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Higa GSV, Viana FJC, Francis-Oliveira J, Cruvinel E, Franchin TS, Marcourakis T, Ulrich H, De Pasquale R. Serotonergic neuromodulation of synaptic plasticity. Neuropharmacology 2024; 257:110036. [PMID: 38876308 DOI: 10.1016/j.neuropharm.2024.110036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 05/15/2024] [Accepted: 06/11/2024] [Indexed: 06/16/2024]
Abstract
Synaptic plasticity constitutes a fundamental process in the reorganization of neural networks that underlie memory, cognition, emotional responses, and behavioral planning. At the core of this phenomenon lie Hebbian mechanisms, wherein frequent synaptic stimulation induces long-term potentiation (LTP), while less activation leads to long-term depression (LTD). The synaptic reorganization of neuronal networks is regulated by serotonin (5-HT), a neuromodulator capable of modify synaptic plasticity to appropriately respond to mental and behavioral states, such as alertness, attention, concentration, motivation, and mood. Lately, understanding the serotonergic Neuromodulation of synaptic plasticity has become imperative for unraveling its impact on cognitive, emotional, and behavioral functions. Through a comparative analysis across three main forebrain structures-the hippocampus, amygdala, and prefrontal cortex, this review discusses the actions of 5-HT on synaptic plasticity, offering insights into its role as a neuromodulator involved in emotional and cognitive functions. By distinguishing between plastic and metaplastic effects, we provide a comprehensive overview about the mechanisms of 5-HT neuromodulation of synaptic plasticity and associated functions across different brain regions.
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Affiliation(s)
- Guilherme Shigueto Vilar Higa
- Laboratório de Neurofisiologia, Departamento de Fisiologia e Biofísica, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil; Departamento de Bioquímica, Instituto de Química (USP), Butantã, São Paulo, SP, 05508-900, Brazil
| | - Felipe José Costa Viana
- Laboratório de Neurofisiologia, Departamento de Fisiologia e Biofísica, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil
| | - José Francis-Oliveira
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Emily Cruvinel
- Laboratório de Neurofisiologia, Departamento de Fisiologia e Biofísica, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil
| | - Thainá Soares Franchin
- Laboratório de Neurofisiologia, Departamento de Fisiologia e Biofísica, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil
| | - Tania Marcourakis
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil
| | - Henning Ulrich
- Departamento de Bioquímica, Instituto de Química (USP), Butantã, São Paulo, SP, 05508-900, Brazil
| | - Roberto De Pasquale
- Laboratório de Neurofisiologia, Departamento de Fisiologia e Biofísica, Universidade de São Paulo, Butantã, São Paulo, SP, 05508-000, Brazil.
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Xiong W, Li X, Huang X, Xu J, Qu Z, Su Y, Li Y, Han Y, Cui T, Zhang X. Impaired motor and social skill development in infancy predict high autistic traits in toddlerhood. Neuroscience 2024; 558:114-121. [PMID: 39168171 DOI: 10.1016/j.neuroscience.2024.08.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 07/26/2024] [Accepted: 08/18/2024] [Indexed: 08/23/2024]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder. Early diagnosis in the critical period is important for ASD children. Recent studies of neurodevelopmental behavioral features and joint attention in high-risk infants showed there are some special cues which can distinguish ASD from typical development infant. But the findings of high-risk population may not be applicable to the general population. It is necessary to "analogically" study the potential warning traits of ASD in infancy in the general population. We did a nested case-control study from June 2019 to November 2022 in Tianjin, China, including 76 general infants whom completed the neurodevelopmental evaluation, the Checklist for Autism in Toddlers-23 (CHAT-23) screening, and eye tracking task. Social behavior quotient in infancy was negatively correlated to CHAT-23 total scores in toddlerhood. Social behavior quotient in infancy was positively correlated to initiating joint attention in toddlerhood. Regression model showed that high fine motor scale and social behaviour scale quotient in infancy were associated with an decreased risk of the total score of CHAT-23 ≥ 2 in toddlerhood. The Receiver operating characteristic curve showed the social behaviour in infancy alone and the combination of fine motor and social behaviour in infancy contributed to auxiliary diagnosis of higher level of autistic traits in toddlerhood. These findings suggest that Impaired development of fine motor and social behavior in infancy are potential warning features of high autistic traits in general population.
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Affiliation(s)
- Wenjuan Xiong
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xinyu Li
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xiaoqing Huang
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Jinghan Xu
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Zhiyi Qu
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuanyuan Su
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yin Li
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yu Han
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Tingkai Cui
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xin Zhang
- Department of Maternal, Child & Adolescence Health, School of Public Health, Tianjin Medical University, Tianjin, China.
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Yin Y, Lyu X, Zhou J, Yu K, Huang M, Shen G, Hao C, Wang Z, Yu H, Gao B. Cerebral cortex functional reorganization in preschool children with congenital sensorineural hearing loss: a resting-state fMRI study. Front Neurol 2024; 15:1423956. [PMID: 38988601 PMCID: PMC11234816 DOI: 10.3389/fneur.2024.1423956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 06/07/2024] [Indexed: 07/12/2024] Open
Abstract
Purpose How cortical functional reorganization occurs after hearing loss in preschool children with congenital sensorineural hearing loss (CSNHL) is poorly understood. Therefore, we used resting-state functional MRI (rs-fMRI) to explore the characteristics of cortical reorganization in these patents. Methods Sixty-three preschool children with CSNHL and 32 healthy controls (HCs) were recruited, and the Categories of Auditory Performance (CAP) scores were determined at the 6-month follow-up after cochlear implantation (CI). First, rs-fMRI data were preprocessed, and amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) were calculated. Second, whole-brain functional connectivity (FC) analysis was performed using bilateral primary auditory cortex as seed points. Finally, Spearman correlation analysis was performed between the differential ALFF, ReHo and FC values and the CAP score. Results ALFF analysis showed that preschool children with CSNHL had lower ALFF values in the bilateral prefrontal cortex and superior temporal gyrus than HCs, but higher ALFF values in the bilateral thalamus and calcarine gyrus. And correlation analysis showed that some abnormal brain regions were weak negatively correlated with CAP score (p < 0.05). The ReHo values in the bilateral superior temporal gyrus, part of the prefrontal cortex and left insular gyrus were lower, whereas ReHo values in the bilateral thalamus, right caudate nucleus and right precentral gyrus were higher, in children with CSNHL than HCs. However, there was no correlation between ReHo values and the CAP scores (p < 0.05). Using primary auditory cortex (PAC) as seed-based FC further analysis revealed enhanced FC in the visual cortex, proprioceptive cortex and motor cortex. And there were weak negative correlations between the FC values in the bilateral superior temporal gyrus, occipital lobe, left postcentral gyrus and right thalamus were weakly negatively correlated and the CAP score (p < 0.05). Conclusion After auditory deprivation in preschool children with CSNHL, the local functions of auditory cortex, visual cortex, prefrontal cortex and somatic motor cortex are changed, and the prefrontal cortex plays a regulatory role in this process. There is functional reorganization or compensation between children's hearing and these areas, which may not be conducive to auditory language recovery after CI in deaf children.
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Affiliation(s)
- Yi Yin
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xinyue Lyu
- Guizhou Medical University, Guiyang, China
| | - Jian Zhou
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Kunlin Yu
- The Key Laboratory for Chemistry of Natural Product of Guizhou Province, Guizhou Medical University, Guiyang, China
| | - Mingming Huang
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Guiquan Shen
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Cheng Hao
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Zhengfu Wang
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hui Yu
- Department of Radiology, Dermatology Hospital of Southern Medical University, Guangzhou, China
| | - Bo Gao
- Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
- Key Laboratory of Brain Imaging, Guizhou Medical University, Guiyang, China
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Xu G, Geng G, Wang A, Li Z, Liu Z, Liu Y, Hu J, Wang W, Li X. Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning. Autism Res 2024. [PMID: 38925611 DOI: 10.1002/aur.3183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 06/12/2024] [Indexed: 06/28/2024]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case-control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity.
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Affiliation(s)
- Guomei Xu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Guohong Geng
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Ankang Wang
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
- Department of Neurology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Zhangyong Li
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Zhichao Liu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Yanping Liu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Jun Hu
- Department of Neurology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Wei Wang
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Xinwei Li
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
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Deng X, Yang X, Bu M, Tang A, Zhang H, Long L, Zeng Z, Wang Y, Chen P, Jiang M, Chen BT. Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation. Heliyon 2024; 10:e29529. [PMID: 38699755 PMCID: PMC11063407 DOI: 10.1016/j.heliyon.2024.e29529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 05/05/2024] Open
Abstract
Background Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI. Methods Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling. Results The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model. Conclusions The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.
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Affiliation(s)
- Xi Deng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Xueqing Yang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Meiru Bu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Anzhou Tang
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Huiting Zhang
- MR Research Collaboration, Siemens Healthineers Ltd., 430000, Wuhan, PR China
| | - Liling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Zisan Zeng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, Sichuan, PR China
| | - Ping Chen
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Muliang Jiang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Bihong T. Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, 1500 E, Duarte, CA, 91010, USA
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Mao Y, Lin X, Wu Y, Lu J, Shen J, Zhong S, Jin X, Ma J. Additive interaction between birth asphyxia and febrile seizures on autism spectrum disorder: a population-based study. Mol Autism 2024; 15:17. [PMID: 38600595 PMCID: PMC11007945 DOI: 10.1186/s13229-024-00596-3] [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: 09/18/2023] [Accepted: 03/21/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) is a pervasive neurodevelopmental disorder that can significantly impact an individual's ability to socially integrate and adapt. It's crucial to identify key factors associated with ASD. Recent studies link both birth asphyxia (BA) and febrile seizures (FS) separately to higher ASD prevalence. However, investigations into the interplay of BA and FS and its relationship with ASD are yet to be conducted. The present study mainly focuses on exploring the interactive effect between BA and FS in the context of ASD. METHODS Utilizing a multi-stage stratified cluster sampling, we initially recruited 84,934 Shanghai children aged 3-12 years old from June 2014 to June 2015, ultimately including 74,251 post-exclusion criteria. A logistic regression model was conducted to estimate the interaction effect after controlling for pertinent covariates. The attributable proportion (AP), the relative excess risk due to interaction (RERI), the synergy index (SI), and multiplicative-scale interaction were computed to determine the interaction effect. RESULTS Among a total of 74,251 children, 192 (0.26%) were diagnosed with ASD. The adjusted odds ratio for ASD in children with BA alone was 3.82 (95% confidence interval [CI] 2.42-6.02), for FS alone 3.06 (95%CI 1.48-6.31), and for comorbid BA and FS 21.18 (95%CI 9.10-49.30), versus children without BA or FS. The additive interaction between BA and FS showed statistical significance (P < 0.001), whereas the multiplicative interaction was statistically insignificant (P > 0.05). LIMITATIONS This study can only demonstrate the relationship between the interaction of BA and FS with ASD but cannot prove causation. Animal brain experimentation is necessary to unravel its neural mechanisms. A larger sample size, ongoing monitoring, and detailed FS classification are needed for confirming BA-FS interaction in ASD. CONCLUSION In this extensive cross-sectional study, both BA and FS were significantly linked to ASD. The coexistence of these factors was associated with an additive increase in ASD prevalence, surpassing the cumulative risk of each individual factor.
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Affiliation(s)
- Yi Mao
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Xindi Lin
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Yuhan Wu
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Jiayi Lu
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Jiayao Shen
- Department of Nephrology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Shaogen Zhong
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Xingming Jin
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Jun Ma
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
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Ma X, Zhou W, Zheng H, Ye S, Yang B, Wang L, Wang M, Dong GH. Connectome-based prediction of the severity of autism spectrum disorder. PSYCHORADIOLOGY 2023; 3:kkad027. [PMID: 38666105 PMCID: PMC10917386 DOI: 10.1093/psyrad/kkad027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/14/2023] [Accepted: 11/23/2023] [Indexed: 04/28/2024]
Abstract
Background Autism spectrum disorder (ASD) is characterized by social and behavioural deficits. Current diagnosis relies on behavioural criteria, but machine learning, particularly connectome-based predictive modelling (CPM), offers the potential to uncover neural biomarkers for ASD. Objective This study aims to predict the severity of ASD traits using CPM and explores differences among ASD subtypes, seeking to enhance diagnosis and understanding of ASD. Methods Resting-state functional magnetic resonance imaging data from 151 ASD patients were used in the model. CPM with leave-one-out cross-validation was conducted to identify intrinsic neural networks that predict Autism Diagnostic Observation Schedule (ADOS) scores. After the model was constructed, it was applied to independent samples to test its replicability (172 ASD patients) and specificity (36 healthy control participants). Furthermore, we examined the predictive model across different aspects of ASD and in subtypes of ASD to understand the potential mechanisms underlying the results. Results The CPM successfully identified negative networks that significantly predicted ADOS total scores [r (df = 150) = 0.19, P = 0.008 in all patients; r (df = 104) = 0.20, P = 0.040 in classic autism] and communication scores [r (df = 150) = 0.22, P = 0.010 in all patients; r (df = 104) = 0.21, P = 0.020 in classic autism]. These results were reproducible across independent databases. The networks were characterized by enhanced inter- and intranetwork connectivity associated with the occipital network (OCC), and the sensorimotor network (SMN) also played important roles. Conclusions A CPM based on whole-brain resting-state functional connectivity can predicted the severity of ASD. Large-scale networks, including the OCC and SMN, played important roles in the predictive model. These findings may provide new directions for the diagnosis and intervention of ASD, and maybe could be the targets in novel interventions.
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Affiliation(s)
- Xuefeng Ma
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Weiran Zhou
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Hui Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Shuer Ye
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Bo Yang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Lingxiao Wang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Min Wang
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
| | - Guang-Heng Dong
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
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Wang M, Xu D, Zhang L, Jiang H. Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review. Diagnostics (Basel) 2023; 13:3027. [PMID: 37835770 PMCID: PMC10571992 DOI: 10.3390/diagnostics13193027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.
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Affiliation(s)
- Miaoyan Wang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Dandan Xu
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Lili Zhang
- Department of Child Health Care, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China
| | - Haoxiang Jiang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
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Barik K, Watanabe K, Hirosawa T, Yoshimura Y, Kikuchi M, Bhattacharya J, Saha G. Autism Detection in Children using Common Spatial Patterns of MEG Signals. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083789 DOI: 10.1109/embc40787.2023.10340449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.
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She HQ, Sun YF, Chen L, Xiao QX, Luo BY, Zhou HS, Zhou D, Chang QY, Xiong LL. Current analysis of hypoxic-ischemic encephalopathy research issues and future treatment modalities. Front Neurosci 2023; 17:1136500. [PMID: 37360183 PMCID: PMC10288156 DOI: 10.3389/fnins.2023.1136500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/09/2023] [Indexed: 06/28/2023] Open
Abstract
Hypoxic-ischemic encephalopathy (HIE) is the leading cause of long-term neurological disability in neonates and adults. Through bibliometric analysis, we analyzed the current research on HIE in various countries, institutions, and authors. At the same time, we extensively summarized the animal HIE models and modeling methods. There are various opinions on the neuroprotective treatment of HIE, and the main therapy in clinical is therapeutic hypothermia, although its efficacy remains to be investigated. Therefore, in this study, we discussed the progress of neural circuits, injured brain tissue, and neural circuits-related technologies, providing new ideas for the treatment and prognosis management of HIE with the combination of neuroendocrine and neuroprotection.
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Affiliation(s)
- Hong-Qing She
- Department of Anesthesiology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Translational Neurology Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- WANG TINGHUA Translation Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Yi-Fei Sun
- Institute of Neurological Disease, West China Hospital, Sichuan University, Chengdu, China
| | - Li Chen
- Institute of Neurological Disease, West China Hospital, Sichuan University, Chengdu, China
| | - Qiu-Xia Xiao
- Institute of Neurological Disease, West China Hospital, Sichuan University, Chengdu, China
| | - Bo-Yan Luo
- WANG TINGHUA Translation Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Hong-Su Zhou
- Department of Anesthesiology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Translational Neurology Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- WANG TINGHUA Translation Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Di Zhou
- Department of Anesthesiology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Quan-Yuan Chang
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
| | - Liu-Lin Xiong
- Department of Anesthesiology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Translational Neurology Laboratory, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- WANG TINGHUA Translation Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, China
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11
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Barik K, Watanabe K, Bhattacharya J, Saha G. Functional connectivity based machine learning approach for autism detection in young children using MEG signals. J Neural Eng 2023; 20. [PMID: 36812588 DOI: 10.1088/1741-2552/acbe1f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 02/22/2023] [Indexed: 02/24/2023]
Abstract
Objective.Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, and identifying early autism biomarkers plays a vital role in improving detection and subsequent life outcomes. This study aims to reveal hidden biomarkers in the patterns of functional brain connectivity as recorded by the neuro-magnetic brain responses in children with ASD.Approach.We recorded resting-state magnetoencephalogram signals from thirty children with ASD (4-7 years) and thirty age and gender-matched typically developing (TD) children. We used a complex coherency-based functional connectivity analysis to understand the interactions between different brain regions of the neural system. The work characterizes the large-scale neural activity at different brain oscillations using functional connectivity analysis and assesses the classification performance of coherence-based (COH) measures for autism detection in young children. A comparative study has also been carried out on COH-based connectivity networks both region-wise and sensor-wise to understand frequency-band-specific connectivity patterns and their connections with autism symptomatology. We used artificial neural network (ANN) and support vector machine (SVM) classifiers in the machine learning framework with a five-fold CV technique.Main results.To classify ASD from TD children, the COH connectivity feature yields the highest classification accuracy of 91.66% in the high gamma (50-100 Hz) frequency band. In region-wise connectivity analysis, the second highest performance is in the delta band (1-4 Hz) after the gamma band. Combining the delta and gamma band features, we achieved a classification accuracy of 95.03% and 93.33% in the ANN and SVM classifiers, respectively. Using classification performance metrics and further statistical analysis, we show that ASD children demonstrate significant hyperconnectivity.Significance.Our findings support the weak central coherency theory in autism detection. Further, despite its lower complexity, we show that region-wise COH analysis outperforms the sensor-wise connectivity analysis. Altogether, these results demonstrate the functional brain connectivity patterns as an appropriate biomarker of autism in young children.
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Affiliation(s)
- Kasturi Barik
- Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Katsumi Watanabe
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan
| | - Joydeep Bhattacharya
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
| | - Goutam Saha
- Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
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12
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Sigar P, Uddin LQ, Roy D. Altered global modular organization of intrinsic functional connectivity in autism arises from atypical node-level processing. Autism Res 2023; 16:66-83. [PMID: 36333956 DOI: 10.1002/aur.2840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by restricted interests and repetitive behaviors as well as social-communication deficits. These traits are associated with atypicality of functional brain networks. Modular organization in the brain plays a crucial role in network stability and adaptability for neurodevelopment. Previous neuroimaging research demonstrates discrepancies in studies of functional brain modular organization in ASD. These discrepancies result from the examination of mixed age groups. Furthermore, recent findings suggest that while much attention has been given to deriving atlases and measuring the connections between nodes, within node information may also be crucial in determining altered modular organization in ASD compared with typical development (TD). However, altered modular organization originating from systematic nodal changes are yet to be explored in younger children with ASD. Here, we used graph-theoretical measures to fill this knowledge gap. To this end, we utilized multicenter resting-state fMRI data collected from 5 to 10-year-old children-34 ASD and 40 TD obtained from the Autism Brain Image Data Exchange (ABIDE) I and II. We demonstrate that alterations in topological roles and modular cohesiveness are the two key properties of brain regions anchored in default mode, sensorimotor, and salience networks, and primarily relate to social and sensory deficits in children with ASD. These results demonstrate that atypical global network organization in children with ASD arises from nodal role changes, and contribute to the growing body of literature suggesting that there is interesting information within nodes providing critical markers of functional brain networks in autistic children.
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Affiliation(s)
- Priyanka Sigar
- Cognitive Brain Dynamics Lab, National Brain Research Center, Manesar, India.,Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Lucina Q Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Dipanjan Roy
- Cognitive Brain Dynamics Lab, National Brain Research Center, Manesar, India.,School of AIDE, Centre for Brain Science and Applications, Karwar, India
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13
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Montenegro JTP, Seguin D, Duerden EG. Joint attention in infants at high familial risk for autism spectrum disorder and the association with thalamic and hippocampal macrostructure. Cereb Cortex Commun 2022; 3:tgac029. [PMID: 36072708 PMCID: PMC9441013 DOI: 10.1093/texcom/tgac029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder. Infants diagnosed with ASD can show impairments in spontaneous gaze-following and will seldom engage in joint attention (JA). The ability to initiate JA (IJA) can be more significantly impaired than the ability to respond to JA (RJA). In a longitudinal study, 101 infants who had a familial risk for ASD were enrolled (62% males). Participants completed magnetic resonance imaging scans at 4 or 6 months of age. Subcortical volumes (thalamus, hippocampus, amygdala, basal ganglia, ventral diencephalon, and cerebellum) were automatically extracted. Early gaze and JA behaviors were assessed with standardized measures. The majority of infants were IJA nonresponders (n = 93, 92%), and over half were RJA nonresponders (n = 50, 52%). In the nonresponder groups, models testing the association of subcortical volumes with later ASD diagnosis accounted for age, sex, and cerebral volumes. In the nonresponder IJA group, using regression method, the left hippocampus (B = −0.009, aOR = 0.991, P = 0.025), the right thalamus (B = −0.016, aOR = 0.984, P = 0.026), as well as the left thalamus (B = 0.015, aOR = 1.015, P = 0.019), predicted later ASD diagnosis. Alterations in thalamic and hippocampal macrostructure in at-risk infants who do not engage in IJA may reflect an enhanced vulnerability and may be the key predictors of later ASD development.
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Affiliation(s)
- Julia T P Montenegro
- Applied Psychology , Faculty of Education, , London, Ontario N6G1G7, Canada
- Western University, Faculty of Education Building 1137 Western Road , Faculty of Education, , London, Ontario N6G1G7, Canada
| | - Diane Seguin
- Applied Psychology , Faculty of Education, , London, Ontario N6G1G7 , Canada
- Western University, Faculty of Education Building 1137 Western Road , Faculty of Education, , London, Ontario N6G1G7 , Canada
- Physiology & Pharmacology , Schulich School of Medicine and Dentistry, , Medical Science Building, Room 216 1151 Richmond St, London, Ontario N6A5C1 , Canada
- Western University , Schulich School of Medicine and Dentistry, , Medical Science Building, Room 216 1151 Richmond St, London, Ontario N6A5C1 , Canada
| | - Emma G Duerden
- Applied Psychology , Faculty of Education, , Faculty of Education Building 1137 Western Road, London, Ontario N6G1G7 , Canada
- Western University , Faculty of Education, , Faculty of Education Building 1137 Western Road, London, Ontario N6G1G7 , Canada
- Western Institute for Neuroscience, Western University, The Brain and Mind Institute Western Interdisciplinary Research Building , Room 3190 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Biomedical Engineering , Faculty of Engineering, , Amit Chakma Engineering Building, Room 2405 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Western University , Faculty of Engineering, , Amit Chakma Engineering Building, Room 2405 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Psychiatry , Schulich School of Medicine and Dentistry, , Parkwood Institute Mental Health Care Building, F4-430, London, Ontario N6C0A7 , Canada
- University of Western Ontario , Schulich School of Medicine and Dentistry, , Parkwood Institute Mental Health Care Building, F4-430, London, Ontario N6C0A7 , Canada
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14
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Effects of Physical Activity on Social, Behavioral, and Cognitive Skills in Children and Young Adults with Autism Spectrum Disorder: a Systematic Review of the Literature. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2022. [DOI: 10.1007/s40489-022-00319-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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15
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Lan Z, Xu S, Yu X, Yu Z, Li M, Chen F, Liu Y, Wang T, Wu Y, Gan Y, Jiang G. Functional Connectivity Underlying Symptoms in Preschool Boys With Autism: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurosci 2022; 16:844821. [PMID: 35495045 PMCID: PMC9047045 DOI: 10.3389/fnins.2022.844821] [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: 12/28/2021] [Accepted: 03/23/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundSingle-sex children have been regarded as one of the best subjects to understand the abnormal development patterns of autism spectrum disorders (ASDs). However, the functional connectivity (FC) behind their symptoms is still unknown.MethodsBased on FC analysis, the acquired resting-state functional magnetic resonance imaging (rs-fMRI) data sets, including 86 boys with ASD and 54 normal controls (NC), were used to detect the neural synchronous activity between brain regions. Pearson correlation analysis was used to evaluate the relationship between the abnormal FC value and clinical features.ResultsIndividuals with ASD showed enhanced FC between the right calcarine and the right lingual gyrus (LG). The right medial orbital frontal cortex also showed increased FC with bilateral inferior temporal gyrus (ITG) [two-tailed, voxel-level p < 0.001, gaussian random field (GRF) correction, cluster-level p < 0.05]. We did not find a correlation between the abnormal FC value and clinical scales.ConclusionOur study reveals a possible relationship between atypical visual attention and poor learning ability in subjects with ASD, and delayed social language development may be a secondary symptom to ASD.
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Affiliation(s)
- Zhihong Lan
- Department of Medical Imaging, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated With Jinan University, Zhuhai, China
| | - Shoujun Xu
- Department of Radiology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Xiangrong Yu
- Department of Medical Imaging, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated With Jinan University, Zhuhai, China
| | - Zhenjie Yu
- Department of Medical Imaging, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated With Jinan University, Zhuhai, China
| | - Meng Li
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Feng Chen
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yu Liu
- Department of Medical Imaging, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated With Jinan University, Zhuhai, China
| | - Tianyue Wang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yunfan Wu
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yungen Gan
- Department of Radiology, Shenzhen Children’s Hospital, Shenzhen, China
- *Correspondence: Yungen Gan,
| | - Guihua Jiang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
- Guihua Jiang,
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16
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Bhat AN, Boulton AJ, Tulsky DS. A further study of relations between motor impairment and social communication, cognitive, language, functional impairments, and repetitive behavior severity in children with ASD using the SPARK study dataset. Autism Res 2022; 15:1156-1178. [PMID: 35357764 DOI: 10.1002/aur.2711] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 01/17/2022] [Accepted: 03/07/2022] [Indexed: 12/11/2022]
Abstract
Motor impairments are pervasive and persistent in children with autism spectrum disorder (ASD) throughout childhood and adolescence. Based on recent studies examining motor impairments in children with ASD between 5 and 15 years (i.e., SPARK study sample), 87-88% of this population is at-risk for a motor impairment, these problems persisted until 15 years, and related to their core (social communication skills and repetitive behaviors [RBs]) and comorbid (language, cognitive, and functional) impairments. Persistent motor impairments extending into adolescence/adulthood could negatively impact their independent daily living skills, physical fitness/activity levels, and physical/mental health. While multiple studies have examined relations between motor dimensions and core/comorbid impairments in young children with ASD, few studies have examined such relations in school-age children/adolescents with ASD. This paper conducts a further multidimensional study of which motor domains (i.e., gross-motor including visuo-motor or multilimb coordination/planning, fine motor [FM] or general coordination [GC] skills) best distinguish subgroups of school-age children/adolescents with ASD and help predict core and comorbid impairments after accounting for age and sex. Visuomotor, FM and certain GC skills were better at explaining variations in/predicting social communication impairments whereas FM skills were slightly better at explaining variations in/predicting RB severity. Multilimb coordination/planning and FM skills explained variations in/predicted cognitive delays whereas visuomotor and FM skills explained variations in and better predicted language delays. All three motor dimensions explained variations in/predicted functional delays. This study provides further evidence for inclusion of motor impairments within the ASD definition (criteria or specifiers). LAY SUMMARY: Gross-motor skills were related to social communication and functional delays of children with ASD (visuomotor skills related to language delays and multilimb coordination/planning skills related to cognitive delays). Fine-motor skills were related to repetitive behavior severity, language, cognitive, and functional delays in ASD. Diagnosticians should recommend systematic motor screening, further evaluations, and treatments for children at-risk for and diagnosed with ASD. Motor advocacy and enhanced public/clinical community awareness is needed to fulfill the unmet motor needs of children with ASD.
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Affiliation(s)
- Anjana N Bhat
- Department of Physical Therapy, University of Delaware, Newark, Delaware, USA.,Biomechanics & Movement Science Program, University of Delaware, Newark, Delaware, USA.,Department of Psychological & Brain Sciences, University of Delaware, Newark, Delaware, USA
| | - Aaron J Boulton
- Department of Physical Therapy, University of Delaware, Newark, Delaware, USA.,Department of Psychological & Brain Sciences, University of Delaware, Newark, Delaware, USA.,Center for Health Assessment Research and Translation, University of Delaware, Newark, Delaware, USA
| | - David S Tulsky
- Department of Physical Therapy, University of Delaware, Newark, Delaware, USA.,Department of Psychological & Brain Sciences, University of Delaware, Newark, Delaware, USA.,Center for Health Assessment Research and Translation, University of Delaware, Newark, Delaware, USA
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17
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Zhao HC, Lv R, Zhang GY, He LM, Cai XT, Sun Q, Yan CY, Bao XY, Lv XY, Fu B. Alterations of Prefrontal-Posterior Information Processing Patterns in Autism Spectrum Disorders. Front Neurosci 2022; 15:768219. [PMID: 35173572 PMCID: PMC8841879 DOI: 10.3389/fnins.2021.768219] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 12/27/2021] [Indexed: 11/22/2022] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous disorder characterized by different levels of repetitive and stereotypic behavior as well as deficits in social interaction and communication. In this current study, we explored the changes in cerebral neural activities in ASD. The purpose of this study is to investigate whether there exists a dysfunction of interactive information processing between the prefrontal cortex and posterior brain regions in ASD. We investigated the atypical connectivity and information flow between the prefrontal cortex and posterior brain regions in ASD utilizing the entropy connectivity (a kind of directional connectivity) method. Eighty-nine patients with ASD and 94 typical developing (TD) teenagers participated in this study. Two-sample t-tests revealed weakened interactive entropy connectivity between the prefrontal cortex and posterior brain regions. This result indicates that there exists interactive prefrontal-posterior underconnectivity in ASD, and this disorder might lead to less prior knowledge being used and updated. Our proposals highlighted that aforementioned atypical change might accelerate the deoptimization of brain networks in ASD.
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18
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Guo P, Lang S, Jiang M, Wang Y, Zeng Z, Wen Z, Liu Y, Chen BT. Alterations of Regional Homogeneity in Children With Congenital Sensorineural Hearing Loss: A Resting-State fMRI Study. Front Neurosci 2021; 15:678910. [PMID: 34690668 PMCID: PMC8526795 DOI: 10.3389/fnins.2021.678910] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022] Open
Abstract
Background: Brain functional alterations have been observed in children with congenital sensorineural hearing loss (CSNHL). The purpose of this study was to assess the alterations of regional homogeneity in children with CSNHL. Methods: Forty-five children with CSNHL and 20 healthy controls were enrolled into this study. Brain resting-state functional MRI (rs-fMRI) for regional homogeneity including the Kendall coefficient consistency (KCC-ReHo) and the coherence-based parameter (Cohe-ReHo) was analyzed and compared between the two groups, i.e., the CSNHL group and the healthy control group. Results: Compared to the healthy controls, children with CSNHL showed increased Cohe-ReHo values in left calcarine and decreased values in bilateral ventrolateral prefrontal cortex (VLPFC) and right dorsolateral prefrontal cortex (DLPFC). Children with CSNHL also had increased KCC-ReHo values in the left calcarine, cuneus, precentral gyrus, and right superior parietal lobule (SPL) and decreased values in the left VLPFC and right DLPFC. Correlations were detected between the ReHo values and age of the children with CSNHL. There were positive correlations between ReHo values in the pre-cuneus/pre-frontal cortex and age (p < 0.05). There were negative correlations between ReHo values in bilateral temporal lobes, fusiform gyrus, parahippocampal gyrus and precentral gyrus, and age (p < 0.05). Conclusion: Children with CSNHL had RoHo alterations in the auditory, visual, motor, and other related brain cortices as compared to the healthy controls with normal hearing. There were significant correlations between ReHo values and age in brain regions involved in information integration and processing. Our study showed promising data using rs-fMRI ReHo parameters to assess brain functional alterations in children with CSNHL.
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Affiliation(s)
- Pingping Guo
- Department of Medical Ultrasound, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China
| | - Siyuan Lang
- Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Muliang Jiang
- Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Zisan Zeng
- Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zuguang Wen
- Department of Radiology, Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Yikang Liu
- Department of Otorhinolaryngology Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States
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19
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Lian F, Northoff G. The Lost Neural Hierarchy of the Autistic Self-Locked-Out of the Mental Self and Its Default-Mode Network. Brain Sci 2021; 11:574. [PMID: 33946964 PMCID: PMC8145974 DOI: 10.3390/brainsci11050574] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 04/16/2021] [Accepted: 04/23/2021] [Indexed: 12/12/2022] Open
Abstract
Autism spectrum disorder (ASD) is characterized by a fundamental change in self-awareness including seemingly paradoxical features like increased ego-centeredness and weakened self-referentiality. What is the neural basis of this so-called "self-paradox"? Conducting a meta-analytic review of fMRI rest and task studies, we show that ASD exhibits consistent hypofunction in anterior and posterior midline regions of the default-mode network (DMN) in both rest and task with decreased self-non-self differentiation. Relying on a multilayered nested hierarchical model of self, as recently established (Qin et al. 2020), we propose that ASD subjects cannot access the most upper layer of their self, the DMN-based mental self-they are locked-out of their own DMN and its mental self. This, in turn, results in strong weakening of their self-referentiality with decreases in both self-awareness and self-other distinction. Moreover, this blocks the extension of non-DMN cortical and subcortical regions at the lower layers of the physical self to the DMN-based upper layer of the mental self, including self-other distinction. The ASD subjects remain stuck and restricted to their intero- and exteroceptive selves as manifested in a relative increase in ego-centeredness (as compared to self-referentiality). This amounts to what we describe as "Hierarchical Model of Autistic Self" (HAS), which, characterizing the autistic self in hierarchical and spatiotemporal terms, aligns well with and extends current theories of ASD including predictive coding and weak central coherence.
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Affiliation(s)
- Fuxin Lian
- Institute of Psychological Sciences, School of Education, Hangzhou Normal University, Hangzhou 311121, China;
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
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20
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Nair A, Jalal R, Liu J, Tsang T, McDonald NM, Jackson L, Ponting C, Jeste SS, Bookheimer SY, Dapretto M. Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder. Cereb Cortex 2021; 31:4191-4205. [PMID: 33866373 DOI: 10.1093/cercor/bhab078] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.
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Affiliation(s)
- Aarti Nair
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92354, USA
| | - Rhideeta Jalal
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Janelle Liu
- Interdepartmental Neuroscience Program, University of California, Los Angeles, CA 90095, USA
| | - Tawny Tsang
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Nicole M McDonald
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Lisa Jackson
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Carolyn Ponting
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Shafali S Jeste
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
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21
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Wang J, Wang X, Wang R, Duan X, Chen H, He C, Zhai J, Wu L, Chen H. Atypical Resting-State Functional Connectivity of Intra/Inter-Sensory Networks Is Related to Symptom Severity in Young Boys With Autism Spectrum Disorder. Front Physiol 2021; 12:626338. [PMID: 33868000 PMCID: PMC8044873 DOI: 10.3389/fphys.2021.626338] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/16/2021] [Indexed: 11/21/2022] Open
Abstract
Autism spectrum disorder (ASD) has been reported to have altered brain connectivity patterns in sensory networks, assessed using resting-state functional magnetic imaging (rs-fMRI). However, the results have been inconsistent. Herein, we aimed to systematically explore the interaction between brain sensory networks in 3–7-year-old boys with ASD (N = 29) using independent component analysis (ICA). Participants were matched for age, head motion, and handedness in the MRI scanner. We estimated the between-group differences in spatial patterns of the sensory resting-state networks (RSNs). Subsequently, the time series of each RSN were extracted from each participant’s preprocessed data and associated estimates of interaction strength between intra- and internetwork functional connectivity (FC) and symptom severity in children with ASD. The auditory network (AN), higher visual network (HVN), primary visual network (PVN), and sensorimotor network (SMN) were identified. Relative to TDs, individuals with ASD showed increased FC in the AN and SMN, respectively. Higher positive connectivity between the PVN and HVN in the ASD group was shown. The strength of such connections was associated with symptom severity. The current study might suggest that the abnormal connectivity patterns of the sensory network regions may underlie impaired higher-order multisensory integration in ASD children, and be associated with social impairments.
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Affiliation(s)
- Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xiaomin Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China.,Pediatric Health Care Section, Ningbo Women & Children's Hospital, Ningbo, China
| | - Runshi Wang
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xujun Duan
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Heng Chen
- School of Medicine, Guizhou University, Guiyang, China
| | - Changchun He
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jinhe Zhai
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Huafu Chen
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
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22
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Guo X, Duan X, Suckling J, Wang J, Kang X, Chen H, Biswal BB, Cao J, He C, Xiao J, Huang X, Wang R, Han S, Fan YS, Guo J, Zhao J, Wu L, Chen H. Mapping Progressive Gray Matter Alterations in Early Childhood Autistic Brain. Cereb Cortex 2021; 31:1500-1510. [PMID: 33123725 DOI: 10.1093/cercor/bhaa304] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/09/2020] [Accepted: 09/14/2020] [Indexed: 12/16/2022] Open
Abstract
Autism spectrum disorder is an early-onset neurodevelopmental condition. This study aimed to investigate the progressive structural alterations in the autistic brain during early childhood. Structural magnetic resonance imaging scans were examined in a cross-sectional sample of 67 autistic children and 63 demographically matched typically developing (TD) children, aged 2-7 years. Voxel-based morphometry and a general linear model were used to ascertain the effects of diagnosis, age, and a diagnosis-by-age interaction on the gray matter volume. Causal structural covariance network analysis was performed to map the interregional influences of brain structural alterations with increasing age. The autism group showed spatially distributed increases in gray matter volume when controlling for age-related effects, compared with TD children. A significant diagnosis-by-age interaction effect was observed in the fusiform face area (FFA, Fpeak = 13.57) and cerebellum/vermis (Fpeak = 12.73). Compared with TD children, the gray matter development of the FFA in autism displayed altered influences on that of the social brain network regions (false discovery rate corrected, P < 0.05). Our findings indicate the atypical neurodevelopment of the FFA in the autistic brain during early childhood and highlight altered developmental effects of this region on the social brain network.
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Affiliation(s)
- Xiaonan Guo
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xujun Duan
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB21 5EF, UK
| | - Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin 150086, China
| | - Xiaodong Kang
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu 611135, China
| | - Heng Chen
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.,School of Medicine, Guizhou University, Guiyang 550025, China
| | - Bharat B Biswal
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
| | - Jing Cao
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu 611135, China
| | - Changchun He
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jinming Xiao
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xinyue Huang
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Runshi Wang
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Shaoqiang Han
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yun-Shuang Fan
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jing Guo
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin 150086, China
| | - Huafu Chen
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
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23
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Bhat AN. Motor Impairment Increases in Children With Autism Spectrum Disorder as a Function of Social Communication, Cognitive and Functional Impairment, Repetitive Behavior Severity, and Comorbid Diagnoses: A SPARK Study Report. Autism Res 2021; 14:202-219. [PMID: 33300285 PMCID: PMC8176850 DOI: 10.1002/aur.2453] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 10/27/2020] [Accepted: 11/03/2020] [Indexed: 12/15/2022]
Abstract
Eighty-seven percent of a large sample of children with autism spectrum disorder (ASD) are at risk for motor impairment (Bhat, Physical Therapy, 2020, 100, 633-644). In spite of the high prevalence for motor impairment in children with ASD, it is not considered among the diagnostic criteria or specifiers within DSM-V. In this article, we analyzed the SPARK study dataset (n = 13,887) to examine associations between risk for motor impairment using the Developmental Coordination Disorder-Questionnaire (DCD-Q), social communication impairment using the Social Communication Questionnaire (SCQ), repetitive behavior severity using the Repetitive Behaviors Scale - Revised (RBS-R), and parent-reported categories of cognitive, functional, and language impairments. Upon including children with ASD with cognitive impairments, 88.2% of the SPARK sample was at risk for motor impairment. The relative risk ratio for motor impairment in children with ASD was 22.2 times greater compared to the general population and that risk further increased up to 6.2 with increasing social communication (5.7), functional (6.2), cognitive (3.8), and language (1.6) impairments as well as repetitive behavior severity (5.0). Additionally, the magnitude of risk for motor impairment (fine- and gross-motor) increased with increasing severity of all impairment types with medium to large effects. These findings highlight the multisystem nature of ASD, the need to recognize motor impairments as one of the diagnostic criteria or specifiers for ASD, and the need for appropriate motor screening and assessment of children with ASD. Interventions must address not only the social communication and cognitive/behavioral challenges of children with ASD but also their motor function and participation. LAY ABSTRACT: Eighty-eight percent of the SPARK sample of children with ASD were at risk for motor impairment. The relative risk for motor impairment was 22.2 times greater in children with ASD compared to the general population and the risk increased with more social communication, repetitive behavior, cognitive, and functional impairment. It is important to recognize motor impairments as one of the diagnostic criteria or specifiers for ASD and there is a need to administer appropriate motor screening, assessment, and interventions in children with ASD.
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Affiliation(s)
- Anjana N Bhat
- Department of Physical Therapy, University of Delaware, Newark, Delaware, USA
- Biomechanics & Movement Science Program, University of Delaware, Newark, Delaware, USA
- Department of Psychological & Brain Sciences, University of Delaware, Newark, Delaware, USA
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24
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Chen H, Long J, Yang S, He B. Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder. Autism Res 2020; 14:464-472. [PMID: 33206448 DOI: 10.1002/aur.2435] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 11/03/2020] [Accepted: 11/05/2020] [Indexed: 11/09/2022]
Abstract
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD.
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Affiliation(s)
- Heng Chen
- School of Medicine, Guizhou University, Guiyang, Guizhou, China.,Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jinjin Long
- School of Medicine, Guizhou University, Guiyang, Guizhou, China
| | - Shanshan Yang
- School of Medicine, Guizhou University, Guiyang, Guizhou, China
| | - Bifang He
- School of Medicine, Guizhou University, Guiyang, Guizhou, China.,Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
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25
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Kupis L, Romero C, Dirks B, Hoang S, Parladé MV, Beaumont AL, Cardona SM, Alessandri M, Chang C, Nomi JS, Uddin LQ. Evoked and intrinsic brain network dynamics in children with autism spectrum disorder. Neuroimage Clin 2020; 28:102396. [PMID: 32891039 PMCID: PMC7479441 DOI: 10.1016/j.nicl.2020.102396] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 07/26/2020] [Accepted: 08/19/2020] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors. METHOD 17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task. Metrics indexing brain dynamics were generated from dynamic CAPs computed across three major large-scale brain networks: midcingulo-insular (M-CIN), medial frontoparietal (M-FPN), and lateral frontoparietal (L-FPN). RESULTS Five time-varying CAPs representing dynamic co-activations among network nodes were identified across rest and task fMRI datasets. Significant Diagnosis × Condition interactions were observed for the dwell time of CAP 3, representing co-activation between nodes of the M-CIN and L-FPN, and the frequency of CAP 1, representing co-activation between nodes of the L-FPN. A significant brain-behavior association between dwell time of CAP 5, representing co-activation between nodes of the M-FPN, and social abilities was also observed across both groups of children. CONCLUSION Analysis of brain co-activation patterns reveals altered dynamics among three core networks in children with ASD, particularly evident during later stages of an attention task. Dimensional analyses demonstrating relationships between M-FPN dwell time and social abilities suggest that metrics of brain dynamics may index individual differences in social cognition and behavior.
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Affiliation(s)
- Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL, USA.
| | - Celia Romero
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Bryce Dirks
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Stephanie Hoang
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Meaghan V Parladé
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Amy L Beaumont
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Sandra M Cardona
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | | | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA.
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26
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Al-Mubarak BR, Omar A, Baz B, Al-Abdulaziz B, Magrashi AI, Al-Yemni E, Jabaan A, Monies D, Abouelhoda M, Abebe D, Ghaziuddin M, Al-Tassan NA. Whole exome sequencing in ADHD trios from single and multi-incident families implicates new candidate genes and highlights polygenic transmission. Eur J Hum Genet 2020; 28:1098-1110. [PMID: 32238911 PMCID: PMC7382449 DOI: 10.1038/s41431-020-0619-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 02/26/2020] [Accepted: 03/10/2020] [Indexed: 12/18/2022] Open
Abstract
Several types of genetic alterations occurring at numerous loci have been described in attention deficit hyperactivity disorder (ADHD). However, the role of rare single nucleotide variants (SNVs) remains under investigated. Here, we sought to identify rare SNVs with predicted deleterious effect that may contribute to ADHD risk. We chose to study ADHD families (including multi-incident) from a population with a high rate of consanguinity in which genetic risk factors tend to accumulate and therefore increasing the chance of detecting risk alleles. We employed whole exome sequencing (WES) to interrogate the entire coding region of 16 trios with ADHD. We also performed enrichment analysis on our final list of genes to identify the overrepresented biological processes. A total of 32 rare variants with predicted damaging effect were identified in 31 genes. At least two variants were detected per proband, most of which were not exclusive to the affected individuals. In addition, the majority of our candidate genes have not been previously described in ADHD including five genes (NEK4, NLE1, PSRC1, PTP4A3, and TMEM183A) that were not previously described in any human condition. Moreover, enrichment analysis highlighted brain-relevant biological themes such as "Glutamatergic synapse", "Cytoskeleton organization", and "Ca2+ pathway". In conclusion, our findings are in keeping with prior studies demonstrating the highly challenging genetic architecture of ADHD involving low penetrance, variable expressivity and locus heterogeneity.
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Affiliation(s)
- Bashayer R Al-Mubarak
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia.
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia.
| | - Aisha Omar
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
| | - Batoul Baz
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Basma Al-Abdulaziz
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
- National center for genomics technology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Amna I Magrashi
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
| | - Eman Al-Yemni
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Amjad Jabaan
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Dorota Monies
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
- Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
| | - Mohamed Abouelhoda
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
- Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
- Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Dejene Abebe
- Psychiatry Department, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia
| | | | - Nada A Al-Tassan
- Behavioral Genetics unit, Department of Genetics, King Faisal Specialist Hospital and Research Center, P.O Box 3354, Riyadh, 11211, Saudi Arabia.
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia.
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27
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Girault JB, Piven J. The Neurodevelopment of Autism from Infancy Through Toddlerhood. Neuroimaging Clin N Am 2019; 30:97-114. [PMID: 31759576 DOI: 10.1016/j.nic.2019.09.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Autism spectrum disorder (ASD) emerges during early childhood and is marked by a relatively narrow window in which infants transition from exhibiting normative behavioral profiles to displaying the defining features of the ASD phenotype in toddlerhood. Prospective brain imaging studies in infants at high familial risk for autism have revealed important insights into the neurobiology and developmental unfolding of ASD. In this article, we review neuroimaging studies of brain development in ASD from birth through toddlerhood, relate these findings to candidate neurobiological mechanisms, and discuss implications for future research and translation to clinical practice.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA.
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA
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28
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Xu S, Li M, Yang C, Fang X, Ye M, Wei L, Liu J, Li B, Gan Y, Yang B, Huang W, Li P, Meng X, Wu Y, Jiang G. Altered Functional Connectivity in Children With Low-Function Autism Spectrum Disorders. Front Neurosci 2019; 13:806. [PMID: 31427923 PMCID: PMC6688725 DOI: 10.3389/fnins.2019.00806] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2019] [Accepted: 07/18/2019] [Indexed: 11/13/2022] Open
Abstract
Neuroimaging studies have shown that autism spectrum disorders (ASDs) may be associated with abnormalities in brain structures and functions at rest as well as during cognitive tasks. However, it remains unclear if functional connectivity (FC) of all brain neural networks is also changed in these subjects. In this study, we acquired functional magnetic resonance imaging scans from 93 children with ASD and 79 matched healthy subjects. Group independent component analysis was executed for all of the participants to estimate FC. One-sample t-tests were then performed to obtain the networks for each group. Group differences in the different brain networks were tested using two-sample t-tests. Finally, relationships between abnormal FC and clinical variables were investigated with Pearson’s correlation analysis. The results from one-sample t-tests revealed nine networks with similar spatial patterns in these two groups. When compared with the controls, children with ASD showed increased connectivity in the right dorsolateral superior frontal gyrus and left middle frontal gyrus (MFG) within the occipital pole network. Children with ASD also showed decreased connectivity in the left gyrus rectus, left middle occipital gyrus, right angular gyrus, right MFG and right inferior frontal gyrus (IFG), orbital part within the lateral visual network (LVN), the left IFG, right precuneus, and right angular gyrus within the left frontoparietal (cognition) network. Furthermore, the mean FC values within the LVN showed significant positive correlations with total score of the Childhood Autism Rating Scale. Our findings indicate that abnormal FC extensively exists within some networks in children with ASD. This abnormal FC may constitute a biomarker of ASD. Our results are an important contribution to the study of neuropathophysiological mechanisms in children with ASD.
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Affiliation(s)
- Shoujun Xu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China.,Department of Radiology, Shenzhen Children's Hospital, Shenzhen, China
| | - Meng Li
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Chunlan Yang
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, China
| | - Xiangling Fang
- Department of Children Healthcare, Shenzhen Children's Hospital, Shenzhen, China
| | - Miaoting Ye
- Department of Children Healthcare, Shenzhen Children's Hospital, Shenzhen, China
| | - Lei Wei
- Network Center, Air Force Medical University, Xi'an, China
| | - Jian Liu
- Network Center, Air Force Medical University, Xi'an, China
| | - Baojuan Li
- Network Center, Air Force Medical University, Xi'an, China
| | - Yungen Gan
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen, China
| | - Binrang Yang
- Department of Children Healthcare, Shenzhen Children's Hospital, Shenzhen, China
| | - Wenxian Huang
- Department of Children Healthcare, Shenzhen Children's Hospital, Shenzhen, China
| | - Peng Li
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen, China
| | - Xianlei Meng
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen, China
| | - Yunfan Wu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guihua Jiang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
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29
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Unruh KE, Martin LE, Magnon G, Vaillancourt DE, Sweeney JA, Mosconi MW. Cortical and subcortical alterations associated with precision visuomotor behavior in individuals with autism spectrum disorder. J Neurophysiol 2019; 122:1330-1341. [PMID: 31314644 DOI: 10.1152/jn.00286.2019] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
In addition to core deficits in social-communication abilities and repetitive behaviors and interests, many patients with autism spectrum disorder (ASD) experience developmental comorbidities, including sensorimotor issues. Sensorimotor issues are common in ASD and associated with more severe clinical symptoms. Importantly, sensorimotor behaviors are precisely quantifiable and highly translational, offering promising targets for neurophysiological studies of ASD. We used functional MRI to identify brain regions associated with sensorimotor behavior using a visually guided precision gripping task in individuals with ASD (n = 20) and age-, IQ-, and handedness-matched controls (n = 18). During visuomotor behavior, individuals with ASD showed greater force variability than controls. The blood oxygen level-dependent signal for multiple cortical and subcortical regions was associated with force variability, including motor and premotor cortex, posterior parietal cortex, extrastriate cortex, putamen, and cerebellum. Activation in the right premotor cortex scaled with sensorimotor variability in controls but not in ASD. Individuals with ASD showed greater activation than controls in left putamen and left cerebellar lobule VIIb, and activation in these regions was associated with more severe clinically rated symptoms of ASD. Together, these results suggest that greater sensorimotor variability in ASD is associated with altered cortical-striatal processes supporting action selection and cortical-cerebellar circuits involved in feedback-guided reactive adjustments of motor output. Our findings also indicate that atypical organization of visuomotor cortical circuits may result in heightened reliance on subcortical circuits typically dedicated to motor skill acquisition. Overall, these results provide new evidence that sensorimotor alterations in ASD involve aberrant cortical and subcortical organization that may contribute to key clinical issues in patients.NEW & NOTEWORTHY This is the first known study to examine functional brain activation during precision visuomotor behavior in autism spectrum disorder (ASD). We replicate previous findings of elevated force variability in ASD and find these deficits are associated with atypical function of ventral premotor cortex, putamen, and posterolateral cerebellum, indicating cortical-striatal processes supporting action selection and cortical-cerebellar circuits involved in feedback-guided reactive adjustments of motor output may be key targets for understanding the neurobiology of ASD.
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Affiliation(s)
- Kathryn E Unruh
- Schiefelbusch Institute for Life Span Studies and Clinical Child Psychology Program, University of Kansas, Lawrence, Kansas.,Kansas Center for Autism Research and Training, University of Kansas Medical School, Kansas City, Kansas
| | - Laura E Martin
- Hoglund Brain Imaging Center and Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Kansas City, Kansas
| | - Grant Magnon
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - John A Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio
| | - Matthew W Mosconi
- Schiefelbusch Institute for Life Span Studies and Clinical Child Psychology Program, University of Kansas, Lawrence, Kansas.,Kansas Center for Autism Research and Training, University of Kansas Medical School, Kansas City, Kansas
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30
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Petanjek Z, Sedmak D, Džaja D, Hladnik A, Rašin MR, Jovanov-Milosevic N. The Protracted Maturation of Associative Layer IIIC Pyramidal Neurons in the Human Prefrontal Cortex During Childhood: A Major Role in Cognitive Development and Selective Alteration in Autism. Front Psychiatry 2019; 10:122. [PMID: 30923504 PMCID: PMC6426783 DOI: 10.3389/fpsyt.2019.00122] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 02/18/2019] [Indexed: 12/12/2022] Open
Abstract
The human specific cognitive shift starts around the age of 2 years with the onset of self-awareness, and continues with extraordinary increase in cognitive capacities during early childhood. Diffuse changes in functional connectivity in children aged 2-6 years indicate an increase in the capacity of cortical network. Interestingly, structural network complexity does not increase during this time and, thus, it is likely to be induced by selective maturation of a specific neuronal subclass. Here, we provide an overview of a subclass of cortico-cortical neurons, the associative layer IIIC pyramids of the human prefrontal cortex. Their local axonal collaterals are in control of the prefrontal cortico-cortical output, while their long projections modulate inter-areal processing. In this way, layer IIIC pyramids are the major integrative element of cortical processing, and changes in their connectivity patterns will affect global cortical functioning. Layer IIIC neurons have a unique pattern of dendritic maturation. In contrast to other classes of principal neurons, they undergo an additional phase of extensive dendritic growth during early childhood, and show characteristic molecular changes. Taken together, circuits associated with layer IIIC neurons have the most protracted period of developmental plasticity. This unique feature is advanced but also provides a window of opportunity for pathological events to disrupt normal formation of cognitive circuits involving layer IIIC neurons. In this manuscript, we discuss how disrupted dendritic and axonal maturation of layer IIIC neurons may lead into global cortical disconnectivity, affecting development of complex communication and social abilities. We also propose a model that developmentally dictated incorporation of layer IIIC neurons into maturing cortico-cortical circuits between 2 to 6 years will reveal a previous (perinatal) lesion affecting other classes of principal neurons. This "disclosure" of pre-existing functionally silent lesions of other neuronal classes induced by development of layer IIIC associative neurons, or their direct alteration, could be found in different forms of autism spectrum disorders. Understanding the gene-environment interaction in shaping cognitive microcircuitries may be fundamental for developing rehabilitation and prevention strategies in autism spectrum and other cognitive disorders.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Domagoj Džaja
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Mladen Roko Rašin
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, United States
| | - Nataša Jovanov-Milosevic
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Medical Biology, School of Medicine, University of Zagreb, Zagreb, Croatia
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