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Zhang S, Jiang L, Hu Z, Liu W, Yu H, Chu Y, Wang J, Chen Y. T1w/T2w ratio maps identify children with autism spectrum disorder and the relationships between myelin-related changes and symptoms. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111040. [PMID: 38806093 DOI: 10.1016/j.pnpbp.2024.111040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/14/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Modern neuroimaging methods have revealed that autistic symptoms are associated with abnormalities in brain morphology, connectivity, and activity patterns. However, the changes in brain microstructure underlying the neurobiological and behavioral deficits of autism remain largely unknown. METHODS we characterized the associated abnormalities in intracortical myelination pattern by constructing cortical T1-weighted/T2-weighted ratio maps. Voxel-wise comparisons of cortical myelination were conducted between 150 children with autism spectrum disorder (ASD) and 139 typically developing (TD) children. Group differences in cortical T1-weighted/T2-weighted ratio and gray matter volume were then examined for associations with autistic symptoms. A convolutional neural network (CNN) model was also constructed to examine the utility of these regional abnormalities in cortical myelination for ASD diagnosis. RESULTS Compared to TD children, the ASD group exhibited widespread reductions in cortical myelination within regions related to default mode, salience, and executive control networks such as the inferior frontal gyrus, bilateral insula, left fusiform gyrus, bilateral hippocampus, right calcarine sulcus, bilateral precentral, and left posterior cingulate gyrus. Moreover, greater myelination deficits in most of these regions were associated with more severe autistic symptoms. In addition, children with ASD exhibited reduced myelination in regions with greater gray matter volume, including left insula, left cerebellum_4_5, left posterior cingulate gyrus, and right calcarine sulcus. Notably, the CNN model based on brain regions with abnormal myelination demonstrated high diagnostic efficacy for ASD. CONCLUSIONS Our findings suggest that microstructural abnormalities in myelination contribute to autistic symptoms and so are potentially promising therapeutic targets as well as biomarkers for ASD diagnosis.
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Affiliation(s)
- Shujun Zhang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Liping Jiang
- Department of Pharmacy, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Zhe Hu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Wenjing Liu
- Children Rehabilitation Center, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Hao Yu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Yao Chu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Jiehuan Wang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
| | - Yueqin Chen
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
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Feng Y, Huang X, Zhao W, Ming Y, Zhou Y, Feng R, Xiao J, Shan X, Kang X, Duan X, Chen H. Association among internalizing problems, white matter integrity, and social difficulties in children with autism spectrum disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111109. [PMID: 39074528 DOI: 10.1016/j.pnpbp.2024.111109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 07/04/2024] [Accepted: 07/24/2024] [Indexed: 07/31/2024]
Abstract
Autism spectrum disorder (ASD) is characterized by social difficulties and often accompanied by internalizing and externalizing problems, which are frequently overlooked. Here, we examined and compared fractional anisotropy (FA) between 79 children with ASD (aged 4-7.8 years) and 70 age-, gender-, and handedness- matched typically developing controls (TDCs, aged 3-7.2 years). We aimed to explore the relationship among social difficulties, internalizing and externalizing problems, and brain structural foundation (characterized by white matter integrity). Compared with the TDCs, the children with ASD exhibited more severe internalizing and externalizing problems, which were positively correlated with social difficulties. Reduced FA values were observed in specific white matter tracts that integrate a fronto-temporal-occipital circuit. In particular, the FA values within this circuit were negatively correlated with internalizing problems and SRS-TOTAL scores. Mediation analysis revealed that internalizing problems mediated the relationship between the FA values in the left middle longitudinal fasciculus (L-MdLF) and corpus callosum forceps major (CCM) and social difficulties in children with ASD. These findings contribute to our understanding of social difficulties, internalizing and externalizing problems, and white matter integrity in children with ASD and highlight internalizing problems as a mediator between social difficulties and white matter integrity.
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Affiliation(s)
- Yu Feng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Xinyue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Weixin Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Yating Ming
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Yuanyue Zhou
- Department of Medical Psychology, The First Affiliated Hospital, Hainan Medical University, Haikou 571199, Hainan, PR China
| | - Rui Feng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Xiaolong Shan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Xiaodong Kang
- Child Rehabilitation Unit, Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan, Bayi Rehabilitation Center, Chengdu 611135, PR China
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China; MOE Key Lab for Neuro information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
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Jia S, Guo C, Li S, Zhou X, Wang X, Wang Q. The effect of physical exercise on disordered social communication in individuals with autism Spectrum disorder: a systematic review and meta-analysis of randomized controlled trials. Front Pediatr 2023; 11:1193648. [PMID: 37456563 PMCID: PMC10347521 DOI: 10.3389/fped.2023.1193648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023] Open
Abstract
Objective The aim of this systematic review and meta-analysis was to systematically investigate the intervention effect of physical exercise on disordered social communication in patients with autism spectrum disorders. Methods This systematic review and meta-analysis used the PubMed, Web of Science, the Cochrane Library, and Embase electronic databases to conduct a systematic search of literature describing randomized controlled trials (RCTs) on the effect of physical exercise on disordered social communication in autistic patients from the first year of inclusion to 21 January 2023. Results A total of 14 RCTs including 460 autistic patients were analyzed. A meta-analysis showed that physical exercise had a positive effect on social communication disorder (SMD = 0.45, 95% CI: 0.15, 0.74, p < 0.05) in autistic patients. Subgroup analysis showed that exercise programs with multiple components (SMD = 0.73, 95% CI: 0.39, 1.06, P < 0.001), a moderate duration (SMD = 0.73, 95% CI: 0.38, 1.08, P < 0.001), a moderate-high frequency (SMD = 0.84, 95% CI: 0.53, 1.14, P < 0.001), and a long duration (SMD = 0.77, 95% CI: 0.36, 1.18, P < 0.001) led to significant improvement. Conclusion Physical exercise can improve disordered social communication in patients with autism spectrum disorders. Specifically, early intervention, multi-component exercise, a moderate period, moderate and high frequency, long duration, and multi-participant programs were most effective. Systematic Review Registration https://www.crd.york.ac.uk/prospero/ RecordID= CRD42023422482.
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Affiliation(s)
- Shuqi Jia
- School of Physical Education, Shanghai University of Sport, Shanghai, China
| | - Chengcheng Guo
- School of Public Administration, Hohai University, Nanjing, China
| | - Shufan Li
- School of Physical Education, Shanghai University of Sport, Shanghai, China
| | - Xiaojing Zhou
- School of Physical Education and Health, Shanghai Lixin University of Accounting and Finance, Shanghai, China
| | - Xing Wang
- School of Physical Education, Shanghai University of Sport, Shanghai, China
| | - Qiang Wang
- School of Physical Education, Shanghai University of Sport, Shanghai, China
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Horien C, Greene AS, Shen X, Fortes D, Brennan-Wydra E, Banarjee C, Foster R, Donthireddy V, Butler M, Powell K, Vernetti A, Mandino F, O’Connor D, Lake EMR, McPartland JC, Volkmar FR, Chun M, Chawarska K, Rosenberg MD, Scheinost D, Constable RT. A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth. Cereb Cortex 2023; 33:6320-6334. [PMID: 36573438 PMCID: PMC10183743 DOI: 10.1093/cercor/bhac506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 12/29/2022] Open
Abstract
Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- MD-PhD Program, Yale School of Medicine, New Haven, CT, United States
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- MD-PhD Program, Yale School of Medicine, New Haven, CT, United States
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Diogo Fortes
- Yale Child Study Center, New Haven, CT, United States
| | | | | | - Rachel Foster
- Yale Child Study Center, New Haven, CT, United States
| | | | | | - Kelly Powell
- Yale Child Study Center, New Haven, CT, United States
| | | | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - David O’Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - James C McPartland
- Yale Child Study Center, New Haven, CT, United States
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Fred R Volkmar
- Yale Child Study Center, New Haven, CT, United States
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Marvin Chun
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Katarzyna Chawarska
- Yale Child Study Center, New Haven, CT, United States
- Department of Statistics and Data Science, Yale University, New Haven, CT, United States
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, United States
| | - Monica D Rosenberg
- Department of Psychology, University of Chicago, Chicago, IL, United States
- Neuroscience Institute, University of Chicago, Chicago, IL, United States
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
- Yale Child Study Center, New Haven, CT, United States
- Department of Statistics and Data Science, Yale University, New Haven, CT, United States
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
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5
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Horien C, Floris DL, Greene AS, Noble S, Rolison M, Tejavibulya L, O'Connor D, McPartland JC, Scheinost D, Chawarska K, Lake EMR, Constable RT. Functional Connectome-Based Predictive Modeling in Autism. Biol Psychiatry 2022; 92:626-642. [PMID: 35690495 PMCID: PMC10948028 DOI: 10.1016/j.biopsych.2022.04.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 04/14/2022] [Accepted: 04/17/2022] [Indexed: 01/08/2023]
Abstract
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut.
| | - Dorothea L Floris
- Methods of Plasticity Research, Department of Psychology, University of Zürich, Zurich, Switzerland; Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Max Rolison
- Yale Child Study Center, New Haven, Connecticut
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - James C McPartland
- Department of Psychology, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Katarzyna Chawarska
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut.
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Zhu XW, Zhang LL, Zhu ZM, Wang LY, Ding ZX, Fang XM. Altered intrinsic brain activity and connectivity in unaffected parents of individuals with autism spectrum disorder: a resting-state fMRI study. Front Hum Neurosci 2022; 16:997150. [PMID: 36248683 PMCID: PMC9563234 DOI: 10.3389/fnhum.2022.997150] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
Objectives: Autism spectrum disorder (ASD) is a juvenile onset neurodevelopmental disorder with social impairment and stereotyped behavior as the main symptoms. Unaffected relatives may also exhibit similar ASD features due to genetic factors. Although previous studies have demonstrated atypical brain morphological features as well as task-state brain function abnormalities in unaffected parents with ASD children, it remains unclear the pattern of brain function in the resting state. Methods: A total of 42 unaffected parents of ASD children (pASD) and 39 age-, sex-, and handedness-matched controls were enrolled. Multiple resting-state fMRI (rsfMRI) analyzing methods were applied, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC), to reveal the functional abnormalities of unaffected parents in ASD-related brain regions. Spearman Rho correlation analysis between imaging metric values and the severity of ASD traits were evaluated as well. Results: ALFF, ReHo, and DC methods all revealed abnormal brain regions in the pASD group, such as the left medial orbitofrontal cortex (mOFC) and rectal gyrus (ROI-1), bilateral supplementary motor area (ROI-2), right caudate nucleus head and right amygdala/para-hippocampal gyrus (ROI-3). FC decreasing was observed between ROI-1 and right anterior cingulate cortex (ACC), ROI-2, and bilateral precuneus. FC enhancing was observed between ROI-3 and right anterior cerebellar lobe, left medial temporal gyrus, left superior temporal gyrus, left medial frontal gyrus, left precentral gyrus, right postcentral gyrus in pASD. In addition, ALFF values in ROI-1, DC values in ROI-3 were positively correlated with AQ scores in pASD (ρ1 = 0.298, P1 = 0.007; ρ2 = 0.220, P2 = 0.040), while FC values between ROI-1 and right ACC were negatively correlated with AQ scores (ρ3 = −0.334, P3 = 0.002). Conclusion: rsfMRI metrics could be used as biomarkers to reveal the underlying neurobiological feature of ASD for unaffected parents.
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Affiliation(s)
- Xiang-Wen Zhu
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Li-Li Zhang
- Department of Child Health Care, Wuxi Children’s Hospital, Wuxi, China
| | - Zong-Ming Zhu
- Department of Radiology, Affiliated Wuxi People’s Hospital, Nanjing Medical University, Wuxi, China
| | - Luo-Yu Wang
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhong-Xiang Ding
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Zhong-Xiang Ding Xiang-Ming Fang
| | - Xiang-Ming Fang
- Department of Radiology, Affiliated Wuxi People’s Hospital, Nanjing Medical University, Wuxi, China
- *Correspondence: Zhong-Xiang Ding Xiang-Ming Fang
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Xie H, Redcay E. A tale of two connectivities: intra- and inter-subject functional connectivity jointly enable better prediction of social abilities. Front Neurosci 2022; 16:875828. [PMID: 36117636 PMCID: PMC9475068 DOI: 10.3389/fnins.2022.875828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/04/2022] [Indexed: 11/22/2022] Open
Abstract
Naturalistic functional magnetic resonance imaging (fMRI) paradigms, such as movie viewing, are attracting increased attention, given their ability to mimic the real-world cognitive demands on attention and multimodal sensory integration. Moreover, naturalistic paradigms allow for characterizing brain network responses associated with dynamic social cognition in a model-free manner using inter-subject functional connectivity (ISFC). While intra-subject functional connectivity (FC) characterizes the individual’s brain functional architecture, ISFC characterizes the neural coupling driven by time-locked extrinsic dynamic stimuli across individuals. Here, we hypothesized that ISFC and FC provide distinct and complementary information about individual differences in social cognition. To test this hypothesis, we examined a public movie-viewing fMRI dataset with 32 healthy adults and 90 typically developing children. Building three partial least squares regression (PLS) models to predict social abilities using FC and/or ISFC, we compared predictive performance to determine whether combining two connectivity measures could improve the prediction accuracy of individuals’ social-cognitive abilities measured by a Theory of Mind (ToM) assessment. Our results indicated that the joint model (ISFC + FC) yielded the highest predictive accuracy and significantly predicted individuals’ social cognitive abilities (rho = 0.34, p < 0.001). We also confirmed that the improved accuracy was not due to the increased feature dimensionality. In conclusion, we demonstrated that intra-/inter-subject connectivity encodes unique information about social abilities, and a joint investigation could help us gain a more complete understanding of the complex processes supporting social cognition.
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李 莉, 张 倩, 刘 欢, 吴 琼, 杨 亭, 陈 洁, 李 廷. Involvement of retinoic acid receptor α in the autistic-like behavior of rats with vitamin A deficiency by regulating neurexin 1 in the visual cortex: a mechanism study. ZHONGGUO DANG DAI ER KE ZA ZHI = CHINESE JOURNAL OF CONTEMPORARY PEDIATRICS 2022; 24:928-935. [PMID: 36036133 PMCID: PMC9425865 DOI: 10.7499/j.issn.1008-8830.2204016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/27/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES To study the mechanism of retinoic acid receptor α (RARα) signal change to regulate neurexin 1 (NRXN1) in the visual cortex and participate in the autistic-like behavior in rats with vitamin A deficiency (VAD). METHODS The models of vitamin A normal (VAN) and VAD pregnant rats were established, and some VAD maternal and offspring rats were given vitamin A supplement (VAS) in the early postnatal period. Behavioral tests were performed on 20 offspring rats in each group at the age of 6 weeks. The three-chamber test and the open-field test were used to observe social behavior and repetitive stereotyped behavior. High-performance liquid chromatography was used to measure the serum level of retinol in the offspring rats in each group. Electrophysiological experiments were used to measure the long-term potentiation (LTP) level of the visual cortex in the offspring rats. Quantitative real-time PCR and Western blot were used to measure the expression levels of RARα, NRXN1, and N-methyl-D-aspartate receptor 1 (NMDAR1). Chromatin co-immunoprecipitation was used to measure the enrichment of RARα transcription factor in the promoter region of the NRXN1 gene. RESULTS The offspring rats in the VAD group had autistic-like behaviors such as impaired social interactions and repetitive stereotypical behaviors, and VAS started immediately after birth improved most of the behavioral deficits in offspring rats. The offspring rats in the VAD group had a significantly lower serum level of retinol than those in the VAN and VAS groups (P<0.05). Compared with the offspring rats in the VAN and VAS groups, the offspring rats in the VAD group had significant reductions in the mRNA and protein expression levels of NMDAR1, RARα, and NRXN1 and the LTP level of the visual cortex (P<0.05). The offspring rats in the VAD group had a significant reduction in the enrichment of RARα transcription factor in the promoter region of the NRXN1 gene in the visual cortex compared with those in the VAN and VAS groups (P<0.05). CONCLUSIONS RARα affects the synaptic plasticity of the visual cortex in VAD rats by regulating NRXN1, thereby participating in the formation of autistic-like behaviors in VAD rats.
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Pang T, Zhao S, Han J, Zhang S, Guo L, Liu T. Gumbel-Softmax based Neural Architecture Search for Hierarchical Brain Networks Decomposition. Med Image Anal 2022; 82:102570. [DOI: 10.1016/j.media.2022.102570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 06/14/2022] [Accepted: 08/04/2022] [Indexed: 11/29/2022]
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10
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Li X, Yang C, An Z, Wang X, Su R, Kang J. Localization and diagnosis of abnormal channels in children with ASD based on WMSSE and ASI. J Neurosci Methods 2022; 375:109595. [DOI: 10.1016/j.jneumeth.2022.109595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 03/14/2022] [Accepted: 04/08/2022] [Indexed: 11/30/2022]
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Yu H, Qu H, Chen A, Du Y, Liu Z, Wang W. Alteration of Effective Connectivity in the Default Mode Network of Autism After an Intervention. Front Neurosci 2022; 15:796437. [PMID: 35002608 PMCID: PMC8727456 DOI: 10.3389/fnins.2021.796437] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 12/08/2021] [Indexed: 11/25/2022] Open
Abstract
Neuroimaging has revealed numerous atypical functional connectivity of default mode network (DMN) dedicated to social communications (SC) in autism spectrum disorder (ASD), yet their nature and directionality remain unclear. Here, preschoolers with autism received physical intervention from a 12-week mini-basketball training program (12W-MBTP). Therefore, the directionality and nature of regional interactions within the DMN after the intervention are evaluated while assessing the impact of an intervention on SC. Based on the results of independent component analysis (ICA), we applied spectral dynamic causal modeling (DCM) for participants aged 3–6 years (experimental group, N = 17, control group, N = 14) to characterize the longitudinal changes following intervention in intrinsic and extrinsic effective connectivity (EC) between core regions of the DMN. Then, we analyzed the correlation between the changes in EC and SRS-2 scores to establish symptom-based validation. We found that after the 12W-MBTP intervention, the SRS-2 score of preschoolers with ASD in the experimental group was decreased. Concurrently, the inhibitory directional connections were observed between the core regions of the DMN, including increased self-inhibition in the medial prefrontal cortex (mPFC), and the changes of EC in mPFC were significantly correlated with change in the social responsiveness scale-2 (SRS-2) score. These new findings shed light on DMN as a potential intervention target, as the inhibitory information transmission between its core regions may play a positive role in improving SC behavior in preschoolers with ASD, which may be a reliable neuroimaging biomarker for future studies. Clinical Trial Registration: This study registered with the Chinese Clinical Trial Registry (ChiCTR1900024973) on August 05, 2019.
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Affiliation(s)
- Han Yu
- Department of Radiology, Medical Imaging Center, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Hang Qu
- Department of Radiology, Medical Imaging Center, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Aiguo Chen
- College of Physical Education, Yangzhou University, Yangzhou, China
| | - Yifan Du
- Department of Radiology, Medical Imaging Center, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Zhimei Liu
- College of Physical Education, Yangzhou University, Yangzhou, China
| | - Wei Wang
- Department of Radiology, Medical Imaging Center, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
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