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Kirkovski M, Singh M, Dhollander T, Fuelscher I, Hyde C, Albein-Urios N, Donaldson PH, Enticott PG. An Investigation of Age-related Neuropathophysiology in Autism Spectrum Disorder Using Fixel-based Analysis of Corpus Callosum White Matter Micro- and Macrostructure. J Autism Dev Disord 2024; 54:2198-2210. [PMID: 37079181 PMCID: PMC11143064 DOI: 10.1007/s10803-023-05980-1] [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] [Accepted: 03/29/2023] [Indexed: 04/21/2023]
Abstract
Fixel-based analysis was used to probe age-related changes in white matter micro- and macrostructure of the corpus callosum between participants with (N = 54) and without (N = 50) autism spectrum disorder (ASD). Data were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Compared to age-matched controls, young adolescents with ASD (11.19 ± 7.54 years) showed reduced macroscopic fiber cross-section (logFC) and combined fiber-density and cross-section (FDC). Reduced fiber-density (FD) and FDC was noted in a marginally older (13.87 ± 3.15 years) ASD cohort. Among the oldest ASD cohort (17.07 ± 3.56 years), a non-significant trend indicative of reduced FD was noted. White matter aberration appears greatest and most widespread among younger ASD cohorts. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.
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Affiliation(s)
- Melissa Kirkovski
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia.
- Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia.
| | - Mervyn Singh
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Thijs Dhollander
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Natalia Albein-Urios
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Peter H Donaldson
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
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Nagai Y, Kirino E, Tanaka S, Usui C, Inami R, Inoue R, Hattori A, Uchida W, Kamagata K, Aoki S. Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI. Cereb Cortex 2024; 34:129-145. [PMID: 38012112 PMCID: PMC11065111 DOI: 10.1093/cercor/bhad451] [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: 07/22/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.
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Affiliation(s)
- Yasuhito Nagai
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, 1129 Nagaoka Izunokuni-shi Shizuoka 410-2295, Japan
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Shoji Tanaka
- Department of Information and Communication Sciences, Sophia University, 7-1 Kioi-cho Chiyoda-ku Tokyo 102-8554, Japan
| | - Chie Usui
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Rie Inami
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Reiichi Inoue
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Aki Hattori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode Urayasu-shi Chiba 279-0013, Japan
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3
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Adil D, Duerden EG, Eagleson R, de Ribaupierre S. Structural Alterations of the Corpus Callosum in Children With Infantile Hydrocephalus. J Child Neurol 2024; 39:66-76. [PMID: 38387869 PMCID: PMC11083734 DOI: 10.1177/08830738241231343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/17/2024] [Accepted: 01/22/2024] [Indexed: 02/24/2024]
Abstract
This study investigates structural alterations of the corpus callosum in children diagnosed with infantile hydrocephalus. We aim to assess both macrostructural (volume) and microstructural (diffusion tensor imaging metrics) facets of the corpus callosum, providing insights into the nature and extent of alterations associated with this condition. Eighteen patients with infantile hydrocephalus (mean age = 9 years) and 18 age- and sex-matched typically developing healthy children participated in the study. Structural magnetic resonance imaging and diffusion tensor imaging were used to assess corpus callosum volume and microstructure, respectively. Our findings reveal significant alterations in corpus callosum volume, particularly in the posterior area, as well as distinct microstructural disparities, notably pronounced in these same segments. These results highlight the intricate interplay between macrostructural and microstructural aspects in understanding the impact of infantile hydrocephalus. Examining these structural alterations provides an understanding into the mechanisms underlying the effects of infantile hydrocephalus on corpus callosum integrity, given its pivotal role in interhemispheric communication. This knowledge offers a more nuanced perspective on neurologic disorders and underscores the significance of investigating the corpus callosum's health in such contexts.
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Affiliation(s)
- Derya Adil
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
| | - Emma G. Duerden
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
- Applied Psychology, Faculty of Education, Western University, London, Ontario, Canada
| | - Roy Eagleson
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
- Electrical and Computer Engineering, Faculty of Engineering, Western University, London, Ontario, Canada
| | - Sandrine de Ribaupierre
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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4
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Liloia D, Cauda F, Uddin LQ, Manuello J, Mancuso L, Keller R, Nani A, Costa T. Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1075-1083. [PMID: 35131520 DOI: 10.1016/j.bpsc.2022.01.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 12/30/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies. METHODS Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD. RESULTS We found that specific brain areas exhibit a >90% probability of gray matter alteration selectivity for ASD: the bilateral precuneus (Brodmann area 7), right inferior occipital gyrus (Brodmann area 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network. CONCLUSIONS The identification of these spatial gray matter alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD and opens attractive prospects for future neuroimaging-based interventions.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy
| | - Lucina Q Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California
| | - Jordi Manuello
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Andrea Nani
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy
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Chen Z, Hu B, Liu X, Becker B, Eickhoff SB, Miao K, Gu X, Tang Y, Dai X, Li C, Leonov A, Xiao Z, Feng Z, Chen J, Chuan-Peng H. Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry. BMC Med 2023; 21:241. [PMID: 37400814 DOI: 10.1186/s12916-023-02941-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/13/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation. METHODS Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses. RESULTS A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (β = - 2.75, p < .001, R2adj = 0.40; r = - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF10 > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance. CONCLUSIONS Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.
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Affiliation(s)
- Zhiyi Chen
- Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Third Military Medical University, Chongqing, China.
- Faculty of Psychology, Southwest University, Chongqing, China.
| | - Bowen Hu
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Xuerong Liu
- Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Third Military Medical University, Chongqing, China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, Chengdu, China
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kuan Miao
- Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Third Military Medical University, Chongqing, China
| | - Xingmei Gu
- Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Third Military Medical University, Chongqing, China
| | - Yancheng Tang
- School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Xin Dai
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Chao Li
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangdong, China
| | - Artemiy Leonov
- School of Psychology, Clark University, Worcester, MA, USA
| | - Zhibing Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zhengzhi Feng
- Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Third Military Medical University, Chongqing, China
| | - Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
- Department of Psychiatry, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China.
| | - Hu Chuan-Peng
- School of Psychology, Nanjing Normal University, Nanjing, China
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6
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Chen Z, Liu X, Yang Q, Wang YJ, Miao K, Gong Z, Yu Y, Leonov A, Liu C, Feng Z, Chuan-Peng H. Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review. JAMA Netw Open 2023; 6:e231671. [PMID: 36877519 PMCID: PMC9989906 DOI: 10.1001/jamanetworkopen.2023.1671] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2023] Open
Abstract
IMPORTANCE Neuroimaging-based artificial intelligence (AI) diagnostic models have proliferated in psychiatry. However, their clinical applicability and reporting quality (ie, feasibility) for clinical practice have not been systematically evaluated. OBJECTIVE To systematically assess the risk of bias (ROB) and reporting quality of neuroimaging-based AI models for psychiatric diagnosis. EVIDENCE REVIEW PubMed was searched for peer-reviewed, full-length articles published between January 1, 1990, and March 16, 2022. Studies aimed at developing or validating neuroimaging-based AI models for clinical diagnosis of psychiatric disorders were included. Reference lists were further searched for suitable original studies. Data extraction followed the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A closed-loop cross-sequential design was used for quality control. The PROBAST (Prediction Model Risk of Bias Assessment Tool) and modified CLEAR (Checklist for Evaluation of Image-Based Artificial Intelligence Reports) benchmarks were used to systematically evaluate ROB and reporting quality. FINDINGS A total of 517 studies presenting 555 AI models were included and evaluated. Of these models, 461 (83.1%; 95% CI, 80.0%-86.2%) were rated as having a high overall ROB based on the PROBAST. The ROB was particular high in the analysis domain, including inadequate sample size (398 of 555 models [71.7%; 95% CI, 68.0%-75.6%]), poor model performance examination (with 100% of models lacking calibration examination), and lack of handling data complexity (550 of 555 models [99.1%; 95% CI, 98.3%-99.9%]). None of the AI models was perceived to be applicable to clinical practices. Overall reporting completeness (ie, number of reported items/number of total items) for the AI models was 61.2% (95% CI, 60.6%-61.8%), and the completeness was poorest for the technical assessment domain with 39.9% (95% CI, 38.8%-41.1%). CONCLUSIONS AND RELEVANCE This systematic review found that the clinical applicability and feasibility of neuroimaging-based AI models for psychiatric diagnosis were challenged by a high ROB and poor reporting quality. Particularly in the analysis domain, ROB in AI diagnostic models should be addressed before clinical application.
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Affiliation(s)
- Zhiyi Chen
- School of Psychology, Third Military Medical University, Chongqing, China
- Experimental Research Center for Medical and Psychological Science, Third Military Medical University, Chongqing, China
| | - Xuerong Liu
- School of Psychology, Third Military Medical University, Chongqing, China
- Experimental Research Center for Medical and Psychological Science, Third Military Medical University, Chongqing, China
| | - Qingwu Yang
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Yan-Jiang Wang
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Kuan Miao
- School of Psychology, Third Military Medical University, Chongqing, China
- Experimental Research Center for Medical and Psychological Science, Third Military Medical University, Chongqing, China
| | - Zheng Gong
- School of Psychology, Third Military Medical University, Chongqing, China
- Experimental Research Center for Medical and Psychological Science, Third Military Medical University, Chongqing, China
| | - Yang Yu
- School of Psychology, Third Military Medical University, Chongqing, China
| | - Artemiy Leonov
- Department of Psychology, Clark University, Worcester, Massachusetts
| | - Chunlei Liu
- School of Psychology, Qufu Normal University, Qufu, China
| | - Zhengzhi Feng
- School of Psychology, Third Military Medical University, Chongqing, China
- Experimental Research Center for Medical and Psychological Science, Third Military Medical University, Chongqing, China
| | - Hu Chuan-Peng
- School of Psychology, Nanjing Normal University, Nanjing, China
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Awad PN, Zerbi V, Johnson-Venkatesh EM, Damiani F, Pagani M, Markicevic M, Nickles S, Gozzi A, Umemori H, Fagiolini M. CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility. Mol Psychiatry 2023:10.1038/s41380-023-01962-y. [PMID: 36737483 DOI: 10.1038/s41380-023-01962-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 01/02/2023] [Accepted: 01/13/2023] [Indexed: 02/05/2023]
Abstract
Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in the brain, which are particularly important for higher-order cognitive function and flexibility. However, whether a causal relationship exists between interhemispheric connectivity alterations and cognitive deficits in NDD remains elusive. Here, we focused on CDKL5 Deficiency Disorder (CDD), a severe neurodevelopmental disorder caused by mutations in the X-linked Cyclin-dependent kinase-like 5 (CDKL5) gene. We found an increase in homotopic interhemispheric connectivity and functional hyperconnectivity across higher cognitive areas in adult male and female CDKL5-deficient mice by resting-state functional MRI (rs-fMRI) analysis. This was accompanied by an increase in the number of callosal synaptic inputs but decrease in local synaptic connectivity in the cingulate cortex of juvenile CDKL5-deficient mice, suggesting an impairment in excitatory synapse development and a differential role of CDKL5 across excitatory neuron subtypes. These deficits were associated with significant cognitive impairments in CDKL5 KO mice. Selective deletion of CDKL5 in the largest subtype of CPN likewise resulted in an increase of functional callosal inputs, without however significantly altering intracortical cingulate networks. Notably, such callosal-specific changes were sufficient to cause cognitive deficits. Finally, when CDKL5 was selectively re-expressed only in this CPN subtype, in otherwise CDKL5-deficient mice, it was sufficient to prevent the cognitive impairments of CDKL5 mutants. Together, these results reveal a novel role of CDKL5 by demonstrating that it is both necessary and sufficient for proper CPN connectivity and cognitive function and flexibility, and further validates a causal relationship between CPN dysfunction and cognitive impairment in a model of NDD.
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Affiliation(s)
- Patricia Nora Awad
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuro-X Institute, School of Engineering (STI), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Erin M Johnson-Venkatesh
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Francesca Damiani
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
- Autism Center, Child Mind Institute, New York, NY, USA
| | - Marija Markicevic
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Sarah Nickles
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Hisashi Umemori
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michela Fagiolini
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Hock E. Tan and K. Lisa Yang Center for Autism Research at Harvard University, Boston, MA, USA.
- International Research Center for Neurointelligence (IRCN), University of Tokyo Institutes for Advanced Study, Tokyo, Japan.
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8
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Previously Marzena Szkodo MOR, Micai M, Caruso A, Fulceri F, Fazio M, Scattoni ML. Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review. Neurosci Biobehav Rev 2023; 145:105021. [PMID: 36581169 DOI: 10.1016/j.neubiorev.2022.105021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 12/27/2022]
Abstract
In recent years, there has been a great interest in utilizing technology in mental health research. The rapid technological development has encouraged researchers to apply technology as a part of a diagnostic process or treatment of Neurodevelopmental Disorders (NDDs). With the large number of studies being published comes an urgent need to inform clinicians and researchers about the latest advances in this field. Here, we methodically explore and summarize findings from studies published between August 2019 and February 2022. A search strategy led to the identification of 4108 records from PubMed and APA PsycInfo databases. 221 quantitative studies were included, covering a wide range of technologies used for diagnosis and/or treatment of NDDs, with the biggest focus on Autism Spectrum Disorder (ASD). The most popular technologies included machine learning, functional magnetic resonance imaging, electroencephalogram, magnetic resonance imaging, and neurofeedback. The results of the review indicate that technology-based diagnosis and intervention for NDD population is promising. However, given a high risk of bias of many studies, more high-quality research is needed.
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Affiliation(s)
| | - Martina Micai
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Angela Caruso
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Francesca Fulceri
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Maria Fazio
- Department of Mathematics, Computer Science, Physics and Earth Sciences (MIFT), University of Messina, Viale F. Stagno d'Alcontres, 31, 98166 Messina, Italy.
| | - Maria Luisa Scattoni
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
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9
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Zhang G, Liu T, Wei W, Zhang R, Wang H, Wang M. Evaluation of altered brain activity in type 2 diabetes using various indices of brain function: A resting-state functional magnetic resonance imaging study. Front Hum Neurosci 2023; 16:1032264. [PMID: 36699964 PMCID: PMC9870028 DOI: 10.3389/fnhum.2022.1032264] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/05/2022] [Indexed: 01/11/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) has been identified as a risk factor that increases the rate of cognitive decline. Previous studies showed that patients with T2DM had brain function alterations based on a single index of resting-state functional magnetic resonance imaging (rs-fMRI). The present study aimed to explore spontaneous brain activity in patients with T2DM by comparing various rs-fMRI indices, and to determine the relationship between these changes and cognitive dysfunction. Methods A total of 52 patients with T2DM and age- and sex-matched control participants were included in this study. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) values were calculated to represent the status of spontaneous neural activity. The Montreal Cognitive Assessment (MoCA) was used for the rapid evaluation of cognition in all subjects. Pearson correlation and mediation analyses were conducted to investigate the relationship between rs-fMRI indices and clinical parameters such as fasting glucose, disease duration, and MoCA. Results Patients with T2DM had alterations of concordant spontaneous brain activity in brain areas including the bilateral cerebellum posterior lobe, the left inferior temporal gyrus (ITG.L), the parahippocampal gyrus, and the left supplementary motor area (SMA.L). The indices were significantly correlated to each other in most of the detected brain areas. Positive correlations were observed between fasting glucose and neural activity in the surrounding areas of the left insula and the inferior frontal gyrus. MoCA scores were negatively correlated with the ReHo values extracted from the left anterior occipital lobe and the superior cerebellar cortex and were positively correlated with VMHC values extracted from the left caudate and the precentral gyrus (PreCG). No significant mediation effect of abnormal brain activity was found in the relationship between clinical parameters and MoCA scores. Conclusion The current study demonstrated the functional concordance of abnormal brain activities in patients with T2DM by comparing ALFF, ReHo, and VMHC measurements. Widespread abnormalities mainly involved in motor and sensory processing functions may provide insight into examining T2DM-related neurological pathophysiology.
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Affiliation(s)
- Ge Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Taiyuan Liu
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Rui Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Huilin Wang
- Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China,*Correspondence: Huilin Wang ✉
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Laboratory of Brian Science and Brain-Like Intelligence Technology, Institute for Integrated Medical Science and Engineering, Henan Academy of Sciences, Zhengzhou, China,Meiyun Wang ✉
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Parellada M, Andreu-Bernabeu Á, Burdeus M, San José Cáceres A, Urbiola E, Carpenter LL, Kraguljac NV, McDonald WM, Nemeroff CB, Rodriguez CI, Widge AS, State MW, Sanders SJ. In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review. Am J Psychiatry 2023; 180:23-40. [PMID: 36475375 PMCID: PMC10123775 DOI: 10.1176/appi.ajp.21100992] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. METHODS A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included. RESULTS A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis." CONCLUSIONS There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.
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Affiliation(s)
- Mara Parellada
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Álvaro Andreu-Bernabeu
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Mónica Burdeus
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Antonia San José Cáceres
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Elena Urbiola
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Linda L Carpenter
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Nina V Kraguljac
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - William M McDonald
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Charles B Nemeroff
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Carolyn I Rodriguez
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Alik S Widge
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Matthew W State
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
| | - Stephan J Sanders
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid (Parellada, Andreu-Bernabeu, Burdeus, San José Cáceres, Urbiola); CIBERSAM, Spain (Parellada, Burdeus, San José Cáceres); School of Medicine, Universidad Complutense, Madrid (Parellada); Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, and Butler Hospital, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, Mulva Clinic for the Neurosciences, Institute of Early Life Adversity Research, Dell Medical School, University of Texas at Austin (Nemeroff); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Rodriguez); Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco (State, Sanders)
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Desprez F, Ung DC, Vourc’h P, Jeanne M, Laumonnier F. Contribution of the dihydropyrimidinase-like proteins family in synaptic physiology and in neurodevelopmental disorders. Front Neurosci 2023; 17:1154446. [PMID: 37144098 PMCID: PMC10153444 DOI: 10.3389/fnins.2023.1154446] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 03/15/2023] [Indexed: 05/06/2023] Open
Abstract
The dihydropyrimidinase-like (DPYSL) proteins, also designated as the collapsin response mediators (CRMP) proteins, constitute a family of five cytosolic phosphoproteins abundantly expressed in the developing nervous system but down-regulated in the adult mouse brain. The DPYSL proteins were initially identified as effectors of semaphorin 3A (Sema3A) signaling and consequently involved in regulation of growth cone collapse in young developing neurons. To date, it has been established that DPYSL proteins mediate signals for numerous intracellular/extracellular pathways and play major roles in variety of cellular process including cell migration, neurite extension, axonal guidance, dendritic spine development and synaptic plasticity through their phosphorylation status. The roles of DPYSL proteins at early stages of brain development have been described in the past years, particularly for DPYSL2 and DPYSL5 proteins. The recent characterization of pathogenic genetic variants in DPYSL2 and in DPYSL5 human genes associated with intellectual disability and brain malformations, such as agenesis of the corpus callosum and cerebellar dysplasia, highlighted the pivotal role of these actors in the fundamental processes of brain formation and organization. In this review, we sought to establish a detailed update on the knowledge regarding the functions of DPYSL genes and proteins in brain and to highlight their involvement in synaptic processing in later stages of neurodevelopment, as well as their particular contribution in human neurodevelopmental disorders (NDDs), such as autism spectrum disorders (ASD) and intellectual disability (ID).
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Affiliation(s)
| | - Dévina C. Ung
- UMR1253, iBrain, Inserm, University of Tours, Tours, France
| | - Patrick Vourc’h
- UMR1253, iBrain, Inserm, University of Tours, Tours, France
- Service de Génétique, Centre Hospitalier Régional Universitaire, Tours, France
- Laboratoire de Biochimie et de Biologie Moléculaire, Centre Hospitalier Régional Universitaire, Tours, France
| | - Médéric Jeanne
- UMR1253, iBrain, Inserm, University of Tours, Tours, France
- Service de Génétique, Centre Hospitalier Régional Universitaire, Tours, France
| | - Frédéric Laumonnier
- UMR1253, iBrain, Inserm, University of Tours, Tours, France
- Service de Génétique, Centre Hospitalier Régional Universitaire, Tours, France
- *Correspondence: Frédéric Laumonnier,
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Yao S, Kendrick KM. Reduced homotopic interhemispheric connectivity in psychiatric disorders: evidence for both transdiagnostic and disorder specific features. PSYCHORADIOLOGY 2022; 2:129-145. [PMID: 38665271 PMCID: PMC11003433 DOI: 10.1093/psyrad/kkac016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 04/28/2024]
Abstract
There is considerable interest in the significance of structural and functional connections between the two brain hemispheres in terms of both normal function and in relation to psychiatric disorders. In recent years, many studies have used voxel mirrored homotopic connectivity analysis of resting state data to investigate the importance of connectivity between homotopic regions in the brain hemispheres in a range of neuropsychiatric disorders. The current review summarizes findings from these voxel mirrored homotopic connectivity studies in individuals with autism spectrum disorder, addiction, attention deficit hyperactivity disorder, anxiety and depression disorders, and schizophrenia, as well as disorders such as Alzheimer's disease, mild cognitive impairment, epilepsy, and insomnia. Overall, other than attention deficit hyperactivity disorder, studies across psychiatric disorders report decreased homotopic resting state functional connectivity in the default mode, attention, salience, sensorimotor, social cognition, visual recognition, primary visual processing, and reward networks, which are often associated with symptom severity and/or illness onset/duration. Decreased homotopic resting state functional connectivity may therefore represent a transdiagnostic marker for general psychopathology. In terms of disorder specificity, the extensive decreases in homotopic resting state functional connectivity in autism differ markedly from attention deficit hyperactivity disorder, despite both occurring during early childhood and showing extensive co-morbidity. A pattern of more posterior than anterior regions showing reductions in schizophrenia is also distinctive. Going forward, more studies are needed to elucidate the functions of these homotopic functional connections in both health and disorder and focusing on associations with general psychopathology, and not only on disorder specific symptoms.
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Affiliation(s)
- Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
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Wu X, Lin F, Zhang T, Sun H, Li J. Acquisition time for functional near-infrared spectroscopy resting-state functional connectivity in assessing autism. NEUROPHOTONICS 2022; 9:045007. [PMID: 36466187 PMCID: PMC9709191 DOI: 10.1117/1.nph.9.4.045007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
SIGNIFICANCE Resting state functional connectivity (RSFC) can be used to assess autism spectrum disorder (ASD). Measuring RSFC usually takes 5 to 10 min, during which children with ASD may have difficulty keeping their heads motionless. Therefore, a short acquisition time for RSFC would make clinical implementation more feasible. AIM To find a suitable acquisition time necessary for measuring RSFC with functional near-infrared spectroscopy (fNIRS) for the differentiation between children with ASD and typically developing (TD) children. APPROACH We used fNIRS to record the spontaneous hemodynamic fluctuations from the bilateral temporal lobes of 25 children with ASD and 22 TD children. The recorded signals were truncated into several segments with different time windows, and then the homotopic RSFC was computed for each of these segments and compared between the two groups. RESULTS We observed even in a very short time duration of 0.5 min, the RSFC had already existed a significant difference between the two groups, and 2.0 min might be the minimal time required for measuring RSFC for accurate differentiation between the two groups. CONCLUSIONS The fNIRS-RSFC acquired even in a short time, e.g., 2.0 min, might be a reliable feature for the differentiation between children with ASD and TD children.
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Affiliation(s)
- Xiaoyin Wu
- South China Normal University, South China Academy of Advanced Optoelectronics, Guangzhou, China
| | - Fang Lin
- South China Normal University, South China Academy of Advanced Optoelectronics, Guangzhou, China
| | - Tingzhen Zhang
- South China Normal University, South China Academy of Advanced Optoelectronics, Guangzhou, China
| | - Huiwen Sun
- South China Normal University, South China Academy of Advanced Optoelectronics, Guangzhou, China
| | - Jun Li
- South China Normal University, South China Academy of Advanced Optoelectronics, Guangzhou, China
- South China Normal University, Key Lab for Behavioral Economic Science and Technology, Guangzhou, China
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Shi C, Xin X, Zhang J. A novel multigranularity feature-selection method based on neighborhood mutual information and its application in autistic patient identification. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Prany W, Patrice C, Franck D, Fabrice W, Mahdi M, Pierre D, Christian M, Jean-Marc G, Fabian G, Francis E, Jean-Marc B, Bérengère GG. EEG resting-state functional connectivity: evidence for an imbalance of external/internal information integration in autism. J Neurodev Disord 2022; 14:47. [PMID: 36030210 PMCID: PMC9419397 DOI: 10.1186/s11689-022-09456-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 08/04/2022] [Indexed: 01/12/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD. Methods Using high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched). Results We observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band. Conclusion These results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts. Supplementary Information The online version contains supplementary material available at 10.1186/s11689-022-09456-8.
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Affiliation(s)
- Wantzen Prany
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Université de Paris, LaPsyDÉ, CNRS, F-75005, Paris, France
| | - Clochon Patrice
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Doidy Franck
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Wallois Fabrice
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Mahmoudzadeh Mahdi
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Desaunay Pierre
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Mille Christian
- Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guilé Jean-Marc
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France.,Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guénolé Fabian
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Eustache Francis
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Baleyte Jean-Marc
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Service de Psychiatrie de l'enfant et de l'adolescent, Centre Hospitalier Interuniversitaire de Créteil, 94000, Créteil, France
| | - Guillery-Girard Bérengère
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.
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16
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Takeguchi R, Kuroda M, Tanaka R, Suzuki N, Akaba Y, Tsujimura K, Itoh M, Takahashi S. Structural and functional changes in the brains of patients with Rett syndrome: A multimodal MRI study. J Neurol Sci 2022; 441:120381. [PMID: 36027642 DOI: 10.1016/j.jns.2022.120381] [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: 04/26/2022] [Revised: 08/05/2022] [Accepted: 08/14/2022] [Indexed: 10/15/2022]
Abstract
OBJECTIVE To clarify the relationship between structural and functional changes in the brains of patients with Rett syndrome (RTT) using multimodal magnetic resonance imaging (MRI). METHODS Nine subjects with typical RTT (RTTs) and an equal number of healthy controls (HCs) underwent structural MRI, diffusion tensor imaging (DTI), and resting-state functional MRI (rs-fMRI). The measurements obtained from each modality were statistically compared between RTTs and HCs and examined for their correlation with the clinical severity of RTTs. RESULTS Structural MRI imaging revealed volume reductions in most cortical and subcortical regions of the brain. Remarkable volume reductions were observed in the frontal and parietal lobes, cerebellum, and subcortical regions including the putamen, hippocampus, and corpus callosum. DTI analysis revealed decreased white matter integrity in broad regions of the brain. Fractional anisotropy values were greatly decreased in the superior longitudinal fasciculus, corpus callosum, and middle cerebellar peduncle. Rs-fMRI analysis showed decreased functional connectivity in the interhemispheric dorsal attention network, and between the visual and cerebellar networks. The clinical severity of RTTs correlated with the volume reduction of the frontal lobe and cerebellum, and with changes in DTI indices in the fronto-occipital fasciculus, corpus callosum, and cerebellar peduncles. CONCLUSION Regional volume and white matter integrity of RTT brains were reduced in broad areas, while most functional connections remained intact. Notably, two functional connectivities, between cerebral hemispheres and between the cerebrum and cerebellum, were decreased in RTT brains, which may reflect the structural changes in these brain regions.
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Affiliation(s)
- Ryo Takeguchi
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan.
| | - Mami Kuroda
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan
| | - Ryosuke Tanaka
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan
| | - Nao Suzuki
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan
| | - Yuichi Akaba
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan; Group of Brain Function and Development, Nagoya University Neuroscience Institute of the Graduate School of Science, Nagoya, Aichi 464-8602, Japan; Research Unit for Developmental Disorders, Institute for Advanced Research, Nagoya University, Nagoya, Aichi 464-8602, Japan
| | - Keita Tsujimura
- Group of Brain Function and Development, Nagoya University Neuroscience Institute of the Graduate School of Science, Nagoya, Aichi 464-8602, Japan; Research Unit for Developmental Disorders, Institute for Advanced Research, Nagoya University, Nagoya, Aichi 464-8602, Japan
| | - Masayuki Itoh
- Department of Mental Retardation and Birth Defect Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan
| | - Satoru Takahashi
- Department of Pediatrics, Asahikawa Medical University, Hokkaido 078-8510, Japan
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17
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Ji J, Ren Y, Lei M. FC–HAT: Hypergraph attention network for functional brain network classification. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.07.041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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18
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Zhao H, Cai H, Mo F, Lu Y, Yao S, Yu Y, Zhu J. Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study. Cereb Cortex 2022; 33:3387-3400. [PMID: 35851912 DOI: 10.1093/cercor/bhac279] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/22/2022] [Accepted: 06/23/2022] [Indexed: 11/15/2022] Open
Abstract
Abstract
Functional homotopy, the high degree of spontaneous activity synchrony and functional coactivation between geometrically corresponding interhemispheric regions, is a fundamental characteristic of the intrinsic functional architecture of the brain. However, little is known about the genetic mechanisms underlying functional homotopy. Resting-state functional magnetic resonance imaging data from a discovery dataset (656 healthy subjects) and 2 independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects) were used to calculate voxel-mirrored homotopic connectivity (VMHC) indexing brain functional homotopy. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analysis was conducted to identify genes linked to VMHC. We found 1,001 genes whose expression measures were spatially associated with VMHC. Functional enrichment analyses demonstrated that these VMHC-related genes were enriched for biological functions including protein kinase activity, ion channel regulation, and synaptic function as well as many neuropsychiatric disorders. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons and immune cells, and during nearly all developmental periods. In addition, the VMHC-associated genes were linked to multiple behavioral domains, including vision, execution, and attention. Our findings suggest that interhemispheric communication and coordination involve a complex interaction of polygenes with a rich range of functional features.
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Affiliation(s)
- Han Zhao
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Huanhuan Cai
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Fan Mo
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Yun Lu
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Shanwen Yao
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Yongqiang Yu
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
| | - Jiajia Zhu
- Department of Radiology , The First Affiliated Hospital of Anhui Medical University, Hefei 230022 , China
- Research Center of Clinical Medical Imaging , Anhui Province, Hefei 230032 , China
- Anhui Provincial Institute of Translational Medicine , Hefei 230032 , China
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19
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Sader M, Williams JHG, Waiter GD. A meta-analytic investigation of grey matter differences in anorexia nervosa and autism spectrum disorder. EUROPEAN EATING DISORDERS REVIEW 2022; 30:560-579. [PMID: 35526083 PMCID: PMC9543727 DOI: 10.1002/erv.2915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 04/21/2022] [Indexed: 11/11/2022]
Abstract
Recent research reports Anorexia Nervosa (AN) to be highly dependent upon neurobiological function. Some behaviours, particularly concerning food selectivity are found in populations with both Autism Spectrum Disorder (ASD) and AN, and there is a proportionally elevated number of anorexic patients exhibiting symptoms of ASD. We performed a systematic review of structural MRI literature with the aim of identifying common structural neural correlates common to both AN and ASD. Across 46 ASD publications, a meta‐analysis of volumetric differences between ASD and healthy controls revealed no consistently affected brain regions. Meta‐analysis of 23 AN publications revealed increased volume within the orbitofrontal cortex and medial temporal lobe, and adult‐only AN literature revealed differences within the genu of the anterior cingulate cortex. The changes are consistent with alterations in flexible reward‐related learning and episodic memory reported in neuropsychological studies. There was no structural overlap between ASD and AN. Findings suggest no consistent neuroanatomical abnormality associated with ASD, and evidence is lacking to suggest that reported behavioural similarities between those with AN and ASD are due to neuroanatomical structural similarities. Findings related to neuroanatomical structure in AN/ASD demonstrate overlap and require revisiting. Meta‐analytic findings show structural increase/decrease versus healthy controls (LPFC/MTL/OFC) in AN, but no clusters found in ASD. The neuroanatomy associated with ASD is inconsistent, but findings in AN reflect condition‐related impairment in executive function and sociocognitive behaviours.
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Affiliation(s)
- Michelle Sader
- Translational Neuroscience, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Justin H G Williams
- Translational Neuroscience, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Gordon D Waiter
- Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
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20
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Li Y, Li C, Jiang L. Well-Being Is Associated With Local to Remote Cortical Connectivity. Front Behav Neurosci 2022; 16:737121. [PMID: 35368310 PMCID: PMC8967134 DOI: 10.3389/fnbeh.2022.737121] [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: 07/06/2021] [Accepted: 02/07/2022] [Indexed: 11/13/2022] Open
Abstract
Wellbeing refers to cognitive and emotional appraisal of an individual’s life and social functioning, which is of great significance to the quality of life of an individual and society. Previous studies have revealed the neural basis of wellbeing, which mostly focused on human brain morphology or network-level connectivity. However, local-to-remote cortical connectivity, which plays a crucial role in defining the human brain architecture, has not been investigated in wellbeing. To examine whether wellbeing was associated with local-to-remote cortical connectivity, we acquired resting-state images from 60 healthy participants and employed the Mental Health Continuum Short Form to measure wellbeing, including three dimensions, namely, emotional wellbeing, psychological wellbeing, and social wellbeing. Functional homogeneity (ReHo) and seed-based functional connectivity were used to evaluate local-to-remote cortical connectivity in these participants. For local connectivity, our results showed that ReHo in the right orbitofrontal sulcus was significantly positively correlated with psychological wellbeing but negatively correlated with social wellbeing. For remote connectivity, connectivity within the right orbitofrontal cortex and interhemispheric connectivity of the orbitofrontal sulcus were both positively associated with psychological wellbeing; functional connectivity between the right orbitofrontal sulcus and the left postcentral sulcus was positively associated with social wellbeing. Our results showed that wellbeing was indeed associated with local-to-remote cortical connectivity, and our findings supplied a new perspective of distance-related neural mechanisms of wellbeing.
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Affiliation(s)
- Yubin Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chunlin Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Lili Jiang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Lili Jiang,
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21
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Caracci MO, Avila ME, Espinoza-Cavieres FA, López HR, Ugarte GD, De Ferrari GV. Wnt/β-Catenin-Dependent Transcription in Autism Spectrum Disorders. Front Mol Neurosci 2021; 14:764756. [PMID: 34858139 PMCID: PMC8632544 DOI: 10.3389/fnmol.2021.764756] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 10/12/2021] [Indexed: 12/20/2022] Open
Abstract
Autism spectrum disorders (ASD) is a heterogeneous group of neurodevelopmental disorders characterized by synaptic dysfunction and defects in dendritic spine morphology. In the past decade, an extensive list of genes associated with ASD has been identified by genome-wide sequencing initiatives. Several of these genes functionally converge in the regulation of the Wnt/β-catenin signaling pathway, a conserved cascade essential for stem cell pluripotency and cell fate decisions during development. Here, we review current information regarding the transcriptional program of Wnt/β-catenin signaling in ASD. First, we discuss that Wnt/β-catenin gain and loss of function studies recapitulate brain developmental abnormalities associated with ASD. Second, transcriptomic approaches using patient-derived induced pluripotent stem cells (iPSC) cells, featuring mutations in high confidence ASD genes, reveal a significant dysregulation in the expression of Wnt signaling components. Finally, we focus on the activity of chromatin-remodeling proteins and transcription factors considered high confidence ASD genes, including CHD8, ARID1B, ADNP, and TBR1, that regulate Wnt/β-catenin-dependent transcriptional activity in multiple cell types, including pyramidal neurons, interneurons and oligodendrocytes, cells which are becoming increasingly relevant in the study of ASD. We conclude that the level of Wnt/β-catenin signaling activation could explain the high phenotypical heterogeneity of ASD and be instrumental in the development of new diagnostics tools and therapies.
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Affiliation(s)
- Mario O. Caracci
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
- Faculty of Life Sciences, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
| | - Miguel E. Avila
- Faculty of Veterinary Medicine and Agronomy, Nucleus of Applied Research in Veterinary and Agronomic Sciences (NIAVA), Institute of Natural Sciences, Universidad de Las Américas, Santiago, Chile
| | - Francisca A. Espinoza-Cavieres
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
- Faculty of Life Sciences, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
| | - Héctor R. López
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
- Faculty of Life Sciences, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
| | - Giorgia D. Ugarte
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
- Faculty of Life Sciences, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
| | - Giancarlo V. De Ferrari
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
- Faculty of Life Sciences, Institute of Biomedical Sciences, Universidad Andres Bello, Santiago, Chile
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22
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Wu X, Lin F, Sun W, Zhang T, Sun H, Li J. Relationship between Short-Range and Homotopic Long-Range Resting State Functional Connectivity in Temporal Lobes in Autism Spectrum Disorder. Brain Sci 2021; 11:brainsci11111467. [PMID: 34827466 PMCID: PMC8615873 DOI: 10.3390/brainsci11111467] [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: 08/22/2021] [Revised: 10/26/2021] [Accepted: 11/04/2021] [Indexed: 11/16/2022] Open
Abstract
To investigate the relationship between short-range and homotopic long-range resting state functional connectivity (RSFC) in children with autism spectrum disorder (ASD) and typically developing (TD) children, we analyzed functional near-infrared spectroscopy (fNIRS) RSFC in 25 children with ASD and 22 age-matched TD children. The resting state fNIRS signals, including spontaneous fluctuations in the oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) concentrations, were recorded from the bilateral temporal lobes. We found that (1) there was no difference in the short-range RSFC between the left and right hemisphere in either ASD or TD group; (2) both the short-range and homotopic long-range RSFC were weaker in the ASD than TD group; and (3) the short-range RSFC was stronger than the homotopic long-range RSFC in the ASD group, whereas no such difference was observed in the TD group. These observations might be helpful for a better understanding of the underlying cortical mechanism in ASD.
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Affiliation(s)
- Xiaoyin Wu
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
| | - Fang Lin
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
| | - Weiting Sun
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
| | - Tingzhen Zhang
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
| | - Huiwen Sun
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
| | - Jun Li
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China; (X.W.); (F.L.); (W.S.); (T.Z.); (H.S.)
- Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou 510006, China
- Correspondence:
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Zhang Z, Gibson JR, Huber KM. Experience-dependent weakening of callosal synaptic connections in the absence of postsynaptic FMRP. eLife 2021; 10:71555. [PMID: 34617509 PMCID: PMC8526058 DOI: 10.7554/elife.71555] [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: 06/23/2021] [Accepted: 10/06/2021] [Indexed: 12/18/2022] Open
Abstract
Reduced structural and functional interhemispheric connectivity correlates with the severity of Autism Spectrum Disorder (ASD) behaviors in humans. Little is known of how ASD-risk genes regulate callosal connectivity. Here, we show that Fmr1, whose loss-of-function leads to Fragile X Syndrome (FXS), cell autonomously promotes maturation of callosal excitatory synapses between somatosensory barrel cortices in mice. Postnatal, cell-autonomous deletion of Fmr1 in postsynaptic Layer (L) 2/3 or L5 neurons results in a selective weakening of AMPA receptor- (R), but not NMDA receptor-, mediated callosal synaptic function, indicative of immature synapses. Sensory deprivation by contralateral whisker trimming normalizes callosal input strength, suggesting that experience-driven activity of postsynaptic Fmr1 KO L2/3 neurons weakens callosal synapses. In contrast to callosal inputs, synapses originating from local L4 and L2/3 circuits are normal, revealing an input-specific role for postsynaptic Fmr1 in regulation of synaptic connectivity within local and callosal neocortical circuits. These results suggest direct cell autonomous and postnatal roles for FMRP in development of specific cortical circuits and suggest a synaptic basis for long-range functional underconnectivity observed in FXS patients.
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Affiliation(s)
- Zhe Zhang
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
| | - Jay R Gibson
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
| | - Kimberly M Huber
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
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24
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Loomba N, Beckerson ME, Ammons CJ, Maximo JO, Kana RK. Corpus callosum size and homotopic connectivity in Autism spectrum disorder. Psychiatry Res Neuroimaging 2021; 313:111301. [PMID: 34022542 DOI: 10.1016/j.pscychresns.2021.111301] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 04/28/2021] [Accepted: 05/07/2021] [Indexed: 12/14/2022]
Abstract
By examining how morphology of the corpus callosum (CC) in autism spectrum disorder (ASD) may affect functional communication across hemispheres, we hope to provide new insights into the structure-function relationship in the brain. We used a sample of 94 participants from the Autism Brain Imaging Data Exchange (ABIDE) database (55 typically-developing (TD) and 39 with ASD). The CC was segmented into five sub-regions (anterior, mid-anterior, central, mid-posterior, posterior) using FreeSurfer software, which were further examined for group differences. The total volume and specific sub-region volumes of the CC, and interhemispheric (homotopic) functional connectivity were calculated, along with the relationship between volume and connectivity. These measures were correlated with social ability assessed by the Social Responsiveness Scale (SRS). The central sub-region of CC was significantly smaller in ASD, although there was no group difference in total CC volume. ASD participants also showed stronger homotopic connectivity in the superior frontal gyrus. SRS scores were negatively correlated with the CC central sub-region volumes in ASD. The findings of this study add to the body of research showing morphological differences in the CC in ASD as well as connectivity differences. The absence of a significant relationship between structure and homotopic functional connectivity aligns with previous findings.
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Affiliation(s)
- Niharika Loomba
- Interdisciplinary Graduate Program, Vanderbilt University, Nashville, TN, United States
| | - Meagan E Beckerson
- Department of Psychology, University of Alabama, Tuscaloosa, AL, United States; Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, AL, United States
| | - Carla J Ammons
- Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, United States
| | - Jose O Maximo
- Department of Psychiatry & Behavior Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Rajesh K Kana
- Department of Psychology, University of Alabama, Tuscaloosa, AL, United States; Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, AL, United States.
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Xu M, Calhoun V, Jiang R, Yan W, Sui J. Brain imaging-based machine learning in autism spectrum disorder: methods and applications. J Neurosci Methods 2021; 361:109271. [PMID: 34174282 DOI: 10.1016/j.jneumeth.2021.109271] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/25/2021] [Accepted: 06/19/2021] [Indexed: 01/09/2023]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is comprised of a constellation of behavioral symptoms. Non-invasive brain imaging techniques, such as magnetic resonance imaging (MRI), provide a valuable objective measurement of the brain. Many efforts have been devoted to developing imaging-based diagnostic tools for ASD based on machine learning (ML) technologies. In this survey, we review recent advances that utilize machine learning approaches to classify individuals with and without ASD. First, we provide a brief overview of neuroimaging-based ASD classification studies, including the analysis of publications and general classification pipeline. Next, representative studies are highlighted and discussed in detail regarding different imaging modalities, methods and sample sizes. Finally, we highlight several common challenges and provide recommendations on future directions. In summary, identifying discriminative biomarkers for ASD diagnosis is challenging, and further establishing more comprehensive datasets and dissecting the individual and group heterogeneity will be critical to achieve better ADS diagnosis performance. Machine learning methods will continue to be developed and are poised to help advance the field in this regard.
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Affiliation(s)
- Ming Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 100049
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA 30303
| | - Rongtao Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190
| | - Weizheng Yan
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA 30303
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China 100088.
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26
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Yao S, Zhou M, Zhang Y, Zhou F, Zhang Q, Zhao Z, Jiang X, Xu X, Becker B, Kendrick KM. Decreased homotopic interhemispheric functional connectivity in children with autism spectrum disorder. Autism Res 2021; 14:1609-1620. [PMID: 33908177 DOI: 10.1002/aur.2523] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/15/2021] [Accepted: 04/16/2021] [Indexed: 11/11/2022]
Abstract
While several functional and structural changes occur in large-scale brain networks in autism spectrum disorder (ASD), reduced interhemispheric resting-state functional connectivity (rsFC) between homotopic regions may be of particular importance as a biomarker. ASD is an early-onset developmental disorder and neural alterations are often age-dependent. Although there is some evidence for homotopic interhemispheric rsFC alterations in language processing regions in ASD children, wider analyses using large data sets have not been performed. The present study, therefore, conducted a voxel-based homotopic interhemispheric rsFC analysis in 146 ASD and 175 typically developing children under-age 10 and examined associations with symptom severity in the autism brain imaging data exchange data sets. Given the role of corpus callosum (CC) in interhemispheric connectivity and reported CC volume changes in ASD we additionally examined whether there were parallel volumetric changes. Results demonstrated decreased homotopic rsFC in ASD children in the posterior cingulate cortex (PCC) and precuneus of the default mode network, the precentral gyrus of the mirror neuron system, and the caudate of the reward system. Homotopic rsFC of the PCC was associated with symptom severity. Furthermore, although no significant CC volume changes were found in ASD children, there was a significant negative correlation between the anterior CC volumes and homotopic rsFC strengths in the caudate. The present study shows that a reduced pattern of homotopic interhemispheric rsFC in ASD adults/adolescents is already present in children of 5-10 years old and further supports their potential use as a general ASD biomarker. LAY SUMMARY: Homotopic interhemispheric functional connectivity plays an important role in synchronizing activity between the two hemispheres and is altered in adults and adolescents with autism spectrum disorder (ASD). In the present study focused on children with ASD, we have observed a similar pattern of decreased homotopic connectivity, suggesting that alterations in homotopic interhemispheric connectivity may occur early in ASD and be a useful general biomarker across ages.
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Affiliation(s)
- Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Menghan Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yuan Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Feng Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Qianqian Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Zhongbo Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Xi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Xiaolei Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
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Yao S, Becker B, Kendrick KM. Reduced Inter-hemispheric Resting State Functional Connectivity and Its Association With Social Deficits in Autism. Front Psychiatry 2021; 12:629870. [PMID: 33746796 PMCID: PMC7969641 DOI: 10.3389/fpsyt.2021.629870] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 02/11/2021] [Indexed: 02/06/2023] Open
Abstract
Autism spectrum disorder (ASD) is an early onset developmental disorder which persists throughout life and is increasing in prevalence over the last few decades. Given its early onset and variable cognitive and emotional functional impairments, it is generally challenging to assess ASD individuals using task-based behavioral and functional MRI paradigms. Consequently, resting state functional MRI (rs-fMRI) has become a key approach for examining ASD-associated neural alterations and revealed functional alterations in large-scale brain networks relative to typically developing (TD) individuals, particularly those involved in social-cognitive and affective processes. Recent progress suggests that alterations in inter-hemispheric resting state functional connectivity (rsFC) between regions in the 2 brain hemispheres, particularly homotopic ones, may be of great importance. Here we have reviewed neuroimaging studies examining inter-hemispheric rsFC abnormities in ASD and its associations with symptom severity. As an index of inter-hemispheric functional connectivity, we have additionally reviewed previous studies on corpus callosum (CC) volumetric and fiber changes in ASD. There are converging findings on reduced inter-hemispheric (including homotopic) rsFC in large-scale brain networks particularly in posterior hubs of the default mode network, reduced volumes in the anterior and posterior CC, and on decreased FA and increased MD or RD across CC subregions. Associations between the strength of inter-hemispheric rsFC and social impairments in ASD together with their classification performance in distinguishing ASD subjects from TD controls across ages suggest that the strength of inter-hemispheric rsFC may be a more promising biomarker for assisting in ASD diagnosis than abnormalities in either brain wide rsFC or brain structure.
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Affiliation(s)
- Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
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28
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Graña M, Silva M. Impact of Machine Learning Pipeline Choices in Autism Prediction From Functional Connectivity Data. Int J Neural Syst 2021; 31:2150009. [PMID: 33472548 DOI: 10.1142/s012906572150009x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Autism Spectrum Disorder (ASD) is a largely prevalent neurodevelopmental condition with a big social and economical impact affecting the entire life of families. There is an intense search for biomarkers that can be assessed as early as possible in order to initiate treatment and preparation of the family to deal with the challenges imposed by the condition. Brain imaging biomarkers have special interest. Specifically, functional connectivity data extracted from resting state functional magnetic resonance imaging (rs-fMRI) should allow to detect brain connectivity alterations. Machine learning pipelines encompass the estimation of the functional connectivity matrix from brain parcellations, feature extraction, and building classification models for ASD prediction. The works reported in the literature are very heterogeneous from the computational and methodological point of view. In this paper, we carry out a comprehensive computational exploration of the impact of the choices involved while building these machine learning pipelines. Specifically, we consider six brain parcellation definitions, five methods for functional connectivity matrix construction, six feature extraction/selection approaches, and nine classifier building algorithms. We report the prediction performance sensitivity to each of these choices, as well as the best results that are comparable with the state of the art.
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Affiliation(s)
- Manuel Graña
- Computational Intelligence Group, University of the Basque Country (UPV/EHU), San Sebastian, Spain
| | - Moises Silva
- Universidad Mayor de San Andres, La Paz, Bolivia
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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: 80] [Impact Index Per Article: 26.7] [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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30
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Jiang X, Ma X, Geng Y, Zhao Z, Zhou F, Zhao W, Yao S, Yang S, Zhao Z, Becker B, Kendrick KM. Intrinsic, dynamic and effective connectivity among large-scale brain networks modulated by oxytocin. Neuroimage 2020; 227:117668. [PMID: 33359350 DOI: 10.1016/j.neuroimage.2020.117668] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 11/06/2020] [Accepted: 12/14/2020] [Indexed: 12/12/2022] Open
Abstract
The neuropeptide oxytocin is a key modulator of social-emotional behavior and its intranasal administration can influence the functional connectivity of brain networks involved in the control of attention, emotion and reward reported in humans. However, no studies have systematically investigated the effects of oxytocin on dynamic or directional aspects of functional connectivity. The present study employed a novel computational framework to investigate these latter aspects in 15 oxytocin-sensitive regions using data from randomized placebo-controlled between-subject resting state functional MRI studies incorporating 200 healthy subjects. In order to characterize the temporal dynamics, the 'temporal state' was defined as a temporal segment of the whole functional MRI signal which exhibited a similar functional interaction pattern among brain regions of interest. Results showed that while no significant effects of oxytocin were found on brain temporal state related characteristics (including temporal state switching frequency, probability of transitions between neighboring states, and averaged dwell time on each state) oxytocin extensively (n = 54 links) modulated effective connectivity among the 15 regions. The effects of oxytocin were primarily characterized by increased effective connectivity both between and within emotion, reward, salience, attention and social cognition processing networks and their interactions with the default mode network. Top-down control over emotional processing regions such as the amygdala was particularly affected. Oxytocin also increased effective homotopic interhemispheric connectivity in almost all these regions. Additionally, the effects of oxytocin on effective connectivity were sex-dependent, being more extensive in males. Overall, these findings suggest that modulatory effects of oxytocin on both within- and between-network interactions may underlie its functional influence on social-emotional behaviors, although in a sex-dependent manner. These findings may be of particular relevance to potential therapeutic use of oxytocin in psychiatric disorders associated with social dysfunction, such as autism spectrum disorder and schizophrenia, where directionality of treatment effects on causal interactions between networks may be of key importance .
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Affiliation(s)
- Xi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaole Ma
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Yayuan Geng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhiying Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Weihua Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Shimin Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhongbo Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
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31
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Jia C, Ou Y, Chen Y, Li P, Lv D, Yang R, Zhong Z, Sun L, Wang Y, Zhang G, Guo H, Sun Z, Wang W, Wang Y, Wang X, Guo W. Decreased Resting-State Interhemispheric Functional Connectivity in Medication-Free Obsessive-Compulsive Disorder. Front Psychiatry 2020; 11:559729. [PMID: 33101081 PMCID: PMC7522198 DOI: 10.3389/fpsyt.2020.559729] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 08/28/2020] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Decreased homotopic connectivity of brain networks such as the cortico-striato-thalamo-cortical (CSTC) circuits may contribute to the pathophysiology of obsessive-compulsive disorder (OCD). However, little is known about interhemispheric functional connectivity (FC) at rest in OCD. In this study, the voxel-mirrored homotopic connectivity (VMHC) method was applied to explore interhemispheric coordination at rest in OCD. METHODS Forty medication-free patients with OCD and 38 sex-, age-, and education level-matched healthy controls (HCs) underwent a resting-state functional magnetic resonance imaging. The VMHC and support vector machine (SVM) methods were used to analyze the data. RESULTS Patients with OCD had remarkably decreased VMHC values in the orbitofrontal cortex, thalamus, middle occipital gyrus, and precentral and postcentral gyri compared with HCs. A combination of the VMHC values in the thalamus and postcentral gyrus could optimally distinguish patients with OCD from HCs. CONCLUSIONS Our findings highlight the contribution of decreased interhemispheric FC within and outside the CSTC circuits in OCD and provide evidence to the pathophysiology of OCD.
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Affiliation(s)
- Cuicui Jia
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Yangpan Ou
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yunhui Chen
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Dan Lv
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Ru Yang
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhaoxi Zhong
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Lei Sun
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Yuhua Wang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Guangfeng Zhang
- Department of Radiology, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China
| | - Hong Guo
- Department of Radiology, The First Hospital of Qiqihar, Qiqihar, China
| | - Zhenghai Sun
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Wei Wang
- Department of Library, Qiqihar Medical University, Qiqihar, China
| | - Yefu Wang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Xiaoping Wang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Wenbin Guo
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
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32
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Structural networks in children with autism spectrum disorder with regression: A graph theory study. Behav Brain Res 2020; 378:112262. [DOI: 10.1016/j.bbr.2019.112262] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/21/2019] [Accepted: 09/24/2019] [Indexed: 12/16/2022]
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33
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Chauvière L. Potential causes of cognitive alterations in temporal lobe epilepsy. Behav Brain Res 2020; 378:112310. [DOI: 10.1016/j.bbr.2019.112310] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/15/2019] [Accepted: 10/15/2019] [Indexed: 12/11/2022]
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