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Liloia D, Zamfira DA, Tanaka M, Manuello J, Crocetta A, Keller R, Cozzolino M, Duca S, Cauda F, Costa T. Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research. Neurosci Biobehav Rev 2024; 164:105791. [PMID: 38960075 DOI: 10.1016/j.neubiorev.2024.105791] [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: 10/26/2023] [Revised: 05/22/2024] [Accepted: 06/27/2024] [Indexed: 07/05/2024]
Abstract
Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Denisa Adina Zamfira
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Masaru Tanaka
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, Szeged, Hungary
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Annachiara Crocetta
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Mauro Cozzolino
- Department of Humanities, Philosophical and Educational Sciences, University of Salerno, Fisciano, Italy
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy
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2
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Ma C, Li W, Ke S, Lv J, Zhou T, Zou L. Identification of autism spectrum disorder using multiple functional connectivity-based graph convolutional network. Med Biol Eng Comput 2024; 62:2133-2144. [PMID: 38457067 DOI: 10.1007/s11517-024-03060-9] [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: 08/18/2023] [Accepted: 02/23/2024] [Indexed: 03/09/2024]
Abstract
Presently, the combination of graph convolutional networks (GCN) with resting-state functional magnetic resonance imaging (rs-fMRI) data is a promising approach for early diagnosis of autism spectrum disorder (ASD). However, the prevalent approach involves exclusively full-brain functional connectivity data for disease classification using GCN, while overlooking the prior information related to the functional connectivity of brain subnetworks associated with ASD. Therefore, in this study, the multiple functional connectivity-based graph convolutional network (MFC-GCN) framework is proposed, using not only full brain functional connectivity data but also the established functional connectivity data from networks of key brain subnetworks associated with ASD, and the GCN is adopted to acquire complementary feature information for the final classification task. Given the heterogeneity within the Autism Brain Imaging Data Exchange (ABIDE) dataset, a novel External Attention Network Readout (EANReadout) is introduced. This design enables the exploration of potential subject associations, effectively addressing the dataset's heterogeneity. Experiments were conducted on the ABIDE dataset using the proposed framework, involving 714 subjects, and the average accuracy of the framework was 70.31%. The experimental results show that the proposed EANReadout outperforms the best traditional readout layer and improves the average accuracy of the framework by 4.32%.
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Affiliation(s)
- Chaoran Ma
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, Jiangsu, China
| | - Wenjie Li
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, 213164, Jiangsu, China
| | - Sheng Ke
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, Jiangsu, China
| | - Jidong Lv
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, 213164, Jiangsu, China
| | - Tiantong Zhou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, 213164, Jiangsu, China
| | - Ling Zou
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, Jiangsu, China.
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, 213164, Jiangsu, China.
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Liu M, Zhang H, Liu M, Chen D, Zhuang Z, Wang X, Zhang L, Peng D, Wang Q. Randomizing Human Brain Function Representation for Brain Disease Diagnosis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2537-2546. [PMID: 38376975 DOI: 10.1109/tmi.2024.3368064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Resting-state fMRI (rs-fMRI) is an effective tool for quantifying functional connectivity (FC), which plays a crucial role in exploring various brain diseases. Due to the high dimensionality of fMRI data, FC is typically computed based on the region of interest (ROI), whose parcellation relies on a pre-defined atlas. However, utilizing the brain atlas poses several challenges including 1) subjective selection bias in choosing from various brain atlases, 2) parcellation of each subject's brain with the same atlas yet disregarding individual specificity; 3) lack of interaction between brain region parcellation and downstream ROI-based FC analysis. To address these limitations, we propose a novel randomizing strategy for generating brain function representation to facilitate neural disease diagnosis. Specifically, we randomly sample brain patches, thus avoiding ROI parcellations of the brain atlas. Then, we introduce a new brain function representation framework for the sampled patches. Each patch has its function description by referring to anchor patches, as well as the position description. Furthermore, we design an adaptive-selection-assisted Transformer network to optimize and integrate the function representations of all sampled patches within each brain for neural disease diagnosis. To validate our framework, we conduct extensive evaluations on three datasets, and the experimental results establish the effectiveness and generality of our proposed method, offering a promising avenue for advancing neural disease diagnosis beyond the confines of traditional atlas-based methods. Our code is available at https://github.com/mjliu2020/RandomFR.
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Chen L, Abate M, Fredericks M, Guo Y, Tao Z, Zhang X. Age-related differences in the intrinsic connectivity of the hippocampus and ventral temporal lobe in autistic individuals. Front Hum Neurosci 2024; 18:1394706. [PMID: 38938289 PMCID: PMC11208705 DOI: 10.3389/fnhum.2024.1394706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Accepted: 05/22/2024] [Indexed: 06/29/2024] Open
Abstract
Introduction Although memory challenges in autistic individuals have been characterized recently, the functional connectivity of the hippocampus and ventral temporal lobe, two structures important for episodic and semantic memory functions, are poorly understood in autistic individuals. Moreover, age-related differences in the functional connectivity associated with these two memory networks are unrevealed. Methods The current study investigated age-related differences in intrinsic connectivity of the hippocampal and ventral temporal lobe (vTL) memory networks in well-matched ASD (n = 73; age range: 10.23-55.40 years old) and Non-ASD groups (n = 74; age range: 10.46-56.20 years old) from the open dataset ABIDE-I. Both theory-driven ROI-to-ROI approach and exploratory seed-based whole-brain approach were used. Results and discussion Our findings revealed reduced connectivity in ASD compared to Non-ASD peers, as well as an age-related reduction in the connectivity of hippocampal and vTL networks with triple networks, namely, the default mode network (DMN), the central executive network (CEN), and the salience network (SN), potentially underpinning their challenges in memory, language, and social functions. However, we did not observe reliable differences in age-related effects between the ASD and Non-ASD groups. Our study underscores the importance of understanding memory network dysfunctions in ASD across the lifespan to inform educational and clinical practices.
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Affiliation(s)
- Lang Chen
- Department of Psychology, Santa Clara University, Santa Clara, CA, United States
- Neuroscience Program, Santa Clara University, Santa Clara, CA, United States
| | - Meghan Abate
- Neuroscience Program, Santa Clara University, Santa Clara, CA, United States
| | | | - Yuanchun Guo
- Department of Counseling Psychology, Santa Clara University, Santa Clara, CA, United States
| | - Zhizhen Tao
- Department of Counseling Psychology, Santa Clara University, Santa Clara, CA, United States
| | - Xiuming Zhang
- Department of Psychology, Santa Clara University, Santa Clara, CA, United States
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Zhou R, Sun C, Sun M, Ruan Y, Li W, Gao X. Altered intra- and inter-network connectivity in autism spectrum disorder. Aging (Albany NY) 2024; 16:10004-10015. [PMID: 38862259 PMCID: PMC11210244 DOI: 10.18632/aging.205913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 05/03/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVE A neurodevelopmental illness termed as the autism spectrum disorder (ASD) is described by social interaction impairments. Previous studies employing resting-state functional imaging (rs-fMRI) identified both hyperconnectivity and hypoconnectivity patterns in ASD people. However, specific patterns of connectivity within and between networks linked to ASD remain largely unexplored. METHODS We utilized a meticulously selected subset of high-quality data, comprising 45 individuals diagnosed with ASD and 47 HCs, obtained from the ABIDE dataset. The pre-processed rs-fMRI time series signals were partitioned into ninety regions of interest. We focused on eight intrinsic connectivity networks and further performed intra- and inter-network analysis. Finally, support vector machine was used to discriminate ASD from HC. RESULTS Through different sparsities, ASD exhibited significantly decreased intra-network connectivity within default mode network and dorsal attention network, increased connectivity between limbic network and subcortical network, and decreased connectivity between default mode network and limbic network. Using the classifier trained on altered intra- and inter-network connectivity, multivariate pattern analyses classified the ASD from HC with 71.74% accuracy, 70.21% specificity and 75.56% sensitivity in 10% sparsity of functional connectivity. CONCLUSIONS ASD showed characteristic reorganization of the brain networks and this provided new insight into the underlying process of the functional connectome dysfunction in ASD.
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Affiliation(s)
- Rui Zhou
- School of Zhang Jian, Nantong University, Nantong, China
- College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, China
| | - Chenhao Sun
- Department of Radiology, Rugao Jian’an Hospital, Nantong, China
| | - Mingxiang Sun
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Yudi Ruan
- College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, China
| | - Weikai Li
- College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Xin Gao
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
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Lord B, Sanguinetti JL, Ruiz L, Miskovic V, Segre J, Young S, Fini ME, Allen JJB. Transcranial focused ultrasound to the posterior cingulate cortex modulates default mode network and subjective experience: an fMRI pilot study. Front Hum Neurosci 2024; 18:1392199. [PMID: 38895168 PMCID: PMC11184145 DOI: 10.3389/fnhum.2024.1392199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/17/2024] [Indexed: 06/21/2024] Open
Abstract
Background Transcranial focused ultrasound (TFUS) is an emerging neuromodulation tool for temporarily altering brain activity and probing network functioning. The effects of TFUS on the default mode network (DMN) are unknown. Objective The study examined the effects of transcranial focused ultrasound (TFUS) on the functional connectivity of the default mode network (DMN), specifically by targeting the posterior cingulate cortex (PCC). Additionally, we investigated the subjective effects of TFUS on mood, mindfulness, and self-related processing. Methods The study employed a randomized, single-blind design involving 30 healthy subjects. Participants were randomly assigned to either the active TFUS group or the sham TFUS group. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted before and after the TFUS application. To measure subjective effects, the Toronto Mindfulness Scale, the Visual Analog Mood Scale, and the Amsterdam Resting State Questionnaire were administered at baseline and 30 min after sonication. The Self Scale and an unstructured interview were also administered 30 min after sonication. Results The active TFUS group exhibited significant reductions in functional connectivity along the midline of the DMN, while the sham TFUS group showed no changes. The active TFUS group demonstrated increased state mindfulness, reduced Global Vigor, and temporary alterations in the sense of ego, sense of time, and recollection of memories. The sham TFUS group showed an increase in state mindfulness, too, with no other subjective effects. Conclusions TFUS targeted at the PCC can alter DMN connectivity and cause changes in subjective experience. These findings support the potential of TFUS to serve both as a research tool and as a potential therapeutic intervention.
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Affiliation(s)
- Brian Lord
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
| | - Joseph L. Sanguinetti
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
- Sanmai Technologies, PBC, Sunnyvale, CA, United States
| | - Lisannette Ruiz
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
- Sanmai Technologies, PBC, Sunnyvale, CA, United States
| | | | - Joel Segre
- X, the Moonshot Factory, Mountain View, CA, United States
| | - Shinzen Young
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
| | - Maria E. Fini
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
| | - John J. B. Allen
- SEMA Lab, Psychology Department, Center for Consciousness Studies, University of Arizona, Tucson, AZ, United States
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Wang L, Qin Y, Yang S, Jin D, Zhu Y, Li X, Li W, Wang Y, Jin C. Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model. Hum Brain Mapp 2024; 45:e26750. [PMID: 38853710 PMCID: PMC11163228 DOI: 10.1002/hbm.26750] [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: 01/10/2024] [Revised: 05/12/2024] [Accepted: 05/22/2024] [Indexed: 06/11/2024] Open
Abstract
The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.
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Affiliation(s)
- Lei Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yue Qin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Shuhan Yang
- Department of Disease Control and PreventionNinth Hospital of Xi'anXi'anChina
| | - Dayong Jin
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yinhu Zhu
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Xin Li
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Wei Li
- Department of Radiology, Tangdu HospitalAir Force Military Medical UniversityXi'anChina
| | - Yarong Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Chenwang Jin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
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Zhang S, Jiang L, Hu Z, Liu W, Yu H, Chu Y, Wang J, Chen Y. T1w/T2w ratio maps identify children with autism spectrum disorder and the relationships between myelin-related changes and symptoms. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111040. [PMID: 38806093 DOI: 10.1016/j.pnpbp.2024.111040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/14/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Modern neuroimaging methods have revealed that autistic symptoms are associated with abnormalities in brain morphology, connectivity, and activity patterns. However, the changes in brain microstructure underlying the neurobiological and behavioral deficits of autism remain largely unknown. METHODS we characterized the associated abnormalities in intracortical myelination pattern by constructing cortical T1-weighted/T2-weighted ratio maps. Voxel-wise comparisons of cortical myelination were conducted between 150 children with autism spectrum disorder (ASD) and 139 typically developing (TD) children. Group differences in cortical T1-weighted/T2-weighted ratio and gray matter volume were then examined for associations with autistic symptoms. A convolutional neural network (CNN) model was also constructed to examine the utility of these regional abnormalities in cortical myelination for ASD diagnosis. RESULTS Compared to TD children, the ASD group exhibited widespread reductions in cortical myelination within regions related to default mode, salience, and executive control networks such as the inferior frontal gyrus, bilateral insula, left fusiform gyrus, bilateral hippocampus, right calcarine sulcus, bilateral precentral, and left posterior cingulate gyrus. Moreover, greater myelination deficits in most of these regions were associated with more severe autistic symptoms. In addition, children with ASD exhibited reduced myelination in regions with greater gray matter volume, including left insula, left cerebellum_4_5, left posterior cingulate gyrus, and right calcarine sulcus. Notably, the CNN model based on brain regions with abnormal myelination demonstrated high diagnostic efficacy for ASD. CONCLUSIONS Our findings suggest that microstructural abnormalities in myelination contribute to autistic symptoms and so are potentially promising therapeutic targets as well as biomarkers for ASD diagnosis.
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Affiliation(s)
- Shujun Zhang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Liping Jiang
- Department of Pharmacy, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Zhe Hu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Wenjing Liu
- Children Rehabilitation Center, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Hao Yu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Yao Chu
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
| | - Jiehuan Wang
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
| | - Yueqin Chen
- Department of Radiology, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China.
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Kang J, Li Y, Lv S, Hao P, Li X. Effects of transcranial direct current stimulation on brain activity and cortical functional connectivity in children with autism spectrum disorders. Front Psychiatry 2024; 15:1407267. [PMID: 38812483 PMCID: PMC11135472 DOI: 10.3389/fpsyt.2024.1407267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 04/22/2024] [Indexed: 05/31/2024] Open
Abstract
Introduction Transcranial direct current stimulation (tDCS) has emerged as a therapeutic option to mitigate symptoms in individuals with autism spectrum disorder (ASD). Our study investigated the effects of a two-week regimen of tDCS targeting the left dorsolateral prefrontal cortex (DLPFC) in children with ASD, examining changes in rhythmic brain activity and alterations in functional connectivity within key neural networks: the default mode network (DMN), sensorimotor network (SMN), and dorsal attention network (DAN). Methods We enrolled twenty-six children with ASD and assigned them randomly to either an active stimulation group (n=13) or a sham stimulation group (n=13). The active group received tDCS at an intensity of 1mA to the left DLPFC for a combined duration of 10 days. Differences in electrical brain activity were pinpointed using standardized low-resolution brain electromagnetic tomography (sLORETA), while functional connectivity was assessed via lagged phase synchronization. Results Compared to the typically developing children, children with ASD exhibited lower current source density across all frequency bands. Post-treatment, the active stimulation group demonstrated a significant increase in both current source density and resting state network connectivity. Such changes were not observed in the sham stimulation group. Conclusion tDCS targeting the DLPFC may bolster brain functional connectivity in patients with ASD, offering a substantive groundwork for potential clinical applications.
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Affiliation(s)
- Jiannan Kang
- College of Electronic & Information Engineering, Hebei University, Baoding, China
| | - Yuqi Li
- College of Electronic & Information Engineering, Hebei University, Baoding, China
| | - Shuaikang Lv
- College of Electronic & Information Engineering, Hebei University, Baoding, China
| | - Pengfei Hao
- College of Electronic & Information Engineering, Hebei University, Baoding, China
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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Lee S, Jung WB, Moon H, Im GH, Noh YW, Shin W, Kim YG, Yi JH, Hong SJ, Jung Y, Ahn S, Kim SG, Kim E. Anterior cingulate cortex-related functional hyperconnectivity underlies sensory hypersensitivity in Grin2b-mutant mice. Mol Psychiatry 2024:10.1038/s41380-024-02572-y. [PMID: 38704508 DOI: 10.1038/s41380-024-02572-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 05/06/2024]
Abstract
Sensory abnormalities are observed in ~90% of individuals with autism spectrum disorders (ASD), but the underlying mechanisms are poorly understood. GluN2B, an NMDA receptor subunit that regulates long-term depression and circuit refinement during brain development, has been strongly implicated in ASD, but whether GRIN2B mutations lead to sensory abnormalities remains unclear. Here, we report that Grin2b-mutant mice show behavioral sensory hypersensitivity and brain hyperconnectivity associated with the anterior cingulate cortex (ACC). Grin2b-mutant mice with a patient-derived C456Y mutation (Grin2bC456Y/+) show sensory hypersensitivity to mechanical, thermal, and electrical stimuli through supraspinal mechanisms. c-fos and functional magnetic resonance imaging indicate that the ACC is hyperactive and hyperconnected with other brain regions under baseline and stimulation conditions. ACC pyramidal neurons show increased excitatory synaptic transmission. Chemogenetic inhibition of ACC pyramidal neurons normalizes ACC hyperconnectivity and sensory hypersensitivity. These results suggest that GluN2B critically regulates ASD-related cortical connectivity and sensory brain functions.
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Affiliation(s)
- Soowon Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Korea
- Department of Anesthesiology and Pain Medicine, Seoul National University Bundang Hospital, Seongnam, 13620, Korea
| | - Won Beom Jung
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419, Korea
- Emotion, Cognition & Behavior Research Group, Korea Brain Research Institute (KBRI), Daegu, 41062, Korea
| | - Heera Moon
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419, Korea
| | - Young Woo Noh
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science (IBS), Daejeon, 34141, Korea
| | - Wangyong Shin
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science (IBS), Daejeon, 34141, Korea
| | - Yong Gyu Kim
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science (IBS), Daejeon, 34141, Korea
| | - Jee Hyun Yi
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science (IBS), Daejeon, 34141, Korea
| | - Seok Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419, Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, Korea
| | - Yongwhan Jung
- Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Korea
| | - Sunjoo Ahn
- Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Korea
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419, Korea.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, 16419, Korea.
| | - Eunjoon Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Korea.
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science (IBS), Daejeon, 34141, Korea.
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Xue Y, Bai MS, Dong HY, Wang TT, Mohamed ZA, Jia FY. Altered intra- and inter-network brain functional connectivity associated with prolonged screen time in pre-school children with autism spectrum disorder. Eur J Pediatr 2024; 183:2391-2399. [PMID: 38448613 DOI: 10.1007/s00431-024-05500-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/27/2024] [Accepted: 02/28/2024] [Indexed: 03/08/2024]
Abstract
Prolonged screen time (ST) has adverse effects on autistic characteristics and language development. However, the mechanisms underlying the effects of prolonged ST on the neurodevelopment of children with autism spectrum disorder (ASD) remain unclear. Neuroimaging technology may help to further explain the role of prolonged ST in individuals with ASD. This study included 164 cases, all cases were divided into low-dose ST exposure (LDE group 108 cases) and high-dose ST exposure (HDE group 56 cases) based on the average ST of all subjects. Spatial independent component analysis (ICA) was used to identify resting state networks (RSNs) and investigate intra- and inter-network alterations in ASD children with prolonged ST. We found that the total Childhood Autism Rating Scale (CARS) scores in the HDE group were significantly higher than those in the LDE group (36.2 ± 3.1 vs. 34.6 ± 3.9, p = 0.008). In addition, the developmental quotient (DQ) of hearing and language in the HDE group were significantly lower than those in the LDE group (31.5 ± 13.1 vs. 42.5 ± 18.5, p < 0.001). A total of 13 independent components (ICs) were identified. Between-group comparison revealed that the HDE group exhibited decreased functional connectivity (FC) in the left precuneus (PCUN) of the default mode network (DMN), the right middle temporal gyrus (MTG) of the executive control network (ECN), and the right median cingulate and paracingulate gyri (MCG) of the attention network (ATN), compared with the LDE group. Additionally, there was an increase in FC in the right orbital part of the middle frontal gyrus (ORBmid) of the salience network (SAN), compared with the LDE group. The inter-network analysis revealed increased FC between the visual network (VN) and basal ganglia (BG) and decreased FC between the sensorimotor network (SMN) and DMN, SMN and ATN, SMN and auditory network (AUN), and DMN and SAN in the HDE group, compared with the LDE group. There was a significant negative correlation between altered FC values in MTG and total CARS scores in subjects (r = - 0.18, p = 0.018). Conclusion: ASD children with prolonged ST often exhibit lower DQ of language development and more severe autistic characteristics. The alteration of intra- and inter-network FC may be a key neuroimaging feature of the effect of prolonged ST on neurodevelopment in ASD children. Clinical trial registration: ChiCTR2100051141. What is Known: • Prolonged ST has adverse effects on autistic characteristics and language development. • Neuroimaging technology may help to further explain the role of prolonged ST in ASD. What is New: • This is the first study to explore the impact of ST on intra- and inter-network FC in children with ASD. • ASD children with prolonged ST have atypical changes in intra- and inter-brain network FC.
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Affiliation(s)
- Yang Xue
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China
- The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Miao-Shui Bai
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China
- The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Han-Yu Dong
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China
- The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Tian-Tian Wang
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China
- The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Zakaria Ahmed Mohamed
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China
- The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Fei-Yong Jia
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China.
- The Child Health Clinical Research Center of Jilin Province, Changchun, China.
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12
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Fradkin Y, De Taboada L, Naeser M, Saltmarche A, Snyder W, Steingold E. Transcranial photobiomodulation in children aged 2-6 years: a randomized sham-controlled clinical trial assessing safety, efficacy, and impact on autism spectrum disorder symptoms and brain electrophysiology. Front Neurol 2024; 15:1221193. [PMID: 38737349 PMCID: PMC11086174 DOI: 10.3389/fneur.2024.1221193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 03/11/2024] [Indexed: 05/14/2024] Open
Abstract
Background Small pilot studies have suggested that transcranial photobiomodulation (tPBM) could help reduce symptoms of neurological conditions, such as depression, traumatic brain injury, and autism spectrum disorder (ASD). Objective To examine the impact of tPBM on the symptoms of ASD in children aged two to six years. Method We conducted a randomized, sham-controlled clinical trial involving thirty children aged two to six years with a prior diagnosis of ASD. We delivered pulses of near-infrared light (40 Hz, 850 nm) noninvasively to selected brain areas twice a week for eight weeks, using an investigational medical device designed for this purpose (Cognilum™, JelikaLite Corp., New York, United States). We used the Childhood Autism Rating Scale (CARS, 2nd Edition) to assess and compare the ASD symptoms of participants before and after the treatment course. We collected electroencephalogram (EEG) data during each session from those participants who tolerated wearing the EEG cap. Results The difference in the change in CARS scores between the two groups was 7.23 (95% CI 2.357 to 12.107, p = 0.011). Seventeen of the thirty participants completed at least two EEGs and time-dependent trends were detected. In addition, an interaction between Active versus Sham and Scaled Time was observed in delta power (Coefficient = 7.521, 95% CI -0.517 to 15.559, p = 0.07) and theta power (Coefficient = -8.287, 95% CI -17.199 to 0.626, p = 0.07), indicating a potential trend towards a greater reduction in delta power and an increase in theta power over time with treatment in the Active group, compared to the Sham group. Furthermore, there was a significant difference in the condition (Treatment vs. Sham) in the power of theta waves (net_theta) (Coefficient = 9.547, 95% CI 0.027 to 19.067, p = 0.049). No moderate or severe side effects or adverse effects were reported or observed during the trial. Conclusion These results indicate that tPBM may be a safe and effective treatment for ASD and should be studied in more depth in larger studies.Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT04660552, identifier NCT04660552.
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Affiliation(s)
- Yuliy Fradkin
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States
| | | | - Margaret Naeser
- Chobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States
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13
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Guo Z, Tang X, Xiao S, Yan H, Sun S, Yang Z, Huang L, Chen Z, Wang Y. Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder. Mol Autism 2024; 15:16. [PMID: 38576034 PMCID: PMC10996269 DOI: 10.1186/s13229-024-00593-6] [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: 11/08/2023] [Accepted: 03/13/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD). METHODS A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software. RESULTS A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences. CONCLUSIONS The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.
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Affiliation(s)
- Zixuan Guo
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xinyue Tang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shu Xiao
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Hong Yan
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shilin Sun
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zibin Yang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Li Huang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhuoming Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Ying Wang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
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14
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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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15
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Gaiser C, van der Vliet R, de Boer AAA, Donchin O, Berthet P, Devenyi GA, Mallar Chakravarty M, Diedrichsen J, Marquand AF, Frens MA, Muetzel RL. Population-wide cerebellar growth models of children and adolescents. Nat Commun 2024; 15:2351. [PMID: 38499518 PMCID: PMC10948906 DOI: 10.1038/s41467-024-46398-2] [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: 08/15/2023] [Accepted: 02/22/2024] [Indexed: 03/20/2024] Open
Abstract
In the past, the cerebellum has been best known for its crucial role in motor function. However, increasingly more findings highlight the importance of cerebellar contributions in cognitive functions and neurodevelopment. Using a total of 7240 neuroimaging scans from 4862 individuals, we describe and provide detailed, openly available models of cerebellar development in childhood and adolescence (age range: 6-17 years), an important time period for brain development and onset of neuropsychiatric disorders. Next to a traditionally used anatomical parcellation of the cerebellum, we generated growth models based on a recently proposed functional parcellation. In both, we find an anterior-posterior growth gradient mirroring the age-related improvements of underlying behavior and function, which is analogous to cerebral maturation patterns and offers evidence for directly related cerebello-cortical developmental trajectories. Finally, we illustrate how the current approach can be used to detect cerebellar abnormalities in clinical samples.
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Affiliation(s)
- Carolin Gaiser
- Department of Neuroscience, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia Children's Hospital, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Rick van der Vliet
- Department of Neuroscience, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Augustijn A A de Boer
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Opher Donchin
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Be'er Sheva, Israel
- Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Pierre Berthet
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Research Centre, McGill University, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Research Centre, McGill University, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Canada
| | - Jörn Diedrichsen
- Western Institute of Neuroscience, Western University, London, Ontario, Canada
- Department of Statistical and Actuarial Sciences, Western University, London, Ontario, Canada
- Department of Computer Science, Western University, London, Ontario, Canada
| | - Andre F Marquand
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Maarten A Frens
- Department of Neuroscience, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands.
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia Children's Hospital, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
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16
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Zanesco AP. Normative Temporal Dynamics of Resting EEG Microstates. Brain Topogr 2024; 37:243-264. [PMID: 37702825 DOI: 10.1007/s10548-023-01004-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/23/2023] [Indexed: 09/14/2023]
Abstract
The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.
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Affiliation(s)
- Anthony P Zanesco
- Department of Psychology, University of Miami, Coral Gables, FL, USA.
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17
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Ryali S, Zhang Y, de los Angeles C, Supekar K, Menon V. Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization. Proc Natl Acad Sci U S A 2024; 121:e2310012121. [PMID: 38377194 PMCID: PMC10907309 DOI: 10.1073/pnas.2310012121] [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: 06/23/2023] [Accepted: 12/21/2023] [Indexed: 02/22/2024] Open
Abstract
Sex plays a crucial role in human brain development, aging, and the manifestation of psychiatric and neurological disorders. However, our understanding of sex differences in human functional brain organization and their behavioral consequences has been hindered by inconsistent findings and a lack of replication. Here, we address these challenges using a spatiotemporal deep neural network (stDNN) model to uncover latent functional brain dynamics that distinguish male and female brains. Our stDNN model accurately differentiated male and female brains, demonstrating consistently high cross-validation accuracy (>90%), replicability, and generalizability across multisession data from the same individuals and three independent cohorts (N ~ 1,500 young adults aged 20 to 35). Explainable AI (XAI) analysis revealed that brain features associated with the default mode network, striatum, and limbic network consistently exhibited significant sex differences (effect sizes > 1.5) across sessions and independent cohorts. Furthermore, XAI-derived brain features accurately predicted sex-specific cognitive profiles, a finding that was also independently replicated. Our results demonstrate that sex differences in functional brain dynamics are not only highly replicable and generalizable but also behaviorally relevant, challenging the notion of a continuum in male-female brain organization. Our findings underscore the crucial role of sex as a biological determinant in human brain organization, have significant implications for developing personalized sex-specific biomarkers in psychiatric and neurological disorders, and provide innovative AI-based computational tools for future research.
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Affiliation(s)
- Srikanth Ryali
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Yuan Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Carlo de los Angeles
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Kaustubh Supekar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
- Stanford Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA94305
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
- Stanford Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA94305
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA94305
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18
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Liloia D, Manuello J, Costa T, Keller R, Nani A, Cauda F. Atypical local brain connectivity in pediatric autism spectrum disorder? A coordinate-based meta-analysis of regional homogeneity studies. Eur Arch Psychiatry Clin Neurosci 2024; 274:3-18. [PMID: 36599959 PMCID: PMC10787009 DOI: 10.1007/s00406-022-01541-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 12/16/2022] [Indexed: 01/05/2023]
Abstract
Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age [Formula: see text] 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Jordi Manuello
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy.
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
- Neuroscience Institute of Turin (NIT), Turin, Italy.
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Andrea Nani
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
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Ross LA, Molholm S, Butler JS, Del Bene VA, Brima T, Foxe JJ. Neural correlates of audiovisual narrative speech perception in children and adults on the autism spectrum: A functional magnetic resonance imaging study. Autism Res 2024; 17:280-310. [PMID: 38334251 DOI: 10.1002/aur.3104] [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: 10/03/2023] [Accepted: 01/19/2024] [Indexed: 02/10/2024]
Abstract
Autistic individuals show substantially reduced benefit from observing visual articulations during audiovisual speech perception, a multisensory integration deficit that is particularly relevant to social communication. This has mostly been studied using simple syllabic or word-level stimuli and it remains unclear how altered lower-level multisensory integration translates to the processing of more complex natural multisensory stimulus environments in autism. Here, functional neuroimaging was used to examine neural correlates of audiovisual gain (AV-gain) in 41 autistic individuals to those of 41 age-matched non-autistic controls when presented with a complex audiovisual narrative. Participants were presented with continuous narration of a story in auditory-alone, visual-alone, and both synchronous and asynchronous audiovisual speech conditions. We hypothesized that previously identified differences in audiovisual speech processing in autism would be characterized by activation differences in brain regions well known to be associated with audiovisual enhancement in neurotypicals. However, our results did not provide evidence for altered processing of auditory alone, visual alone, audiovisual conditions or AV- gain in regions associated with the respective task when comparing activation patterns between groups. Instead, we found that autistic individuals responded with higher activations in mostly frontal regions where the activation to the experimental conditions was below baseline (de-activations) in the control group. These frontal effects were observed in both unisensory and audiovisual conditions, suggesting that these altered activations were not specific to multisensory processing but reflective of more general mechanisms such as an altered disengagement of Default Mode Network processes during the observation of the language stimulus across conditions.
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Affiliation(s)
- Lars A Ross
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- Department of Imaging Sciences, University of Rochester Medical Center, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
| | - Sophie Molholm
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
| | - John S Butler
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
- School of Mathematics and Statistics, Technological University Dublin, City Campus, Dublin, Ireland
| | - Victor A Del Bene
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
- Heersink School of Medicine, Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Tufikameni Brima
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - John J Foxe
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
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Hill AT, Bailey NW, Zomorrodi R, Hadas I, Kirkovski M, Das S, Lum JAG, Enticott PG. EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power. Hum Brain Mapp 2023; 44:6484-6498. [PMID: 37873867 PMCID: PMC10681660 DOI: 10.1002/hbm.26525] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/04/2023] [Accepted: 10/06/2023] [Indexed: 10/25/2023] Open
Abstract
Electroencephalographic (EEG) microstates can provide a unique window into the temporal dynamics of large-scale brain networks across brief (millisecond) timescales. Here, we analysed fundamental temporal features of microstates extracted from the broadband EEG signal in a large (N = 139) cohort of children spanning early-to-middle childhood (4-12 years of age). Linear regression models were used to examine if participants' age and biological sex could predict the temporal parameters GEV, duration, coverage, and occurrence, for five microstate classes (A-E) across both eyes-closed and eyes-open resting-state recordings. We further explored associations between these microstate parameters and posterior alpha power after removal of the 1/f-like aperiodic signal. The microstates obtained from our neurodevelopmental EEG recordings broadly replicated the four canonical microstate classes (A to D) frequently reported in adults, with the addition of the more recently established microstate class E. Biological sex served as a significant predictor in the regression models for four of the five microstate classes (A, C, D, and E). In addition, duration and occurrence for microstate E were both found to be positively associated with age for the eyes-open recordings, while the temporal parameters of microstates C and E both exhibited associations with alpha band spectral power. Together, these findings highlight the influence of age and sex on large-scale functional brain networks during early-to-middle childhood, extending understanding of neural dynamics across this important period for brain development.
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Affiliation(s)
- Aron T. Hill
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
| | - Neil W. Bailey
- Monarch Research InstituteMonarch Mental Health GroupSydneyAustralia
- School of Medicine and PsychologyThe Australian National UniversityCanberraAustralia
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental HealthUniversity of TorontoTorontoCanada
| | - Itay Hadas
- Department of Psychiatry, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Institute for Health and SportVictoria UniversityMelbourneAustralia
| | - Sushmit Das
- Azrieli Adult Neurodevelopmental CentreCentre for Addiction and Mental HealthTorontoCanada
| | - Jarrad A. G. Lum
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
| | - Peter G. Enticott
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
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21
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Meier EL, Sheppard SM, Sebastian R, Berube S, Goldberg EB, Shea J, Stein CM, Hillis AE. Resting state correlates of picture description informativeness in left vs. right hemisphere chronic stroke. Front Neurol 2023; 14:1288801. [PMID: 38145117 PMCID: PMC10744570 DOI: 10.3389/fneur.2023.1288801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Introduction Despite a growing emphasis on discourse processing in clinical neuroscience, relatively little is known about the neurobiology of discourse production impairments. Individuals with a history of left or right hemisphere stroke can exhibit difficulty with communicating meaningful discourse content, which implies both cerebral hemispheres play a role in this skill. However, the extent to which successful production of discourse content relies on network connections within domain-specific vs. domain-general networks in either hemisphere is unknown. Methods In this study, 45 individuals with a history of either left or right hemisphere stroke completed resting state fMRI and the Cookie Theft picture description task. Results Participants did not differ in the total number of content units or the percentage of interpretative content units they produced. Stroke survivors with left hemisphere damage produced significantly fewer content units per second than individuals with right hemisphere stroke. Intrinsic connectivity of the left language network was significantly weaker in the left compared to the right hemisphere stroke group for specific connections. Greater efficiency of communication of picture scene content was associated with stronger left but weaker right frontotemporal connectivity of the language network in patients with a history of left hemisphere (but not right hemisphere) stroke. No significant relationships were found between picture description measures and connectivity of the dorsal attention, default mode, or salience networks or with connections between language and other network regions. Discussion These findings add to prior behavioral studies of picture description skills in stroke survivors and provide insight into the role of the language network vs. other intrinsic networks during discourse production.
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Affiliation(s)
- Erin L. Meier
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Shannon M. Sheppard
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Rajani Sebastian
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, United States
| | - Shauna Berube
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Emily B. Goldberg
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Jennifer Shea
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Colin M. Stein
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Argye E. Hillis
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, United States
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, United States
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22
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Liu M, Zhang J, Wang Y, Zhou Y, Xie F, Guo Q, Shi F, Zhang H, Wang Q, Shen D. A common spectrum underlying brain disorders across lifespan revealed by deep learning on brain networks. iScience 2023; 26:108244. [PMID: 38026184 PMCID: PMC10651682 DOI: 10.1016/j.isci.2023.108244] [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: 06/12/2023] [Revised: 09/26/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Brain disorders in the early and late life of humans potentially share pathological alterations in brain functions. However, the key neuroimaging evidence remains unrevealed for elucidating such commonness and the relationships among these disorders. To explore this puzzle, we build a restricted single-branch deep learning model, using multi-site functional magnetic resonance imaging data (N = 4,410, 6 sites), for classifying 5 different early- and late-life brain disorders from healthy controls (cognitively unimpaired). Our model achieves 62.6 ± 1.9% overall classification accuracy and thus supports us in detecting a set of commonly affected functional subnetworks, including default mode, executive control, visual, and limbic networks. In the deep-layer representation of data, we observe young and aging patients with disorders are continuously distributed, which is in line with the clinical concept of the "spectrum of disorders." The relationships among brain disorders from the revealed spectrum promote the understanding of disorder comorbidities and time associations in the lifespan.
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Affiliation(s)
- Mianxin Liu
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
| | - Jingyang Zhang
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yao Wang
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200001, China
| | - Yan Zhou
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200001, China
| | - Fang Xie
- PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Feng Shi
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai 200232, China
| | - Han Zhang
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Qian Wang
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Dinggang Shen
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai 200232, China
- Shanghai Clinical Research and Trial Center, Shanghai 201210, China
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23
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Sun B, Wang B, Wei Z, Feng Z, Wu ZL, Yassin W, Stone WS, Lin Y, Kong XJ. Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking. Front Neurosci 2023; 17:1236637. [PMID: 37886678 PMCID: PMC10598595 DOI: 10.3389/fnins.2023.1236637] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023] Open
Abstract
Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.
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Affiliation(s)
- Binbin Sun
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Bryan Wang
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of English and Creative Writing, Brandeis University, Waltham, MA, United States
| | - Zhen Wei
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhe Feng
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhi-Liu Wu
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Walid Yassin
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- McLean Hospital, Harvard Medical School, Belmont, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - William S. Stone
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Yan Lin
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Xue-Jun Kong
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
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24
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Pan H, Mao Y, Liu P, Li Y, Wei G, Qiao X, Ren Y, Zhao F. Extracting transition features among brain states based on coarse-grained similarity measurement for autism spectrum disorder analysis. Med Phys 2023; 50:6269-6282. [PMID: 36995984 DOI: 10.1002/mp.16406] [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: 01/13/2023] [Revised: 03/13/2023] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND The abnormal brain functional connectivity (FC) of patients with mental diseases is closely linked to the transition features among brain states. However, the current research on state transition will produce certain division deviations in the measurement method of state division, and also ignore the transition features among multiple states that contain more abundant information for analyzing brain diseases. PURPOSE To investigate the potential of the proposed method based on coarse-grained similarity measurement to solve the problem of state division, and consider the transition features among multiple states to analyze the FC abnormalities of autism spectrum disorder (ASD) patients. METHODS We used resting-state functional magnetic resonance imaging to examine 45 ASD and 47 healthy controls (HC). The FC between brain regions was calculated by the sliding window and correlation algorithm, and a novel coarse-grained similarity measure method was used to cluster the FC networks into five states, and then extract the features both of the state itself and the transition features among multiple states for analysis and diagnosis. RESULTS (1) The state as divided by the coarse-grained measurement method improves the diagnostic performance of individuals with ASD compared with previous methods. (2) The transition features among multiple states can provide complementary information to the features of the state itself in the ASD analysis and diagnosis. (3) ASD individuals have different brain state transitions than HC. Specifically, the abnormalities in intra- and inter-network connectivity of ASD patients mainly occur in the default mode network, the visual network, and the cerebellum. CONCLUSIONS Such results demonstrate that our approach with new measurements and new features is effective and promising in brain state analysis and ASD diagnosis.
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Affiliation(s)
- Hongxin Pan
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Yanyan Mao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Peiqiang Liu
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Yuan Li
- School of Management Science and Engineering, Shandong Technology and Business University, Yantai, China
| | - Guanglan Wei
- Information Network Center, Shandong Second Provincial General Hospital, Jinan, China
| | - Xiaoyan Qiao
- School of Mathematics and Information Science, Shandong Technology and Business University, Yantai, China
| | - Yande Ren
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Feng Zhao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
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25
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Fateh AA, Huang W, Hassan M, Zhuang Y, Lin J, Luo Y, Yang B, Zeng H. Default mode network connectivity and social dysfunction in children with Attention Deficit/Hyperactivity Disorder. Int J Clin Health Psychol 2023; 23:100393. [PMID: 37829190 PMCID: PMC10564936 DOI: 10.1016/j.ijchp.2023.100393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/23/2023] [Indexed: 10/14/2023] Open
Abstract
Objective Attention Deficit/Hyperactivity Disorder (ADHD) negatively affects social functioning; however, its neurological underpinnings remain unclear. Altered Default Mode Network (DMN) connectivity may contribute to social dysfunction in ADHD. We investigated whether DMN's dynamic functional connectivity (dFC) alterations were associated with social dysfunction in individuals with ADHD. Methods Resting-state fMRI was used to examine DMN subsystems (dorsal medial prefrontal cortex (dMPFC), medial temporal lobe (MTL)) and the midline core in 40 male ADHD patients (7-10 years) and 45 healthy controls (HCs). Connectivity correlations with symptoms and demographic data were assessed. Group-based analyses compared rsFC between groups with two-sample t-tests and post-hoc analyses. Results Social dysfunction in ADHD patients was related to reduced DMN connectivity, specifically in the MTL subsystem and the midline core. ADHD patients showed decreased dFC between parahippocampal cortex (PHC) and left superior frontal gyrus, and between ventral medial prefrontal cortex (vMPFC) and right middle frontal gyrus compared to HCs (MTL subsystem). Additionally, decreased dFC between posterior cingulate cortex (PCC), anterior medial prefrontal cortex (aMPFC), and right angular gyrus (midline core) was observed in ADHD patients relative to HCs. No abnormal connectivity was found within the dMPFC. Conclusion Preliminary findings suggest that DMN connectional abnormalities may contribute to social dysfunction in ADHD, providing insights into the disorder's neurobiology and pathophysiology.
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Affiliation(s)
- Ahmed Ameen Fateh
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Wenxian Huang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Muhammad Hassan
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Yijiang Zhuang
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Jieqiong Lin
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Yi Luo
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Binrang Yang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Hongwu Zeng
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
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26
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Deserno MK, Bathelt J, Groenman AP, Geurts HM. Probing the overarching continuum theory: data-driven phenotypic clustering of children with ASD or ADHD. Eur Child Adolesc Psychiatry 2023; 32:1909-1923. [PMID: 35687205 PMCID: PMC10533623 DOI: 10.1007/s00787-022-01986-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 04/06/2022] [Indexed: 11/03/2022]
Abstract
The clinical validity of the distinction between ADHD and ASD is a longstanding discussion. Recent advances in the realm of data-driven analytic techniques now enable us to formally investigate theories aiming to explain the frequent co-occurrence of these neurodevelopmental conditions. In this study, we probe different theoretical positions by means of a pre-registered integrative approach of novel classification, subgrouping, and taxometric techniques in a representative sample (N = 434), and replicate the results in an independent sample (N = 219) of children (ADHD, ASD, and typically developing) aged 7-14 years. First, Random Forest Classification could predict diagnostic groups based on questionnaire data with limited accuracy-suggesting some remaining overlap in behavioral symptoms between them. Second, community detection identified four distinct groups, but none of them showed a symptom profile clearly related to either ADHD or ASD in neither the original sample nor the replication sample. Third, taxometric analyses showed evidence for a categorical distinction between ASD and typically developing children, a dimensional characterization of the difference between ADHD and typically developing children, and mixed results for the distinction between the diagnostic groups. We present a novel framework of cutting-edge statistical techniques which represent recent advances in both the models and the data used for research in psychiatric nosology. Our results suggest that ASD and ADHD cannot be unambiguously characterized as either two separate clinical entities or opposite ends of a spectrum, and highlight the need to study ADHD and ASD traits in tandem.
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Affiliation(s)
- M K Deserno
- Dutch Autism and ADHD Research Centre (d'Arc), Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
- Max Planck Institute for Human Development, Berlin, Germany.
| | - J Bathelt
- Dutch Autism and ADHD Research Centre (d'Arc), Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Royal Holloway, University of London, Egham, UK
| | - A P Groenman
- Dutch Autism and ADHD Research Centre (d'Arc), Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - H M Geurts
- Dutch Autism and ADHD Research Centre (d'Arc), Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Leo Kannerhuis, Amsterdam (Youz, Parnassiagroep), Amsterdam, The Netherlands
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27
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Shan J, Gu Y, Zhang J, Hu X, Wu H, Yuan T, Zhao D. A scoping review of physiological biomarkers in autism. Front Neurosci 2023; 17:1269880. [PMID: 37746140 PMCID: PMC10512710 DOI: 10.3389/fnins.2023.1269880] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/23/2023] [Indexed: 09/26/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by pervasive deficits in social interaction, communication impairments, and the presence of restricted and repetitive behaviors. This complex disorder is a significant public health concern due to its escalating incidence and detrimental impact on quality of life. Currently, extensive investigations are underway to identify prospective susceptibility or predictive biomarkers, employing a physiological biomarker-based framework. However, knowledge regarding physiological biomarkers in relation to Autism is sparse. We performed a scoping review to explore putative changes in physiological activities associated with behaviors in individuals with Autism. We identified studies published between January 2000 and June 2023 from online databases, and searched keywords included electroencephalography (EEG), magnetoencephalography (MEG), electrodermal activity markers (EDA), eye-tracking markers. We specifically detected social-related symptoms such as impaired social communication in ASD patients. Our results indicated that the EEG/ERP N170 signal has undergone the most rigorous testing as a potential biomarker, showing promise in identifying subgroups within ASD and displaying potential as an indicator of treatment response. By gathering current data from various physiological biomarkers, we can obtain a comprehensive understanding of the physiological profiles of individuals with ASD, offering potential for subgrouping and targeted intervention strategies.
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Affiliation(s)
- Jiatong Shan
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Arts and Sciences, New York University Shanghai, Shanghai, China
| | - Yunhao Gu
- Graduate School of Education, University of Pennsylvania, Philadelphia, PA, United States
| | - Jie Zhang
- Department of Neurology, Institute of Neurology, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoqing Hu
- Department of Psychology, The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
- HKU, Shenzhen Institute of Research and Innovation, Shenzhen, China
| | - Haiyan Wu
- Center for Cognitive and Brain Sciences and Department of Psychology, Macau, China
| | - Tifei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Zhao
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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28
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Fakheir Y, Khalil R. The effects of abnormal visual experience on neurodevelopmental disorders. Dev Psychobiol 2023; 65:e22408. [PMID: 37607893 DOI: 10.1002/dev.22408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/14/2023] [Accepted: 06/13/2023] [Indexed: 08/24/2023]
Abstract
Normal visual development is supported by intrinsic neurobiological mechanisms and by appropriate stimulation from the environment, both of which facilitate the maturation of visual functions. However, an offset of this balance can give rise to visual disorders. Therefore, understanding the factors that support normal vision during development and in the mature brain is important, as vision guides movement, enables social interaction, and allows children to recognize and understand their environment. In this paper, we review fundamental mechanisms that support the maturation of visual functions and discuss and draw links between the perceptual and neurobiological impairments in autism spectrum disorder (ASD) and schizophrenia. We aim to explore how this is evident in the case of ASD, and how perceptual and neurobiological deficits further degrade social ability. Furthermore, we describe the altered perceptual experience of those with schizophrenia and evaluate theories of the underlying neural deficits that alter perception.
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Affiliation(s)
- Yara Fakheir
- Department of Biology, Chemistry, and Environmental Sciences, American University of Sharjah, Sharjah, UAE
| | - Reem Khalil
- Department of Biology, Chemistry, and Environmental Sciences, American University of Sharjah, Sharjah, UAE
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29
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Li Y, Li R, Wang N, Gu J, Gao J. Gender effects on autism spectrum disorder: a multi-site resting-state functional magnetic resonance imaging study of transcriptome-neuroimaging. Front Neurosci 2023; 17:1203690. [PMID: 37409103 PMCID: PMC10318192 DOI: 10.3389/fnins.2023.1203690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 05/22/2023] [Indexed: 07/07/2023] Open
Abstract
Introduction The gender disparity in autism spectrum disorder (ASD) has been one of the salient features of condition. However, its relationship between the pathogenesis and genetic transcription in patients of different genders has yet to reach a reliable conclusion. Methods To address this gap, this study aimed to establish a reliable potential neuro-marker in gender-specific patients, by employing multi-site functional magnetic resonance imaging (fMRI) data, and to further investigate the role of genetic transcription molecules in neurogenetic abnormalities and gender differences in autism at the neuro-transcriptional level. To this end, age was firstly used as a regression covariate, followed by the use of ComBat to remove the site effect from the fMRI data, and abnormal functional activity was subsequently identified. The resulting abnormal functional activity was then correlated by genetic transcription to explore underlying molecular functions and cellular molecular mechanisms. Results Abnormal brain functional activities were identified in autism patients of different genders, mainly located in the default model network (DMN) and precuneus-cingulate gyrus-frontal lobe. The correlation analysis of neuroimaging and genetic transcription further found that heterogeneous brain regions were highly correlated with genes involved in signal transmission between neurons' plasma membranes. Additionally, we further identified different weighted gene expression patterns and specific expression tissues of risk genes in ASD of different genders. Discussion Thus, this work not only identified the mechanism of abnormal brain functional activities caused by gender differences in ASD, but also explored the genetic and molecular characteristics caused by these related changes. Moreover, we further analyzed the genetic basis of sex differences in ASD from a neuro-transcriptional perspective.
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Affiliation(s)
- Yanling Li
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China
| | - Rui Li
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China
| | - Ning Wang
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China
| | - Jiahe Gu
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China
| | - Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
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30
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Chen J, Wei Z, Xu C, Peng Z, Yang J, Wan G, Chen B, Gong J, Zhou K. Social visual preference mediates the effect of cortical thickness on symptom severity in children with autism spectrum disorder. Front Psychiatry 2023; 14:1132284. [PMID: 37398604 PMCID: PMC10311909 DOI: 10.3389/fpsyt.2023.1132284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 05/29/2023] [Indexed: 07/04/2023] Open
Abstract
Background Evidence suggests that there is a robust relationship between altered neuroanatomy and autistic symptoms in individuals with autism spectrum disorder (ASD). Social visual preference, which is regulated by specific brain regions, is also related to symptom severity. However, there were a few studies explored the potential relationships among brain structure, symptom severity, and social visual preference. Methods The current study investigated relationships among brain structure, social visual preference, and symptom severity in 43 children with ASD and 26 typically developing (TD) children (aged 2-6 years). Results Significant differences were found in social visual preference and cortical morphometry between the two groups. Decreased percentage of fixation time in digital social images (%DSI) was negatively related to not only the thickness of the left fusiform gyrus (FG) and right insula, but also the Calibrated Severity Scores for the Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA-CSS). Mediation analysis showed that %DSI partially mediated the relationship between neuroanatomical alterations (specifically, thickness of the left FG and right insula) and symptom severity. Conclusion These findings offer initial evidence that atypical neuroanatomical alterations may not only result in direct effects on symptom severity but also lead to indirect effects on symptom severity through social visual preference. This finding enhances our understanding of the multiple neural mechanisms implicated in ASD.
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Affiliation(s)
- Jierong Chen
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhen Wei
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
- Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, China
| | - Chuangyong Xu
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Ziwen Peng
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Junjie Yang
- Department of Child Health Care, Luohu District Maternal and Child Health Care Hospital, Shenzhen, China
| | - Guobin Wan
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Bin Chen
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Jianhua Gong
- Department of Child Health Care, Luohu District Maternal and Child Health Care Hospital, Shenzhen, China
| | - Keying Zhou
- Department of Pediatrics, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, China
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Openshaw RL, Thomson DM, Bristow GC, Mitchell EJ, Pratt JA, Morris BJ, Dawson N. 16p11.2 deletion mice exhibit compromised fronto-temporal connectivity, GABAergic dysfunction, and enhanced attentional ability. Commun Biol 2023; 6:557. [PMID: 37225770 DOI: 10.1038/s42003-023-04891-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 05/01/2023] [Indexed: 05/26/2023] Open
Abstract
Autism spectrum disorders are more common in males, and have a substantial genetic component. Chromosomal 16p11.2 deletions in particular carry strong genetic risk for autism, yet their neurobiological impact is poorly characterised, particularly at the integrated systems level. Here we show that mice reproducing this deletion (16p11.2 DEL mice) have reduced GABAergic interneuron gene expression (decreased parvalbumin mRNA in orbitofrontal cortex, and male-specific decreases in Gad67 mRNA in parietal and insular cortex and medial septum). Metabolic activity was increased in medial septum, and in its efferent targets: mammillary body and (males only) subiculum. Functional connectivity was altered between orbitofrontal, insular and auditory cortex, and between septum and hippocampus/subiculum. Consistent with this circuit dysfunction, 16p11.2 DEL mice showed reduced prepulse inhibition, but enhanced performance in the continuous performance test of attentional ability. Level 1 autistic individuals show similarly heightened performance in the equivalent human test, also associated with parietal, insular-orbitofrontal and septo-subicular dysfunction. The data implicate cortical and septal GABAergic dysfunction, and resulting connectivity changes, as the cause of pre-attentional and attentional changes in autism.
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Affiliation(s)
- Rebecca L Openshaw
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK
| | - David M Thomson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Greg C Bristow
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, BD7 1DP, UK
| | - Emma J Mitchell
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Judith A Pratt
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Brian J Morris
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK.
| | - Neil Dawson
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK.
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Itahashi T, Yamashita A, Takahara Y, Yahata N, Aoki YY, Fujino J, Yoshihara Y, Nakamura M, Aoki R, Ohta H, Sakai Y, Takamura M, Ichikawa N, Okada G, Okada N, Kasai K, Tanaka SC, Imamizu H, Kato N, Okamoto Y, Takahashi H, Kawato M, Yamashita O, Hashimoto RI. Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.26.534053. [PMID: 37034620 PMCID: PMC10081283 DOI: 10.1101/2023.03.26.534053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P < 0.05 , family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.
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Affiliation(s)
- Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ayumu Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yuji Takahara
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD, Osaka, Japan
| | - Noriaki Yahata
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yuta Y. Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry, Aoki Clinic, Tokyo, Japan
| | - Junya Fujino
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Motoaki Nakamura
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ryuta Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Language Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Haruhisa Ohta
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yuki Sakai
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Masahiro Takamura
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
- Department of Neurology, Shimane University, Shimane, Japan
| | - Naho Ichikawa
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
- UTokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), The University of Tokyo, Tokyo, Japan
| | - Saori C. Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Division of Information Science, Nara Institute of Science and Technology, Nara, Japan
| | - Hiroshi Imamizu
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan
| | - Nobumasa Kato
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- XNef Incorporation, Kyoto, Japan
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- RIKEN, Center for Advanced Intelligence Project, Tokyo, Japan
| | - Ryu-ichiro Hashimoto
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Pagni BA, Hill E, Walsh MJM, Delaney S, Ogbeama D, Monahan L, Cook JR, Guerithault N, Dixon MV, Ballard L, Braden BB. Distinct and shared therapeutic neural mechanisms of mindfulness-based and social support stress reduction groups in adults with autism spectrum disorder. J Psychiatry Neurosci 2023; 48:E102-E114. [PMID: 36990468 PMCID: PMC10065804 DOI: 10.1503/jpn.220159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/16/2022] [Accepted: 12/09/2022] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Mindfulness-based stress reduction (MBSR) alleviates depression and anxiety in adults with autism spectrum disorder (ASD); however, underlying therapeutic neural mechanisms and mindfulness-specific effects have yet to be elucidated. METHODS We randomly assigned adults with ASD to MBSR or social support/education (SE). They completed questionnaires that assessed depression, anxiety, mindfulness traits, autistic traits and executive functioning abilities as well as a self-reflection functional MRI task. We used repeated-measures analysis of covariance (ANCOVA) to evaluate behavioural changes. To identify task-specific connectivity changes, we performed a generalized psychophysiological interactions (gPPI) functional connectivity (FC) analysis on regions of interest (ROIs; insula, amygdala, cingulum and prefrontal cortex [PFC]). We used Pearson correlations to explore brain-behaviour relationships. RESULTS Our final sample included 78 adults with ASD - 39 who received MBSR and 39 who received SE. Mindfulness-based stress reduction uniquely improved executive functioning abilities and increased mindfulness traits, whereas both MBSR and SE groups showed reductions in depression, anxiety and autistic traits. Decreases specific to MBSR in insula-thalamus FC were associated with anxiety reduction and increased mindfulness traits, including the trait "nonjudgment;" MBSR-specific decreases in PFC-posterior cingulate connectivity correlated with improved working memory. Both groups showed decreased amygdala-sensorimotor and medial-lateral PFC connectivity, which corresponded with reduced depression. LIMITATIONS Larger sample sizes and neuropsychological evaluations are needed to replicate and extend these findings. CONCLUSION Together, our findings suggest that MBSR and SE are similarly efficacious for depression, anxiety and autistic traits, whereas MBSR produced additional salutary effects related to executive functioning and mindfulness traits. Findings from gPPI identified shared and distinct therapeutic neural mechanisms, implicating the default mode and salience networks. Our results mark an early step toward the development of personalized medicine for psychiatric symptoms in ASD and offer novel neural targets for future neurostimulation research. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov identifier NCT04017793.
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Affiliation(s)
- Broc A Pagni
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Ethan Hill
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Melissa J M Walsh
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Shanna Delaney
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Destiny Ogbeama
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Leanna Monahan
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - James R Cook
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | | | - Maria V Dixon
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - Lisa Ballard
- From Arizona State University, College of Health Solutions, Phoenix, AZ
| | - B Blair Braden
- From Arizona State University, College of Health Solutions, Phoenix, AZ
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34
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Yu Q, Ouyang M, Detre J, Kang H, Hu D, Hong B, Fang F, Peng Y, Huang H. Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network. eLife 2023; 12:e78397. [PMID: 36693116 PMCID: PMC9873253 DOI: 10.7554/elife.78397] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 01/12/2023] [Indexed: 01/25/2023] Open
Abstract
Human infancy is characterized by most rapid regional cerebral blood flow (rCBF) increases across lifespan and emergence of a fundamental brain system default-mode network (DMN). However, how infant rCBF changes spatiotemporally across the brain and how the rCBF increase supports emergence of functional networks such as DMN remains unknown. Here, by acquiring cutting-edge multi-modal MRI including pseudo-continuous arterial-spin-labeled perfusion MRI and resting-state functional MRI of 48 infants cross-sectionally, we elucidated unprecedented 4D spatiotemporal infant rCBF framework and region-specific physiology-function coupling across infancy. We found that faster rCBF increases in the DMN than visual and sensorimotor networks. We also found strongly coupled increases of rCBF and network strength specifically in the DMN, suggesting faster local blood flow increase to meet extraneuronal metabolic demands in the DMN maturation. These results offer insights into the physiological mechanism of brain functional network emergence and have important implications in altered network maturation in brain disorders.
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Affiliation(s)
- Qinlin Yu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Minhui Ouyang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - John Detre
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Neurology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Huiying Kang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Di Hu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Bo Hong
- Department of Biomedical Engineering, Tsinghua UniversityBeijingChina
| | - Fang Fang
- School of Psychological and Cognitive Sciences, Peking UniversityBeijingChina
| | - Yun Peng
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Hao Huang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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35
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Jiang X, Yan J, Zhao Y, Jiang M, Chen Y, Zhou J, Xiao Z, Wang Z, Zhang R, Becker B, Zhu D, Kendrick KM, Liu T. Characterizing functional brain networks via Spatio-Temporal Attention 4D Convolutional Neural Networks (STA-4DCNNs). Neural Netw 2023; 158:99-110. [PMID: 36446159 DOI: 10.1016/j.neunet.2022.11.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/17/2022] [Accepted: 11/03/2022] [Indexed: 11/11/2022]
Abstract
Characterizing individualized spatio-temporal patterns of functional brain networks (FBNs) via functional magnetic resonance imaging (fMRI) provides a foundation for understanding complex brain function. Although previous studies have achieved promising performances based on either shallow or deep learning models, there is still much space to improve the accuracy of spatio-temporal pattern characterization of FBNs by optimally integrating the four-dimensional (4D) features of fMRI. In this study, we introduce a novel Spatio-Temporal Attention 4D Convolutional Neural Network (STA-4DCNN) model to characterize individualized spatio-temporal patterns of FBNs. Particularly, STA-4DCNN is composed of two subnetworks, in which the first Spatial Attention 4D CNN (SA-4DCNN) models the spatio-temporal features of 4D fMRI data and then characterizes the spatial pattern of FBNs, and the second Temporal Guided Attention Network (T-GANet) further characterizes the temporal pattern of FBNs under the guidance of the spatial pattern together with 4D fMRI data. We evaluate the proposed STA-4DCNN on seven different task fMRI and one resting state fMRI datasets from the publicly released Human Connectome Project. The experimental results demonstrate that STA-4DCNN has superior ability and generalizability in characterizing individualized spatio-temporal patterns of FBNs when compared to other state-of-the-art models. We further apply STA-4DCNN on another independent ABIDE I resting state fMRI dataset including both autism spectrum disorder (ASD) and typical developing (TD) subjects, and successfully identify abnormal spatio-temporal patterns of FBNs in ASD compared to TD. In general, STA-4DCNN provides a powerful tool for FBN characterization and for clinical applications on brain disease characterization at the individual level.
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Affiliation(s)
- Xi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiadong Yan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Zhao
- Syngo Innovation, Siemens Healthineers, Malvern, PA 19355, USA
| | - Mingxin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuzhong Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingchao Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhenxiang Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zifan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rong Zhang
- Neuroscience Research Institute, Key Laboratory for Neuroscience, Ministry of Education of China, China; Key Laboratory for Neuroscience, National Committee of Health and Family Planning of China, China; Department of Neurobiology, School of Basic Medical Sciences, Peking University, Beijing, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, USA.
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36
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Karavallil Achuthan S, Coburn KL, Beckerson ME, Kana RK. Amplitude of low frequency fluctuations during resting state fMRI in autistic children. Autism Res 2023; 16:84-98. [PMID: 36349875 DOI: 10.1002/aur.2846] [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: 03/30/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022]
Abstract
Resting state fMRI (rs-fMRI) provides an excellent platform for examining the amplitude of low frequency fluctuations (ALFF) and fractional amplitude of low frequency fluctuations (fALFF), which are key indices of brain functioning. However, ALFF and fALFF have been used only sporadically to study autism. rs-fMRI data from 69 children (40 autistic, mean age = 8.47 ± 2.20 years; age range: 5.2 to 13.2; and 29 non-autistic, mean age = 9.02 ± 1.97 years; age range 5.9 to 12.9) were obtained from the Autism Brain Imaging Data Exchange (ABIDE II). ALFF and fALFF were measured using CONN connectivity toolbox and SPM12, at whole-brain & network-levels. A two-sampled t-test and a 2 Group (autistic, non-autistic) × 7 Networks ANOVA were conducted to test group differences in ALFF and fALFF. The whole-brain analysis identified significantly reduced ALFF values for autistic participants in left parietal opercular cortex, precuneus, and right insula. At the network level, there was a significant effect of diagnostic group and brain network on ALFF values, and only significant effect of network, not group, on fALFF values. Regression analyses indicated a significant effect of age on ALFF values of certain networks in autistic participants. Such intrinsically different network-level responses in autistic participants may have implications for task-level recruitment and synchronization of brain areas, which may in turn impact optimal cognitive functioning. Moreover, differences in low frequency fluctuations of key networks, such as the DMN and SN, may underlie alterations in brain responses in autism that are frequently reported in the literature.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Kelly L Coburn
- Department of Speech-Language Pathology & Audiology, Towson University, Towson, Maryland, USA
| | - Meagan E Beckerson
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Rajesh K Kana
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
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Wang Z, Xu Y, Peng D, Gao J, Lu F. Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression. Cereb Cortex 2022; 33:6407-6419. [PMID: 36587290 DOI: 10.1093/cercor/bhac513] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 12/02/2022] [Accepted: 12/03/2022] [Indexed: 01/02/2023] Open
Abstract
Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to brain activity and genetics. Most of the ASD diagnostic models perform feature selection at the group level without considering individualized information. Evidence has shown the unique topology of the individual brain has a fundamental impact on brain diseases. Thus, a data-constructing method fusing individual topological information and a corresponding classification model is crucial in ASD diagnosis and biomarker discovery. In this work, we trained an attention-based graph neural network (GNN) to perform the ASD diagnosis with the fusion of graph data. The results achieved an accuracy of 79.78%. Moreover, we found the model paid high attention to brain regions mainly involved in the social-brain circuit, default-mode network, and sensory perception network. Furthermore, by analyzing the covariation between functional magnetic resonance imaging data and gene expression, current studies detected several ASD-related genes (i.e. MUTYH, AADAT, and MAP2), and further revealed their links to image biomarkers. Our work demonstrated that the ASD diagnostic framework based on graph data and attention-based GNN could be an effective tool for ASD diagnosis. The identified functional features with high attention values may serve as imaging biomarkers for ASD.
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Affiliation(s)
- Zhengning Wang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Yuhang Xu
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Dawei Peng
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
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38
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Antezana L, Coffman MC, DiCriscio AS, Richey JA. Effects of nonsocial and circumscribed interest images on neural mechanisms of emotion regulation in autistic adults. Front Behav Neurosci 2022; 16:1057736. [PMID: 36570705 PMCID: PMC9771392 DOI: 10.3389/fnbeh.2022.1057736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
Introduction Emotion dysregulation is commonly reported among autistic individuals. Prior work investigating the neurofunctional mechanisms of emotion regulation (ER) in autistic adults has illustrated alterations in dorsolateral prefrontal cortex (dlPFC) activity, as well as concurrent atypical patterns of activation in subcortical regions related to affect during cognitive reappraisal of social images. Whereas most research examining ER in autism has focused on regulation of negative emotions, the effects of regulating positive emotions has been generally understudied. This is surprising given the relevance of positive motivational states to understanding circumscribed interests (CI) in autism. Methods Accordingly, the purpose of this study was to use fMRI with simultaneous eye-tracking and pupillometry to investigate the neural mechanisms of ER during passive viewing and cognitive reappraisal of a standardized set of nonsocial images and personalized (self-selected) CI images. Results The autistic group demonstrated comparatively reduced modulation of posterior cingulate cortex (PCC) activation during cognitive reappraisal of CI images compared to viewing of CI, although no eye-tracking/pupillometry differences emerged between-groups. Further, the autistic group demonstrated increased PCC connectivity with left lateral occipital and right supramarginal areas when engaging in cognitive reappraisal vs. viewing CI. Discussion In autistic adults, CI may be differentially modulated via PCC. Considering the documented role of the PCC as a core hub of the default mode network, we further postulate that ER of CI could potentially be related to self-referential cognition.
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Affiliation(s)
- Ligia Antezana
- Department of Psychology, Virginia Tech, Blacksburg, VA, United States
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Marika C. Coffman
- Department of Psychology, Virginia Tech, Blacksburg, VA, United States
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | | | - John A. Richey
- Department of Psychology, Virginia Tech, Blacksburg, VA, United States
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39
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Camasio A, Panzeri E, Mancuso L, Costa T, Manuello J, Ferraro M, Duca S, Cauda F, Liloia D. Linking neuroanatomical abnormalities in autism spectrum disorder with gene expression of candidate ASD genes: A meta-analytic and network-oriented approach. PLoS One 2022; 17:e0277466. [PMID: 36441779 PMCID: PMC9704678 DOI: 10.1371/journal.pone.0277466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 10/27/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a set of developmental conditions with widespread neuroanatomical abnormalities and a strong genetic basis. Although neuroimaging studies have indicated anatomical changes in grey matter (GM) morphometry, their associations with gene expression remain elusive. METHODS Here, we aim to understand how gene expression correlates with neuroanatomical atypicalities in ASD. To do so, we performed a coordinate-based meta-analysis to determine the common GM variation pattern in the autistic brain. From the Allen Human Brain Atlas, we selected eight genes from the SHANK, NRXN, NLGN family and MECP2, which have been implicated with ASD, particularly in regards to altered synaptic transmission and plasticity. The gene expression maps for each gene were built. We then assessed the correlation between the gene expression maps and the GM alteration maps. Lastly, we projected the obtained clusters of GM alteration-gene correlations on top of the canonical resting state networks, in order to provide a functional characterization of the structural evidence. RESULTS We found that gene expression of most genes correlated with GM alteration (both increase and decrease) in regions located in the default mode network. Decreased GM was also correlated with gene expression of some ASD genes in areas associated with the dorsal attention and cerebellar network. Lastly, single genes were found to be significantly correlated with increased GM in areas located in the somatomotor, limbic and ganglia/thalamus networks. CONCLUSIONS This approach allowed us to combine the well beaten path of genetic and brain imaging in a novel way, to specifically investigate the relation between gene expression and brain with structural damage, and individuate genes of potential interest for further investigation in the functional domain.
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Affiliation(s)
- Alessia Camasio
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Department of Physics, University of Turin, Turin, Italy
| | - Elisa Panzeri
- School of Biological Sciences, University of Leicester, Leicester, United Kingdom
| | - Lorenzo Mancuso
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
- * E-mail:
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Mario Ferraro
- Department of Physics, University of Turin, Turin, Italy
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Donato Liloia
- GCS-fMRI, Koelliker Hospital, Turin, Italy
- Focus Lab, Department of Psychology, University of Turin, Turin, Italy
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Pourmotahari F, Doosti H, Borumandnia N, Tabatabaei SM, Alavi Majd H. Group-level comparison of brain connectivity networks. BMC Med Res Methodol 2022; 22:273. [PMID: 36253728 PMCID: PMC9575214 DOI: 10.1186/s12874-022-01712-8] [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: 05/24/2022] [Accepted: 08/16/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Functional connectivity (FC) studies are often performed to discern different patterns of brain connectivity networks between healthy and patient groups. Since many neuropsychiatric disorders are related to the change in these patterns, accurate modelling of FC data can provide useful information about disease pathologies. However, analysing functional connectivity data faces several challenges, including the correlations of the connectivity edges associated with network topological characteristics, the large number of parameters in the covariance matrix, and taking into account the heterogeneity across subjects. METHODS This study provides a new statistical approach to compare the FC networks between subgroups that consider the network topological structure of brain regions and subject heterogeneity. RESULTS The power based on the heterogeneity structure of identity scaled in a sample size of 25 exhibited values greater than 0.90 without influencing the degree of correlation, heterogeneity, and the number of regions. This index had values above 0.80 in the small sample size and high correlation. In most scenarios, the type I error was close to 0.05. Moreover, the application of this model on real data related to autism was also investigated, which indicated no significant difference in FC networks between healthy and patient individuals. CONCLUSIONS The results from simulation data indicated that the proposed model has high power and near-nominal type I error rates in most scenarios.
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Affiliation(s)
- Fatemeh Pourmotahari
- Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hassan Doosti
- Department of Mathematics and Statistics, Macquarie University, Macquarie, Australia
| | - Nasrin Borumandnia
- Urology and Nephrology Research Centre, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyyed Mohammad Tabatabaei
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hamid Alavi Majd
- Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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41
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Alamdari SB, Sadeghi Damavandi M, Zarei M, Khosrowabadi R. Cognitive theories of autism based on the interactions between brain functional networks. Front Hum Neurosci 2022; 16:828985. [PMID: 36310850 PMCID: PMC9614840 DOI: 10.3389/fnhum.2022.828985] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 08/15/2022] [Indexed: 12/03/2022] Open
Abstract
Cognitive functions are directly related to interactions between the brain's functional networks. This functional organization changes in the autism spectrum disorder (ASD). However, the heterogeneous nature of autism brings inconsistency in the findings, and specific pattern of changes based on the cognitive theories of ASD still requires to be well-understood. In this study, we hypothesized that the theory of mind (ToM), and the weak central coherence theory must follow an alteration pattern in the network level of functional interactions. The main aim is to understand this pattern by evaluating interactions between all the brain functional networks. Moreover, the association between the significantly altered interactions and cognitive dysfunctions in autism is also investigated. We used resting-state fMRI data of 106 subjects (5–14 years, 46 ASD: five female, 60 HC: 18 female) to define the brain functional networks. Functional networks were calculated by applying four parcellation masks and their interactions were estimated using Pearson's correlation between pairs of them. Subsequently, for each mask, a graph was formed based on the connectome of interactions. Then, the local and global parameters of the graph were calculated. Finally, statistical analysis was performed using a two-sample t-test to highlight the significant differences between autistic and healthy control groups. Our corrected results show significant changes in the interaction of default mode, sensorimotor, visuospatial, visual, and language networks with other functional networks that can support the main cognitive theories of autism. We hope this finding sheds light on a better understanding of the neural underpinning of autism.
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Affiliation(s)
| | | | - Mojtaba Zarei
- University of Southern Denmark, Neurology Unit, Odense, Denmark
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
- *Correspondence: Reza Khosrowabadi
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Oda K, Colman R, Koshiba M. Simplified Attachable EEG Revealed Child Development Dependent Neurofeedback Brain Acute Activities in Comparison with Visual Numerical Discrimination Task and Resting. SENSORS (BASEL, SWITZERLAND) 2022; 22:7207. [PMID: 36236305 PMCID: PMC9572555 DOI: 10.3390/s22197207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
The development of an easy-to-attach electroencephalograph (EEG) would enable its frequent use for the assessment of neurodevelopment and clinical monitoring. In this study, we designed a two-channel EEG headband measurement device that could be used safely and was easily attachable and removable without the need for restraint or electrode paste or gel. Next, we explored the use of this device for neurofeedback applications relevant to education or neurocognitive development. We developed a prototype visual neurofeedback game in which the size of a familiar local mascot changes in the PC display depending on the user's brain wave activity. We tested this application at a local children's play event. Children at the event were invited to experience the game and, upon agreement, were provided with an explanation of the game and support in attaching the EEG device. The game began with a consecutive number visual discrimination task which was followed by an open-eye resting condition and then a neurofeedback task. Preliminary linear regression analyses by the least-squares method of the acquired EEG and age data in 30 participants from 5 to 20 years old suggested an age-dependent left brain lateralization of beta waves at the neurofeedback stage (p = 0.052) and of alpha waves at the open-eye resting stage (p = 0.044) with potential involvement of other wave bands. These results require further validation.
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Affiliation(s)
- Kazuyuki Oda
- Engineering Department, Graduate School of Sciences and Technology for Innovation Yamaguchi University, Yamaguchi 755-8611, Japan
| | - Ricki Colman
- Department of Cell and Regenerative Biology, University of Wisconsin, Madison, Madison, WI 53706, USA
| | - Mamiko Koshiba
- Engineering Department, Graduate School of Sciences and Technology for Innovation Yamaguchi University, Yamaguchi 755-8611, Japan
- Department of Pediatrics, Saitama Medical University, Saitama 350-0495, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai 980-8579, Japan
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43
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Glaubitz L, Stumme J, Lucht S, Moebus S, Schramm S, Jockwitz C, Hoffmann B, Caspers S. Association between Long-Term Air Pollution, Chronic Traffic Noise, and Resting-State Functional Connectivity in the 1000BRAINS Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:97007. [PMID: 36154234 PMCID: PMC9512146 DOI: 10.1289/ehp9737] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 07/04/2022] [Accepted: 07/22/2022] [Indexed: 06/02/2023]
Abstract
BACKGROUND Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown. OBJECTIVE This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks. METHODS Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter (PM10, PM2.5, and PM2.5 absorbance), accumulation mode particle number (PNAM), and nitrogen dioxide (NO2) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h (Lden) and nighttime (Lnight) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables. RESULTS Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, -0.006 (95% CI: -0.021, 0.009) per 0.3 ×10-5/m increase in PM2.5 absorbance and -0.004 (95% CI: -0.006, -0.002) per 1-y age increase]. CONCLUSION High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.
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Affiliation(s)
- Lina Glaubitz
- Environmental Epidemiology Group, Institute of Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Johanna Stumme
- Institute of Neuroscience and Medicine, Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sarah Lucht
- Environmental Epidemiology Group, Institute of Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Susanne Moebus
- Institute for Urban Public Health, University of Duisburg-Essen, Essen, Germany
| | - Sara Schramm
- Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine, Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Barbara Hoffmann
- Environmental Epidemiology Group, Institute of Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine, Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Prany W, Patrice C, Franck D, Fabrice W, Mahdi M, Pierre D, Christian M, Jean-Marc G, Fabian G, Francis E, Jean-Marc B, Bérengère GG. EEG resting-state functional connectivity: evidence for an imbalance of external/internal information integration in autism. J Neurodev Disord 2022; 14:47. [PMID: 36030210 PMCID: PMC9419397 DOI: 10.1186/s11689-022-09456-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 08/04/2022] [Indexed: 01/12/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD. Methods Using high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched). Results We observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band. Conclusion These results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts. Supplementary Information The online version contains supplementary material available at 10.1186/s11689-022-09456-8.
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Affiliation(s)
- Wantzen Prany
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Université de Paris, LaPsyDÉ, CNRS, F-75005, Paris, France
| | - Clochon Patrice
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Doidy Franck
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Wallois Fabrice
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Mahmoudzadeh Mahdi
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Desaunay Pierre
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Mille Christian
- Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guilé Jean-Marc
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France.,Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guénolé Fabian
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Eustache Francis
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Baleyte Jean-Marc
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Service de Psychiatrie de l'enfant et de l'adolescent, Centre Hospitalier Interuniversitaire de Créteil, 94000, Créteil, France
| | - Guillery-Girard Bérengère
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.
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Lee JK, Andrews DS, Ozturk A, Solomon M, Rogers S, Amaral DG, Nordahl CW. Altered Development of Amygdala-Connected Brain Regions in Males and Females with Autism. J Neurosci 2022; 42:6145-6155. [PMID: 35760533 PMCID: PMC9351637 DOI: 10.1523/jneurosci.0053-22.2022] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 04/30/2022] [Accepted: 06/08/2022] [Indexed: 02/05/2023] Open
Abstract
Altered amygdala development is implicated in the neurobiology of autism, but little is known about the coordinated development of the brain regions directly connected with the amygdala. Here we investigated the volumetric development of an amygdala-connected network, defined as the set of brain regions with monosynaptic connections with the amygdala, in autism from early to middle childhood. A total of 950 longitudinal structural MRI scans were acquired from 282 children (93 female) with autism and 128 children with typical development (61 female) at up to four time points (mean ages: 39, 52, 64, and 137 months, respectively). Volumes from 32 amygdala-connected brain regions were examined using mixed effects multivariate distance matrix regression. The Social Responsiveness Scale-2 was administered to assess degree of autistic traits and social impairments. The amygdala-connected network exhibited persistent diagnostic differences (p values ≤ 0.03) that increased over time (p values ≤ 0.02). These differences were most prominent in autistics with more impacted social functioning at baseline. This pattern was not observed across regions without monosynaptic amygdala connection. We observed qualitative sex differences. In males, the bilateral subgenual anterior cingulate cortices were most affected, while in females the left fusiform and superior temporal gyri were most affected. In conclusion, (1) autism is associated with widespread alterations to the development of brain regions connected with the amygdala, which were associated with autistic social behaviors; and (2) autistic males and females exhibited different patterns of alterations, adding to a growing body of evidence of sex differences in the neurobiology of autism.SIGNIFICANCE STATEMENT Global patterns of development across brain regions with monosynaptic connection to the amygdala differentiate autism from typical development, and are modulated by social functioning in early childhood. Alterations to brain regions within the amygdala-connected network differed in males and females with autism. Results also indicate larger volumetric differences in regions having monosynaptic connection with the amygdala than in regions without monosynaptic connection.
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Affiliation(s)
- Joshua K Lee
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Derek S Andrews
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Arzu Ozturk
- Department of Radiology, University of California Davis School of Medicine, Sacramento, California 95817
| | - Marjorie Solomon
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Sally Rogers
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - David G Amaral
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Christine Wu Nordahl
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
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Zhao X, Zhu S, Cao Y, Cheng P, Lin Y, Sun Z, Li Y, Jiang W, Du Y. Regional homogeneity of adolescents with high-functioning autism spectrum disorder and its association with symptom severity. Brain Behav 2022; 12:e2693. [PMID: 35816591 PMCID: PMC9392530 DOI: 10.1002/brb3.2693] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 05/13/2022] [Accepted: 06/23/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND AND PURPOSE Previous studies have revealed abnormal regional homogeneity (ReHo) in individuals with autism spectrum disorder (ASD); however, there is little consistency across the findings within these studies, partly due to small sample size and great heterogeneity among participants between studies. Additionally, few studies have explored the association between ReHo aberrance and clinical symptoms in individuals with ASD. METHODS Forty-eight adolescents with high-functioning ASD and 63 group-matched typically developing (TD) controls received functional magnetic resonance imaging at rest. Group-level analysis was performed to detect differences in ReHo between ASD and TD. Evaluation of symptom severity in individuals with ASD was based on the Autism Behavior Checklist (ABC). Voxel-wise correlation analysis was undergone to examine the correlations between the symptom severity and ReHo map in individuals with ASD within brain areas with ReHo abnormalities. RESULTS Compared with the TD controls, individuals with ASD exhibited increased ReHo in the bilateral anterior cingulate cortex, left caudate, right posterior cerebellum (cerebellar tonsil), and bilateral brainstem and decreased ReHo in the left precentral gyrus, left inferior parietal lobule, bilateral postcentral gyrus, and right anterior cerebellum (culmen). The correlation analysis indicated that the ReHo value in the brainstem was negatively associated with the ABC total scores and the scores of Relating factor, respectively. CONCLUSIONS Our findings indicated that widespread ReHo abnormalities occurred in ASD, shedding light on the underlying neurobiology of pathogenesis and symptomatology of ASD.
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Affiliation(s)
- Xiaoxin Zhao
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuyi Zhu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Cao
- Department of Psychiatry, Suzhou Guangji Hospital, Suzhou, China
| | - Peipei Cheng
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuxiong Lin
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhixin Sun
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenqing Jiang
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yasong Du
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Bogdanova OV, Bogdanov VB, Pizano A, Bouvard M, Cazalets JR, Mellen N, Amestoy A. The Current View on the Paradox of Pain in Autism Spectrum Disorders. Front Psychiatry 2022; 13:910824. [PMID: 35935443 PMCID: PMC9352888 DOI: 10.3389/fpsyt.2022.910824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/17/2022] [Indexed: 01/18/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which affects 1 in 44 children and may cause severe disabilities. Besides socio-communicational difficulties and repetitive behaviors, ASD also presents as atypical sensorimotor function and pain reactivity. While chronic pain is a frequent co-morbidity in autism, pain management in this population is often insufficient because of difficulties in pain evaluation, worsening their prognosis and perhaps driving higher mortality rates. Previous observations have tended to oversimplify the experience of pain in autism as being insensitive to painful stimuli. Various findings in the past 15 years have challenged and complicated this dogma. However, a relatively small number of studies investigates the physiological correlates of pain reactivity in ASD. We explore the possibility that atypical pain perception in people with ASD is mediated by alterations in pain perception, transmission, expression and modulation, and through interactions between these processes. These complex interactions may account for the great variability and sometimes contradictory findings from the studies. A growing body of evidence is challenging the idea of alterations in pain processing in ASD due to a single factor, and calls for an integrative view. We propose a model of the pain cycle that includes the interplay between the molecular and neurophysiological pathways of pain processing and it conscious appraisal that may interfere with pain reactivity and coping in autism. The role of social factors in pain-induced response is also discussed. Pain assessment in clinical care is mostly based on subjective rather than objective measures. This review clarifies the strong need for a consistent methodology, and describes innovative tools to cope with the heterogeneity of pain expression in ASD, enabling individualized assessment. Multiple measures, including self-reporting, informant reporting, clinician-assessed, and purely physiological metrics may provide more consistent results. An integrative view on the regulation of the pain cycle offers a more robust framework to characterize the experience of pain in autism.
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Affiliation(s)
- Olena V. Bogdanova
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
| | - Volodymyr B. Bogdanov
- Laboratoire EA 4136 – Handicap Activité Cognition Santé HACS, Collège Science de la Sante, Institut Universitaire des Sciences de la Réadaptation, Université de Bordeaux, Bordeaux, France
| | - Adrien Pizano
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
| | - Manuel Bouvard
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
| | - Jean-Rene Cazalets
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
| | - Nicholas Mellen
- Department of Neurology, University of Louisville, Louisville, KY, United States
| | - Anouck Amestoy
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
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48
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Zhao F, Zhang H, Wang P, Cui W, Xu K, Chen D, Hu M, Li Z, Geng X, Wei S. Oxytocin and serotonin in the modulation of neural function: Neurobiological underpinnings of autism-related behavior. Front Neurosci 2022; 16:919890. [PMID: 35937893 PMCID: PMC9354980 DOI: 10.3389/fnins.2022.919890] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/27/2022] [Indexed: 12/12/2022] Open
Abstract
Autism spectrum disorders (ASD) is a group of generalized neurodevelopmental disorders. Its main clinical features are social communication disorder and repetitive stereotyped behavioral interest. The abnormal structure and function of brain network is the basis of social dysfunction and stereotyped performance in patients with autism spectrum disorder. The number of patients diagnosed with ASD has increased year by year, but there is a lack of effective intervention and treatment. Oxytocin has been revealed to effectively improve social cognitive function and significantly improve the social information processing ability, empathy ability and social communication ability of ASD patients. The change of serotonin level also been reported affecting the development of brain and causes ASD-like behavioral abnormalities, such as anxiety, depression like behavior, stereotyped behavior. Present review will focus on the research progress of serotonin and oxytocin in the pathogenesis, brain circuit changes and treatment of autism. Revealing the regulatory effect and neural mechanism of serotonin and oxytocin on patients with ASD is not only conducive to a deeper comprehension of the pathogenesis of ASD, but also has vital clinical significance.
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Affiliation(s)
- Feng Zhao
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Hao Zhang
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Peng Wang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Wenjie Cui
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Kaiyong Xu
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Dan Chen
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Minghui Hu
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zifa Li
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
- Zifa Li,
| | - Xiwen Geng
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
- Xiwen Geng,
| | - Sheng Wei
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, China
- TAIYUE Postdoctoral Innovation and Practice Base, Jinan, China
- Chinese Medicine and Brain Science Core Facility, Shandong University of Traditional Chinese Medicine, Jinan, China
- *Correspondence: Sheng Wei,
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49
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Li L, Su X, Zheng Q, Xiao J, Huang XY, Chen W, Yang K, Nie L, Yang X, Chen H, Shi S, Duan X. Cofluctuation analysis reveals aberrant default mode network patterns in adolescents and youths with autism spectrum disorder. Hum Brain Mapp 2022; 43:4722-4732. [PMID: 35781734 PMCID: PMC9491294 DOI: 10.1002/hbm.25986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/30/2022] [Accepted: 06/02/2022] [Indexed: 11/24/2022] Open
Abstract
Resting‐state functional connectivity (rsFC) approaches provide informative estimates of the functional architecture of the brain, and recently‐proposed cofluctuation analysis temporally unwraps FC at every moment in time, providing refined information for quantifying brain dynamics. As a brain network disorder, autism spectrum disorder (ASD) was characterized by substantial alteration in FC, but the contribution of moment‐to‐moment‐activity cofluctuations to the overall dysfunctional connectivity pattern in ASD remains poorly understood. Here, we used the cofluctuation approach to explore the underlying dynamic properties of FC in ASD, using a large multisite resting‐state functional magnetic resonance imaging (rs‐fMRI) dataset (ASD = 354, typically developing controls [TD] = 446). Our results verified that the networks estimated using high‐amplitude frames were highly correlated with the traditional rsFC. Moreover, these frames showed higher average amplitudes in participants with ASD than those in the TD group. Principal component analysis was performed on the activity patterns in these frames and aggregated over all subjects. The first principal component (PC1) corresponds to the default mode network (DMN), and the PC1 coefficients were greater in participants with ASD than those in the TD group. Additionally, increased ASD symptom severity was associated with the increased coefficients, which may result in excessive internally oriented cognition and social cognition deficits in individuals with ASD. Our finding highlights the utility of cofluctuation approaches in prevalent neurodevelopmental disorders and verifies that the aberrant contribution of DMN to rsFC may underline the symptomatology in adolescents and youths with ASD.
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Affiliation(s)
- Lei Li
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoran Su
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.,Department of MR, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Qingyu Zheng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xin Yue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Wan Chen
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Kaihua Yang
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Lei Nie
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Xin Yang
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Huafu Chen
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shengli Shi
- Medical Imaging Department, Henan Children's Hospital, Zhengzhou Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
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50
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Chaudry S, Vasudevan N. mTOR-Dependent Spine Dynamics in Autism. Front Mol Neurosci 2022; 15:877609. [PMID: 35782388 PMCID: PMC9241970 DOI: 10.3389/fnmol.2022.877609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/25/2022] [Indexed: 12/12/2022] Open
Abstract
Autism Spectrum Conditions (ASC) are a group of neurodevelopmental disorders characterized by deficits in social communication and interaction as well as repetitive behaviors and restricted range of interests. ASC are complex genetic disorders with moderate to high heritability, and associated with atypical patterns of neural connectivity. Many of the genes implicated in ASC are involved in dendritic spine pruning and spine development, both of which can be mediated by the mammalian target of rapamycin (mTOR) signaling pathway. Consistent with this idea, human postmortem studies have shown increased spine density in ASC compared to controls suggesting that the balance between autophagy and spinogenesis is altered in ASC. However, murine models of ASC have shown inconsistent results for spine morphology, which may underlie functional connectivity. This review seeks to establish the relevance of changes in dendritic spines in ASC using data gathered from rodent models. Using a literature survey, we identify 20 genes that are linked to dendritic spine pruning or development in rodents that are also strongly implicated in ASC in humans. Furthermore, we show that all 20 genes are linked to the mTOR pathway and propose that the mTOR pathway regulating spine dynamics is a potential mechanism underlying the ASC signaling pathway in ASC. We show here that the direction of change in spine density was mostly correlated to the upstream positive or negative regulation of the mTOR pathway and most rodent models of mutant mTOR regulators show increases in immature spines, based on morphological analyses. We further explore the idea that these mutations in these genes result in aberrant social behavior in rodent models that is due to these altered spine dynamics. This review should therefore pave the way for further research on the specific genes outlined, their effect on spine morphology or density with an emphasis on understanding the functional role of these changes in ASC.
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