged parents' participation to promote children's social interaction and communication. MBTP was performed 5 times per week (from Monday to Friday) and lasted for 12 weeks. Each MBTP course consists of 40 min with three parts, including 10-min warm-up activities, 25-min basketball skill learning or basketball games, and 5-min cool-down activities. The 25-min basketball learning consisted of 3 phrases. The first phase was for 2 weeks and the participants learnt how to catch, tap and throw the basketball to increase their interest in and familiarity with basketball. In the 8-week second phase, the participants learnt skilled movement, like dribbling and shooting to acquire new abilities and reduce the occurrence of stereotyped and repetitive behaviors. In the last 2 weeks, the basketball-based game was taught to enhance their sense of cooperation (Cai et al., [<reflink idref="bib6" id="ref32">6</reflink>]; Wang et al., [<reflink idref="bib43" id="ref33">43</reflink>]). We conducted MBTP in the same facility where the ASD children were recruited.</p> <p>The behavior measurements were provided at the beginning and the end of MBTP. Core symptom of ASD was evaluated using the Social Responsiveness Scale-2 (SRS-2), a 65-item scale measurement for social behavior evaluation, and the Repetitive Behavior Scale (RBS-R), a six-dimension system used to assess restricted and stereotypical behavior. SRS-2 and RBS-R were filled out by parents of participants and clinicians were responsible for calculating their final score. All parents and clinicians were blind to group allocation and study hypotheses. Higher scores represent more severe ASD symptoms. Fifty subjects (50/58) reached the endpoint with successful SRS-2 and RBS-R evaluation. Two children in the experiment group and six control group children could not be evaluated by SRS-2 and RBS-R at the endpoint due to lack of parents' cooperation.</p> <hd id="AN0180804672-6">Data Acquisition</hd> <p>Data were obtained from participants before and after MBTP intervention (within 0–3 days). In case that the scan was interrupted, we provided fMRI and collected data again within 7 days after the initial failure. The exact length of the time window between the end of MBTP and the harvest of fMRI data, defined as interval time was set as a co-variable factor in the next statistical analysis.</p> <p>To avoid excessive head motion, participants were sedation with 10% chloral hydrate (dosage: 30 mg/kg; maximum dose: 1 g) due to its high efficacy, high safety and low complication rates (Cote & Wilson, [<reflink idref="bib9" id="ref34">9</reflink>]; Many et al., [<reflink idref="bib29" id="ref35">29</reflink>]), and informed consent were approved by parents. The procedure was conducted at night, and parents were informed to keep their children awake on the day of the scan. 30 min after the sedation, the nurse measured every participant's consciousness level and scanning began. The scanning was stopped immediately if the child woke up or moved.</p> <p>MRI data were acquired using a 3.0 T GE scanner (GE Discovery MR750w 3.0T, Chicago, United States) in the Affiliated Hospital of Yangzhou University. fMRI data were collected with echo-planar imaging (EPI) sequence using two acquisition parameters: (<reflink idref="bib1" id="ref36">1</reflink>) repetition time (TR) = 2000 ms, echo time (TE) = 30 ms, timepoint = 240, flip angle (FA) = 90°, matrix size = 64 × 64, field of view (FoV) = 224 mm × 224 mm, voxel size = 3.5 mm × 3.5 mm × 4 mm, slice thickness = 4 mm, slice gap = 5 mm and slice number = 28; (<reflink idref="bib2" id="ref37">2</reflink>) TR = 2300 ms, TE = 30 ms, timepoint = 240, FA = 90°, matrix size = 64 × 64, FoV = 224 mm × 224 mm, voxel size = 3.5 mm × 3.5 mm × 4 mm, slice thickness = 3 mm, slice gap = 4 mm and slice number = 32. For children with large head circumference, the second parameter was used to obtain better imaging (experiment group: 17 subjects; control group:16 subjects). T1-weighted structural images were acquired using a three-dimensional magnetization-prepared rapid acquisition with gradient-echo (MPRAGE) sequence (TR/TE = 7.1/3.2 ms, FA = 12°, Fov = 224 mm × 224 mm and voxel size = 1 mm × 1 mm × 1 mm).</p> <hd id="AN0180804672-7">fMRI Data Preprocessing</hd> <p>Resting-state fMRI data were preprocessed using FSL package (Woolrich et al., [<reflink idref="bib46" id="ref38">46</reflink>]) and FsFast package (<ulink href="http://surfer.nmr.mgh.harvard.edu/fswiki/FsFast">http://surfer.nmr.mgh.harvard.edu/fswiki/FsFast</ulink>). Briefly, the first six volumes were discarded, and the head motion was corrected with FSL; images with head motion exceeding 3-mm were excluded in further analysis; band-pass filter (0.01–0.08 Hz) was applied; and the component that had the strongest correlation with global signal was removed from each subject by using a method based on singular value decomposition (SVD).</p> <p>Structural data were preprocessed using the FreeSurfer software package (<ulink href="http://surfer.nmr.mgh.harvard.edu">http://surfer.nmr.mgh.harvard.edu</ulink>). The structural and functional images were aligned by boundary-based registration with FsFast. Functional images were registered to Freesurfer template; smoothed with a 6-mm full-width half-maximum (FWHM) smoothing kernel; and then down-sampled to a mesh of 2,562 vertices in each hemisphere.</p> <hd id="AN0180804672-8">Construction of Individual-Specific FC Network</hd> <p>We used the iterative algorithms (Wang et al., [<reflink idref="bib40" id="ref39">40</reflink>]) to identify individual-specific functional networks to characterize brain-behavior associations more accurately. First, the group-level atlas including 18 cortical networks (Wang et al., [<reflink idref="bib40" id="ref40">40</reflink>]) was registered onto each subject's cortical surface, adapted from 17 cortical networks based on 1000 healthy subjects (Thomas Yeo et al., [<reflink idref="bib37" id="ref41">37</reflink>]), from which the hand sensorimotor network was separated. The individual subject's time courses were calculated by averaging within each network. Each vertex on cortical surface was reassigned to the maximal correlation network. Then individual-specific network atlas was generated by iteratively adjusted network boundary using the inter-subject variability in functional connectivity (Mueller et al., [<reflink idref="bib31" id="ref42">31</reflink>]) and signal-to-noise (SNR) distribution. Further, 18 × 18 correlation maps were obtained by extracting mean time series from the individual-specific atlas and calculating Pearson correlation coefficients (r) in each pair of 18 networks. Finally, the correlation coefficients r maps were converted into Z-score maps using Fisher's r-to-z transform to improve data distribution for statistical analysis.</p> <hd id="AN0180804672-9">sMRI Data Preprocessing</hd> <p>T1-weighted images were preprocessed using FSL pipeline for VBM analysis to obtain grey matter volumes for each subject (Douaud et al., [<reflink idref="bib11" id="ref43">11</reflink>], <ulink href="http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM">http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM</ulink>). Briefly, structural images were processed by FSL's BET and FreeSurfer to remove non-brain tissue more accurately, all brain-extracted images were segmented into grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Then, segmented GM images were linearly registered to the MNI 152 standard space. GM images in standard space were then averaged together and flipped along x-axis to create a study-specific GM template. All native GM images were then non-linearly registered to the study-specific template. At the last step, the resulting GM images were smoothed with a 6-mm full-width half-maximum (FWHM) smoothing kernel.</p> <hd id="AN0180804672-10">Construction of Individual MBN</hd> <p>Individual morphological brain networks (MBNs) were constructed based on their own GM images in which nodes represent brain regions and edges represent the similarity between two regions' morphological measure distributions. We used brain regions defined by automated anatomical labelling (AAL) atlas (Tzourio-Mazoyer et al., [<reflink idref="bib38" id="ref44">38</reflink>]), which included 90 brain regions. Network edges were quantified by the symmetric Kullback-Leibler divergence-based similarity (KLS) (Kong et al., [<reflink idref="bib25" id="ref45">25</reflink>]; Wang et al., [<reflink idref="bib42" id="ref46">42</reflink>]) and defined as follows:</p> <p> <ephtml> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>K</mi><mi>L</mi><mi>S</mi><mspace width="0.166667em" /><mfenced close=")" open="("><mrow><mi>p</mi><mo>,</mo><mspace width="0.166667em" /><mi>q</mi></mrow></mfenced><mo>=</mo><msup><mi>e</mi><mrow><mo>-</mo><msubsup><mo>∑</mo><mrow><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow></mrow><mi>n</mi></msubsup><mfenced close=")" open="("><mrow><mi>p</mi><mfenced close=")" open="("><mi>i</mi></mfenced><mo>log</mo><mfrac><mrow><mi>p</mi><mfenced close=")" open="("><mi>i</mi></mfenced></mrow><mrow><mi>q</mi><mfenced close=")" open="("><mi>i</mi></mfenced></mrow></mfrac><mo>+</mo><mi>q</mi><mfenced close=")" open="("><mi>i</mi></mfenced><mo>log</mo><mfrac><mrow><mi>p</mi><mfenced close=")" open="("><mi>i</mi></mfenced></mrow><mrow><mi>q</mi><mfenced close=")" open="("><mi>i</mi></mfenced></mrow></mfrac></mrow></mfenced></mrow></msup></mrow></math> </ephtml> </p> <p>Graph</p> <p>where p and q are grey matter density probability distributions in two different brain regions and were estimated using kernel density estimation (KDE) (Botev et al., [<reflink idref="bib4" id="ref47">4</reflink>]). N is the number of sampling points (n = 2<sups>7</sups> was used in this study, the same as the one in Wang et al. ([<reflink idref="bib42" id="ref48">42</reflink>]), which was a tradeoff between stability and computational complexity). KLS ranges from 0 to 1, where 1 indicates that p and q have identical distributions.</p> <hd id="AN0180804672-11">Graph Theoretical Analysis</hd> <p>Graph theoretical analysis was conducted on individual MBN to explore the change of topological properties after MBTP. All network properties in this study were calculated using GRETNA toolbox (Wang et al., [<reflink idref="bib45" id="ref49">45</reflink>]) (https://<ulink href="http://www.nitrc.org/projects/gretna/">www.nitrc.org/projects/gretna/</ulink>). The global network metrics included global efficiency (E<subs><emph>glob</emph></subs>), local efficiency (E<subs><emph>loc</emph></subs>), clustering coefficient (C<subs><emph>p</emph></subs>), characteristic path length (L<subs><emph>p</emph></subs>) and small-worldness attributes (σ). At the nodal level, we evaluated nodal degree and nodal efficiency.</p> <p>Considering that the network metrics strongly depend on the network densities, we calculated all network metrics under a wide range of sparsity from 5 to 50% with a step of 5% instead of at a specific threshold. We computed the area under the curve (AUC) from any single threshold for each network metric to provide a comprehensive measure of the topological organization of brain networks.</p> <hd id="AN0180804672-12">Statistical Analysis</hd> <p>A two-sample t-test was used to test for group differences in age and CARS scores, and a chi-square test was used to test for sex differences and verbal level differences between two groups at baseline.</p> <p>For clinical scales and functional connectivity, we regressed out age, sex, TR, motion parameters and interval time using General Linear Model (GLM). For structural metrics, age, sex, total brain volume and interval time were regressed. Then we extracted the residual to perform a 2 (time: baseline vs. endpoint) × 2 (group: experiment group vs. control group) repeated measures ANOVA analysis to explore the effect of MBTP on brain metrics. Once the significant time × group interaction effects were found, we conducted simple effects analysis (baseline vs. endpoint within the experiment group; baseline vs. endpoint within the control group; experiment group vs. control group at baseline; experiment group vs. control group at endpoint). All statistical analysis was conducted using R package version 0.8.x (https://CRAN.R-project.org/package=bruceR). Multiple comparisons were corrected by using the false discovery rate (FDR) method (Benjamini & Hochberg, [<reflink idref="bib3" id="ref50">3</reflink>]).</p> <p>To further establish an association between altered brain regions and cognitive implications, we performed a meta-analysis using the Neurosynth database (https://neurosynth.org/) (Yarkoni et al., [<reflink idref="bib47" id="ref51">47</reflink>]). For both FC and MBN, we generated a map that included all regions with altered functional connections and structural connections by MBTP. Next, we decoded the cognitive terms for each region map and retained the top 30 terms with substantial relevance.</p> <p>For MBN connectivity, we utilized Network-Based Statistic (NBS) approach (Zalesky et al., [<reflink idref="bib49" id="ref52">49</reflink>]) to examine within-group and between-group changes. The NBS analysis was performed in the following steps. First, after regressing out sex, age, total brain volume as well as interval time, we separately performed a paired t-test within the experiment group and within the control group, a two-sample t-test between experiment group and control group (at baseline and at endpoint, respectively). And we retained the connectivity (<emph>p</emph> < 0.05, uncorrected) as a mask in each t-test step. Then, within this mask, significantly between-group and within-group altered components within these connections were identified by NBS with each connection statistic T > 3.1. Finally, a permutation approach was used to estimate the significance of each component (5000 permutations). We set component significance at <emph>p</emph> < 0.05.</p> <p>Further, for those functional connectivity, topological metrics or MBN components with significant group differences, we examined their relationship with the changes in clinical scores (post-pre) using Pearson correlation.</p> <hd id="AN0180804672-13">K-Means Analysis</hd> <p>In order to identify groups with similar altered neuroanatomical profiles and further validate the association between altered brain metrics and the improvement of core symptoms, we conducted K-means clustering (1000 iterations) across functional and structural brain metrics adjusted by MBTP in the above analysis. The optimal number of clusters (k = 1–5) was assessed by the silhouette criterion based on a squared Euclidean distance function. Each individual's change in each brain metric from baseline to endpoint was calculated. Then, we performed a two-sample t-test to investigate differences in clinical scores and brain metrics across clusters. Multiple comparisons were corrected by using the false discovery rate (FDR) method.</p> <hd id="AN0180804672-14">Result</hd> <p></p> <hd id="AN0180804672-15">Demographic and Clinical Characteristics</hd> <p>Demographic characteristics, including age, sex, verbal ability as well as CARS score, did not significantly differ between the experiment and control groups at baseline. (Supplementary Table 1).</p> <p>To investigate the effect of MBTP on clinical scores, including SRS total scores, RBSR total scores as well as their subscale scores, ANOVA analysis with a 2 (time: baseline vs. endpoint) × 2 (group: EXP vs. CON) repeated measures were performed. The significant interaction between group (EXP vs. CON) and time (baseline vs. endpoint) indicated MBTP's effect on ASD core symptom, according to clinical scores. The results demonstrated that EXP group children had significantly decreased SRS total scores (F = 6.009, <emph>p</emph> = 0.046 corrected), SRS-Social Communication scores (F = 8.301, <emph>p</emph> = 0.033 corrected) and RBSR-Self-Injurious Behavior scores (F = 9.156, <emph>p</emph> = 0.033 corrected) compared to CON group. At the same time, EXP children showed significant reduction in these scores at endpoint compared with baseline (<emph>t</emph> = − 4.035, <emph>p</emph> < 0.001; <emph>t</emph> = − 3.458, <emph>p</emph> = 0.002; <emph>t</emph> = <bold>− </bold>4.927, <emph>p</emph> < 0.001, respectively), while CON children did not (Fig. 1a). Clinical characteristics are presented in Supplementary Table 2.</p> <hd id="AN0180804672-16">Functional Connectivity Results</hd> <p>There were significant interaction effects (group (EXP vs. CON) × time (baseline vs. endpoint)) observed in the within- and between-network FC of the sensorimotor network (SM) (Fig. 1b, Supplementary Fig. 1a, b).</p> <p>Graph: Fig. 1 MBTP effects on behavior performance and on functional connectivity (FC). a The bar graph showed mean clinical scores and the line graph (right) showed the interaction effect between time (baseline, endpoint) and group (EXP, CON). After multiple comparison correction, *p < 0.05, **p < 0.01, ***p < 0.001. b The boxplot displayed the median and interquartile range of connectivity z-scores and the line graph (right) showed the interaction effect on FC. All regions listed didn't pass fdr correction for the multiple comparisons. *p < 0.05, **p < 0.01, ***p < 0.001 (uncorrected). c Correlation between change of FC and change of clinical variables. Each dot represented the change of one child (post-pre). The negative value on clinical score change represented the improvement in core symptom</p> <p>Specifically, following MBTP, children in EXP group showed decreased connectivity between the hand sensorimotor network (SM4) and lateral sensorimotor network (SM2) (F = 12.63, <emph>p</emph> < 0.001 uncorrected), as well as decreased connectivity between the auditory network (SM3) and salience network (SN) (F = 4.14, <emph>p</emph> = 0.047 uncorrected) compared to CON. Such decreased SM4–SM2 and SM3-SN FC at endpoint compared to baseline were only observed in EXP group (SM4–SM2: <emph>t</emph> = − 2.96, <emph>p</emph> = 0.005 uncorrected; SM3-SN: <emph>t</emph> = − 2.45, <emph>p</emph> = 0.017 uncorrected) (Fig. 1b).</p> <p>Using the NeuroSynth meta-analytic database, we found that those regions where MBTP had changed FC were mainly associated with the function of motor, movement and execution (Supplementary Fig. 1c).</p> <p>Further analyses also revealed a positive correlation between the change of FC in SM4–SM2 and the improvement of stereotyped behavior (<emph>r</emph> = 0.245, <emph>p</emph> = 0.086), as well as a significant positive correlation between the change of FC in SM3-SN and the reduction of self-injurious behaviors (<emph>r</emph> = 0.31, <emph>p</emph> = 0.028) (Fig. 1c).</p> <hd id="AN0180804672-17">MBN Connectivity Results Detected by NBS Analysis</hd> <p>NBS analysis showed that significant changes in MBN connectivity occurred and the connection of two subnetworks decreased after MBTP. One change involved a cortical–cortical network centered on the left inferior temporal gyrus (ITG.L) defined as Network-1 (<emph>p</emph> = 0.015 corrected). In this network, ITG.L was centrally connected to the left medial superior frontal gyrus (SFGmed.L), the right medial superior frontal gyrus (SFGmed.R), the right supplementary motor area (SMA.R) and the right superior parietal gyrus (SPG.R), but these four cortical regions had no direct connections. Another was a subcortical–cortical network centered on the left caudate (CAU.L) named as Network-2 (<emph>p</emph> = 0.025 corrected). Similarly, CAU.L directly connected to the right posterior cingulate gyrus (PCG.R), the right calcarine fissure (CAL.R) and the left calcarine fissure (CAL.L) (Fig. 2a). According to the decoding result, these regions are mainly associated with social cognitive function, including episodic memory, retrieval of mind and theory of mind (TOM) (Fig. 2c).</p> <p>Graph: Fig. 2 Altered network components identified by NBS analysis after MBTP. a A cortical–cortical network centered on the left inferior temporal gyrus (ITG.L) and a subcortical–cortical network centered on the left caudate (CAU.L) induced by MBTP had decreased MBN connectivity in the experiment group (EXP) compared to control group (CON). b The scatter graphs showed positive correlations between change of the average MBN connectivity in two subnetworks and change of core symptom in ASD. c Cognitive terms associated with regions in which these two networks included. Font size has been scaled to represent the correlation value for each cognitive term. d A subcortical–cortical network with lower MBN connectivity in EXP than CON at endpoint, while not at baseline. 90 ROIs from AAL atlas were grouped in 6 different networks as shown in the circle with brain plots and with different colors. e BrainNetViewer showed this subcortical–cortical network. Nodes with top nodal degree were left thalamus (THA.L), CAU.L and ITG.L</p> <p>Next, we attempted to analyze the potential association between changes in the network connectivity and changes in ASD symptom. The results showed that the decrease in the aforementioned Network-1 was positively correlated with the decrease in SRS-social motivation scores (<emph>r</emph> = 0.31, <emph>p</emph> = 0.03), and the aforementioned Network-2 decrease had a positive correlation with the reduce in RBSR self-injurious behavior scores (<emph>r</emph> = 0.48, <emph>p</emph> < 0.001) (Fig. 2b).</p> <p>As being expected, there was no difference in subnetwork between the EXP group and CON group at baseline. However, at the endpoint, a subcortical–cortical subnetwork including 53 nodes and 74 lower MBN connections (<emph>p</emph> < 0.001 corrected), was identified in EXP group, but not seen in CON group. This subnetwork centered on subcortical regions like the left caudate (CAU.L), the left thalamus (THA.L), and the left inferior temporal gyrus (ITG.L), and connected with multiple cortical regions in the frontal, occipital, parietal, temporal areas (Fig. 2d, e).</p> <hd id="AN0180804672-18">Global and Nodal Topological Properties Results</hd> <p>Morphological networks in both EXP and CON groups showed γ > 1 and λ ≈ 1, indicating a small-world organization (Fig. 3a).</p> <p>Graph: Fig. 3 The MBTP effect on topological properties. a Children in both EXP and CON exhibited γ > 1 and λ ≈ 1, which are typical features of small-world topology. γ, normalized clustering coefficient; λ, normalized characteristic path length. b The bar graph showed mean characteristic path length (Lp) and global efficiency (Eglob). And the line graph (right) showed the interaction effect between time and group. c Correlation between change of global topological properties and clinical scores were represented. d The bar graph showed mean nodal efficiency (Ne) and nodal degree (Dc). All results didn't pass fdr correction for the multiple comparisons. *p < 0.05, **p < 0.01, ***p < 0.001 (uncorrected). e Correlation between change of local topological properties and clinical scores were represented. ITG.L: left inferior temporal gyrus, CAU.L: left caudate</p> <p>Children in CON group did not show significant differences in these global network metrics at endpoint. Nevertheless, in EXP group, significantly increased L<subs><emph>p</emph></subs> and decreased E<subs><emph>glob</emph></subs> were observed at endpoint (<emph>t</emph> = 3.088, <emph>p</emph> = 0.003; <emph>t</emph> = − 4.159, <emph>p</emph> < 0.001, uncorrected) (Fig. 3b, Supplementary Table 3). Besides, there was no significant difference in L<subs><emph>p</emph></subs> and E<subs><emph>glob</emph></subs> in two groups at baseline (<emph>t</emph> = 0.214, <emph>p</emph> = 0.831; <emph>t</emph> = − 0.61, <emph>p</emph> = 0.545, uncorrected). While at endpoint, compared to CON group, there were higher L<subs><emph>p</emph></subs> and lower E<subs><emph>glob</emph></subs> in EXP group (<emph>t</emph> = 2.642, <emph>p</emph> = 0.011; <emph>t</emph> = − 2.885, <emph>p</emph> = 0.006, uncorrected). Especially, significant group × time interaction effects were observed in L<subs><emph>p</emph></subs> and E<subs><emph>glob</emph></subs>, which meant children in EXP group had increased characteristic path length and decreased global efficiency compared to CON group (F = 4.241, <emph>p</emph> = 0.044; F = 4.133, <emph>p</emph> = 0.047, uncorrected).</p> <p>Next, there was a negative correlation between the change in L<subs><emph>p</emph></subs> and SRS total score change (<emph>r</emph> = − 0.276, <emph>p</emph> = 0.055). There was a significant negative correlation between the change in E<subs><emph>glob</emph></subs> and SRS total score change (<emph>r</emph> = 0.298, <emph>p</emph> = 0.037) (Fig. 3c).</p> <p>Following the MBTP, children in EXP group had decreased nodal degree in the left inferior temporal gyrus (ITG.L), as well as decreased nodal efficiency in the left caudate (CAU.L) and left inferior temporal gyrus (ITG.L) (<emph>t</emph> = − 3.307, <emph>p</emph> = 0.002; <emph>t</emph> = − 4.476, <emph>p</emph> < 0.001; <emph>t</emph> = − 3.855, <emph>p</emph> < 0.001, uncorrected) (Fig. 3d, Supplementary Table 3).</p> <p>Further, interaction results showed that compared to CON group, children in EXP group had decreased nodal degree and nodal efficiency in ITG.L, with decreased nodal efficiency in CAU.L (F = 10.153, <emph>p</emph> = 0.003; F = 12.697, <emph>p</emph> < 0.001; F = 6.599, <emph>p</emph> = 0.013). For nodal efficiency, changes in CAU.L as well as ITG.L were positively correlated with the changes of SRS-Social communication score and the SRS total score (<emph>r</emph> = 0.323, <emph>p</emph> = 0.024; <emph>r</emph> = 0.29, <emph>p</emph> = 0.044). Regarding to nodal degree, the decrease in ITG.L was positively correlated with the decrease in SRS total score (<emph>r</emph> = 0.289, <emph>p</emph> = 0.044) (Fig. 3e).</p> <hd id="AN0180804672-19">K-Means Results</hd> <p>We conducted K-means clustering analysis with 7 brain metrics (SM4-SM2 FC, SN-SM3 FC and nodal efficiency in CAU.L and ITG.L, as well as nodal degree in ITG.L, L<subs><emph>p</emph></subs> and E<subs><emph>glob</emph></subs>) affected by MBTP, and the optimal number of clustering was k = 2 (Fig. 4a). Children in Cluster1 showed significant improvement in SRS-Total score (<emph>t</emph> = − 2.730, <emph>p</emph> = 0.011 uncorrected), SRS-Communication score (<emph>t</emph> = − 2.086, <emph>p</emph> = 0.042 uncorrected) and SRS-Autistic behavior score (<emph>t</emph> = − 2.948, <emph>p</emph> = 0.005 uncorrected) compared to Cluster2 (Fig. 4d). The proportion of Cluster1 of EXP group was also larger than that of CON group (EXP-Cluster1: 17 children; EXP-Cluster2: 13 children; CON-Cluster1: 4 children; CON-Cluster2: 16 children), which indicated that more children in EXP group showed improvement of core symptoms compared to CON group (Fig. 4b, c).</p> <p>Graph: Fig. 4 Result of K-means clustering for valuating the relationship between change in behavior scores and change in brain metrics. a The optimal number of clustering. The figure showed that k = 2 was optimal. b TSNE project of children in two clusters. Cluster1 represented children with improvement of social deficits. Cluster1 was showed by asterisk. c The proportion of two clusters in EXP and CON. d Group comparation on behaviors between two clusters. The bolder line represented Cluster1, which showed more improvement on social skills than Cluster2. *p < 0.05, **p < 0.01, ***p < 0.001 (uncorrected). All results didn't pass fdr correction. e Group comparation on brain metrics between two clusters. *p < 0.05, **p < 0.01, ***p < 0.001 (fdr corrected). We used brain metrics Z-score to display</p> <p>In addition, children in Cluster1 showed a significantly more decrease in SM4-SM2 FC (<emph>t</emph> = − 3.567, <emph>p</emph> = 0.002 corrected), nodal efficiency in CAU.L (<emph>t</emph> = − 5.737, <emph>p</emph> < 0.001 corrected) and ITG.L (<emph>t</emph> = − 3.127, <emph>p</emph> = 0.008 corrected), nodal degree in ITG.L (<emph>t</emph> = − 2.527, <emph>p</emph> = 0.021 corrected), increased L<subs><emph>p</emph></subs> (<emph>t</emph> = 6.077, <emph>p</emph> < 0.001 corrected) and decreased E<subs><emph>glob</emph></subs> (<emph>t</emph> = − 6.405, <emph>p</emph> < 0.001 corrected) than children in Cluster2 (Fig. 4e). These results followed the same trend as that being observed in Pearson correlation, which suggested that the improvement of social deficits was associated with decreased nodal efficiency in CAU.L and ITG.L, decreased nodal degree in ITG.L, increased L<subs><emph>p</emph></subs> and decreased E<subs><emph>glob</emph></subs>.</p> <hd id="AN0180804672-20">Discussion</hd> <p>In this study, we explored the effect of MBTP intervention in children with ASD using individual-based analysis of brain function and structure. To the best of our knowledge, this is the first study investigating the structural and functional changes of brain after MBTP in ASD children. Our results suggested that certain specific neurological responses occurred after MBTP in several aspects.</p> <p>Our results found that following MBTP, ASD children had significantly (<reflink idref="bib1" id="ref53">1</reflink>) improved social communication and reduced self-injurious behavior; (<reflink idref="bib2" id="ref54">2</reflink>) decreased functional connectivity within sensorimotor network (lateral sensorimotor network and hand sensorimotor network), as well as decreased functional connectivity between sensorimotor network (auditory network) and salience network; (<reflink idref="bib3" id="ref55">3</reflink>) decreased morphological connectivity in 2 subnetworks centered on the left inferior temporal gyrus (ITG.L) and left caudate (CAU.L); (<reflink idref="bib4" id="ref56">4</reflink>) decreased global efficiency, increased characteristic path length, decreased nodal degree in ITG.L, as well as decreased nodal efficiency in ITG.L and CAU.L in morphological brain networks (MBN). More importantly, we found that changes in these brain metrics were associated with improved core symptoms of ASD in both group-level and K-means analyses.</p> <hd id="AN0180804672-21">Decreased Functional Connectivity Related to SM Following MBTP</hd> <p>Atypical sensory processing and motor processing in ASD have been increasingly reported in recent years. Further, early motor and sensory abnormalities have been associated with the repetitive behavior in ASD individuals (Fetta et al., [<reflink idref="bib14" id="ref57">14</reflink>]). The sensorimotor network (SM) involved the input of external stimuli and motor control, and overconnectivity within SM has been reported, which was explained to result in isolation of motor sensation from cognition processing, thus contributing to the stereotyped behavior (Cummings et al., [<reflink idref="bib10" id="ref58">10</reflink>]; Oldehinkel et al., [<reflink idref="bib32" id="ref59">32</reflink>]; Supekar et al., [<reflink idref="bib36" id="ref60">36</reflink>]; Wang et al., [<reflink idref="bib45" id="ref61">45</reflink>]). Here, this may explain the relationship between re-established FC (being decreased) in SM4–SM2 and improved stereotyped behavior after MBTP.</p> <p>The salience network (SN) plays a role in determining whether internal or external stimuli requires more attention. Atypical resting-state FC involving SN has been repeatedly reported (Chen et al., [<reflink idref="bib8" id="ref62">8</reflink>]; Uddin et al., [<reflink idref="bib39" id="ref63">39</reflink>]). The fact that the overconnectivity between SM and SN may reflect a lack of functional separation between these two networks and indicate that children with ASD over-allocate attention to basic sensory stimuli rather than social stimuli (Green et al., [<reflink idref="bib15" id="ref64">15</reflink>]). Based on this theory, interventions which could help to decrease the salience of extraneous sensory stimuli or increase attention to social stimuli, should be beneficial to ASD children (Cummings et al., [<reflink idref="bib10" id="ref65">10</reflink>]). The MBTP intervention, as a team sport that requires participants to support, communicate and cooperate with each other, is helpful to increase social stimuli to some extent. Thus, it improves some of the core symptoms of ASD in our study. The reduction of RBSR subscale—self injurious score was associated with the decrease in SN-SM3 FC.</p> <p>Our findings suggest that MBTP might have improved core symptoms of ASD and modulated atypical functional connectivity involving SM and SN.</p> <hd id="AN0180804672-22">Increased Characteristic Path Length and Decreased Global Efficiency</hd> <p>The abnormal brain network topology in ASD has been reported (Harlalka et al., [<reflink idref="bib16" id="ref66">16</reflink>]; Li et al., [<reflink idref="bib28" id="ref67">28</reflink>]), but the findings are frequently inconsistent. A study in 24-month-old ASD infants showed reduced global and local efficiency, supporting the under-connectivity theory of ASD (Lewis et al., [<reflink idref="bib27" id="ref68">27</reflink>]). Yet, another study in adolescents with ASD reported higher global efficiency and lower local efficiency in functional networks (Rudie et al., [<reflink idref="bib34" id="ref69">34</reflink>]). One study reported decreased characteristic path length, increased global efficiency, and increased clustering coefficient in preschool children with ASD based on the graph analysis of diffusion-tensor imaging data, and these findings are similar to our results (Li et al., [<reflink idref="bib28" id="ref70">28</reflink>]). Randomly connected networks tend to have decreased characteristic path length, suggesting the possibility that higher global efficiency may reflect a more random distribution of edges. These studies may provide evidence that brain network in ASD individuals has increased randomness of networks compared to typical development (Harlalka et al., [<reflink idref="bib16" id="ref71">16</reflink>]). We found lower global efficiency and larger characteristic path length in MBN of children with ASD after MBTP. These changes were accompanied by improvement of social deficits, implying that MBTP reduced randomness in ASD brain network and brought it closer to normal-like brain networks.</p> <hd id="AN0180804672-23">Decreased MBN Connectivity in Two Networks Centered on ITG.L and CAU.L</hd> <p>Our results also reported that after MBTP, children with ASD exhibited decreased MBN connectivity in two subnetworks centered on ITG.L and CAU.L respectively. Further, nodal degree in ITG.L and nodal efficiency in ITG.L and CAU.L were also found to be significantly decreased.</p> <p>The CAU belongs to the subcortical regions and is the main area in CSTC circuitry (Stein et al., [<reflink idref="bib35" id="ref72">35</reflink>]), which plays an important role in the sensorimotor, cognition and motivation process. In previous studies, larger CAU volume was observed in adolescents with ASD than in the control group individuals and the volume measurements were correlated with ASD social scores (Zuo et al., [<reflink idref="bib50" id="ref73">50</reflink>]). In addition, it has been reported that the subcortical–cortical over-connectivity involving subcortical structures such as thalamus, putamen, and cortical regions, associated with symptom severity in children with ASD (He et al., [<reflink idref="bib17" id="ref74">17</reflink>]; Maximo & Kana, [<reflink idref="bib30" id="ref75">30</reflink>]). The ITG is involved in visual perception and processing, which is related to transmitting information back and forth and plays a key role in language and emotional cognition (Hillis, [<reflink idref="bib19" id="ref76">19</reflink>]). Increased gray matter volume in ITG and increased FC between the medial orbital frontal cortex and ITG have also been reported in preschool boys with ASD (Cai et al., [<reflink idref="bib5" id="ref77">5</reflink>]; Lan et al., [<reflink idref="bib26" id="ref78">26</reflink>]). In addition, the overconnectivity of the right Heschl's and ITG in preschoolers with ASD had also been suggested to correlate with symptom severity (Kim et al., [<reflink idref="bib24" id="ref79">24</reflink>]). These studies suggested that the abnormality in ITG and CAU may play critical roles in the neurobiology of ASD.</p> <p>Our results showed that: (<reflink idref="bib1" id="ref80">1</reflink>) the decreased connection in the subcortical–cortical subnetwork centered on CAU.L was related to the reduction of self-injurious behavior; (<reflink idref="bib2" id="ref81">2</reflink>) the reduced connections in the cortical–cortical subnetwork centered on ITG.L were related to the improvement of social deficits; (<reflink idref="bib3" id="ref82">3</reflink>) the decreased nodal degree and nodal efficiency in ITG.L and CAU.L may reflect that MBTP modulated abnormal local connectivity involving the ITG and CAU and increased the separation of the brain network, and may be a result of brain network remodeling towards a more "normal" brain. All findings demonstrated that MBTP reconstructed connectivity in MBN networks in ASD children.</p> <p>Using k-means analysis, our study aimed to identify children with similar changes in brain phenotype and examine the association between brain changes and core symptom improvements. Our results showed that the group with improved social function detected by brain pattern had decreased FC within SM, nodal degree and nodal efficiency in ITG.L and CAU.L, global efficiency, as well as increased characteristic path length. Two groups identified by different brain changes may had specific brain patterns and it's crucial to guide targeted interventions for them.</p> <p>In conclusion, our study demonstrated the effectiveness of MBTP intervention to improve core symptoms of ASD, ameliorating social deficits as well as restricted and repetitive behaviors. We used a multimodal approach and found that MBTP significantly decreased abnormal connectivity involving SM and SN of functional network and connectivity in two subnetworks centered on the ITG.L and CAU.L in structural morphological network. These changes were all related to the core symptom improvements and drove the brain change towards normal-like neuroanatomy. Our results emphasize the importance of timely intervention during the critical pre-adolescent period for brain plasticity in ASD children. Furthermore, the identification of certain brain areas affected by MBTP would provide us insights further understanding the neurological mechanisms of ASD, which is instructive for making more targeted and individualized intervention strategy.</p> <hd id="AN0180804672-24">Limitations and Future Research</hd> <p>There are several limitations in our study. Firstly, the lack of observational measures of behavioral symptom (ADOS or ADI-R) was a limitation, and therefore, we missed some behavior-quantifying dimensions. Our future work would include these scales into quantification. Secondly, six participants had missing behavioral scores, which may affect the accuracy of our correlation analysis between behavioral test results and brain metric results. Thirdly, our data were obtained from ASD children on the sedation, which may cause confounding effect on our results. Lastly, the sample size of our study was relatively small and a larger number of participant recruitment should be needed in future to validate our current findings and further investigate the neurological changes and mechanism of ASD.</p> <hd id="AN0180804672-25">Acknowledgments</hd> <p>This work was supported by Science and Technology Planning Project of Liaoning Province (no. 2022JH2/10700002); The fifth "333 Project" scientific research funding project of Jiangsu Province (BRA2019283); Scientific research and practice innovation Project of Jiangsu Province (3161).</p> <hd id="AN0180804672-26">Author Contributions</hd> <p>DZ and ZL contributed equally to this study. DZ conducted data analysis and drafted the manuscript; ZL provided clinical expertise, data collection and the manuscript correction; AC designed and conducted mini-basketball training program; HL designed the data analysis pipeline and drafted the manuscript; KC contributed to MRI data collection; DZ, YZ, LL, FC, HL contributed to data analysis and interpretation of result; HX contributed to the figure; GG helped revise the grammar and some expressions to make the manuscript easier to read. All authors provided critical revision of the manuscript. All authors approved the final manuscript.</p> <hd id="AN0180804672-27">Declarations</hd> <p></p> <hd id="AN0180804672-28">Conflict of interest</hd> <p>The authors declare no conflict of interest.</p> <hd id="AN0180804672-29">Ethical Approval</hd> <p>The study with quasi-experimental design was conducted between October and December 2018 in Yangzhou, China. Approval letters have been received from both the Ethics Committee of Yangzhou Maternal and Child Health Hospital (No. 201806001) and the Ethics and Human Protection Committee of the Affiliated Hospital of Yangzhou University. Meanwhile, this study was registered with the Chinese Clinical Trial Registry (ChiCTR1900024973) on 5 August 2019, prior to the beginning of experiments.</p> <hd id="AN0180804672-30">Informed Consent</hd> <p>Informed consent was obtained from all individual participants included in the study.</p> <hd id="AN0180804672-31">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary material 1 (DOCX 401.2 kb)</p> <hd id="AN0180804672-32">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0180804672-33"> <title> References </title> <blist> <bibl id="bib1" idref="ref24" type="bt">1</bibl> <bibtext> Alexander-Bloch A, Giedd JN, Bullmore E. Imaging structural co-variance between human brain regions. 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  Data: Decreased Functional and Structural Connectivity Is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder after Mini-Basketball Training Program
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  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dongyue+Zhou%22">Dongyue Zhou</searchLink><br /><searchLink fieldCode="AR" term="%22Zhimei+Liu%22">Zhimei Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Guanyu+Gong%22">Guanyu Gong</searchLink><br /><searchLink fieldCode="AR" term="%22Yunge+Zhang%22">Yunge Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Lin+Lin%22">Lin Lin</searchLink><br /><searchLink fieldCode="AR" term="%22Kelong+Cai%22">Kelong Cai</searchLink><br /><searchLink fieldCode="AR" term="%22Huashuai+Xu%22">Huashuai Xu</searchLink><br /><searchLink fieldCode="AR" term="%22Fengyu+Cong%22">Fengyu Cong</searchLink><br /><searchLink fieldCode="AR" term="%22Huanjie+Li%22">Huanjie Li</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-1056-1579">0000-0002-1056-1579</externalLink>)<br /><searchLink fieldCode="AR" term="%22Aiguo+Chen%22">Aiguo Chen</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Autism+and+Developmental+Disorders%22"><i>Journal of Autism and Developmental Disorders</i></searchLink>. 2024 54(12):4515-4528.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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– Name: Pages
  Label: Page Count
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  Data: 14
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  Label: Publication Date
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  Data: 2024
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  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Exercise%22">Exercise</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms+%28Individual+Disorders%29%22">Symptoms (Individual Disorders)</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Team+Sports%22">Team Sports</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+Hemisphere+Functions%22">Brain Hemisphere Functions</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Preadolescents%22">Preadolescents</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10803-023-06160-x
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0162-3257<br />1573-3432
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention. We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3-12 years (experiment group: n = 32, control group: n = 26). ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical--cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD. Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.
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  Data: 2024
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1447762
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        StartPage: 4515
    Subjects:
      – SubjectFull: Exercise
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Symptoms (Individual Disorders)
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      – SubjectFull: Team Sports
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      – SubjectFull: Preadolescents
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      – TitleFull: Decreased Functional and Structural Connectivity Is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder after Mini-Basketball Training Program
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