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Chen J, Liu T, Shi H. End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion. PLoS One 2024; 19:e0305079. [PMID: 38870175 PMCID: PMC11175492 DOI: 10.1371/journal.pone.0305079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.
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Affiliation(s)
- Jie Chen
- Department of Security, Huaide College of Changzhou University, Jingjiang, Jiangsu, China
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
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2
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Li L, Zheng Q, Xue Y, Bai M, Mu Y. Coactivation pattern analysis reveals altered whole-brain functional transient dynamics in autism spectrum disorder. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02474-y. [PMID: 38814465 DOI: 10.1007/s00787-024-02474-y] [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: 02/13/2024] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Recent studies on autism spectrum disorder (ASD) have identified recurring states dominated by similar coactivation pattern (CAP) and revealed associations between dysfunction in seed-based large-scale brain networks and clinical symptoms. However, the presence of abnormalities in moment-to-moment whole-brain dynamics in ASD remains uncertain. In this study, we employed seed-free CAP analysis to identify transient brain activity configurations and investigate dynamic abnormalities in ASD. We utilized a substantial multisite resting-state fMRI dataset consisting of 354 individuals with ASD and 446 healthy controls (HCs, from HC groups and 2). CAP were generated from a subgroup of all HC subjects (HC group 1) through temporal K-means clustering, identifying four CAPs. These four CAPs exhibited either the activation or inhibition of the default mode network (DMN) and were grouped into two pairs with opposing spatial CAPs. CAPs for HC group 2 and ASD were identified by their spatial similarity to those for HC group 1. Compared with individuals in HC group 2, those with ASD spent more time in CAPs involving the ventral attention network but less time in CAPs related to executive control and the dorsal attention network. Support vector machine analysis demonstrated that the aberrant dynamic characteristics of CAPs achieved an accuracy of 74.87% in multisite classification. In addition, we used whole-brain dynamics to predict symptom severity in ASD. Our findings revealed whole-brain dynamic functional abnormalities in ASD from a single transient perspective, emphasizing the importance of the DMN in abnormal dynamic functional activity in ASD and suggesting that temporally dynamic techniques offer novel insights into time-varying neural processes.
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Affiliation(s)
- Lei Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Qingyu Zheng
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, People's Republic of China
| | - Yang Xue
- Department of Developmental and Behavioral Pediatrics, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Miaoshui Bai
- Department of Developmental and Behavioral Pediatrics, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Yueming Mu
- Department of Dermatology, The First Hospital of Jilin University, Jilin University, 71 Xinmin Street, Changchun, 130021, People's Republic of China.
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Andrews DS, Diers K, Lee JK, Harvey DJ, Heath B, Cordero D, Rogers SJ, Reuter M, Solomon M, Amaral DG, Nordahl CW. Sex differences in trajectories of cortical development in autistic children from 2-13 years of age. Mol Psychiatry 2024:10.1038/s41380-024-02592-8. [PMID: 38755243 DOI: 10.1038/s41380-024-02592-8] [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: 10/04/2023] [Revised: 04/30/2024] [Accepted: 05/02/2024] [Indexed: 05/18/2024]
Abstract
Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.
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Affiliation(s)
- Derek S Andrews
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA.
| | - Kersten Diers
- AI in Medical Imaging, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Joshua K Lee
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Danielle J Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, University of California, Davis, CA, USA
| | - Brianna Heath
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Devani Cordero
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Sally J Rogers
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Martin Reuter
- AI in Medical Imaging, German Center for Neurodegenerative Diseases, Bonn, Germany
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Marjorie Solomon
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - David G Amaral
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
| | - Christine Wu Nordahl
- Department of Psychiatry & Behavioral Sciences, the MIND Institute, University of California, Davis, CA, USA
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4
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Evans MM, Kim J, Abel T, Nickl-Jockschat T, Stevens HE. Developmental Disruptions of the Dorsal Striatum in Autism Spectrum Disorder. Biol Psychiatry 2024; 95:102-111. [PMID: 37652130 PMCID: PMC10841118 DOI: 10.1016/j.biopsych.2023.08.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 08/10/2023] [Accepted: 08/24/2023] [Indexed: 09/02/2023]
Abstract
Autism spectrum disorder (ASD) is an increasingly prevalent neurodevelopmental condition characterized by social and communication deficits as well as patterns of restricted, repetitive behavior. Abnormal brain development has long been postulated to underlie ASD, but longitudinal studies aimed at understanding the developmental course of the disorder have been limited. More recently, abnormal development of the striatum in ASD has become an area of interest in research, partially due to overlap of striatal functions and deficit areas in ASD, as well as the critical role of the striatum in early development, when ASD is first detected. Focusing on the dorsal striatum and the associated symptom domain of restricted, repetitive behavior, we review the current literature on dorsal striatal abnormalities in ASD, including studies on functional connectivity, morphometry, and cellular and molecular substrates. We highlight that observed striatal abnormalities in ASD are often dynamic across development, displaying disrupted developmental trajectories. Important findings include an abnormal trajectory of increasing corticostriatal functional connectivity with age and increased striatal growth during childhood in ASD. We end by discussing striatal findings from animal models of ASD. In sum, the studies reviewed here demonstrate a key role for developmental disruptions of the dorsal striatum in the pathogenesis of ASD. Directing attention toward these findings will improve our understanding of ASD and of how associated deficits may be better addressed.
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Affiliation(s)
- Maya M Evans
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa
| | - Jaekyoon Kim
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa
| | - Ted Abel
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa; Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa
| | - Hanna E Stevens
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa.
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Shen L, Zhang J, Fan S, Ping L, Yu H, Xu F, Cheng Y, Xu X, Yang C, Zhou C. Cortical thickness abnormalities in autism spectrum disorder. Eur Child Adolesc Psychiatry 2024; 33:65-77. [PMID: 36542200 DOI: 10.1007/s00787-022-02133-0] [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: 09/22/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.
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Affiliation(s)
- Liancheng Shen
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Junqing Zhang
- Department of Pharmacy, Shandong Daizhuang Hospital, Jining, China
| | - Shiran Fan
- School of Mental Health, Jining Medical University, Jining, China
| | - Liangliang Ping
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Hao Yu
- School of Mental Health, Jining Medical University, Jining, China
| | - Fangfang Xu
- School of Mental Health, Jining Medical University, Jining, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Chunyan Yang
- School of Rehabilitation Medicine, Jining Medical University, Jining, China.
| | - Cong Zhou
- School of Mental Health, Jining Medical University, Jining, China.
- Department of Psychology, Affiliated Hospital of Jining Medical University, Jining, China.
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Millevert C, Vidas-Guscic N, Vanherp L, Jonckers E, Verhoye M, Staelens S, Bertoglio D, Weckhuysen S. Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents. J Neurosci 2023; 43:8275-8293. [PMID: 38073598 PMCID: PMC10711730 DOI: 10.1523/jneurosci.1043-23.2023] [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: 09/18/2023] [Revised: 06/09/2023] [Accepted: 09/13/2023] [Indexed: 12/18/2023] Open
Abstract
Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.
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Affiliation(s)
- Charissa Millevert
- Applied & Translational Neurogenomics Group, Vlaams Instituut voor Biotechnology (VIB) Center for Molecular Neurology, VIB, Antwerp 2610, Belgium
- Department of Neurology, University Hospital of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Nicholas Vidas-Guscic
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Liesbeth Vanherp
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Elisabeth Jonckers
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp (MICA), University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Daniele Bertoglio
- Bio-Imaging Lab, University of Antwerp, Antwerp 2610, Belgium
- Molecular Imaging Center Antwerp (MICA), University of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Sarah Weckhuysen
- Applied & Translational Neurogenomics Group, Vlaams Instituut voor Biotechnology (VIB) Center for Molecular Neurology, VIB, Antwerp 2610, Belgium
- Department of Neurology, University Hospital of Antwerp, Antwerp 2610, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
- Translational Neurosciences, Faculty of Medicine and Health Science, University of Antwerp, Antwerp 2610, Belgium
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7
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Tkalcec A, Bierlein M, Seeger-Schneider G, Walitza S, Jenny B, Menks WM, Felhbaum LV, Borbas R, Cole DM, Raschle N, Herbrecht E, Stadler C, Cubillo A. Empathy deficits, callous-unemotional traits and structural underpinnings in autism spectrum disorder and conduct disorder youth. Autism Res 2023; 16:1946-1962. [PMID: 37548142 DOI: 10.1002/aur.2993] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/06/2023] [Indexed: 08/08/2023]
Abstract
Distinct empathy deficits are often described in patients with conduct disorder (CD) and autism spectrum disorder (ASD) yet their neural underpinnings and the influence of comorbid Callous-Unemotional (CU) traits are unclear. This study compares the cognitive (CE) and affective empathy (AE) abilities of youth with CD and ASD, their potential neuroanatomical correlates, and the influence of CU traits on empathy. Adolescents and parents/caregivers completed empathy questionnaires (N = 148 adolescents, mean age = 15.16 years) and T1 weighted images were obtained from a subsample (N = 130). Group differences in empathy and the influence of CU traits were investigated using Bayesian analyses and Voxel-Based Morphometry with Threshold-Free Cluster Enhancement focusing on regions involved in AE (insula, amygdala, inferior frontal gyrus and cingulate cortex) and CE processes (ventromedial prefrontal cortex, temporoparietal junction, superior temporal gyrus, and precuneus). The ASD group showed lower parent-reported AE and CE scores and lower self-reported CE scores while the CD group showed lower parent-reported CE scores than controls. When accounting for the influence of CU traits no AE deficits in ASD and CE deficits in CD were found, but CE deficits in ASD remained. Across all participants, CU traits were negatively associated with gray matter volumes in anterior cingulate which extends into the mid cingulate, ventromedial prefrontal cortex, and precuneus. Thus, although co-occurring CU traits have been linked to global empathy deficits in reports and underlying brain structures, its influence on empathy aspects might be disorder-specific. Investigating the subdimensions of empathy may therefore help to identify disorder-specific empathy deficits.
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Affiliation(s)
- Antonia Tkalcec
- Child and Youth Psychiatry, University Psychiatric Clinic, Basel, Switzerland
| | - Maria Bierlein
- Child and Youth Psychiatry, University Psychiatric Clinic, Basel, Switzerland
| | - Gudrun Seeger-Schneider
- Child and Youth Psychiatry, Psychiatric University Clinic, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Child and Youth Psychiatry, Psychiatric University Clinic, University of Zurich, Zurich, Switzerland
| | - Bettina Jenny
- Child and Youth Psychiatry, Psychiatric University Clinic, University of Zurich, Zurich, Switzerland
| | - Willeke M Menks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, and Radboud University Medical Centre, Nijmegen, the Netherlands
- Psychology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Lynn V Felhbaum
- Jacobs Center for Productive Youth, University of Zurich, Zurich, Switzerland
| | - Reka Borbas
- Jacobs Center for Productive Youth, University of Zurich, Zurich, Switzerland
| | - David M Cole
- Translational Psychiatry, University Psychiatric Clinic, Basel, Switzerland
| | - Nora Raschle
- Jacobs Center for Productive Youth, University of Zurich, Zurich, Switzerland
| | - Evelyn Herbrecht
- Child and Youth Psychiatry, University Psychiatric Clinic, Basel, Switzerland
| | - Christina Stadler
- Child and Youth Psychiatry, University Psychiatric Clinic, Basel, Switzerland
| | - Ana Cubillo
- Child and Youth Psychiatry, University Psychiatric Clinic, Basel, Switzerland
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Leisman G, Melillo R, Melillo T. Prefrontal Functional Connectivities in Autism Spectrum Disorders: A Connectopathic Disorder Affecting Movement, Interoception, and Cognition. Brain Res Bull 2023; 198:65-76. [PMID: 37087061 DOI: 10.1016/j.brainresbull.2023.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/05/2023] [Accepted: 04/17/2023] [Indexed: 04/24/2023]
Abstract
The prefrontal cortex is included in a neuronal system that includes the basal ganglia, the thalamus, and the cerebellum. Most of the higher and more complex motor, cognitive, and emotional behavioral functions are thought to be found primarily in the frontal lobes. Insufficient connectivity between the medial prefrontal cortex (mPFC) and other regions of the brain that are distant from each other involved in top-down information processing rely on the global integration of data from multiple input sources and enhance low level perception processes (bottom-up information processing). The reduced deactivation in mPFC and in the rest of the Default Network during global task processing is consistent with the integrative modulatory role served by the mPFC. We stress the importance of understanding the degree to which sensory and movement anomalies in individuals with autism spectrum disorder (ASD) can contribute to social impairment. Further investigation on the neurobiological basis of sensory symptoms and its relationship to other clinical features found in ASD is required Treatment perhaps should not be first behaviorally based but rather based on facilitating sensory motor development.
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Affiliation(s)
- Gerry Leisman
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel; University of the Medical Sciences of Havana, Department of Clinical Neurophysiology, Institute of Neurology and Neurosurgery, Havana, Cuba.
| | - Robert Melillo
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
| | - Ty Melillo
- Northeast College of the Health Sciencs, Seneca Falls, NY USA
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9
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Duan X, Chen H. Mapping brain functional and structural abnormities in autism spectrum disorder: moving toward precision treatment. PSYCHORADIOLOGY 2022; 2:78-85. [PMID: 38665600 PMCID: PMC10917159 DOI: 10.1093/psyrad/kkac013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/09/2022] [Accepted: 10/12/2022] [Indexed: 04/28/2024]
Abstract
Autism spectrum disorder (ASD) is a formidable challenge for psychiatry and neuroscience because of its high prevalence, lifelong nature, complexity, and substantial heterogeneity. A major goal of neuroimaging studies of ASD is to understand the neurobiological underpinnings of this disorder from multi-dimensional and multi-level perspectives, by investigating how brain anatomy, function, and connectivity are altered in ASD, and how they vary across the population. However, ongoing debate exists within those studies, and neuroimaging findings in ASD are often contradictory. Over the past decade, we have dedicated to delineate a comprehensive and consistent mapping of the abnormal structure and function of the autistic brain, and this review synthesizes the findings across our studies reaching a consensus that the "social brain" are the most affected regions in the autistic brain at different levels and modalities. We suggest that the social brain network can serve as a plausible biomarker and potential target for effective intervention in individuals with ASD.
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Affiliation(s)
- Xujun Duan
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China
- MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
| | - Huafu Chen
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China
- MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 610054, PR China
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