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Ruan L, Chen G, Yao M, Li C, Chen X, Luo H, Ruan J, Zheng Z, Zhang D, Liang S, Lü M. Brain functional gradient and structure features in adolescent and adult autism spectrum disorders. Hum Brain Mapp 2024; 45:e26792. [PMID: 39037170 PMCID: PMC11261594 DOI: 10.1002/hbm.26792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 06/16/2024] [Accepted: 07/06/2024] [Indexed: 07/23/2024] Open
Abstract
Understanding how function and structure are organized and their coupling with clinical traits in individuals with autism spectrum disorder (ASD) is a primary goal in network neuroscience research for ASD. Atypical brain functional networks and structures in individuals with ASD have been reported, but whether these associations show heterogeneous hierarchy modeling in adolescents and adults with ASD remains to be clarified. In this study, 176 adolescent and 74 adult participants with ASD without medication or comorbidities and sex, age matched healthy controls (HCs) from 19 research groups from the openly shared Autism Brain Imaging Data Exchange II database were included. To investigate the relationship between the functional gradient, structural changes, and clinical symptoms of brain networks in adolescents and adults with ASD, functional gradient and voxel-based morphometry (VBM) analyses based on 1000 parcels defined by Schaefer mapped to Yeo's seven-network atlas were performed. Pearson's correlation was calculated between the gradient scores, gray volume and density, and clinical traits. The subsystem-level analysis showed that the second gradient scores of the default mode networks and frontoparietal network in patients with ASD were relatively compressed compared to adolescent HCs. Adult patients with ASD showed an overall compression gradient of 1 in the ventral attention networks. In addition, the gray density and volumes of the subnetworks showed no significant differences between the ASD and HC groups at the adolescent stage. However, adults with ASD showed decreased gray density in the limbic network. Moreover, numerous functional gradient parameters, but not VBM parameters, in adolescents with ASD were considerably correlated with clinical traits in contrast to those in adults with ASD. Our findings proved that the atypical changes in adolescent ASD mainly involve the brain functional network, while in adult ASD, the changes are more related to brain structure, including gray density and volume. These changes in functional gradients or structures are markedly correlated with clinical traits in patients with ASD. Our study provides a novel understanding of the pathophysiology of the structure-function hierarchy in ASD.
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Affiliation(s)
- Lili Ruan
- Department of NeurologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
- Laboratory of Neurological Diseases and Brain FunctionLuzhouChina
| | - Guangxiang Chen
- Department of RadiologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
| | - Menglin Yao
- College of Integrated MedicineSouthwest Medical UniversityLuzhouChina
| | - Cheng Li
- Department of PediatricsThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
- Sichuan Clinical Research Center for Birth DefectsLuzhouChina
| | - Xiu Chen
- Department of NeurologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
- Laboratory of Neurological Diseases and Brain FunctionLuzhouChina
| | - Hua Luo
- Department of NeurologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
- Laboratory of Neurological Diseases and Brain FunctionLuzhouChina
| | - Jianghai Ruan
- Department of NeurologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
- Laboratory of Neurological Diseases and Brain FunctionLuzhouChina
| | - Zhong Zheng
- Center for Neurological Function Test and Neuromodulation, West China Xiamen HospitalSichuan UniversityXiamenChina
| | - Dechou Zhang
- Department of NeurologySouthwest Medical University Affiliated Hospital of Traditional Chinese MedicineLuzhouChina
| | - Sicheng Liang
- Department of GastroenterologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
| | - Muhan Lü
- Department of GastroenterologyThe Affiliated Hospital of Southwest Medical UniversityLuzhouChina
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Zhao S, Lv Q, Zhang G, Zhang J, Wang H, Zhang J, Wang M, Wang Z. Quantitative Expression of Latent Disease Factors in Individuals Associated with Psychopathology Dimensions and Treatment Response. Neurosci Bull 2024:10.1007/s12264-024-01224-z. [PMID: 38842612 DOI: 10.1007/s12264-024-01224-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 01/02/2024] [Indexed: 06/07/2024] Open
Abstract
Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.
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Affiliation(s)
- Shaoling Zhao
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, Zhengzhou, 450003, China
| | - Jiangtao Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Heqiu Wang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Jianmin Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, Zhengzhou, 450003, China.
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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Lyuboslavsky P, Ordemann GJ, Kizimenko A, Brumback AC. Two contrasting mediodorsal thalamic circuits target the mouse medial prefrontal cortex. J Neurophysiol 2024; 131:876-890. [PMID: 38568510 DOI: 10.1152/jn.00456.2023] [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: 12/11/2023] [Revised: 02/28/2024] [Accepted: 03/17/2024] [Indexed: 05/09/2024] Open
Abstract
At the heart of the prefrontal network is the mediodorsal (MD) thalamus. Despite the importance of MD in a broad range of behaviors and neuropsychiatric disorders, little is known about the physiology of neurons in MD. We injected the retrograde tracer cholera toxin subunit B (CTB) into the medial prefrontal cortex (mPFC) of adult wild-type mice. We prepared acute brain slices and used current clamp electrophysiology to measure and compare the intrinsic properties of the neurons in MD that project to mPFC (MD→mPFC neurons). We show that MD→mPFC neurons are located predominantly in the medial (MD-M) and lateral (MD-L) subnuclei of MD. MD-L→mPFC neurons had shorter membrane time constants and lower membrane resistance than MD-M→mPFC neurons. Relatively increased hyperpolarization-activated cyclic nucleotide-gated (HCN) channel activity in MD-L neurons accounted for the difference in membrane resistance. MD-L neurons had a higher rheobase that resulted in less readily generated action potentials compared with MD-M→mPFC neurons. In both cell types, HCN channels supported generation of burst spiking. Increased HCN channel activity in MD-L neurons results in larger after-hyperpolarization potentials compared with MD-M neurons. These data demonstrate that the two populations of MD→mPFC neurons have divergent physiologies and support a differential role in thalamocortical information processing and potentially behavior.NEW & NOTEWORTHY To realize the potential of circuit-based therapies for psychiatric disorders that localize to the prefrontal network, we need to understand the properties of the populations of neurons that make up this network. The mediodorsal (MD) thalamus has garnered attention for its roles in executive functioning and social/emotional behaviors mediated, at least in part, by its projections to the medial prefrontal cortex (mPFC). Here, we identify and compare the physiology of the projection neurons in the two MD subnuclei that provide ascending inputs to mPFC in mice. Differences in intrinsic excitability between the two populations of neurons suggest that neuromodulation strategies targeting the prefrontal thalamocortical network will have differential effects on these two streams of thalamic input to mPFC.
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Affiliation(s)
- Polina Lyuboslavsky
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, Texas, United States
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States
| | - Gregory J Ordemann
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, Texas, United States
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States
| | - Alena Kizimenko
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, Texas, United States
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States
| | - Audrey C Brumback
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, Texas, United States
- Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, Texas, United States
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States
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de Medeiros Marcos GVT, Feitosa DDM, Paiva KM, Oliveira RF, da Rocha GS, de Medeiros Guerra LM, de Araújo DP, Goes HM, Costa S, de Oliveira LC, Guzen FP, de Souza Júnior JE, de Moura Freire MA, de Aquino ACQ, de Gois Morais PLA, de Paiva Cavalcanti JRL. Volumetric alterations in the basal ganglia in autism Spectrum disorder: A systematic review. Int J Dev Neurosci 2024; 84:163-176. [PMID: 38488315 DOI: 10.1002/jdn.10322] [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: 11/28/2023] [Revised: 01/29/2024] [Accepted: 02/13/2024] [Indexed: 05/04/2024] Open
Abstract
INTRODUCTION Recent research indicates that some brain structures show alterations in conditions such as Autism Spectrum Disorder (ASD). Among them, are the basal ganglia that are involved in motor, cognitive and behavioral neural circuits. OBJECTIVE Review the literature that describes possible volumetric alterations in the basal ganglia of individuals with ASD and the impacts that these changes have on the severity of the condition. METHODOLOGY This systematic review was registered in the design and reported according to the PRISMA Items and registered in PROSPERO (CRD42023394787). The study analyzed data from published clinical, case-contemplate, and cohort trials. The following databases were consulted: PubMed, Embase, Scopus, and Cochrane Central Register of Controlled Trials, using the Medical Subject Titles (MeSH) "Autism Spectrum Disorder" and "Basal Ganglia". The last search was carried out on February 28, 2023. RESULTS Thirty-five eligible articles were collected, analyzed, and grouped according to the levels of alterations. CONCLUSION The present study showed important volumetric alterations in the basal ganglia in ASD. However, the examined studies have methodological weaknesses that do not allow generalization and correlation with ASD manifestations.
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Affiliation(s)
| | | | - Karina Maia Paiva
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Rodrigo Freire Oliveira
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Gabriel Sousa da Rocha
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Luís Marcos de Medeiros Guerra
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Dayane Pessoa de Araújo
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | | | - Silva Costa
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Lucidio Clebeson de Oliveira
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Fausto Pierdoná Guzen
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - José Edvan de Souza Júnior
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Marco Aurélio de Moura Freire
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
| | - Antonio Carlos Queiroz de Aquino
- Laboratory of Experimental Neurology, Department of Health Sciences, State University of Rio Grande do Norte, Mossoró, RN, Brazil
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Pereira DJ, Morais S, Sayal A, Pereira J, Meneses S, Areias G, Direito B, Macedo A, Castelo-Branco M. Neurofeedback training of executive function in autism spectrum disorder: distinct effects on brain activity levels and compensatory connectivity changes. J Neurodev Disord 2024; 16:14. [PMID: 38605323 PMCID: PMC11008042 DOI: 10.1186/s11689-024-09531-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 03/28/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND Deficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD. METHODS Thirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity. RESULTS The ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex. CONCLUSIONS Neurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.
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Affiliation(s)
- Daniela Jardim Pereira
- Neurorradiology Functional Area, Imaging Department, Coimbra Hospital and University Center, Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Sofia Morais
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Psychiatry Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - Alexandre Sayal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Siemens Healthineers Portugal, Lisboa, Portugal
| | - João Pereira
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Sofia Meneses
- Psychology Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - Graça Areias
- Psychology Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - Bruno Direito
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- IATV-Instituto do Ambiente, Tecnologia e Vida (IATV), Coimbra, Portugal
| | - António Macedo
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Siemens Healthineers Portugal, Lisboa, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal.
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal.
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Yoon N, Kim S, Oh MR, Kim M, Lee JM, Kim BN. Intrinsic network abnormalities in children with autism spectrum disorder: an independent component analysis. Brain Imaging Behav 2024; 18:430-443. [PMID: 38324235 DOI: 10.1007/s11682-024-00858-x] [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: 01/16/2024] [Indexed: 02/08/2024]
Abstract
Aberrant intrinsic brain networks are consistently observed in individuals with autism spectrum disorder. However, studies examining the strength of functional connectivity across brain regions have yielded conflicting results. Therefore, this study aimed to investigate the functional connectivity of the resting brain in children with low-functioning autism, including during the early developmental stages. We explored the functional connectivity of 43 children with autism spectrum disorder and 54 children with typical development aged 2 to 12 years using resting-state functional magnetic resonance imaging data. We used independent component analysis to classify the brain regions into six intrinsic networks and analyzed the functional connectivity within each network. Moreover, we analyzed the relationship between functional connectivity and clinical scores. In children with autism, the under-connectivities were observed within several brain networks, including the cognitive control, default mode, visual, and somatomotor networks. In contrast, we found over-connectivities between the subcortical, visual, and somatomotor networks in children with autism compared with children with typical development. Moderate effect sizes were observed in entire networks (Cohen's d = 0.43-0.77). These network alterations were significantly correlated with clinical scores such as the communication sub-score (r = - 0.442, p = 0.045) and the calibrated severity score (r = - 0.435, p = 0.049) of the Autism Diagnostic Observation Schedule. These opposing results observed based on the brain areas suggest that aberrant neurodevelopment proceeds in various ways depending on the functional brain regions in individuals with autism spectrum disorder.
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Affiliation(s)
- Narae Yoon
- Division of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, 101 Daehakno, Jongno-gu, Seoul, Korea
| | - Sohui Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Mee Rim Oh
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Minji Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Sanhak-kisulkwan Bldg., #319, 222 Wangsipri-ro, Sungdong-gu, Seoul, 133-791, Republic of Korea.
| | - Bung-Nyun Kim
- Division of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, 101 Daehakno, Jongno-gu, Seoul, Korea.
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Zhu J, Jiao Y, Chen R, Wang XH, Han Y. Aberrant dynamic and static functional connectivity of the striatum across specific low-frequency bands in patients with autism spectrum disorder. Psychiatry Res Neuroimaging 2023; 336:111749. [PMID: 37977097 DOI: 10.1016/j.pscychresns.2023.111749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 10/06/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Dysfunctions of the striatum have been repeatedly observed in autism spectrum disorder (ASD). However, previous studies have explored the static functional connectivity (sFC) of the striatum in a single frequency band, ignoring the dynamics and frequency specificity of brain FC. Therefore, we investigated the dynamic FC (dFC) and sFC of the striatum in the slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) frequency bands. METHODS Data of 47 ASD patients and 47 typically developing (TD) controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. A seed-based approach was used to compute the dFC and sFC. Then, a two-sample t-test was performed. For regions showing abnormal sFC and dFC, we performed clinical correlation analysis and constructed support vector machine (SVM) models. RESULTS The middle frontal gyrus (MFG), precuneus, and medial superior frontal gyrus (mPFC) showed both dynamic and static alterations. The reduced striatal dFC in the right MFG was associated with autism symptoms. The dynamic‒static FC model had a great performance in ASD classification, with 95.83 % accuracy. CONCLUSIONS The striatal dFC and sFC were altered in ASD, which were frequency specific. Examining brain activity using dynamic and static FC provides a comprehensive view of brain activity.
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Affiliation(s)
- Junsa Zhu
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Yun Jiao
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China; Network Information Center, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China.
| | - Ran Chen
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Xun-Heng Wang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Yunyan Han
- Public Health School of Dalian Medical University, Dalian 116000, China
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Rasero J, Jimenez-Marin A, Diez I, Toro R, Hasan MT, Cortes JM. The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals. Biol Psychiatry 2023; 94:804-813. [PMID: 37088169 DOI: 10.1016/j.biopsych.2023.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 03/24/2023] [Accepted: 04/14/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND There is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles. METHODS A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants. RESULTS Two major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD. CONCLUSIONS Our results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.
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Affiliation(s)
- Javier Rasero
- Cognitive Axon Laboratory, Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.
| | - Antonio Jimenez-Marin
- Computational Neuroimaging Laboratory, Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain; Biomedical Research Doctorate Program, University of the Basque Country, Leioa, Spain
| | - Ibai Diez
- Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Roberto Toro
- Institut Pasteur, Université de Paris, Département de neuroscience, Paris, France
| | - Mazahir T Hasan
- Laboratory of Brain Circuits Therapeutics, Achucarro Basque Center for Neuroscience, Leioa, Spain; Ikerbasque, The Basque Foundation for Science, Bilbao, Spain
| | - Jesus M Cortes
- Computational Neuroimaging Laboratory, Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain; Ikerbasque, The Basque Foundation for Science, Bilbao, Spain; Department of Cell Biology and Histology, University of the Basque Country, Leioa, Spain
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Zhou D, Liu Z, Gong G, Zhang Y, Lin L, Cai K, Xu H, Cong F, Li H, Chen A. Decreased Functional and Structural Connectivity is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder After Mini-basketball Training Program. J Autism Dev Disord 2023:10.1007/s10803-023-06160-x. [PMID: 37882897 DOI: 10.1007/s10803-023-06160-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/15/2023] [Indexed: 10/27/2023]
Abstract
Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention. We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3-12 years (experiment group: n = 32, control group: n = 26). ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical-cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD. Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.
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Affiliation(s)
- Dongyue Zhou
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, China
| | - Zhimei Liu
- College of Physical Education, Yangzhou University, Yangzhou, China
| | - Guanyu Gong
- Department of Oncology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Yunge Zhang
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, China
| | - Lin Lin
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, China
| | - Kelong Cai
- College of Physical Education, Yangzhou University, Yangzhou, China
| | - Huashuai Xu
- Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland
| | - Fengyu Cong
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, China
- Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland
- Key Laboratory of Integrated Circuit and Biomedical Electronic System, Dalian University of Technology, Dalian, Liaoning Province, China
| | - Huanjie Li
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, China.
- Key Laboratory of Integrated Circuit and Biomedical Electronic System, Dalian University of Technology, Dalian, Liaoning Province, China.
| | - Aiguo Chen
- College of Physical Education, Yangzhou University, Yangzhou, China.
- Key Laboratory of Brain Disease and Integration of Sport and Health, Yangzhou University, Yangzhou, China.
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10
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Feng Y, Kang X, Wang H, Cong J, Zhuang W, Xue K, Li F, Yao D, Xu P, Zhang T. The relationships between dynamic resting-state networks and social behavior in autism spectrum disorder revealed by fuzzy entropy-based temporal variability analysis of large-scale network. Cereb Cortex 2023; 33:764-776. [PMID: 35297491 DOI: 10.1093/cercor/bhac100] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 02/13/2022] [Accepted: 02/14/2022] [Indexed: 02/03/2023] Open
Abstract
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by a core deficit in social processes. However, it is still unclear whether the core clinical symptoms of the disorder can be reflected by the temporal variability of resting-state network functional connectivity (FC). In this article, we examined the large-scale network FC temporal variability at the local region, within-network, and between-network levels using the fuzzy entropy technique. Then, we correlated the network FC temporal variability to social-related scores. We found that the social behavior correlated with the FC temporal variability of the precuneus, parietal, occipital, temporal, and precentral. Our results also showed that social behavior was significantly negatively correlated with the temporal variability of FC within the default mode network, between the frontoparietal network and cingulo-opercular task control network, and the dorsal attention network. In contrast, social behavior correlated significantly positively with the temporal variability of FC within the subcortical network. Finally, using temporal variability as a feature, we construct a model to predict the social score of ASD. These findings suggest that the network FC temporal variability has a close relationship with social behavioral inflexibility in ASD and may serve as a potential biomarker for predicting ASD symptom severity.
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Affiliation(s)
- Yu Feng
- Mental Health Education Center and School of Science, Xihua University, No. 999, Jinzhou Road, Jinniu District, Chengdu 610039, China
| | - Xiaodong Kang
- The Department of Sichuan 81 Rehabilitation Center, Chengdu University of TCM, No.37, Twelfth Bridge Road,Chengdu 610075, China
| | - Hesong Wang
- Department of Gastroenterology, Guangdong Provincial Key Laboratory of Gastroenterology, Institute of Gastroenterology of Guangdong Province, Nanfang Hospital, Southern Medical University, No. 1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Jing Cong
- Mental Health Education Center and School of Science, Xihua University, No. 999, Jinzhou Road, Jinniu District, Chengdu 610039, China
| | - Wenwen Zhuang
- Mental Health Education Center and School of Science, Xihua University, No. 999, Jinzhou Road, Jinniu District, Chengdu 610039, China
| | - Kaiqing Xue
- School of Computer and Software Engineering, Xihua University, No. 999, Jinzhou Road, Jinniu District, Chengdu 610039, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Dadao, Gaoxin District, Chengdu 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Dadao, Gaoxin District, Chengdu 611731, China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Dadao, Gaoxin District, Chengdu 611731, China
| | - Tao Zhang
- Mental Health Education Center and School of Science, Xihua University, No. 999, Jinzhou Road, Jinniu District, Chengdu 610039, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Dadao, Gaoxin District, Chengdu 611731, China
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11
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Linke AC, Chen B, Olson L, Ibarra C, Fong C, Reynolds S, Apostol M, Kinnear M, Müller RA, Fishman I. Sleep Problems in Preschoolers With Autism Spectrum Disorder Are Associated With Sensory Sensitivities and Thalamocortical Overconnectivity. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:21-31. [PMID: 34343726 PMCID: PMC9826645 DOI: 10.1016/j.bpsc.2021.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/08/2021] [Accepted: 07/21/2021] [Indexed: 01/18/2023]
Abstract
BACKGROUND Projections between the thalamus and sensory cortices are established early in development and play an important role in regulating sleep as well as in relaying sensory information to the cortex. Atypical thalamocortical functional connectivity frequently observed in children with autism spectrum disorder (ASD) might therefore be linked to sensory and sleep problems common in ASD. METHODS Here, we investigated the relationship between auditory-thalamic functional connectivity measured during natural sleep functional magnetic resonance imaging, sleep problems, and sound sensitivities in 70 toddlers and preschoolers (1.5-5 years old) with ASD compared with a matched group of 46 typically developing children. RESULTS In children with ASD, sleep problems and sensory sensitivities were positively correlated, and increased sleep latency was associated with overconnectivity between the thalamus and auditory cortex in a subsample with high-quality magnetic resonance imaging data (n = 29). In addition, auditory cortex blood oxygen level-dependent signal amplitude was elevated in children with ASD, potentially reflecting reduced sensory gating or a lack of auditory habituation during natural sleep. CONCLUSIONS These findings indicate that atypical thalamocortical functional connectivity can be detected early in development and may play a crucial role in sleep problems and sensory sensitivities in ASD.
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Affiliation(s)
- Annika Carola Linke
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California.
| | - Bosi Chen
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Lindsay Olson
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Cynthia Ibarra
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Chris Fong
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Sarah Reynolds
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Michael Apostol
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Mikaela Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Ralph-Axel Müller
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California; SDSU Center for Autism and Developmental Disorders, San Diego, California
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California; SDSU Center for Autism and Developmental Disorders, San Diego, California
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12
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Inter-individual heterogeneity of functional brain networks in children with autism spectrum disorder. Mol Autism 2022; 13:52. [PMID: 36572935 PMCID: PMC9793594 DOI: 10.1186/s13229-022-00535-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/20/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable clinical heterogeneity. This study aimed to explore the heterogeneity of ASD based on inter-individual heterogeneity of functional brain networks. METHODS Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were used in this study for 105 children with ASD and 102 demographically matched typical controls (TC) children. Functional connectivity (FC) networks were first obtained for ASD and TC groups, and inter-individual deviation of functional connectivity (IDFC) from the TC group was then calculated for each individual with ASD. A k-means clustering algorithm was used to obtain ASD subtypes based on IDFC patterns. The FC patterns were further compared between ASD subtypes and the TC group from the brain region, network, and whole-brain levels. The relationship between IDFC and the severity of clinical symptoms of ASD for ASD subtypes was also analyzed using a support vector regression model. RESULTS Two ASD subtypes were identified based on the IDFC patterns. Compared with the TC group, the ASD subtype 1 group exhibited a hypoconnectivity pattern and the ASD subtype 2 group exhibited a hyperconnectivity pattern. IDFC for ASD subtype 1 and subtype 2 was found to predict the severity of social communication impairments and the severity of restricted and repetitive behaviors in ASD, respectively. LIMITATIONS Only male children were selected for this study, which limits the ability to study the effects of gender and development on ASD heterogeneity. CONCLUSIONS These results suggest the existence of subtypes with different FC patterns in ASD and provide insight into the complex pathophysiological mechanism of clinical manifestations of ASD.
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13
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Mylonas D, Machado S, Larson O, Patel R, Cox R, Vangel M, Maski K, Stickgold R, Manoach DS. Dyscoordination of non-rapid eye movement sleep oscillations in autism spectrum disorder. Sleep 2022; 45:6505127. [DOI: 10.1093/sleep/zsac010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/13/2021] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study Objectives
Converging evidence from neuroimaging, sleep, and genetic studies suggest that dysregulation of thalamocortical interactions mediated by the thalamic reticular nucleus (TRN) contribute to autism spectrum disorder (ASD). Sleep spindles assay TRN function, and their coordination with cortical slow oscillations (SOs) indexes thalamocortical communication. These oscillations mediate memory consolidation during sleep. In the present study, we comprehensively characterized spindles and their coordination with SOs in relation to memory and age in children with ASD.
Methods
Nineteen children and adolescents with ASD, without intellectual disability, and 18 typically developing (TD) peers, aged 9–17, completed a home polysomnography study with testing on a spatial memory task before and after sleep. Spindles, SOs, and their coordination were characterized during stages 2 (N2) and 3 (N3) non-rapid eye movement sleep.
Results
ASD participants showed disrupted SO-spindle coordination during N2 sleep. Spindles peaked later in SO upstates and their timing was less consistent. They also showed a spindle density (#/min) deficit during N3 sleep. Both groups showed significant sleep-dependent memory consolidation, but their relations with spindle density differed. While TD participants showed the expected positive correlations, ASD participants showed the opposite.
Conclusions
The disrupted SO-spindle coordination and spindle deficit provide further evidence of abnormal thalamocortical interactions and TRN dysfunction in ASD. The inverse relations of spindle density with memory suggest a different function for spindles in ASD than TD. We propose that abnormal sleep oscillations reflect genetically mediated disruptions of TRN-dependent thalamocortical circuit development that contribute to the manifestations of ASD and are potentially treatable.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Sasha Machado
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Olivia Larson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, PA,USA
| | - Rudra Patel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam,The Netherlands
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA,USA
| | - Kiran Maski
- Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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14
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Markopoulos A, Inserra A, De Gregorio D, Gobbi G. Evaluating the Potential Use of Serotonergic Psychedelics in Autism Spectrum Disorder. Front Pharmacol 2022; 12:749068. [PMID: 35177979 PMCID: PMC8846292 DOI: 10.3389/fphar.2021.749068] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 11/04/2021] [Indexed: 01/29/2023] Open
Abstract
Recent clinical and preclinical evidence points towards empathogenic and prosocial effects elicited by psychedelic compounds, notably the serotonin 5-HT2A agonists lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), and their derivatives. These findings suggest a therapeutic potential of psychedelic compounds for some of the behavioural traits associated with autism spectrum disorder (ASD), a neurodevelopmental condition characterized by atypical social behaviour. In this review, we highlight evidence suggesting that psychedelics may potentially ameliorate some of the behavioural atypicalities of ASD, including reduced social behaviour and highly co-occurring anxiety and depression. Next, we discuss dysregulated neurobiological systems in ASD and how they may underlie or potentially limit the therapeutic effects of psychedelics. These phenomena include: 1) synaptic function, 2) serotonergic signaling, 3) prefrontal cortex activity, and 4) thalamocortical signaling. Lastly, we discuss clinical studies from the 1960s and 70s that assessed the use of psychedelics in the treatment of children with ASD. We highlight the positive behavioural outcomes of these studies, including enhanced mood and social behaviour, as well as the adverse effects of these trials, including increases in aggressive behaviour and dissociative and psychotic states. Despite preliminary evidence, further studies are needed to determine whether the benefits of psychedelic treatment in ASD outweigh the risks associated with the use of these compounds in this population, and if the 5-HT2A receptor may represent a target for social-behavioural disorders.
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Affiliation(s)
- Athanasios Markopoulos
- Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Antonio Inserra
- Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Danilo De Gregorio
- Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Gabriella Gobbi
- Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada.,McGill University Health Centre, McGill University, Montreal, QC, Canada
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15
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Lorenzini L, van Wingen G, Cerliani L. Atypically high influence of subcortical activity on primary sensory regions in autism. Neuroimage Clin 2022; 32:102839. [PMID: 34624634 PMCID: PMC8503568 DOI: 10.1016/j.nicl.2021.102839] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/20/2021] [Accepted: 09/21/2021] [Indexed: 12/20/2022]
Abstract
The age-dependent decrease of subcortico-cortical connectivity is attenuated in ASD. Primary sensory regions remain less segregated from subcortical activity in ASD. This could underlie an excessive amount of sensory input relayed to the cortex.
Background Hypersensitivity, stereotyped behaviors and attentional problems in autism spectrum disorder (ASD) are compatible with inefficient filtering of undesired or irrelevant sensory information at early stages of neural processing. This could stem from the persistent overconnectivity between primary sensory regions and deep brain nuclei in both children and adults with ASD – as reported by several previous studies – which could reflect a decreased or arrested maturation of brain connectivity. However, it has not yet been investigated whether this overconnectivity can be modelled as an excessive directional influence of subcortical brain activity on primary sensory cortical regions in ASD, with respect to age-matched typically developing (TD) individuals. Methods To this aim, we used dynamic causal modelling to estimate (1) the directional influence of subcortical activity on cortical processing and (2) the functional segregation of primary sensory cortical regions from subcortical activity in 166 participants with ASD and 193 TD participants from the Autism Brain Imaging Data Exchange (ABIDE). We then specifically tested the hypothesis that the age-related changes of these indicators of brain connectivity would differ between the two groups. Results We found that in TD participants age was significantly associated with decreased influence of subcortical activity on cortical processing, paralleled by an increased functional segregation of cortical sensory processing from subcortical activity. Instead these effects were highly reduced and mostly absent in ASD participants, suggesting a delayed or arrested development of the segregation between subcortical and cortical sensory processing in ASD. Conclusion This atypical configuration of subcortico-cortical connectivity in ASD can result in an excessive amount of unprocessed sensory input relayed to the cortex, which is likely to impact cognitive functioning in everyday situations where it is beneficial to limit the influence of basic sensory information on cognitive processing, such as activities requiring focused attention or social interactions.
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Affiliation(s)
- Luigi Lorenzini
- Dept. of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 5, 1105AZ Amsterdam, The Netherlands; Dept. Radiology and Nuclear Medicine, Amsterdam UMC, VU University, Amsterdam Neuroscience, De Boelelaan 1117, 1081HV Amsterdam, The Netherlands.
| | - Guido van Wingen
- Dept. of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 5, 1105AZ Amsterdam, The Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018WT, University of Amsterdam, The Netherlands
| | - Leonardo Cerliani
- Dept. of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 5, 1105AZ Amsterdam, The Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018WT, University of Amsterdam, The Netherlands; Netherlands Institute for Neuroscience, Social Brain Lab, Meibergdreef 47, 1105BA Amsterdam, The Netherlands
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16
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Bathelt J, Geurts HM, Borsboom D. More than the sum of its parts: Merging network psychometrics and
network neuroscience with application in autism. Netw Neurosci 2021; 6:445-466. [PMID: 35733421 PMCID: PMC9207995 DOI: 10.1162/netn_a_00222] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 12/08/2021] [Indexed: 11/05/2022] Open
Abstract
Network approaches that investigate the interaction between symptoms and behaviours have opened new ways of understanding psychological phenomena in health and disorder in recent years. In parallel, network approaches that characterise the interaction between brain regions have become the dominant approach in neuroimaging research. In this paper, we introduce a methodology for combining network psychometrics and network neuroscience. This approach utilises the information from the psychometric network to obtain neural correlates that are associated with each node in the psychometric network (network-based regression). Moreover, we combine the behavioural variables and their neural correlates in a joint network to characterise their interactions. We illustrate the approach by highlighting the interaction between the triad of autistic traits and their resting-state functional connectivity associations. To this end, we utilise data from 172 male autistic participants (10–21 years) from the autism brain data exchange (ABIDE, ABIDE-II) that completed resting-state fMRI and were assessed using the autism diagnostic interview (ADI-R). Our results indicate that the network-based regression approach can uncover both unique and shared neural correlates of behavioural measures. For instance, our example analysis indicates that the overlap between communication and social difficulties is not reflected in the overlap between their functional brain correlates. The article introduces a method to combine common practices in network psychometrics and network neuroimaging. Namely, we use the unique variance in behavioural measures as regressors to identify unique neural correlates. This enables the description of brain-level and behavioural-level data into a joint network while keeping the dimensionality of the results manageable and interpretable. We illustrate this approach by showing the network of autistic traits and their correlates in resting-state functional connectivity.
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Affiliation(s)
- Joe Bathelt
- Department of Psychology, Royal Holloway, University of London, Egham, Surrey TW20 0EX, United Kingdom
- Department of Psychology, University of Amsterdam
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17
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Mouga S, Duarte IC, Café C, Sousa D, Duque F, Oliveira G, Castelo-Branco M. Attentional Cueing and Executive Deficits Revealed by a Virtual Supermarket Task Coupled With Eye-Tracking in Autism Spectrum Disorder. Front Psychol 2021; 12:671507. [PMID: 34531782 PMCID: PMC8438237 DOI: 10.3389/fpsyg.2021.671507] [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: 02/23/2021] [Accepted: 07/20/2021] [Indexed: 11/13/2022] Open
Abstract
Executive functioning (EF) impairments in Autism Spectrum Disorder (ASD) impact on complex functions, such as social cognition. We assessed this link between EF, attentional cueing, and social cognition with a novel ecological task, "EcoSupermarketX." Our task had three blocks of increasing executive load and incorporated social and non-social cues, with different degrees of saliency. Performance of ASD and typical neurodevelopment was compared. The ASD showed a significant performance dependence on the presence of contextual cues. Difficulties increased as a function of cognitive load. Between-group differences were found both for social and non-social salient cues. Eye-tracking measures showed significantly larger fixation time of more salient social cues in ASD. In sum, EcoSupermarketX is sensitive to detect EF and attentional cueing deficits in ASD.
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Affiliation(s)
- Susana Mouga
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.,Center for Neuroscience and Cell Biology - Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurodevelopmental and Autism Unit From Child Developmental Centre, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Isabel Catarina Duarte
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Cátia Café
- Neurodevelopmental and Autism Unit From Child Developmental Centre, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Daniela Sousa
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.,Neurodevelopmental and Autism Unit From Child Developmental Centre, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Frederico Duque
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Center for Neuroscience and Cell Biology - Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurodevelopmental and Autism Unit From Child Developmental Centre, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Centro de Investigação e Formação Clínica, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Faculty of Medicine, University Clinic of Pediatrics, University of Coimbra, Coimbra, Portugal
| | - Guiomar Oliveira
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Center for Neuroscience and Cell Biology - Institute for Biomedical Imaging and Life Sciences, Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurodevelopmental and Autism Unit From Child Developmental Centre, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Centro de Investigação e Formação Clínica, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Faculty of Medicine, University Clinic of Pediatrics, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal.,Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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18
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Ma X, Wei J, Cui Y, Xia B, Zhang L, Nehme A, Zuo Y, Ferguson D, Levitt P, Qiu S. Disrupted Timing of MET Signaling Derails the Developmental Maturation of Cortical Circuits and Leads to Altered Behavior in Mice. Cereb Cortex 2021; 32:1769-1786. [PMID: 34470051 PMCID: PMC9016286 DOI: 10.1093/cercor/bhab323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/11/2021] [Accepted: 08/12/2021] [Indexed: 01/21/2023] Open
Abstract
The molecular regulation of the temporal dynamics of circuit maturation is a key contributor to the emergence of normal structure-function relations. Developmental control of cortical MET receptor tyrosine kinase, expressed early postnatally in subpopulations of excitatory neurons, has a pronounced impact on the timing of glutamatergic synapse maturation and critical period plasticity. Here, we show that using a controllable overexpression (cto-Met) transgenic mouse, extending the duration of MET signaling after endogenous Met is switched off leads to altered molecular constitution of synaptic proteins, persistent activation of small GTPases Cdc42 and Rac1, and sustained inhibitory phosphorylation of cofilin. These molecular changes are accompanied by an increase in the density of immature dendritic spines, impaired cortical circuit maturation of prefrontal cortex layer 5 projection neurons, and altered laminar excitatory connectivity. Two photon in vivo imaging of dendritic spines reveals that cto-Met enhances de novo spine formation while inhibiting spine elimination. Extending MET signaling for two weeks in developing cortical circuits leads to pronounced repetitive activity and impaired social interactions in adult mice. Collectively, our data revealed that temporally controlled MET signaling as a critical mechanism for controlling cortical circuit development and emergence of normal behavior.
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Affiliation(s)
- Xiaokuang Ma
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Jing Wei
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Yuehua Cui
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Baomei Xia
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Le Zhang
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Antoine Nehme
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Yi Zuo
- Department of Molecular, Cellular and Developmental Neurobiology, University of California at Santa Cruz, Santa Cruz, CA 95064, USA
| | - Deveroux Ferguson
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Pat Levitt
- Program in Developmental Neuroscience and Developmental Neurogenetics, The Saban Research Institute and Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA 90027, USA
| | - Shenfeng Qiu
- Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
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19
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Ma ZH, Lu B, Li X, Mei T, Guo YQ, Yang L, Wang H, Tang XZ, Ji ZZ, Liu JR, Xu LZ, Yang YL, Cao QJ, Yan CG, Liu J. Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2021; 26:1108-1122. [PMID: 34465247 DOI: 10.1177/13623613211041904] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT Autism spectrum disorder has long been conceptualized as a disorder of "atypical development of functional brain connectivity (which refers to correlations in activity levels of distant brain regions)." However, most of the research has focused on the connectivity between cortical regions, and much remains unknown about the developmental changes of functional connectivity between subcortical and cortical areas in autism spectrum disorder. We used the technique of resting-state functional magnetic resonance imaging to explore the developmental characteristics of intrinsic functional connectivity (functional brain connectivity when people are asked not to do anything) between subcortical and cortical regions in individuals with and without autism spectrum disorder aged 6-30 years. We focused on one important subcortical structure called striatum, which has roles in motor, cognitive, and affective processes. We found that cortico-striatal intrinsic functional connectivities showed opposite developmental trajectories in autism spectrum disorder and typically developing individuals, with connectivity increasing with age in autism spectrum disorder and decreasing or constant in typically developing individuals. We also found significant negative behavioral correlations between those atypical cortico-striatal intrinsic functional connectivities and autistic symptoms, such as social-communication deficits, and restricted/repetitive behaviors and interests. Taken together, this work highlights that the atypical development of cortico-subcortical functional connectivity might be largely involved in the neuropathological mechanisms of autism spectrum disorder.
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Affiliation(s)
- Zeng-Hui Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, China.,Department of Psychology, University of Chinese Academy of Sciences, China
| | - Xue Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ting Mei
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yan-Qing Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Liu Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hui Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xin-Zhou Tang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhao-Zheng Ji
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jing-Ran Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ling-Zi Xu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yu-Lu Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Qing-Jiu Cao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, China.,Department of Psychology, University of Chinese Academy of Sciences, China.,Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, China.,International Big-Data Research Center for Depression (IBRCD), Institute of Psychology, Chinese Academy of Sciences, China
| | - Jing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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20
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Park S, Haak KV, Cho HB, Valk SL, Bethlehem RAI, Milham MP, Bernhardt BC, Di Martino A, Hong SJ. Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism. Front Psychiatry 2021; 12:699813. [PMID: 34489757 PMCID: PMC8417581 DOI: 10.3389/fpsyt.2021.699813] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 07/16/2021] [Indexed: 12/12/2022] Open
Abstract
A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology.
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Affiliation(s)
- Shinwon Park
- Institute for Basic Science, Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Koen V. Haak
- Donders Institute of Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Han Byul Cho
- Institute for Basic Science, Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Sofie L. Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7), Forschungszentrum Jülich, Jülich, Germany
| | - Richard A. I. Bethlehem
- Department of Psychiatry, Autism Research Centre, University of Cambridge, Cambridge, United Kingdom
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Michael P. Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, New York, NY, United States
| | - Boris C. Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | | | - Seok-Jun Hong
- Institute for Basic Science, Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
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21
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In Prototypical Autism, the Genetic Ability to Learn Language Is Triggered by Structured Information, Not Only by Exposure to Oral Language. Genes (Basel) 2021; 12:genes12081112. [PMID: 34440286 PMCID: PMC8391732 DOI: 10.3390/genes12081112] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/24/2021] [Accepted: 07/19/2021] [Indexed: 12/24/2022] Open
Abstract
What does the way that autistic individuals bypass, learn, and eventually master language tell us about humans’ genetically encoded linguistic ability? In this theoretical review, we argue that autistic non-social acquisition of language and autistic savant abilities provide a strong argument for an innate, human-specific orientation towards (and mastery of) complex embedded structures. Autistic non-social language learning may represent a widening of the material processed during development beyond oral language. The structure detection and manipulation and generative production of non-linguistic embedded and chained material (savant abilities in calendar calculation, musical composition, musical interpretation, and three-dimensional drawing) may thus represent an application of such innate mechanisms to non-standard materials. Typical language learning through exposure to the child’s mother tongue may represent but one of many possible achievements of the same capacity. The deviation from typical language development in autism may ultimately allow access to oral language, sometimes in its most elaborate forms, and also explain the possibility of the absence of its development when applied exclusively to non-linguistic structured material. Such an extension of human capacities beyond or in parallel to their usual limits call into question what we consider to be specific or expected in humans and therefore does not necessarily represent a genetic “error”. Regardless of the adaptive success or failure of non-social language learning, it is the duty of science and ethical principles to strive to maintain autism as a human potentiality to further foster our vision of a plural society.
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22
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Pretzsch CM, Floris DL, Voinescu B, Elsahib M, Mendez MA, Wichers R, Ajram L, Ivin G, Heasman M, Pretzsch E, Williams S, Murphy DGM, Daly E, McAlonan GM. Modulation of striatal functional connectivity differences in adults with and without autism spectrum disorder in a single-dose randomized trial of cannabidivarin. Mol Autism 2021; 12:49. [PMID: 34210360 PMCID: PMC8252312 DOI: 10.1186/s13229-021-00454-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/17/2021] [Indexed: 11/17/2022] Open
Abstract
Background Autism spectrum disorder (ASD) has a high cost to affected individuals and society, but treatments for core symptoms are lacking. To expand intervention options, it is crucial to gain a better understanding of potential treatment targets, and their engagement, in the brain. For instance, the striatum (caudate, putamen, and nucleus accumbens) plays a central role during development and its (atypical) functional connectivity (FC) may contribute to multiple ASD symptoms. We have previously shown, in the adult autistic and neurotypical brain, the non-intoxicating cannabinoid cannabidivarin (CBDV) alters the balance of striatal ‘excitatory–inhibitory’ metabolites, which help regulate FC, but the effects of CBDV on (atypical) striatal FC are unknown. Methods To examine this in a small pilot study, we acquired resting state functional magnetic resonance imaging data from 28 men (15 neurotypicals, 13 ASD) on two occasions in a repeated-measures, double-blind, placebo-controlled study. We then used a seed-based approach to (1) compare striatal FC between groups and (2) examine the effect of pharmacological probing (600 mg CBDV/matched placebo) on atypical striatal FC in ASD. Visits were separated by at least 13 days to allow for drug washout. Results Compared to the neurotypicals, ASD individuals had lower FC between the ventral striatum and frontal and pericentral regions (which have been associated with emotion, motor, and vision processing). Further, they had higher intra-striatal FC and higher putamenal FC with temporal regions involved in speech and language. In ASD, CBDV reduced hyperconnectivity to the neurotypical level. Limitations Our findings should be considered in light of several methodological aspects, in particular our participant group (restricted to male adults), which limits the generalizability of our findings to the wider and heterogeneous ASD population. Conclusion In conclusion, here we show atypical striatal FC with regions commonly associated with ASD symptoms. We further provide preliminary proof of concept that, in the adult autistic brain, acute CBDV administration can modulate atypical striatal circuitry towards neurotypical function. Future studies are required to determine whether modulation of striatal FC is associated with a change in ASD symptoms. Trial registration clinicaltrials.gov, Identifier: NCT03537950. Registered May 25th, 2018—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03537950?term=NCT03537950&draw=2&rank=1. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-021-00454-6.
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Affiliation(s)
- Charlotte M Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Bogdan Voinescu
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Department of Liaison Psychiatry, Bristol Royal Infirmary, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Malka Elsahib
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Maria A Mendez
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Robert Wichers
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Department of Psychiatry GGZ Geest, Amsterdam, The Netherlands
| | - Laura Ajram
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Medicines Discovery Catapult, Alderley Park, Alderley Edge, SK10 4TG, Cheshire, UK
| | - Glynis Ivin
- South London and Maudsley NHS Foundation Trust Pharmacy, London, UK
| | - Martin Heasman
- South London and Maudsley NHS Foundation Trust Pharmacy, London, UK
| | - Elise Pretzsch
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Steven Williams
- Department of Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Gráinne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
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23
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He C, Cortes JM, Kang X, Cao J, Chen H, Guo X, Wang R, Kong L, Huang X, Xiao J, Shan X, Feng R, Chen H, Duan X. Individual-based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder. Hum Brain Mapp 2021; 42:3282-3294. [PMID: 33934442 PMCID: PMC8193534 DOI: 10.1002/hbm.25434] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 03/04/2021] [Accepted: 03/25/2021] [Indexed: 01/01/2023] Open
Abstract
Individual-based morphological brain networks built from T1-weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio-cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual-based morphological networks were constructed by using high-resolution structural MRI data from 40 young children with ASD (age range: 2-8 years) and 38 age-, gender-, and handedness-matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small-worldness (i.e., σ) of individual-level morphological brain networks, increased morphological connectivity in cortico-striatum-thalamic-cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico-cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio-cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically-relevant biomarkers for ASD.
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Affiliation(s)
- Changchun He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Jesus M. Cortes
- Computational Neuroimaging LaboratoryBiocruces‐Bizkaia Health Research InstituteBarakaldoSpain
- Ikerbasque: The Basque Foundation for ScienceBilbaoSpain
- Department of Cell Biology and HistologyUniversity of the Basque CountryLeioaSpain
| | - Xiaodong Kang
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCMSichuan Bayi Rehabilitation CenterChengduChina
| | - Jing Cao
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCMSichuan Bayi Rehabilitation CenterChengduChina
| | - Heng Chen
- School of MedicineMedical College of Guizhou UniversityGuiyangChina
| | - Xiaonan Guo
- School of Information Science and EngineeringYanshan UniversityQinhuangdaoChina
- Hebei Key Laboratory of information transmission and signal processingYanshan UniversityQinhuangdaoChina
| | - Ruishi Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Lingyin Kong
- Department of Biomedical Engineering, School of Material Science and EngineeringSouth China University of TechnologyGuangzhouChina
| | - Xinyue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Xiaolong Shan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Rui Feng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
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24
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Altered Cerebellum Spontaneous Activity in Juvenile Autism Spectrum Disorders Associated with Clinical Traits. J Autism Dev Disord 2021; 52:2497-2504. [PMID: 34184142 DOI: 10.1007/s10803-021-05167-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/22/2021] [Indexed: 10/21/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder. The associations between the cerebellum and clinical traits remain unclear. We performed amplitude of low-frequency fluctuation (ALFF) analysis to explore the associations between spontaneous brain activity and clinical traits. 361 juvenile ASD patients were included from the ABIDEII database. In the ASD group, the mean ALFF values of cerebellum 4 5 were correlated with SRS awareness and communication. The mean ALFF values of cerebellum 6 and vermis 4 5 were both positively correlated with SRS total, awareness, communication, and motivation. In contrast, the mean ALFF values of vermis 1 2 were negatively correlated with SRS total, awareness, and mannerisms. Our study suggests a role of the cerebellum in functional impairments in ASD.
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25
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Walsh MJM, Wallace GL, Gallegos SM, Braden BB. Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findings. Neuroimage Clin 2021; 31:102719. [PMID: 34153690 PMCID: PMC8233229 DOI: 10.1016/j.nicl.2021.102719] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/02/2021] [Accepted: 06/03/2021] [Indexed: 12/12/2022]
Abstract
Females with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical cohorts. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in "protection." When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain "masculinization" and "feminization" across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.
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Affiliation(s)
- Melissa J M Walsh
- College of Health Solutions, Arizona State University, 975 S. Myrtle Ave, Tempe, AZ 85281, USA
| | - Gregory L Wallace
- Department of Speech, Language, and Hearing Sciences, The George Washington University, 2115 G St. NW, Washington, DC 20052, USA.
| | - Stephen M Gallegos
- College of Health Solutions, Arizona State University, 975 S. Myrtle Ave, Tempe, AZ 85281, USA
| | - B Blair Braden
- College of Health Solutions, Arizona State University, 975 S. Myrtle Ave, Tempe, AZ 85281, USA.
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26
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Nair A, Jalal R, Liu J, Tsang T, McDonald NM, Jackson L, Ponting C, Jeste SS, Bookheimer SY, Dapretto M. Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder. Cereb Cortex 2021; 31:4191-4205. [PMID: 33866373 DOI: 10.1093/cercor/bhab078] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.
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Affiliation(s)
- Aarti Nair
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92354, USA
| | - Rhideeta Jalal
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Janelle Liu
- Interdepartmental Neuroscience Program, University of California, Los Angeles, CA 90095, USA
| | - Tawny Tsang
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Nicole M McDonald
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Lisa Jackson
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Carolyn Ponting
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Shafali S Jeste
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
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27
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Park BY, Hong SJ, Valk SL, Paquola C, Benkarim O, Bethlehem RAI, Di Martino A, Milham MP, Gozzi A, Yeo BTT, Smallwood J, Bernhardt BC. Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism. Nat Commun 2021; 12:2225. [PMID: 33850128 PMCID: PMC8044226 DOI: 10.1038/s41467-021-21732-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 02/05/2021] [Indexed: 01/14/2023] Open
Abstract
The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.
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Affiliation(s)
- Bo-Yong Park
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
- Department of Data Science, Inha University, Incheon, South Korea.
| | - Seok-Jun Hong
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Center for the Developing Brain, Child Mind Institute, New York City, NY, USA
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Sofie L Valk
- Forschungszentrum, Julich, Germany
- Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Oualid Benkarim
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Richard A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Adriana Di Martino
- Center for the Developing Brain, Child Mind Institute, New York City, NY, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York City, NY, USA
| | - Alessandro Gozzi
- Istituto Italiano di Tecnologia, Centre for Neuroscience and Cognitive Systems @ UNITN, Rovereto, Italy
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - Jonathan Smallwood
- Department of Psychology, York Neuroimaging Centre, University of York, York, UK
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
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28
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Zoccante L, Ciceri ML, Gozzi LA, Gennaro GD, Zerman N. The "Connectivome Theory": A New Model to Understand Autism Spectrum Disorders. Front Psychiatry 2021; 12:794516. [PMID: 35250650 PMCID: PMC8892379 DOI: 10.3389/fpsyt.2021.794516] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/23/2021] [Indexed: 12/20/2022] Open
Abstract
The classical approach to autism spectrum disorders (ASD) is often limited to considering their neuro-functional aspects. However, recent scientific literature has shown that ASDs also affect many body systems and apparatuses such as the immune system, the sensory-motor system, and the gut-brain axis. The connective tissue, a common thread linking all these structures, may have a pathogenetic role in the multisystem involvement of ASD. Depending on its different anatomical sites, the connective tissue performs functions of connection and support; furthermore, it acts as a barrier between the external and internal environments, regulating the interchange between the two and performing immunological surveillance. The connective tissue shares a close relationship with the central nervous system, the musculoskeletal system and the immune system. Alterations in brain connectivity are common to various developmental disorders, including ASD, and for this reason here we put forward the hypothesis that alterations in the physiological activity of microglia could be implicated in the pathogenesis of ASD. Also, muscle hypotonia is likely to clinically correlate with an altered sensoriality and, in fact, discomfort or early muscle fatigue are often reported in ASDs. Furthermore, patients with ASD often suffer from intestinal dysfunctions, malabsorption and leaky gut syndrome, all phenomena that may be linked to reduced intestinal connectivity. In addition, at the cutaneous and subcutaneous levels, ASDs show a greater predisposition to inflammatory events due to the lack of adequate release of anti-inflammatory mediators. Alveolar-capillary dysfunctions have also been observed in ASD, most frequently interstitial inflammations, immune-mediated forms of allergic asthma, and bronchial hyper-reactivity. Therefore, in autism, altered connectivity can result in phenomena of altered sensitivity to environmental stimuli. The following interpretative model, that we define as the "connectivome theory," considers the alterations in connective elements of common mesodermal origin located in the various organs and apparatuses and entails the evaluation and interpretation of ASDs through also highlighting somatic elements. We believe that this broader approach could be helpful for a more accurate analysis, as it is able to enrich clinical evaluation and define more multidisciplinary and personalized interventions.
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Affiliation(s)
- Leonardo Zoccante
- Child and Adolescent Neuropsychiatry Unit, Maternal-Child Integrated Care Department, Integrated University Hospital Verona, Verona, Italy.,Autism Spectrum Disorders Regional Centre of Verona, Verona, Italy
| | - Marco Luigi Ciceri
- Child and Adolescent Neuropsychiatry Unit, Maternal-Child Integrated Care Department, Integrated University Hospital Verona, Verona, Italy.,Autism Spectrum Disorders Regional Centre of Verona, Verona, Italy
| | - Luigi Alberto Gozzi
- Child and Adolescent Neuropsychiatry Unit, Maternal-Child Integrated Care Department, Integrated University Hospital Verona, Verona, Italy.,Autism Spectrum Disorders Regional Centre of Verona, Verona, Italy
| | - Gianfranco Di Gennaro
- Department of Pathology and Diagnostics, Integrated University Hospital Verona, Verona, Italy
| | - Nicoletta Zerman
- Department of Surgery, Dentistry, Paediatrics and Gynaecology, University of Verona, Verona, Italy
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29
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Bansal R, Peterson BS. Use of random matrix theory in the discovery of resting state brain networks. Magn Reson Imaging 2020; 77:69-87. [PMID: 33326838 DOI: 10.1016/j.mri.2020.12.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 12/01/2020] [Accepted: 12/06/2020] [Indexed: 11/30/2022]
Abstract
Connectomics identifies brain networks in vivo in resting state functional MRI. However, the presence of noise produces spurious identification of brain networks, which have low test-retest reliability. A Network Based Statistics approach to network identification has been previously proposed that affords much better statistical power relative to Bonferroni method but nevertheless provides a sufficiently conservative, family-wise control for false positives. We propose the use of Random Matrix Theory (RMT) to discover brain networks and to associate those networks with demographic and clinical variables. We parcellated the brain into cortical and subcortical regions using either an anatomical or a functional brain atlas. We applied RMT to study functional connectivity across brain regions by first computing the correlation matrix for time courses in those brain regions and then identifying eigenvalues that deviate from the theoretical random distribution that RMT predicts, on the assumption that real brain networks would produce eigenvalues that differ significantly from the random distribution. We assessed the specificity and test-retest reliability of identified networks through application of this RMT-based approach to (1) synthetic data generated under the null-hypothesis, (2) resting state functional MRI data from 4 real-world cohorts of patients and healthy controls, and (3) synthetic data generated by the addition of increasing amounts of noise to real-world datasets. Our findings showed that RMT method was robust to the atlas used for parcellating the brain and did not discover a brain network in synthetic data when in fact a network was not present (i.e., specificity was high); RMT-identified networks in the real-world dataset had high test-retest reliability; and RMT-based method consistently discovered the same network in the presence of increasing noise in the real-world dataset.
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Affiliation(s)
- Ravi Bansal
- Institute for the Developing Mind, Children's Hospital Los Angeles, CA 90027, USA; Department of Pediatrics, Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033, USA.
| | - Bradley S Peterson
- Institute for the Developing Mind, Children's Hospital Los Angeles, CA 90027, USA; Department of Psychiatry, Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033, USA
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30
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Beyond diagnosis: Cross-diagnostic features in canonical resting-state networks in children with neurodevelopmental disorders. NEUROIMAGE-CLINICAL 2020; 28:102476. [PMID: 33201803 PMCID: PMC7649647 DOI: 10.1016/j.nicl.2020.102476] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 10/15/2020] [Accepted: 10/17/2020] [Indexed: 11/24/2022]
Abstract
Resting-state connectivity did not differ across neurodevelopmental disorders. General adaptive function across all participants related to subcortical connectivity. Participants in the same data-driven clusters were highly heterogeneous in diagnosis. Neurobiological similarity and dissimilarity may be seen in beyond-diagnosis categories.
Children with neurodevelopmental disorders (NDDs) share common behavioural manifestations despite distinct categorical diagnostic criteria. Here, we examined canonical resting-state network connectivity in three diagnostic groups (autism spectrum disorder, attention-deficit/hyperactivity disorder and paediatric obsessive–compulsive disorder) and typically developing controls (TD) in a large single-site sample (N = 407), applying diagnosis-based and dimensional approaches to understand underlying neurobiology across NDDs. Each participant’s functional network graphs were computed using five graph metrics. In diagnosis-based comparisons, an analysis of covariance was performed to compare all NDDs to TD, followed by pairwise comparisons between NDDs. In the dimensional approach, participants’ functional network graphs were correlated with continuous behavioural measures, and a data-driven k-means clustering analysis was applied to determine if subgroups of participants were seen, without diagnostic information having been included. In the diagnosis-based comparisons, children with NDDs did not differ significantly from the TD group and the NDD categorical groups also did not differ significantly from each other, across all graph metrics. In the dimensional, diagnostic-independent approach, however, subcortical functional connectivity was significantly correlated with participants’ general adaptive functioning across all participants. The clustering analysis identified an optimal solution of two clusters, and participants assigned in the same data-driven cluster were highly heterogeneous in diagnosis. Neither cluster exclusively contained a specific diagnostic group, nor did NDDs separate cleanly from TDs. Each participant’s distance ratio between the two clusters was significantly correlated with general adaptive functioning, social deficits and attentional problems. Our results suggest the neurobiological similarity and dissimilarity between NDDs need to be investigated beyond DSM/ICD-based, behaviourally-defined diagnostic categories.
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31
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Zhang H, Wang YF, Zheng LJ, Lin L, Zhang XY, Yang YT, Liu Y, Lu GM, Zhang LJ. Impacts of FKBP5 variants on large-scale brain network connectivity in healthy adults. J Affect Disord 2020; 273:32-40. [PMID: 32421620 DOI: 10.1016/j.jad.2020.04.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 03/18/2020] [Accepted: 04/10/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND FK506 binding protein 5 (FKBP5) rs1360780 polymorphism has been identified as a molecular genetic marker associated with the dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis. The impact of FKBP5 rs1360780 on the large-scale brain network connectivity in healthy adults is still unknown. METHODS 479 healthy volunteers (age: 20-80years) completed MRI scans, neuropsychological assessments and blood analysis.All subjects were divided into CC, CT and TT genotypes. Within and between network connectivities (10 sub-networks) were calculated using resting state functional MRI (rs-fMRI) data. The genetic effects and gene-gender/age interaction on large-scale network connectivity were explored. RESULTS Compared with CC and CT groups, TT group showed increased intra-connectivity in default mode network (DMN) and increased inter-connectivity mainly distributed among the network of DMN, salience network (SAN), dorsal attention network (DAN), ventral attention network (VAN), subcortical network (SUB), and visual network (VIS). Gene-by-gender and gene-by-age interaction were found in inter-connectivity of DAN to VIS and DMN to FPN, respectively. The altered connectivities correlated with anxiety status test score. LIMITATIONS Plasma adrenocorticotropic hormone (ACTH) or cortisol were not measured,or else, we could estimate the hypothalamic-pituitary-adrenal (HPA) axis activity which may strengthen our results. CONCLUSIONS FKBP5 rs1360780 modulates the large-scale brain network connectivity in healthy adults. TT carriers showed the increased intra- and inter-connectivities mainly distributed among the network of DMN, SAN, DAN, VAN, SUB and VIS.
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Affiliation(s)
- Han Zhang
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Yun Fei Wang
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Li Juan Zheng
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Li Lin
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Xin Yuan Zhang
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Yu Ting Yang
- Department of Medical Imaging, Medical Imaging Center, Nanjing Clinical School, Southern Medical University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Ya Liu
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Guang Ming Lu
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China
| | - Long Jiang Zhang
- Department of Medical Imaging, Medical Imaging Center, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, Jiangsu Province, 210002, China.
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32
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Khrameeva E, Kurochkin I, Han D, Guijarro P, Kanton S, Santel M, Qian Z, Rong S, Mazin P, Sabirov M, Bulat M, Efimova O, Tkachev A, Guo S, Sherwood CC, Camp JG, Pääbo S, Treutlein B, Khaitovich P. Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains. Genome Res 2020; 30:776-789. [PMID: 32424074 PMCID: PMC7263190 DOI: 10.1101/gr.256958.119] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 04/30/2020] [Indexed: 12/14/2022]
Abstract
Identification of gene expression traits unique to the human brain sheds light on the molecular mechanisms underlying human evolution. Here, we searched for uniquely human gene expression traits by analyzing 422 brain samples from humans, chimpanzees, bonobos, and macaques representing 33 anatomical regions, as well as 88,047 cell nuclei composing three of these regions. Among 33 regions, cerebral cortex areas, hypothalamus, and cerebellar gray and white matter evolved rapidly in humans. At the cellular level, astrocytes and oligodendrocyte progenitors displayed more differences in the human evolutionary lineage than the neurons. Comparison of the bulk tissue and single-nuclei sequencing revealed that conventional RNA sequencing did not detect up to two-thirds of cell-type-specific evolutionary differences.
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Affiliation(s)
| | - Ilia Kurochkin
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia
| | - Dingding Han
- Guangzhou Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China
| | - Patricia Guijarro
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai, 200031, China
| | - Sabina Kanton
- Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
| | - Malgorzata Santel
- Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
| | - Zhengzong Qian
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai, 200031, China
| | - Shen Rong
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai, 200031, China
| | - Pavel Mazin
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.,Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127051, Russia
| | - Marat Sabirov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Matvei Bulat
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia
| | - Olga Efimova
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia
| | - Anna Tkachev
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.,Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127051, Russia
| | - Song Guo
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.,CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai, 200031, China
| | - Chet C Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - J Gray Camp
- Institute of Molecular and Clinical Ophthalmology, Basel, 4057, Switzerland
| | - Svante Pääbo
- Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
| | - Barbara Treutlein
- Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology in Zurich, Basel, 4058, Switzerland
| | - Philipp Khaitovich
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.,CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai, 200031, China.,Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
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33
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Ramirez-Zamora A, Giordano J, Gunduz A, Alcantara J, Cagle JN, Cernera S, Difuntorum P, Eisinger RS, Gomez J, Long S, Parks B, Wong JK, Chiu S, Patel B, Grill WM, Walker HC, Little SJ, Gilron R, Tinkhauser G, Thevathasan W, Sinclair NC, Lozano AM, Foltynie T, Fasano A, Sheth SA, Scangos K, Sanger TD, Miller J, Brumback AC, Rajasethupathy P, McIntyre C, Schlachter L, Suthana N, Kubu C, Sankary LR, Herrera-Ferrá K, Goetz S, Cheeran B, Steinke GK, Hess C, Almeida L, Deeb W, Foote KD, Okun MS. Proceedings of the Seventh Annual Deep Brain Stimulation Think Tank: Advances in Neurophysiology, Adaptive DBS, Virtual Reality, Neuroethics and Technology. Front Hum Neurosci 2020; 14:54. [PMID: 32292333 PMCID: PMC7134196 DOI: 10.3389/fnhum.2020.00054] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 02/05/2020] [Indexed: 12/12/2022] Open
Abstract
The Seventh Annual Deep Brain Stimulation (DBS) Think Tank held on September 8th of 2019 addressed the most current: (1) use and utility of complex neurophysiological signals for development of adaptive neurostimulation to improve clinical outcomes; (2) Advancements in recent neuromodulation techniques to treat neuropsychiatric disorders; (3) New developments in optogenetics and DBS; (4) The use of augmented Virtual reality (VR) and neuromodulation; (5) commercially available technologies; and (6) ethical issues arising in and from research and use of DBS. These advances serve as both "markers of progress" and challenges and opportunities for ongoing address, engagement, and deliberation as we move to improve the functional capabilities and translational value of DBS. It is in this light that these proceedings are presented to inform the field and initiate ongoing discourse. As consistent with the intent, and spirit of this, and prior DBS Think Tanks, the overarching goal is to continue to develop multidisciplinary collaborations to rapidly advance the field and ultimately improve patient outcomes.
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Affiliation(s)
- Adolfo Ramirez-Zamora
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - James Giordano
- Departments of Neurology and Biochemistry, and Neuroethics Studies Program—Pellegrino Center for Clinical Bioethics, Georgetown University Medical Center, Washington, DC, United States
| | - Aysegul Gunduz
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Jose Alcantara
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Jackson N. Cagle
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Stephanie Cernera
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Parker Difuntorum
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Robert S. Eisinger
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Julieth Gomez
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Sarah Long
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Brandon Parks
- J. Crayton Pruitt Family Department of Biomedical Engineering, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Joshua K. Wong
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Shannon Chiu
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Bhavana Patel
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Warren M. Grill
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Harrison C. Walker
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Simon J. Little
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Ro’ee Gilron
- Graduate Program in Neuroscience, Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and the University of Bern, Bern, Switzerland
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Wesley Thevathasan
- Department of Neurology, The Royal Melbourne and Austin Hospitals, University of Melbourne, Melbourne, VIC, Australia
- Medical Bionics Department, University of Melbourne, East Melbourne, VIC, Australia
- Bionics Institute, East Melbourne, VIC, Australia
| | - Nicholas C. Sinclair
- Medical Bionics Department, University of Melbourne, East Melbourne, VIC, Australia
- Bionics Institute, East Melbourne, VIC, Australia
| | - Andres M. Lozano
- Department of Surgery, Division of Neurosurgery, University of Toronto, Toronto, ON, Canada
| | - Thomas Foltynie
- Institute of Neurology, University College London, London, United Kingdom
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson’s Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Toronto, ON, Canada
- Division of Neurology, University of Toronto, Krembil Brain Institute, Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
| | - Sameer A. Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Katherine Scangos
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Terence D. Sanger
- Department of Biomedical Engineering, Neurology, Biokinesiology, University of Southern California, Los Angeles, CA, United States
| | - Jonathan Miller
- Case Western Reserve University School of Medicine, University Hospitals Cleveland Medical Center, Cleveland, OH, United States
| | - Audrey C. Brumback
- Departments of Neurology and Pediatrics at Dell Medical School and the Center for Learning and Memory, University of Texas at Austin, Austin, TX, United States
| | - Priya Rajasethupathy
- Laboratory for Neural Dynamics and Cognition, Rockefeller University, New York, NY, United States
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| | - Cameron McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Leslie Schlachter
- Department of Neurosurgery, Mount Sinai Health System, New York, NY, United States
| | - Nanthia Suthana
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Cynthia Kubu
- Department of Neurology, Cleveland Clinic, Cleveland, OH, United States
| | - Lauren R. Sankary
- Center for Bioethics, Cleveland Clinic, Cleveland, OH, United States
| | | | - Steven Goetz
- Medtronic Neuromodulation, Minneapolis, MN, United States
| | - Binith Cheeran
- Neuromodulation Division, Abbott, Plano, TX, United States
| | - G. Karl Steinke
- Boston Scientific Neuromodulation, Valencia, CA, United States
| | - Christopher Hess
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Leonardo Almeida
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Wissam Deeb
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Kelly D. Foote
- Department of Neurosurgery, Norman Fixel Institute for Neurological Diseases, Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
| | - Michael S. Okun
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Program for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, United States
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Prohl AK, Scherrer B, Tomas-Fernandez X, Davis PE, Filip-Dhima R, Prabhu SP, Peters JM, Bebin EM, Krueger DA, Northrup H, Wu JY, Sahin M, Warfield SK. Early white matter development is abnormal in tuberous sclerosis complex patients who develop autism spectrum disorder. J Neurodev Disord 2019; 11:36. [PMID: 31838998 PMCID: PMC6912944 DOI: 10.1186/s11689-019-9293-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 11/11/2019] [Indexed: 11/23/2022] Open
Abstract
Background Autism spectrum disorder (ASD) is prevalent in tuberous sclerosis complex (TSC), occurring in approximately 50% of patients, and is hypothesized to be caused by disruption of neural circuits early in life. Tubers, or benign hamartomas distributed stochastically throughout the brain, are the most conspicuous of TSC neuropathology, but have not been consistently associated with ASD. Widespread neuropathology of the white matter, including deficits in myelination, neuronal migration, and axon formation, exist and may underlie ASD in TSC. We sought to identify the neural circuits associated with ASD in TSC by identifying white matter microstructural deficits in a prospectively recruited, longitudinally studied cohort of TSC infants. Methods TSC infants were recruited within their first year of life and longitudinally imaged at time of recruitment, 12 months of age, and at 24 months of age. Autism was diagnosed at 24 months of age with the ADOS-2. There were 108 subjects (62 TSC-ASD, 55% male; 46 TSC+ASD, 52% male) with at least one MRI and a 24-month ADOS, for a total of 187 MRI scans analyzed (109 TSC-ASD; 78 TSC+ASD). Diffusion tensor imaging properties of multiple white matter fiber bundles were sampled using a region of interest approach. Linear mixed effects modeling was performed to test the hypothesis that infants who develop ASD exhibit poor white matter microstructural integrity over the first 2 years of life compared to those who do not develop ASD. Results Subjects with TSC and ASD exhibited reduced fractional anisotropy in 9 of 17 white matter regions, sampled from the arcuate fasciculus, cingulum, corpus callosum, anterior limbs of the internal capsule, and the sagittal stratum, over the first 2 years of life compared to TSC subjects without ASD. Mean diffusivity trajectories did not differ between groups. Conclusions Underconnectivity across multiple white matter fiber bundles develops over the first 2 years of life in subjects with TSC and ASD. Future studies examining brain-behavior relationships are needed to determine how variation in the brain structure is associated with ASD symptoms.
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Affiliation(s)
- Anna K Prohl
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Benoit Scherrer
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Xavier Tomas-Fernandez
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Peter E Davis
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Rajna Filip-Dhima
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Sanjay P Prabhu
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Jurriaan M Peters
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA.,Department of Neurology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - E Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Darcy A Krueger
- Department of Neurology and Rehabilitation Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Joyce Y Wu
- Division of Pediatric Neurology, University of California at Los Angeles Mattel Children's Hospital, David Geffen School of Medicine, University of California, California, Los Angeles, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA.,F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts, USA.
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35
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Hoch MJ, Bruno MT, Faustin A, Cruz N, Mogilner AY, Crandall L, Wisniewski T, Devinsky O, Shepherd TM. 3T MRI Whole-Brain Microscopy Discrimination of Subcortical Anatomy, Part 2: Basal Forebrain. AJNR Am J Neuroradiol 2019; 40:1095-1105. [PMID: 31196861 DOI: 10.3174/ajnr.a6088] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Accepted: 04/22/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND PURPOSE The basal forebrain contains multiple structures of great interest to emerging functional neurosurgery applications, yet many neuroradiologists are unfamiliar with this neuroanatomy because it is not resolved with current clinical MR imaging. MATERIALS AND METHODS We applied an optimized TSE T2 sequence to washed whole postmortem brain samples (n = 13) to demonstrate and characterize the detailed anatomy of the basal forebrain using a clinical 3T MR imaging scanner. We measured the size of selected internal myelinated pathways and measured subthalamic nucleus size, oblique orientation, and position relative to the intercommissural point. RESULTS We identified most basal ganglia and diencephalon structures using serial axial, coronal, and sagittal planes relative to the intercommissural plane. Specific oblique image orientations demonstrated the positions and anatomic relationships for selected structures of interest to functional neurosurgery. We observed only 0.2- to 0.3-mm right-left differences in the anteroposterior and superoinferior length of the subthalamic nucleus (P = .084 and .047, respectively). Individual variability for the subthalamic nucleus was greatest for angulation within the sagittal plane (range, 15°-37°), transverse dimension (range, 2-6.7 mm), and most inferior border (range, 4-7 mm below the intercommissural plane). CONCLUSIONS Direct identification of basal forebrain structures in multiple planes using the TSE T2 sequence makes this challenging neuroanatomy more accessible to practicing neuroradiologists. This protocol can be used to better define individual variations relevant to functional neurosurgical targeting and validate/complement advanced MR imaging methods being developed for direct visualization of these structures in living patients.
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Affiliation(s)
- M J Hoch
- From the Department of Radiology and Imaging Sciences, (M.J.H.), Emory University, Atlanta, Georgia
| | - M T Bruno
- Departments of Radiology (M.T.B., N.C., T.M.S.)
| | | | - N Cruz
- Departments of Radiology (M.T.B., N.C., T.M.S.)
| | | | - L Crandall
- Neurology (L.C., T.W., O.D.).,SUDC Foundation (L.C., O.D.), New York, New York
| | - T Wisniewski
- Pathology (A.F., T.W.).,Neurology (L.C., T.W., O.D.).,Psychiatry (T.W.), New York University, New York, New York
| | - O Devinsky
- Neurology (L.C., T.W., O.D.).,SUDC Foundation (L.C., O.D.), New York, New York
| | - T M Shepherd
- Departments of Radiology (M.T.B., N.C., T.M.S.) .,Center for Advanced Imaging Innovation and Research (T.M.S.), New York, New York
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Kilroy E, Aziz-Zadeh L, Cermak S. Ayres Theories of Autism and Sensory Integration Revisited: What Contemporary Neuroscience Has to Say. Brain Sci 2019; 9:brainsci9030068. [PMID: 30901886 PMCID: PMC6468444 DOI: 10.3390/brainsci9030068] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 03/15/2019] [Accepted: 03/17/2019] [Indexed: 11/17/2022] Open
Abstract
Abnormal sensory-based behaviors are a defining feature of autism spectrum disorders (ASD). Dr. A. Jean Ayres was the first occupational therapist to conceptualize Sensory Integration (SI) theories and therapies to address these deficits. Her work was based on neurological knowledge of the 1970’s. Since then, advancements in neuroimaging techniques make it possible to better understand the brain areas that may underlie sensory processing deficits in ASD. In this article, we explore the postulates proposed by Ayres (i.e., registration, modulation, motivation) through current neuroimaging literature. To this end, we review the neural underpinnings of sensory processing and integration in ASD by examining the literature on neurophysiological responses to sensory stimuli in individuals with ASD as well as structural and network organization using a variety of neuroimaging techniques. Many aspects of Ayres’ hypotheses about the nature of the disorder were found to be highly consistent with current literature on sensory processing in children with ASD but there are some discrepancies across various methodological techniques and ASD development. With additional characterization, neurophysiological profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions, such as SI therapy.
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Affiliation(s)
- Emily Kilroy
- Mrs. T.H. Chan Division of Occupational Science and Occupational Therapy, University Southern California, Los Angeles, CA 90089, USA.
- Brain and Creativity Institute, University Southern California, Los Angeles, CA 90089, USA.
| | - Lisa Aziz-Zadeh
- Mrs. T.H. Chan Division of Occupational Science and Occupational Therapy, University Southern California, Los Angeles, CA 90089, USA.
- Brain and Creativity Institute, University Southern California, Los Angeles, CA 90089, USA.
| | - Sharon Cermak
- Mrs. T.H. Chan Division of Occupational Science and Occupational Therapy, University Southern California, Los Angeles, CA 90089, USA.
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Demetriou EA, DeMayo MM, Guastella AJ. Executive Function in Autism Spectrum Disorder: History, Theoretical Models, Empirical Findings, and Potential as an Endophenotype. Front Psychiatry 2019; 10:753. [PMID: 31780959 PMCID: PMC6859507 DOI: 10.3389/fpsyt.2019.00753] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Accepted: 09/19/2019] [Indexed: 12/13/2022] Open
Abstract
This review presents an outline of executive function (EF) and its application to autism spectrum disorder (ASD). The development of the EF construct, theoretical models of EF, and limitations in the study of EF are outlined. The potential of EF as a cognitive endophenotype for ASD is reviewed, and the Research Domain Criteria (RDoC) framework is discussed for researching EF in ASD given the multifaceted factors that influence EF performance. A number of executive-focused cognitive models have been proposed to explain the symptom clusters observed in ASD. Empirical studies suggest a broad impairment in EF, although there is significant inter-individual variability in EF performance. The observed heterogeneity of EF performance is considered a limiting factor in establishing EF as a cognitive endophenotype in ASD. We propose, however, that this variability in EF performance presents an opportunity for subtyping within the spectrum that can contribute to targeted diagnostic and intervention strategies. Enhanced understanding of the neurobiological basis that underpins EF performance, such as the excitation/inhibition hypothesis, will likely be important. Application of the RDoC framework could provide clarity on the nature of EF impairment in ASD with potential for greater understanding of, and improved interventions for, this disorder.
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Affiliation(s)
- Eleni A Demetriou
- Autism Clinic for Translational Research, Brain and Mind Centre, Faculty of Medicine and Health, Children's Hospital Westmead Clinical School, University of Sydney, Sydney, NSW, Australia
| | - Marilena M DeMayo
- Autism Clinic for Translational Research, Brain and Mind Centre, Faculty of Medicine and Health, Children's Hospital Westmead Clinical School, University of Sydney, Sydney, NSW, Australia
| | - Adam J Guastella
- Autism Clinic for Translational Research, Brain and Mind Centre, Faculty of Medicine and Health, Children's Hospital Westmead Clinical School, University of Sydney, Sydney, NSW, Australia
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