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Kuzu Kumcu M, Törenli Kaya Z, Hoşgören Alıcı Y. Mentalizing self mind but not others: Self-reported mentalization difficulties in multiple sclerosis. Brain Behav 2024; 14:e3612. [PMID: 38970254 PMCID: PMC11226550 DOI: 10.1002/brb3.3612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 05/30/2024] [Accepted: 06/05/2024] [Indexed: 07/08/2024] Open
Abstract
BACKGROUND Mentalization can be defined as a mental process by which an individual directly or indirectly perceives and interprets one's own and others' behavior, emotions, beliefs, and needs based on designed mental states. Mentalization problems may be linked to remove associative white matter fiber disconnection. Multiple sclerosis (MS) is one of the diseases with white matter lesions. By comparing MS patients with healthy controls, it was aimed to assess whether MS patients' mentalization skills are affected. METHOD This study involved 243 participants (170 healthy controls and 73 patients with MS). All the participants completed a sociodemographic questionnaire and the Mentalization Scale (MentS). RESULTS While it was discovered that MentS scores for the dimension of others-based mentalization (MentS-O) were statistically lower in MS group, there was no statistically significant difference between the groups in terms of the dimensions of motivation to mentalize (MentS-M) and self-based mentalization (MentS-S) scores. CONCLUSION We may conclude that MS patients have trouble comprehending other people's thoughts. This effect can be one of the causes of MS patients' issues with social cognition.
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Affiliation(s)
- Müge Kuzu Kumcu
- Department of NeurologyLokman Hekim UniversityAnkaraTurkey
- Department of NeuroscienceAnkara UniversityAnkaraTurkey
| | | | - Yasemin Hoşgören Alıcı
- Department of NeuroscienceAnkara UniversityAnkaraTurkey
- Department of PsychiatryBaşkent UniversityAnkaraTurkey
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Nagai Y, Kirino E, Tanaka S, Usui C, Inami R, Inoue R, Hattori A, Uchida W, Kamagata K, Aoki S. Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI. Cereb Cortex 2024; 34:129-145. [PMID: 38012112 PMCID: PMC11065111 DOI: 10.1093/cercor/bhad451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.
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Affiliation(s)
- Yasuhito Nagai
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, 1129 Nagaoka Izunokuni-shi Shizuoka 410-2295, Japan
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Shoji Tanaka
- Department of Information and Communication Sciences, Sophia University, 7-1 Kioi-cho Chiyoda-ku Tokyo 102-8554, Japan
| | - Chie Usui
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Rie Inami
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Reiichi Inoue
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Aki Hattori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode Urayasu-shi Chiba 279-0013, Japan
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Hsieh CCJ, Lo YC, Wang HH, Shen HY, Chen YY, Lee YC. Amelioration of the brain structural connectivity is accompanied with changes of gut microbiota in a tuberous sclerosis complex mouse model. Transl Psychiatry 2024; 14:68. [PMID: 38296969 PMCID: PMC10830571 DOI: 10.1038/s41398-024-02752-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: 11/15/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 02/02/2024] Open
Abstract
Tuberous sclerosis complex (TSC) is a genetic disease that causes benign tumors and dysfunctions in many organs, including the brain. Aside from the brain malformations, many individuals with TSC exhibit neuropsychiatric symptoms. Among these symptoms, autism spectrum disorder (ASD) is one of the most common co-morbidities, affecting up to 60% of the population. Past neuroimaging studies strongly suggested that the impairments in brain connectivity contribute to ASD, whether or not TSC-related. Specifically, the tract-based diffusion tensor imaging (DTI) analysis provides information on the fiber integrity and has been used to study the neuropathological changes in the white matter of TSC patients with ASD symptoms. In our previous study, curcumin, a diet-derived mTOR inhibitor has been shown to effectively mitigate learning and memory deficits and anxiety-like behavior in Tsc2+/- mice via inhibiting astroglial proliferation. Recently, gut microbiota, which is greatly influenced by the diet, has been considered to play an important role in regulating several components of the central nervous system, including glial functions. In this study, we showed that the abnormal social behavior in the Tsc2+/- mice can be ameliorated by the dietary curcumin treatment. Second, using tract-based DTI analysis, we found that the Tsc2+/- mice exhibited altered fractional anisotropy, axial and radial diffusivities of axonal bundles connecting the prefrontal cortex, nucleus accumbens, hypothalamus, and amygdala, indicating a decreased brain network. Third, the dietary curcumin treatment improved the DTI metrics, in accordance with changes in the gut microbiota composition. At the bacterial phylum level, we showed that the abundances of Actinobacteria, Verrucomicrobia, and Tenericutes were significantly correlated with the DTI metrics FA, AD, and RD, respectively. Finally, we revealed that the expression of myelin-associated proteins, myelin bassic protein (MBP) and proteolipid protein (PLP) was increased after the treatment. Overall, we showed a strong correlation between structural connectivity alterations and social behavioral deficits, as well as the diet-dependent changes in gut microbiota composition.
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Affiliation(s)
| | - Yu-Chun Lo
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
- Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan
| | - Hsin-Hui Wang
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Hsin-Ying Shen
- Biomedical Translation Research Center, Academia Sinica, Taipei, Taiwan
| | - You-Yin Chen
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Yi-Chao Lee
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
- Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan.
- International Master Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
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DiPiero M, Cordash H, Prigge MB, King CK, Morgan J, Guerrero-Gonzalez J, Adluru N, King JB, Lange N, Bigler ED, Zielinski BA, Alexander AL, Lainhart JE, Dean DC. Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males. Front Neurosci 2023; 17:1231719. [PMID: 37829720 PMCID: PMC10565827 DOI: 10.3389/fnins.2023.1231719] [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: 05/30/2023] [Accepted: 09/07/2023] [Indexed: 10/14/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males. Methods Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated. Results All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores. Conclusion Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.
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Affiliation(s)
- Marissa DiPiero
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Hassan Cordash
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Molly B. Prigge
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Carolyn K. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Jubel Morgan
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | | | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, United States
| | - Erin D. Bigler
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, University of Utah, Salt Lake City, UT, United States
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, United States
- Department of Neurology, University of California, Davis, Davis, CA, United States
| | - Brandon A. Zielinski
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Pediatrics, University of Utah, Salt Lake City, UT, United States
- Departments of Pediatrics and Neurology, University of Florida, Gainesville, FL, United States
- McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
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5
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Soylu F, May K, Kana R. White and gray matter correlates of theory of mind in autism: a voxel-based morphometry study. Brain Struct Funct 2023; 228:1671-1689. [PMID: 37452864 DOI: 10.1007/s00429-023-02680-5] [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: 06/07/2022] [Accepted: 07/02/2023] [Indexed: 07/18/2023]
Abstract
Autism spectrum disorder (ASD) is characterized by difficulties in theory of mind (ToM) and social communication. Studying structural and functional correlates of ToM in the brain and how autistic and nonautistic groups differ in terms of these correlates can help with diagnosis and understanding the biological mechanisms of ASD. In this study, we investigated white matter volume (WMV) and gray matter volume (GMV) differences between matching autistic and nonautistic samples, and how these structural features relate to age and ToM skills, indexed by the Reading the Mind in the Eyes (RMIE) measure. The results showed widespread GMV and WMV differences between the two groups in regions crucial for social processes. The autistic group did not express the typically observed negative GMV and positive WMV correlations with age at the same level as the nonautistic group, pointing to abnormalities in developmental structural changes. In addition, we found differences between the two groups in how GMV relates to ToM, particularly in the left frontal regions, and how WMV relates to ToM, mostly in the cingulate and corpus callosum. Finally, GMV in the left insula, a region that is part of the salience network, was found to be crucial in distinguishing ToM performance between the two groups.
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Affiliation(s)
- Firat Soylu
- Educational Psychology Program, The University of Alabama, Tuscaloosa, USA.
| | - Kaitlyn May
- Educational Psychology Program, The University of Alabama, Tuscaloosa, USA
| | - Rajesh Kana
- Department of Psychology, & the Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, USA
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6
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Wang Z, He M, Lv Y, Ge E, Zhang S, Qiang N, Liu T, Zhang F, Li X, Ge B. Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism. Cereb Cortex 2023:7133663. [PMID: 37083279 DOI: 10.1093/cercor/bhad125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 04/22/2023] Open
Abstract
Fiber tract segmentation is a prerequisite for tract-based statistical analysis. Brain fiber streamlines obtained by diffusion magnetic resonance imaging and tractography technology are usually difficult to be leveraged directly, thus need to be segmented into fiber tracts. Previous research mainly consists of two steps: defining and computing the similarity features of fiber streamlines, then adopting machine learning algorithms for fiber clustering or classification. Defining the similarity feature is the basic premise and determines its potential reliability and application. In this study, we adopt geometric features for fiber tract segmentation and develop a novel descriptor (FiberGeoMap) for the corresponding representation, which can effectively depict fiber streamlines' shapes and positions. FiberGeoMap can differentiate fiber tracts within the same subject, meanwhile preserving the shape and position consistency across subjects, thus can identify common fiber tracts across brains. We also proposed a Transformer-based encoder network called FiberGeoMap Learner, to perform segmentation based on the geometric features. Experimental results showed that the proposed method can differentiate the 103 various fiber tracts, which outperformed the existing methods in both the number of categories and segmentation accuracy. Furthermore, the proposed method identified some fiber tracts that were statistically different on fractional anisotropy (FA), mean diffusion (MD), and fiber number ration in autism.
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Affiliation(s)
- Zhenwei Wang
- Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi'an, China
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
| | - Mengshen He
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
| | - Yifan Lv
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
| | - Enjie Ge
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
| | - Shu Zhang
- Center for Brain and Brain-Inspired Computing Research, Department of Computer Science, Northwestern Polytechnical University, Xi'an, China
| | - Ning Qiang
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
- Center for Brain and Brain-Inspired Computing Research, Department of Computer Science, Northwestern Polytechnical University, Xi'an, China
| | - Tianming Liu
- Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States
| | - Fan Zhang
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Xiang Li
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Bao Ge
- Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi'an, China
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
- Center for Brain and Brain-Inspired Computing Research, Department of Computer Science, Northwestern Polytechnical University, Xi'an, China
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7
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Corpus callosum organization and its implication to core and co-occurring symptoms of Autism Spectrum Disorder. Brain Struct Funct 2023; 228:775-785. [PMID: 36867240 DOI: 10.1007/s00429-023-02617-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/31/2023] [Indexed: 03/04/2023]
Abstract
Autism Spectrum Disorder (ASD) is characterized by social interaction and communication deficits, repetitive behavior and often by co-occurring conditions such as language and non-verbal IQ development delays. Previous studies reported that those behavioral abnormalities can be associated with corpus callosum organization. However, little is known about the specific differences in white matter structure of the corpus callosum parts in children with ASD and TD peers and their relationships to core and co-occurring symptoms of ASD. The aim of the study was to investigate the volumetric and microstructural characteristics of the corpus callosum parts crucially involved in social, language, and non-verbal IQ behavior in primary-school-aged children with ASD and to assess the relationships between these characteristics and behavioral measures. 38 children (19 with ASD and 19 typically developing (TD) controls) were scanned using diffusion-weighted MRI and assessed with behavioral tests. The tractography of the corpus callosum parts were performed using Quantitative Imaging Toolkit software; diffusivity and volumetric measurements were extracted for the analysis. In the ASD group, fractional anisotropy (FA) was decreased across the supplementary motor area and the ventromedial prefrontal cortex, and axial diffusivity (AD) was reduced across each of the corpus callosum parts in comparison to the TD group. Importantly, the AD decrease was related to worse language skills and more severe autistic traits in individuals with ASD. The microstructure of the corpus callosum parts differs between children with and without ASD. Abnormalities in white matter organization of the corpus callosum parts are associated with core and co-occurring symptoms of ASD.
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Individual differences in white matter microstructure of the face processing brain network are more differentiated from global fibers with increasing ability. Sci Rep 2022; 12:14075. [PMID: 35982145 PMCID: PMC9388653 DOI: 10.1038/s41598-022-17850-4] [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: 10/17/2021] [Accepted: 08/02/2022] [Indexed: 11/23/2022] Open
Abstract
Face processing—a crucial social ability—is known to be carried out in multiple dedicated brain regions which form a distinguishable network. Previous studies on face processing mainly targeted the functionality of face-selective grey matter regions. Thus, it is still partly unknown how white matter structures within the face network underpins abilities in this domain. Furthermore, how relevant abilities modulate the relationship between face-selective and global fibers remains to be discovered. Here, we aimed to fill these gaps by exploring linear and non-linear associations between microstructural properties of brain fibers (namely fractional anisotropy, mean diffusivity, axial and radial diffusivity) and face processing ability. Using structural equation modeling, we found significant linear associations between specific properties of fibers in the face network and face processing ability in a young adult sample (N = 1025) of the Human Connectome Project. Furthermore, individual differences in the microstructural properties of the face processing brain system tended toward stronger differentiation from global brain fibers with increasing ability. This is especially the case in the low or high ability range. Overall, our study provides novel evidence for ability-dependent specialization of brain structure in the face network, which promotes a comprehensive understanding of face selectivity.
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Tsurugizawa T. Translational Magnetic Resonance Imaging in Autism Spectrum Disorder From the Mouse Model to Human. Front Neurosci 2022; 16:872036. [PMID: 35585926 PMCID: PMC9108701 DOI: 10.3389/fnins.2022.872036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous syndrome characterized by behavioral features such as impaired social communication, repetitive behavior patterns, and a lack of interest in novel objects. A multimodal neuroimaging using magnetic resonance imaging (MRI) in patients with ASD shows highly heterogeneous abnormalities in function and structure in the brain associated with specific behavioral features. To elucidate the mechanism of ASD, several ASD mouse models have been generated, by focusing on some of the ASD risk genes. A specific behavioral feature of an ASD mouse model is caused by an altered gene expression or a modification of a gene product. Using these mouse models, a high field preclinical MRI enables us to non-invasively investigate the neuronal mechanism of the altered brain function associated with the behavior and ASD risk genes. Thus, MRI is a promising translational approach to bridge the gap between mice and humans. This review presents the evidence for multimodal MRI, including functional MRI (fMRI), diffusion tensor imaging (DTI), and volumetric analysis, in ASD mouse models and in patients with ASD and discusses the future directions for the translational study of ASD.
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Affiliation(s)
- Tomokazu Tsurugizawa
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
- Faculty of Engineering, University of Tsukuba, Tsukuba, Japan
- *Correspondence: Tomokazu Tsurugizawa,
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10
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Andica C, Kamagata K, Kirino E, Uchida W, Irie R, Murata S, Aoki S. Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism. Mol Autism 2021; 12:48. [PMID: 34193257 PMCID: PMC8247240 DOI: 10.1186/s13229-021-00456-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 06/24/2021] [Indexed: 11/10/2022] Open
Abstract
Background Evidences suggesting the association between behavioral anomalies in autism and white matter (WM) microstructural alterations are increasing. Diffusion tensor imaging (DTI) is widely used to infer tissue microstructure. However, due to its lack of specificity, the underlying pathology of reported differences in DTI measures in autism remains poorly understood. Herein, we applied neurite orientation dispersion and density imaging (NODDI) to quantify and define more specific causes of WM microstructural changes associated with autism in adults. Methods NODDI (neurite density index [NDI], orientation dispersion index, and isotropic volume fraction [ISOVF]) and DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity, and radial diffusivity [RD]) measures were compared between autism (N = 26; 19 males and 7 females; 32.93 ± 9.24 years old) and age- and sex-matched typically developing (TD; N = 25; 17 males and 8 females; 34.43 ± 9.02 years old) groups using tract-based spatial statistics and region-of-interest analyses. Linear discriminant analysis using leave-one-out cross-validation (LDA-LOOCV) was also performed to assess the discriminative power of diffusion measures in autism and TD. Results Significantly lower NDI and higher ISOVF, suggestive of decreased neurite density and increased extracellular free-water, respectively, were demonstrated in the autism group compared with the TD group, mainly in commissural and long-range association tracts, but with distinct predominant sides. Consistent with previous reports, the autism group showed lower FA and higher MD and RD when compared with TD group. Notably, LDA-LOOCV suggests that NDI and ISOVF have relatively higher accuracy (82%) and specificity (NDI, 84%; ISOVF, 88%) compared with that of FA, MD, and RD (accuracy, 67–73%; specificity, 68–80%). Limitations The absence of histopathological confirmation limit the interpretation of our findings. Conclusions Our results suggest that NODDI measures might be useful as imaging biomarkers to diagnose autism in adults and assess its behavioral characteristics. Furthermore, NODDI allows interpretation of previous findings on changes in WM diffusion tensor metrics in individuals with autism.
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Affiliation(s)
- Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Psychiatry, Juntendo University Shizuoka Hospital, Shizuoka, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Syo Murata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiological Sciences, Faculty of Healthy Sciences, Komazawa University, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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11
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Gyori NG, Clark CA, Alexander DC, Kaden E. On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol. Neuroimage 2021; 239:118303. [PMID: 34174390 PMCID: PMC8363942 DOI: 10.1016/j.neuroimage.2021.118303] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 06/16/2021] [Accepted: 06/22/2021] [Indexed: 12/14/2022] Open
Abstract
B-tensor encoding enables estimation of spherical cellular structures in the brain. Spherical compartments may provide markers for apparent neural soma density. Model parameters can be estimated in a fast and robust way using deep learning. Practical acquisition times are achievable on widely available clinical scanners.
Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.
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Affiliation(s)
- Noemi G Gyori
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
| | - Christopher A Clark
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Enrico Kaden
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
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12
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Demir A, Ozkan M, Ulug AM. A Macro-Structural Dispersion Characteristic of Brain White Matter and Its Application to Bipolar Disorder. IEEE Trans Biomed Eng 2020; 68:428-435. [PMID: 32746027 DOI: 10.1109/tbme.2020.3002688] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Our goal is to find distinct characteristics of brain white matter in bipolar disorder, of which the development of diagnostic imaging measures is necessary for early diagnosis and prospective studies. METHODS Given a tractogram dataset which is a dense set of white matter fiber pathways of the whole brain obtained from diffusion magnetic resonance imaging, we propose to compute a global measure for a voxel from the dispersion statistics of a set of fibers which indicates the complexity of the white matter voxel not locally but at macroscopic scales. RESULTS Our findings demonstrate that macro-structural dispersion information is significant for discrimination of the bipolar patients from the healthy controls, particularly in the frontally associative bundles such as cingulum and inferior occipito-frontal fascicles. CONCLUSION The proposed measure is as informative as the local diffusion measures for the detection of changes in the white matter regions. SIGNIFICANCE Our findings show that the proposed measure is a potential diagnostic imaging marker in bipolar disorder and the proposed novel dispersion map of the brain could be used for other neurological applications.
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13
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Dimond D, Schuetze M, Smith RE, Dhollander T, Cho I, Vinette S, Ten Eycke K, Lebel C, McCrimmon A, Dewey D, Connelly A, Bray S. Reduced White Matter Fiber Density in Autism Spectrum Disorder. Cereb Cortex 2020; 29:1778-1788. [PMID: 30668849 PMCID: PMC6418389 DOI: 10.1093/cercor/bhy348] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Revised: 11/03/2018] [Indexed: 12/13/2022] Open
Abstract
Differences in brain networks and underlying white matter abnormalities have been suggested to underlie symptoms of autism spectrum disorder (ASD). However, robustly characterizing microstructural white matter differences has been challenging. In the present study, we applied an analytic technique that calculates structural metrics specific to differently-oriented fiber bundles within a voxel, termed "fixels". Fixel-based analyses were used to compare diffusion-weighted magnetic resonance imaging data from 25 individuals with ASD (mean age = 16.8 years) and 27 typically developing age-matched controls (mean age = 16.9 years). Group comparisons of fiber density (FD) and bundle morphology were run on a fixel-wise, tract-wise, and global white matter (GWM) basis. We found that individuals with ASD had reduced FD, suggestive of decreased axonal count, in several major white matter tracts, including the corpus callosum (CC), bilateral inferior frontal-occipital fasciculus, right arcuate fasciculus, and right uncinate fasciculus, as well as a GWM reduction. Secondary analyses assessed associations with social impairment in participants with ASD, and showed that lower FD in the splenium of the CC was associated with greater social impairment. Our findings suggest that reduced FD could be the primary microstructural white matter abnormality in ASD.
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Affiliation(s)
- Dennis Dimond
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary AB, Canada
| | - Manuela Schuetze
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary AB, Canada
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne VIC, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne VIC, Australia
| | - Thijs Dhollander
- The Florey Institute of Neuroscience and Mental Health, Melbourne VIC, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne VIC, Australia
| | - Ivy Cho
- Department of Psychological Clinical Sciences, University of Toronto, Toronto ON, Canada
| | - Sarah Vinette
- Faculty of Medicine, University of Toronto, Toronto ON, Canada
| | - Kayla Ten Eycke
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Department of Community Health Sciences, University of Calgary, Calgary AB, Canada.,Owerko Centre, University of Calgary, Calgary AB, Canada
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary AB, Canada.,Owerko Centre, University of Calgary, Calgary AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB, Canada
| | - Adam McCrimmon
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Owerko Centre, University of Calgary, Calgary AB, Canada.,Werklund School of Education, University of Calgary, Calgary AB, Canada
| | - Deborah Dewey
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Department of Community Health Sciences, University of Calgary, Calgary AB, Canada.,Owerko Centre, University of Calgary, Calgary AB, Canada
| | - Alan Connelly
- The Florey Institute of Neuroscience and Mental Health, Melbourne VIC, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne VIC, Australia
| | - Signe Bray
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary AB, Canada.,Owerko Centre, University of Calgary, Calgary AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary AB, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB, Canada
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14
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Haigh SM, Keller TA, Minshew NJ, Eack SM. Reduced White Matter Integrity and Deficits in Neuropsychological Functioning in Adults With Autism Spectrum Disorder. Autism Res 2020; 13:702-714. [PMID: 32073209 DOI: 10.1002/aur.2271] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 12/06/2019] [Accepted: 01/15/2020] [Indexed: 12/31/2022]
Abstract
Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full-scale-IQ-matched healthy volunteers. Tract-based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (P = 0.022) and the right cingulum (P = 0.008). All neuropsychological measures were worse in the ASD group, but none of the measures significantly correlated with reduced FA in either tract in the adults with ASD or in the healthy volunteers. Together, this indicates that the tracts that are the most impacted in autism may not be (at least directly) responsible for the behavioral deficits in ASD. Autism Res 2020, 13: 702-714. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: White matter tracts are the data cables in the brain that efficiently transfer information, and damage to these tracts could be the cause for the abnormal behaviors that are associated with autism. We found that two long-range tracts (the anterior thalamic radiation and the cingulum) were both impaired in autism but were not directly related to the impairments in behavior. This suggests that the abnormal tracts and behavior are the effects of another underlying mechanism.
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Affiliation(s)
- Sarah M Haigh
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.,Department of Psychology and Integrative Neuroscience, University of Nevada, Reno, Nevada
| | - Timothy A Keller
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Nancy J Minshew
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Shaun M Eack
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,School of Social Work, University of Pittsburgh, Pittsburgh, Pennsylvania
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15
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Haigh SM, Eack SM, Keller T, Minshew NJ, Behrmann M. White matter structure in schizophrenia and autism: Abnormal diffusion across the brain in schizophrenia. Neuropsychologia 2019; 135:107233. [PMID: 31655160 PMCID: PMC6884694 DOI: 10.1016/j.neuropsychologia.2019.107233] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 10/14/2019] [Accepted: 10/14/2019] [Indexed: 01/23/2023]
Abstract
BACKGROUND Schizophrenia and autism share many behavioral and neurological similarities, including altered white matter tract structure. However, because schizophrenia and autism are rarely compared directly, it is difficult to establish whether white matter abnormalities are disorder-specific or are common across these disorders that share some symptomatology. METHODS In the current study, we compared white matter water diffusion using tensor imaging in 25 adults with autism, 15 adults with schizophrenia, all with IQ scores above 88, and 19 neurotypical adults. RESULTS Although the three groups evinced no statistically significant differences in measures of fractional anisotropy (FA), the schizophrenia group showed significantly greater mean diffusivity (MD; Cohen's d > 0.77), due to greater radial diffusivity (RD; Cohen's d > 0.92), compared to both the autism and control groups. This effect was evident across the brain rather than specific to a particular tract. CONCLUSIONS The greater MD and RD in schizophrenia appears to be diagnosis-specific. The altered diffusion may reflect subtle abnormalities in myelination, which could be a potential mechanism underlying the widespread behavioral deficits associated with schizophrenia.
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Affiliation(s)
- Sarah M Haigh
- Department of Psychology, Carnegie Mellon University, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University, USA; Department of Psychology and Center for Integrative Neuroscience, University of Nevada, Reno, USA.
| | - Shaun M Eack
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; School of Social Work, University of Pittsburgh, USA
| | - Timothy Keller
- Department of Psychology, Carnegie Mellon University, USA
| | - Nancy J Minshew
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; Department of Neurology, University of Pittsburgh, USA
| | - Marlene Behrmann
- Department of Psychology, Carnegie Mellon University, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University, USA
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16
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Abstract
Autism Spectrum Disorders (ASDs) are characterised by impaired social communication and restricted repetitive behaviours. Researchers posit that these core features may be underpinned by disrupted structural connectivity. A tract based spatial statistical analysis of diffusion MRI data was performed to investigate white matter organisation (an indication of structural connectivity) in a well-defined cohort of 45 ASD and 45 age and IQ matched control participants. Aberrant structural connectivity characterised by reduced fractional anisotropy was observed in several fiber pathways in ASD relative to controls. Disrupted white matter organisation was associated with social deficits and restricted repetitive behaviours in ASD. Abnormal structural connectivity is apparent in ASD and may be linked to the core behavioural features of the disorder.
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17
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Cooper HE, Kaden E, Halliday LF, Bamiou DE, Mankad K, Peters C, Clark CA. White matter microstructural abnormalities in children with severe congenital hypothyroidism. NEUROIMAGE-CLINICAL 2019; 24:101980. [PMID: 31446316 PMCID: PMC6713841 DOI: 10.1016/j.nicl.2019.101980] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 07/29/2019] [Accepted: 08/08/2019] [Indexed: 12/30/2022]
Abstract
This study assessed white matter microstructural integrity and behavioral correlates for children with severe congenital hypothyroidism (CH) who were identified and treated early following newborn screening. Eighteen children with severe CH and 21 healthy controls underwent a battery of behavioral measures of hearing, language and communication, along with diffusion MR imaging. Tract-based spatial statistics were performed on standard diffusion parameters of fractional anisotropy and diffusivity metrics. Microscopic diffusion anisotropy mapping based on the Spherical Mean Technique was also used to evaluate biologically specific metrics. Compared with age-matched controls, children with severe CH had poorer hearing and communication skills, albeit generally within normal limits. Children with severe CH had fractional anisotropy that was significantly lower in the cerebellum, bilateral thalami and right temporal lobe, and radial diffusivity that was significantly higher in the cerebellum and bilateral thalami. Microscopic fractional anisotropy and intra-neurite volume fraction were also significantly decreased, and transverse microscopic diffusivity was significantly increased, in the CH group in areas including the cerebellum, thalamus, occipital lobe, and corpus callosum, and in the white matter adjacent to sensorimotor cortex, particularly in the left hemisphere. Significant and widespread correlations were observed between behavioral measures and measures of white matter microstructural integrity in children with CH. The results indicate that children with severe CH who are identified through newborn screening may have significant brain white matter microstructural abnormalities despite early treatment. Children with severe CH show reductions in white matter microstructural integrity. Hearing and communication abilities are impaired for some children with severe CH. White matter abnormalities are associated with communication abilities in CH.
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Affiliation(s)
- Hannah E Cooper
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK; Royal Berkshire NHS Foundation Trust, Reading, UK.
| | - Enrico Kaden
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Lorna F Halliday
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Doris-Eva Bamiou
- UCL Ear Institute, Faculty of Brain Sciences, University College London, London, UK; National Institute of Health Research (NIHR), University College London Hospitals Biomedical Research Centre, London, UK
| | - Kshitij Mankad
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
| | - Catherine Peters
- Department of Endocrinology, Great Ormond Street Hospital for Children, London, UK
| | - Christopher A Clark
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
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18
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White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging. Neuroradiology 2019; 61:1343-1353. [PMID: 31209529 DOI: 10.1007/s00234-019-02238-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 05/29/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales. METHODS Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm2). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined. RESULTS The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social-emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi. CONCLUSIONS Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.
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19
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Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers: Preliminary Data from a DWI Analysis. J Clin Med 2019; 8:jcm8040487. [PMID: 30974902 PMCID: PMC6518033 DOI: 10.3390/jcm8040487] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/02/2019] [Accepted: 04/06/2019] [Indexed: 11/17/2022] Open
Abstract
Autism Spectrum Disorders (ASD) is a group of neurodevelopmental disorders that is characterized by an altered brain connectivity organization. Autistic traits below the clinical threshold (i.e., the broad autism phenotype; BAP) are frequent among first-degree relatives of subjects with ASD; however, little is known regarding whether subthreshold behavioral manifestations of ASD mirror also at the neuroanatomical level in parents of ASD probands. To this aim, we applied advanced diffusion network analysis to MRI of 16 dyads consisting of a child with ASD and his father in order to investigate: (i) the correlation between structural network organization and autistic features in preschoolers with ASD (all males; age range 1.5-5.2 years); (ii) the correlation between structural network organization and BAP features in the fathers of individuals with ASD (fath-ASD). Local network measures significantly correlated with autism severity in ASD children and with BAP traits in fath-ASD, while no significant association emerged when considering the global measures of brain connectivity. Notably, an overlap of some brain regions that are crucial for social functioning (cingulum, superior temporal gyrus, inferior temporal gyrus, middle frontal gyrus, frontal pole, and amygdala) in patients with ASD and fath-ASD was detected, suggesting an intergenerational transmission of these neural substrates. Overall, the results of this study may help in elucidating the neurostructural endophenotype of ASD, paving the way for bridging connections between underlying genetic and ASD symptomatology.
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20
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Gibbard CR, Ren J, Skuse DH, Clayden JD, Clark CA. Structural connectivity of the amygdala in young adults with autism spectrum disorder. Hum Brain Mapp 2018; 39:1270-1282. [PMID: 29265723 PMCID: PMC5838552 DOI: 10.1002/hbm.23915] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 11/30/2017] [Accepted: 12/01/2017] [Indexed: 01/11/2023] Open
Abstract
Autism spectrum disorder (ASD) is characterized by impairments in social cognition, a function associated with the amygdala. Subdivisions of the amygdala have been identified which show specificity of structure, connectivity, and function. Little is known about amygdala connectivity in ASD. The aim of this study was to investigate the microstructural properties of amygdala-cortical connections and their association with ASD behaviours, and whether connectivity of specific amygdala subregions is associated with particular ASD traits. The brains of 51 high-functioning young adults (25 with ASD; 26 controls) were scanned using MRI. Amygdala volume was measured, and amygdala-cortical connectivity estimated using probabilistic tractography. An iterative 'winner takes all' algorithm was used to parcellate the amygdala based on its primary cortical connections. Measures of amygdala connectivity were correlated with clinical scores. In comparison with controls, amygdala volume was greater in ASD (F(1,94) = 4.19; p = .04). In white matter (WM) tracts connecting the right amygdala to the right cortex, ASD subjects showed increased mean diffusivity (t = 2.35; p = .05), which correlated with the severity of emotion recognition deficits (rho = -0.53; p = .01). Following amygdala parcellation, in ASD subjects reduced fractional anisotropy in WM connecting the left amygdala to the temporal cortex was associated with with greater attention switching impairment (rho = -0.61; p = .02). This study demonstrates that both amygdala volume and the microstructure of connections between the amygdala and the cortex are altered in ASD. Findings indicate that the microstructure of right amygdala WM tracts are associated with overall ASD severity, but that investigation of amygdala subregions can identify more specific associations.
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Affiliation(s)
- Clare R. Gibbard
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, 30 Guilford StreetLondonWC1N 1EHUnited Kingdom
| | - Juejing Ren
- Behavioural Sciences UnitUCL Great Ormond Street Institute of Child Health, 30 Guilford StreetLondonWC1N 1EHUnited Kingdom
| | - David H. Skuse
- Behavioural Sciences UnitUCL Great Ormond Street Institute of Child Health, 30 Guilford StreetLondonWC1N 1EHUnited Kingdom
| | - Jonathan D. Clayden
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, 30 Guilford StreetLondonWC1N 1EHUnited Kingdom
| | - Chris A. Clark
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, 30 Guilford StreetLondonWC1N 1EHUnited Kingdom
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21
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Chien YL, Chen YJ, Hsu YC, Tseng WYI, Gau SSF. Altered white-matter integrity in unaffected siblings of probands with autism spectrum disorders. Hum Brain Mapp 2017; 38:6053-6067. [PMID: 28940697 DOI: 10.1002/hbm.23810] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 07/27/2017] [Accepted: 09/05/2017] [Indexed: 11/10/2022] Open
Abstract
Despite the evidence of altered white-matter tract property in individuals with autism spectrum disorder (ASD), little is known about their unaffected siblings. This study aimed to investigate white-matter integrity in unaffected siblings of ASD probands. Thirty-nine unaffected siblings (mean age 15.6 ± 6.0 years; 27 males, 69.2%) and 39 typically developing controls (TDC) (14.2 ± 5.6 years; 26 males, 66.7%) were assessed with diffusion spectrum images and neuropsychological tests. Using the tract-based automatic analysis and the threshold-free cluster weighted (TFCW) scores, we searched for the segments among 76 tracts with the largest difference over the entire brain compared to TDC. Tract integrity was quantified by calculating the mean generalized fractional anisotropy (mGFA) values of the segments with the largest difference in TFCW scores. Unaffected siblings showed reduced mGFA in the bilateral frontal aslant tracts, the right superior longitudinal fasciculus 2 (SLF2), the frontostriatal tracts from the right dorsolateral and left ventrolateral prefrontal cortices, the thalamic radiations of the left ventral and the right dorsal thalamus, the callosal fibers of the splenium, and the increased mGFA of the callosal fibers of the precuneus and the left inferior longitudinal fasciculus. Among these, reduced right SLF2 mGFA was associated with social awareness deficits; impaired frontostriatal tract was associated with internalizing problems, while right frontal aslant tract integrity was associated with visual memory deficits. In conclusion, unaffected siblings showed the aberrant integrity of several white-matter tracts, which were correlated with clinical symptoms and neurocognitive dysfunction. The altered tract integrity could be further examined in the probands with ASD. Hum Brain Mapp 38:6053-6067, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.,Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yu-Jen Chen
- Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
| | - Yung-Chin Hsu
- Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.,Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
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22
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Yordanova YN, Duffau H, Herbet G. Neural pathways subserving face-based mentalizing. Brain Struct Funct 2017; 222:3087-3105. [DOI: 10.1007/s00429-017-1388-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 02/13/2017] [Indexed: 10/20/2022]
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23
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Mehling MH, Tassé MJ. Severity of Autism Spectrum Disorders: Current Conceptualization, and Transition to DSM-5. J Autism Dev Disord 2017; 46:2000-2016. [PMID: 26873143 DOI: 10.1007/s10803-016-2731-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Mirroring the evolution of the conceptualization of autism has been changes in the diagnostic process, including the most recent revisions to the DSM-5 and the addition of severity-based diagnostic modifiers assigned on the basis of intensity of needed supports. A review of recent literature indicates that in research stratifying individuals on the basis of autism severity, core ASD symptomology is the primary consideration. This conceptualization is disparate from the conceptualization put forth in DSM-5 in which severity determination is based on level of needed support, which is also impacted by cognitive, language, behavioral, and adaptive functioning. This paper reviews literature in this area and discusses possible instruments that may be useful to inform clinical judgment in determining ASD severity levels.
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Affiliation(s)
- Margaret H Mehling
- Nisonger Center, The Ohio State University, McCampbell Hall Room 279, 1581 Dodd Dr, Columbus, OH, 43210, USA.
| | - Marc J Tassé
- Nisonger Center, The Ohio State University, McCampbell Hall Room 279, 1581 Dodd Dr, Columbus, OH, 43210, USA
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24
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Bradstreet LE, Hecht EE, King TZ, Turner JL, Robins DL. Associations between autistic traits and fractional anisotropy values in white matter tracts in a nonclinical sample of young adults. Exp Brain Res 2016; 235:259-267. [PMID: 27699442 DOI: 10.1007/s00221-016-4791-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2016] [Accepted: 09/28/2016] [Indexed: 11/24/2022]
Abstract
Whereas a number of studies have examined relationships among brain activity, social cognitive skills, and autistic traits, fewer studies have evaluated whether structural connections among brain regions relate to these traits and skills. Uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF) are white matter tracts that may underpin the behavioral expression of these skills because they connect regions within or provide sensory information to brain areas implicated in social cognition, and structural differences in these tracts have been associated with autistic traits. We examined relationships among self-reported autistic traits, mentalizing, and water diffusivity in UF and ILF in a nonclinical sample of 24 young adults (mean age = 21.92 years, SD = 4.72 years; 15 women). We measured autistic traits using the Autism-Spectrum Quotient, and we measured mentalizing using the Dynamic Interactive Shapes Clips task. We used Tract-Based Spatial Statistics and randomize to examine relationships among fractional anisotropy (FA) values in bilateral ILF and UF, age, cognitive abilities, autistic traits, and mentalizing. Autistic traits were positively related to FA values in left ILF. No other relationships between FA values and other variables were significant. Results suggest that left ILF may be involved in the expression of autistic traits in individuals without clinical diagnoses.
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Affiliation(s)
- Lauren E Bradstreet
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302-5010, USA. .,A.J. Drexel Autism Institute, Drexel University, 3020 Market Street, Suite 560, Philadelphia, PA, 19104, USA.
| | - Erin E Hecht
- Center for Behavioral Neuroscience, Georgia State University, P.O. Box 5090, Atlanta, GA, 30302-5090, USA.,Neuroscience Institute, Georgia State University, P.O. Box 5030, Atlanta, GA, 30302-5030, USA
| | - Tricia Z King
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302-5010, USA.,Center for Behavioral Neuroscience, Georgia State University, P.O. Box 5090, Atlanta, GA, 30302-5090, USA.,Neuroscience Institute, Georgia State University, P.O. Box 5030, Atlanta, GA, 30302-5030, USA
| | - Jessica L Turner
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302-5010, USA.,Neuroscience Institute, Georgia State University, P.O. Box 5030, Atlanta, GA, 30302-5030, USA
| | - Diana L Robins
- Department of Psychology, Georgia State University, P.O. Box 5010, Atlanta, GA, 30302-5010, USA.,Center for Behavioral Neuroscience, Georgia State University, P.O. Box 5090, Atlanta, GA, 30302-5090, USA.,Neuroscience Institute, Georgia State University, P.O. Box 5030, Atlanta, GA, 30302-5030, USA.,A.J. Drexel Autism Institute, Drexel University, 3020 Market Street, Suite 560, Philadelphia, PA, 19104, USA
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25
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Koolschijn PCMP, Caan MWA, Teeuw J, Olabarriaga SD, Geurts HM. Age-related differences in autism: The case of white matter microstructure. Hum Brain Mapp 2016; 38:82-96. [PMID: 27511627 DOI: 10.1002/hbm.23345] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 07/25/2016] [Accepted: 08/01/2016] [Indexed: 11/09/2022] Open
Abstract
Autism spectrum disorder (ASD) is typified as a brain connectivity disorder in which white matter abnormalities are already present early on in life. However, it is unknown if and to which extent these abnormalities are hard-wired in (older) adults with ASD and how this interacts with age-related white matter changes as observed in typical aging. The aim of this first cross-sectional study in mid- and late-aged adults with ASD was to characterize white matter microstructure and its relationship with age. We utilized diffusion tensor imaging with head motion control in 48 adults with ASD and 48 age-matched controls (30-74 years), who also completed a Flanker task. Intra-individual variability of reaction times (IIVRT) measures based on performance on the Flanker interference task were used to assess IIVRT-white matter microstructure associations. We observed primarily higher mean and radial diffusivity in white matter microstructure in ASD, particularly in long-range fibers, which persisted after taking head motion into account. Importantly, group-by-age interactions revealed higher age-related mean and radial diffusivity in ASD, in projection and association fiber tracts. Subtle dissociations were observed in IIVRT-white matter microstructure relations between groups, with the IIVRT-white matter association pattern in ASD resembling observations in cognitive aging. The observed white matter microstructure differences are lending support to the structural underconnectivity hypothesis in ASD. These reductions seem to have behavioral percussions given the atypical relationship with IIVRT. Taken together, the current results may indicate different age-related patterns of white matter microstructure in adults with ASD. Hum Brain Mapp 38:82-96, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- P Cédric M P Koolschijn
- Dutch Autism & ADHD Research Center, Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition (ABC), University of Amsterdam, Amsterdam, The Netherlands
| | - Matthan W A Caan
- Department of Radiology, Brain Imaging Center, Academic Medical Center, University of Amsterdam, The Netherlands
| | - Jalmar Teeuw
- Department of Radiology, Brain Imaging Center, Academic Medical Center, University of Amsterdam, The Netherlands.,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sílvia D Olabarriaga
- Department of Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, The Netherlands
| | - Hilde M Geurts
- Dutch Autism & ADHD Research Center, Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition (ABC), University of Amsterdam, Amsterdam, The Netherlands.,Dr Leo Kannerhuis, The Netherlands
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Dougherty CC, Evans DW, Myers SM, Moore GJ, Michael AM. A Comparison of Structural Brain Imaging Findings in Autism Spectrum Disorder and Attention-Deficit Hyperactivity Disorder. Neuropsychol Rev 2015; 26:25-43. [DOI: 10.1007/s11065-015-9300-2] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 09/22/2015] [Indexed: 01/30/2023]
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27
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Simard I, Luck D, Mottron L, Zeffiro TA, Soulières I. Autistic fluid intelligence: Increased reliance on visual functional connectivity with diminished modulation of coupling by task difficulty. NEUROIMAGE-CLINICAL 2015; 9:467-78. [PMID: 26594629 PMCID: PMC4596928 DOI: 10.1016/j.nicl.2015.09.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Revised: 08/18/2015] [Accepted: 09/09/2015] [Indexed: 11/16/2022]
Abstract
Different test types lead to different intelligence estimates in autism, as illustrated by the fact that autistic individuals obtain higher scores on the Raven's Progressive Matrices (RSPM) test than they do on the Wechsler IQ, in contrast to relatively similar performance on both tests in non-autistic individuals. However, the cerebral processes underlying these differences are not well understood. This study investigated whether activity in the fluid “reasoning” network, which includes frontal, parietal, temporal and occipital regions, is differently modulated by task complexity in autistic and non-autistic individuals during the RSPM. In this purpose, we used fMRI to study autistic and non-autistic participants solving the 60 RSPM problems focussing on regions and networks involved in reasoning complexity. As complexity increased, activity in the left superior occipital gyrus and the left middle occipital gyrus increased for autistic participants, whereas non-autistic participants showed increased activity in the left middle frontal gyrus and bilateral precuneus. Using psychophysiological interaction analyses (PPI), we then verified in which regions did functional connectivity increase as a function of reasoning complexity. PPI analyses revealed greater connectivity in autistic, compared to non-autistic participants, between the left inferior occipital gyrus and areas in the left superior frontal gyrus, right superior parietal lobe, right middle occipital gyrus and right inferior temporal gyrus. We also observed generally less modulation of the reasoning network as complexity increased in autistic participants. These results suggest that autistic individuals, when confronted with increasing task complexity, rely mainly on visuospatial processes when solving more complex matrices. In addition to the now well-established enhanced activity observed in visual areas in a range of tasks, these results suggest that the enhanced reliance on visual perception has a central role in autistic cognition. Reasoning network is less modulated by problem complexity in autism. Autistic individuals rely more extensively on visuospatial processes to solve complex problems. Results support the central role of visual perception in autistic cognition.
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Affiliation(s)
- Isabelle Simard
- Department of Psychology, University of Montreal, Pavillon Marie-Victorin, C.P. 6128, Succursale Centre-ville, Montréal, Québec H3C 3J7, Canada ; Research Center, Institut universitaire en santé mentale de Montréal, 7401, rue Hochelaga, Montréal, Québec H1N 3M5, Canada
| | - David Luck
- Research Center, Institut universitaire en santé mentale de Montréal, 7401, rue Hochelaga, Montréal, Québec H1N 3M5, Canada ; Department of Psychiatry, University of Montreal, Pavillon Roger-Gaudry, Faculté de Medicine, C.P. 6128, Succursale Centre-ville, Montreal, Québec H3C 3J7, Canada
| | - Laurent Mottron
- Research Center, Institut universitaire en santé mentale de Montréal, 7401, rue Hochelaga, Montréal, Québec H1N 3M5, Canada ; Department of Psychiatry, University of Montreal, Pavillon Roger-Gaudry, Faculté de Medicine, C.P. 6128, Succursale Centre-ville, Montreal, Québec H3C 3J7, Canada
| | - Thomas A Zeffiro
- Neural Systems Group, Massachusetts General Hospital, 149 13th St, Psychiatry, Rm 2651, Charlestown, MA 02129, USA
| | - Isabelle Soulières
- Research Center, Institut universitaire en santé mentale de Montréal, 7401, rue Hochelaga, Montréal, Québec H1N 3M5, Canada ; Department of Psychology, University of Quebec in Montreal (UQAM), C.P. 8888, Succ. Centre-Ville, Montreal, Quebec H3C 3P8, Canada
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28
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Mueller BA, Lim KO, Hemmy L, Camchong J. Diffusion MRI and its Role in Neuropsychology. Neuropsychol Rev 2015; 25:250-71. [PMID: 26255305 PMCID: PMC4807614 DOI: 10.1007/s11065-015-9291-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Accepted: 07/21/2015] [Indexed: 12/13/2022]
Abstract
Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain's white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition.
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Kirkovski M, Enticott PG, Maller JJ, Rossell SL, Fitzgerald PB. Diffusion tensor imaging reveals no white matter impairments among adults with autism spectrum disorder. Psychiatry Res 2015; 233:64-72. [PMID: 26032898 DOI: 10.1016/j.pscychresns.2015.05.003] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Revised: 12/22/2014] [Accepted: 05/06/2015] [Indexed: 12/20/2022]
Abstract
Abnormalities within white matter (WM) have been identified in autism spectrum disorder (ASD). Although there is some support for greater neurobiological deficits among females with ASD, there is little research investigating sex differences in WM in ASD. We used diffusion tensor imaging (DTI) to investigate WM aberration in 25 adults with high-functioning ASD and 24 age-, sex- and IQ-matched controls. Tract-based spatial statistics (TBSS) was used to explore differences in WM in major tract bundles. The effects of biological sex were also investigated. TBSS revealed no differences in fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), or axial diffusivity (AD) between groups. There were no effects of biological sex. We consider whether methodological differences between past studies have contributed to the highly heterogeneous findings in the literature. Finally, we suggest that, among a high-functioning sample of adults with ASD, differences in WM microstructure may not be related to clinical impairment.
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Affiliation(s)
- Melissa Kirkovski
- Monash Alfred Psychiatry Research Centre, The Alfred and Central Clinical School, Monash University, Melbourne, Victoria, Australia; Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Victoria, Australia.
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Victoria, Australia; Monash Alfred Psychiatry Research Centre, The Alfred and Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Jerome J Maller
- Monash Alfred Psychiatry Research Centre, The Alfred and Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Susan L Rossell
- Brain and Psychological Science Research Centre, Faculty Health, Arts and Design, Swinburne University, Hawthorn, Victoria, Australia; Monash Alfred Psychiatry Research Centre, The Alfred and Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Paul B Fitzgerald
- Monash Alfred Psychiatry Research Centre, The Alfred and Central Clinical School, Monash University, Melbourne, Victoria, Australia
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Saleh M, Nashaat NH, Fahim C, Ibrahim AS, Meguid N. MRI Surface-Based Brain Morphometry in Egyptian Autistic and Typically Developing Children. Folia Phoniatr Logop 2015; 67:29-35. [PMID: 25967922 DOI: 10.1159/000368962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES The verbal abilities of autistic children differ from those of typically developing ones and they also differ among autistic children themselves. Neuroanatomical changes and an abnormal organization of functional networks are expected to accompany such a neurodevelopmental disorder. The aim of this study was to delineate the brain neuroanatomical changes in Egyptian children with autism and to compare them with previous studies in order to add more insight into the global brain imaging deviations linked to autism. PATIENTS AND METHODS Twenty-five autistic children and 25 typically developing children underwent MRI. Further analysis was performed using surface-based morphometry to obtain cortical thickness, brain volume, and cortical complexity. RESULTS MRI analysis results revealed significantly greater cortical thickness, cortical complexity, and gray matter volume in the autistic as compared to the control group. On the other hand, the white matter volume was significantly smaller. CONCLUSION These findings generally align with findings in previous studies, except for occasional differences.
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Affiliation(s)
- Marwa Saleh
- Unit of Phoniatrics, Department of Otolaryngology, Ain Shams University, Cairo, Egypt
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31
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Cheng I, Miller SP, Duerden EG, Sun K, Chau V, Adams E, Poskitt KJ, Branson HM, Basu A. Stochastic process for white matter injury detection in preterm neonates. NEUROIMAGE-CLINICAL 2015; 7:622-30. [PMID: 25844316 PMCID: PMC4375636 DOI: 10.1016/j.nicl.2015.02.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 02/09/2015] [Accepted: 02/23/2015] [Indexed: 11/30/2022]
Abstract
Preterm births are rising in Canada and worldwide. As clinicians strive to identify preterm neonates at greatest risk of significant developmental or motor problems, accurate predictive tools are required. Infants at highest risk will be able to receive early developmental interventions, and will also enable clinicians to implement and evaluate new methods to improve outcomes. While severe white matter injury (WMI) is associated with adverse developmental outcome, more subtle injuries are difficult to identify and the association with later impairments remains unknown. Thus, our goal was to develop an automated method for detection and visualization of brain abnormalities in MR images acquired in very preterm born neonates. We have developed a technique to detect WMI in T1-weighted images acquired in 177 very preterm born infants (24–32 weeks gestation). Our approach uses a stochastic process that estimates the likelihood of intensity variations in nearby pixels; with small variations being more likely than large variations. We first detect the boundaries between normal and injured regions of the white matter. Following this we use a measure of pixel similarity to identify WMI regions. Our algorithm is able to detect WMI in all of the images in the ground truth dataset with some false positives in situations where the white matter region is not segmented accurately.
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Affiliation(s)
- Irene Cheng
- Department of Computing Science, University of Alberta, Edmonton, AB T6G 2H1, Canada
| | - Steven P Miller
- Hospital for Sick Children and the University of Toronto, Toronto, Canada
| | - Emma G Duerden
- Hospital for Sick Children and the University of Toronto, Toronto, Canada
| | - Kaiyu Sun
- Department of Computing Science, University of Alberta, Edmonton, AB T6G 2H1, Canada
| | - Vann Chau
- Hospital for Sick Children and the University of Toronto, Toronto, Canada
| | - Elysia Adams
- Hospital for Sick Children and the University of Toronto, Toronto, Canada
| | - Kenneth J Poskitt
- BC Children's Hospital and the University of British Columbia, Vancouver, Canada
| | - Helen M Branson
- Hospital for Sick Children and the University of Toronto, Toronto, Canada
| | - Anup Basu
- Department of Computing Science, University of Alberta, Edmonton, AB T6G 2H1, Canada
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Roine U, Salmi J, Roine T, Wendt TNV, Leppämäki S, Rintahaka P, Tani P, Leemans A, Sams M. Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome. Mol Autism 2015; 6:4. [PMID: 25874076 PMCID: PMC4396538 DOI: 10.1186/2040-2392-6-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Accepted: 12/11/2014] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND The aim of this study was to investigate potential differences in neural structure in individuals with Asperger syndrome (AS), high-functioning individuals with autism spectrum disorder (ASD). The main symptoms of AS are severe impairments in social interactions and restricted or repetitive patterns of behaviors, interests or activities. METHODS Diffusion weighted magnetic resonance imaging data were acquired for 14 adult males with AS and 19 age, sex and IQ-matched controls. Voxelwise group differences in fractional anisotropy (FA) were studied with tract-based spatial statistics (TBSS). Based on the results of TBSS, a tract-level comparison was performed with constrained spherical deconvolution (CSD)-based tractography, which is able to detect complex (for example, crossing) fiber configurations. In addition, to investigate the relationship between the microstructural changes and the severity of symptoms, we looked for correlations between FA and the Autism Spectrum Quotient (AQ), Empathy Quotient and Systemizing Quotient. RESULTS TBSS revealed widely distributed local increases in FA bilaterally in individuals with AS, most prominent in the temporal part of the superior longitudinal fasciculus, corticospinal tract, splenium of corpus callosum, anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), posterior thalamic radiation, uncinate fasciculus and inferior longitudinal fasciculus (ILF). CSD-based tractography also showed increases in the FA in multiple tracts. However, only the difference in the left ILF was significant after a Bonferroni correction. These results were not explained by the complexity of microstructural organization, measured using the planar diffusion coefficient. In addition, we found a correlation between AQ and FA in the right IFO in the whole group. CONCLUSIONS Our results suggest that there are local and tract-level abnormalities in white matter (WM) microstructure in our homogenous and carefully characterized group of adults with AS, most prominent in the left ILF.
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Affiliation(s)
- Ulrika Roine
- Brain and Mind Laboratory, Department of Biomedical Engineering and Computational Science, Aalto University, Rakentajanaukio 2 C, FI-02150 Espoo, Finland
| | - Juha Salmi
- Brain and Mind Laboratory, Department of Biomedical Engineering and Computational Science, Aalto University, Rakentajanaukio 2 C, FI-02150 Espoo, Finland
| | - Timo Roine
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Antwerp Belgium
| | - Taina Nieminen-von Wendt
- Neuropsychiatric Rehabilitation and Medical Centre Neuromental, Kaupintie 11 A, FI-00440 Helsinki, Finland
| | - Sami Leppämäki
- Department of Psychiatry, Clinic for Neuropsychiatry, Helsinki University Central Hospital, Tukholmankatu 8 F, FI-00290 Helsinki, Finland ; Finnish Institute of Occupational Health, Topeliuksenkatu 41, FI-00290 Helsinki, Finland
| | - Pertti Rintahaka
- Department of Psychiatry, Clinic for Neuropsychiatry, Helsinki University Central Hospital, Tukholmankatu 8 F, FI-00290 Helsinki, Finland
| | - Pekka Tani
- Department of Psychiatry, Clinic for Neuropsychiatry, Helsinki University Central Hospital, Tukholmankatu 8 F, FI-00290 Helsinki, Finland
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Mikko Sams
- Brain and Mind Laboratory, Department of Biomedical Engineering and Computational Science, Aalto University, Rakentajanaukio 2 C, FI-02150 Espoo, Finland ; Advanced Magnetic Imaging Centre, Aalto University, Otakaari 5, FI-02150 Espoo, Finland
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Ruzich E, Allison C, Smith P, Watson P, Auyeung B, Ring H, Baron-Cohen S. Measuring autistic traits in the general population: a systematic review of the Autism-Spectrum Quotient (AQ) in a nonclinical population sample of 6,900 typical adult males and females. Mol Autism 2015; 6:2. [PMID: 25874074 PMCID: PMC4396128 DOI: 10.1186/2040-2392-6-2] [Citation(s) in RCA: 291] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Accepted: 12/17/2014] [Indexed: 02/06/2023] Open
Abstract
The Autism-Spectrum Quotient (AQ) is a self-report measure of autistic traits. It is frequently cited in diverse fields and has been administered to adults of at least average intelligence with autism and to nonclinical controls, as well as to clinical control groups such as those with schizophrenia, prosopagnosia, anorexia, and depression. However, there has been no empirical systematic review of the AQ since its inception in 2001. The present study reports a comprehensive systematic review of the literature to estimate a reliable mean AQ score in individuals without a diagnosis of an autism spectrum condition (ASC), in order to establish a reference norm for future studies. A systematic search of computerized databases was performed to identify studies that administered the AQ to nonclinical participant samples representing the adult male and female general population. Inclusion was based on a set of formalized criteria that evaluated the quality of the study, the usage of the AQ, and the population being assessed. After selection, 73 articles, detailing 6,934 nonclinical participants, as well as 1,963 matched clinical cases of ASC (from available cohorts within each individual study), were analyzed. Mean AQ score for the nonclinical population was 16.94 (95% CI 11.6, 20.0), while mean AQ score for the clinical population with ASC was found to be 35.19 (95% CI 27.6, 41.1). In addition, in the nonclinical population, a sex difference in autistic traits was found, although no sex difference in AQ score was seen in the clinical ASC population. These findings have implications for the study of autistic traits in the general population. Here, we confirm previous norms with more rigorous data and for the first time establish average AQ scores based on a systematic review, for populations of adult males and females with and without ASC. Finally, we advise future researchers to avoid risk of bias by carefully considering the recruitment strategy for both clinical and nonclinical groups and to demonstrate transparency by reporting recruitment methods for all participants.
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Affiliation(s)
- Emily Ruzich
- />Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, CB2 8AH Cambridge, UK
- />Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH UK
| | - Carrie Allison
- />Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH UK
| | - Paula Smith
- />Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH UK
| | - Peter Watson
- />MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge, CB2 7EF UK
| | - Bonnie Auyeung
- />Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH UK
- />Psychology Department, University of Edinburgh, 3 Charles Street, Edinburgh, EH8 9AD UK
| | - Howard Ring
- />Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, CB2 8AH Cambridge, UK
- />NIHR CLAHRC for the East of England, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH England, UK
- />Cambridgeshire and Peterborough NHS Foundation Trust, Peterborough, CB21 5EF UK
| | - Simon Baron-Cohen
- />Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH UK
- />NIHR CLAHRC for the East of England, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH England, UK
- />CLASS Clinic, Cambridgeshire and Peterborough NHS Foundation Trust, Peterborough, CB21 5EF UK
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Itahashi T, Yamada T, Nakamura M, Watanabe H, Yamagata B, Jimbo D, Shioda S, Kuroda M, Toriizuka K, Kato N, Hashimoto R. Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: a multimodal brain imaging study. NEUROIMAGE-CLINICAL 2014; 7:155-69. [PMID: 25610777 PMCID: PMC4299973 DOI: 10.1016/j.nicl.2014.11.019] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Revised: 11/22/2014] [Accepted: 11/26/2014] [Indexed: 11/17/2022]
Abstract
Growing evidence suggests that a broad range of behavioral anomalies in people with autism spectrum disorder (ASD) can be linked with morphological and functional alterations in the brain. However, the neuroanatomical underpinnings of ASD have been investigated using either structural magnetic resonance imaging (MRI) or diffusion tensor imaging (DTI), and the relationships between abnormalities revealed by these two modalities remain unclear. This study applied a multimodal data-fusion method, known as linked independent component analysis (ICA), to a set of structural MRI and DTI data acquired from 46 adult males with ASD and 46 matched controls in order to elucidate associations between different aspects of atypical neuroanatomy of ASD. Linked ICA identified two composite components that showed significant between-group differences, one of which was significantly correlated with age. In the other component, participants with ASD showed decreased gray matter (GM) volumes in multiple regions, including the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral pre- and post-central gyri. These GM changes were linked with a pattern of decreased fractional anisotropy (FA) in several white matter tracts, such as the bilateral inferior longitudinal fasciculi, bilateral inferior fronto-occipital fasciculi, and bilateral corticospinal tracts. Furthermore, unimodal analysis for DTI data revealed significant reductions of FA along with increased mean diffusivity in those tracts for ASD, providing further evidence of disrupted anatomical connectivity. Taken together, our findings suggest that, in ASD, alterations in different aspects of brain morphology may co-occur in specific brain networks, providing a comprehensive view for understanding the neuroanatomy of this disorder. Structural alterations of gray (GM) and white matter (WM) in ASD were investigated. Linked independent component analysis was used for multimodal data analysis. Alterations of GM and WM in ASD co-occurred in cognitive and affective networks. Results reveal an integrative view of multiple aspects of structural changes in ASD.
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Affiliation(s)
- Takashi Itahashi
- Department of Pharmacognosy and Phytochemistry, Showa University School of Pharmacy, Tokyo, Japan
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Takashi Yamada
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Motoaki Nakamura
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
- Kinko Hospital, Kanagawa Psychiatric Center, Kanagawa, Japan
| | - Hiromi Watanabe
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Bun Yamagata
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Daiki Jimbo
- Department of Anatomy, Showa University School of Medicine, Tokyo, Japan
| | - Seiji Shioda
- Department of Anatomy, Showa University School of Medicine, Tokyo, Japan
| | - Miho Kuroda
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
- Child Mental Health-care Center, Fukushima University, Fukushima, Japan
- Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kazuo Toriizuka
- Department of Pharmacognosy and Phytochemistry, Showa University School of Pharmacy, Tokyo, Japan
| | - Nobumasa Kato
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ryuichiro Hashimoto
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Language Sciences, Graduate School of Humanities, Tokyo Metropolitan University, Tokyo, Japan
- Corresponding author at: Medical Institute of Developmental Disabilities Research, Showa University, 6-11-11, Kita-karasuyama, Setagaya-ku, Tokyo 157-8577, Japan. Tel.: +81 3 5315 9357.
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Perkins TJ, Stokes MA, McGillivray JA, Mussap AJ, Cox IA, Maller JJ, Bittar RG. Increased left hemisphere impairment in high-functioning autism: a tract based spatial statistics study. Psychiatry Res 2014; 224:119-23. [PMID: 25159311 DOI: 10.1016/j.pscychresns.2014.08.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Revised: 06/23/2014] [Accepted: 08/04/2014] [Indexed: 10/24/2022]
Abstract
There is evidence emerging from Diffusion Tensor Imaging (DTI) research that autism spectrum disorders (ASD) are associated with greater impairment in the left hemisphere. Although this has been quantified with volumetric region of interest analyses, it has yet to be tested with white matter integrity analysis. In the present study, tract based spatial statistics was used to contrast white matter integrity of 12 participants with high-functioning autism or Aspergers syndrome (HFA/AS) with 12 typically developing individuals. Fractional Anisotropy (FA) was examined, in addition to axial, radial and mean diffusivity (AD, RD and MD). In the left hemisphere, participants with HFA/AS demonstrated significantly reduced FA in predominantly thalamic and fronto-parietal pathways and increased RD. Symmetry analyses confirmed that in the HFA/AS group, WM disturbance was significantly greater in the left compared to right hemisphere. These findings contribute to a growing body of literature suggestive of reduced FA in ASD, and provide preliminary evidence for RD impairments in the left hemisphere.
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Affiliation(s)
- Thomas John Perkins
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia.
| | - Mark Andrew Stokes
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia
| | - Jane Anne McGillivray
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia
| | - Alexander Julien Mussap
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia
| | - Ivanna Anne Cox
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia
| | - Jerome Joseph Maller
- Monash Alfred Psychiatry Research Centre, The Alfred and Monash University Central Clinical School, Commercial Rd, Melbourne, Victoria, Australia
| | - Richard Garth Bittar
- Cognitive Neuroscience Unit, Department of Psychology, School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Victoria, Australia; Precision Brain Spine and Pain Centre, Australia; Department of Neurosurgery, Royal Melbourne Hospital, Australia
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Ameis SH, Catani M. Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder. Cortex 2014; 62:158-81. [PMID: 25433958 DOI: 10.1016/j.cortex.2014.10.014] [Citation(s) in RCA: 208] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Revised: 10/20/2014] [Accepted: 10/22/2014] [Indexed: 01/01/2023]
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) symptoms have been hypothesized to result from altered brain connectivity. The 'disconnectivity' hypothesis has been used to explain characteristic impairments in socio-emotional function, observed clinically in ASD. Here, we review the evidence for impaired white matter connectivity as a neural substrate for socio-emotional dysfunction in ASD. A review of diffusion tensor imaging (DTI) studies, and focused discussion of relevant post-mortem, structural, and functional neuroimaging studies, is provided. METHODS Studies were identified using a sensitive search strategy in MEDLINE, Embase and PsycINFO article databases using the OvidSP database interface. Search terms included database subject headings for the concepts of pervasive developmental disorders, and DTI. Seventy-two published DTI studies examining white matter microstructure in ASD were reviewed. A comprehensive discussion of DTI studies that examined white matter tracts linking socio-emotional structures is presented. RESULTS Several DTI studies reported microstructural differences indicative of developmental alterations in white matter organization, and potentially myelination, in ASD. Altered structure within long-range white matter tracts linking socio-emotional processing regions was implicated. While alterations of the uncinate fasciculus and frontal and temporal thalamic projections have been associated with social symptoms in ASD, few studies examined association of tract microstructure with core impairment in this disorder. CONCLUSIONS The uncinate fasciculus and frontal and temporal thalamic projections mediate limbic connectivity and integrate structures responsible for complex socio-emotional functioning. Impaired development of limbic connectivity may represent one neural substrate contributing to ASD social impairments. Future efforts to further elucidate the nature of atypical white matter development, and its relationship to core symptoms, may offer new insights into etiological mechanisms contributing to ASD impairments and uncover novel opportunities for targeted intervention.
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Affiliation(s)
- Stephanie H Ameis
- The Hospital for Sick Children, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Child, Youth and Family Program, Research Imaging Centre, The Campbell Family Mental Health Institute, The Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.
| | - Marco Catani
- NATBRAINLAB, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry PO50, King's College London, London, UK.
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Herbet G, Lafargue G, Bonnetblanc F, Moritz-Gasser S, Menjot de Champfleur N, Duffau H. Inferring a dual-stream model of mentalizing from associative white matter fibres disconnection. ACTA ACUST UNITED AC 2014; 137:944-59. [PMID: 24519980 DOI: 10.1093/brain/awt370] [Citation(s) in RCA: 124] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
In the field of cognitive neuroscience, it is increasingly accepted that mentalizing is subserved by a complex frontotemporoparietal cortical network. Some researchers consider that this network can be divided into two distinct but interacting subsystems (the mirror system and the mentalizing system per se), which respectively process low-level, perceptive-based aspects and high-level, inference-based aspects of this sociocognitive function. However, evidence for this type of functional dissociation in a given neuropsychological population is currently lacking and the structural connectivities of the two mentalizing subnetworks have not been established. Here, we studied mentalizing in a large sample of patients (n = 93; 46 females; age range: 18-65 years) who had been resected for diffuse low-grade glioma-a rare tumour that migrates preferentially along associative white matter pathways. This neurological disorder constitutes an ideal pathophysiological model in which to study the functional anatomy of associative pathways. We mapped the location of each patient's resection cavity and residual lesion infiltration onto the Montreal Neurological Institute template brain and then performed multilevel lesion analyses (including conventional voxel-based lesion-symptom mapping and subtraction lesion analyses). Importantly, we estimated each associative pathway's degree of disconnection (i.e. the degree of lesion infiltration) and built specific hypotheses concerning the connective anatomy of the mentalizing subnetworks. As expected, we found that impairments in mentalizing were mainly related to the disruption of right frontoparietal connectivity. More specifically, low-level and high-level mentalizing accuracy were correlated with the degree of disconnection in the arcuate fasciculus and the cingulum, respectively. To the best of our knowledge, our findings constitute the first experimental data on the structural connectivity of the mentalizing network and suggest the existence of a dual-stream hodological system. Our results may lead to a better understanding of disorders that affect social cognition, especially in neuropathological conditions characterized by atypical/aberrant structural connectivity, such as autism spectrum disorders.
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Affiliation(s)
- Guillaume Herbet
- 1 Department of Neurosurgery, Gui de Chauliac hospital, F-34295 Montpellier, France
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