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Cao G, Zhang S, He Z, Wang Z, Guo L, Yan Z, Han J, Jiang X, Zhang T. Gyral peak variations between HCP and CHCP: functional and structural implications. Brain Struct Funct 2025; 230:37. [PMID: 39903275 DOI: 10.1007/s00429-025-02894-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Accepted: 01/11/2025] [Indexed: 02/06/2025]
Abstract
Significant culture and ethnic diversity play an important role in shaping brain structure and function. Many attempts have been undertaken to connect ethnic variations with brain function, which, however, fluctuates over time and is costly, limiting its utility to identify consistent brain markers as well as its application to a broad population. In contrast, brain anatomy is less altered during a short period of time, but it is not fully understood whether it could serve as the ethnicity-sensitive landmark, or its variation is associated with functional one. In this study, We utilized gyral peaks, a set of early cortical folds, as cortical landmarks to explore the role of ethnic factors in brain anatomy and their relationship to brain function. Comparative experiments were conducted using the Human Connectome Project and the Chinese Human Connectome Project. In populations with similar ethnic backgrounds, gyral peak patterns showed greater consistency. For groups with significantly different ethnic backgrounds, we identified both shared peaks and peaks unique to each group. Compared to shared peaks, unique peaks showed significant differences in anatomical and functional network attributes and were spatially associated with working memory networks, which exhibited increased activation in their presence. Gene enrichment analysis provided additional support, suggesting that the unique peaks are associated with genes linked to working memory functions. These findings could provide new knowledge to understanding how ethnic diversity interplay with brain functions and associate with brain shapes.
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Affiliation(s)
- Guannan Cao
- School of Automation, Northwestern Polytechnic University, 127 West Youyi Road, Xi'an, 710072, Shaanxi, China
| | - Songyao Zhang
- Faculty of Medicine, Dalian University of Technology, No. 2 Lingong Road, Dalian, 116081, Liaoning, China
| | - Zhibin He
- School of Automation, Northwestern Polytechnic University, 127 West Youyi Road, Xi'an, 710072, Shaanxi, China
| | - Zifan Wang
- School of Life Sciences and Technology, University of Electronic Science and Technology, 2006 Xiyuan Avenue, Chengdu, 611731, Sichuan, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnic University, 127 West Youyi Road, Xi'an, 710072, Shaanxi, China
| | - Zhiqiang Yan
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710072, Shaanxi, China
| | - Junwei Han
- School of Automation, Northwestern Polytechnic University, 127 West Youyi Road, Xi'an, 710072, Shaanxi, China
| | - Xi Jiang
- School of Life Sciences and Technology, University of Electronic Science and Technology, 2006 Xiyuan Avenue, Chengdu, 611731, Sichuan, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnic University, 127 West Youyi Road, Xi'an, 710072, Shaanxi, China.
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Ma W, Wang F, Yi Y, Huang Y, Li X, Liu Y, Tu Y. Mapping the electric field of high-definition transcranial electrical stimulation across the lifespan. Sci Bull (Beijing) 2024; 69:3876-3888. [PMID: 39424454 DOI: 10.1016/j.scib.2024.10.001] [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: 03/27/2024] [Revised: 07/23/2024] [Accepted: 09/24/2024] [Indexed: 10/21/2024]
Abstract
Transcranial electrical stimulation (tES) is a non-invasive technique widely used in modulating brain activity and behavior, but its effects differ across individuals and are influenced by head anatomy. In this study, we investigated how the electric field (EF) generated by high-definition tES varies across the lifespan among different demographic groups and its relationship with neural responses measured by functional magnetic resonance imaging (fMRI). We employed an MRI-guided finite element method to simulate the EF for the two most common tES montages (i.e., targeting the dorsolateral prefrontal cortex and motor cortex, respectively) in two large cohorts of white and Asian participants aged 12 to 100 years. We found that the EF intensity decreased with age, particularly in individuals under 25 years of age, and was influenced by gender and ethnicity. We identified skull thickness, scalp thickness, and epidural cerebrospinal fluid thickness, as the primary anatomical factors accounting for the inter-individual EF variability. Using a concurrent tES-fMRI approach, we observed a spatial consistency between the simulated EF and the brain activity changes induced by tES in the target region. Finally, we developed an open-source toolbox incorporating age-stratified head models to facilitate efficient EF calculations. These findings characterize and quantify the individual differences in tES-induced EF, offering a reference for implementing personalized neuromodulation strategies.
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Affiliation(s)
- Weiwei Ma
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Feixue Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yangyang Yi
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yu Huang
- Research & Development, Soterix Medical Inc., Woodbridge, NJ 07095, USA
| | - Xinying Li
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ya'ou Liu
- Department of Radiology, Beijing Tiantan Hospital, Beijing 100070, China.
| | - Yiheng Tu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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Chang YL, Cheng WY. Revealing Cultural Dynamics in WAIS-IV Performance: a Comparative Analysis of Age Cohorts in Taiwanese and U.S. Populations. Arch Clin Neuropsychol 2024; 39:1342-1353. [PMID: 39470388 DOI: 10.1093/arclin/acae089] [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: 09/09/2024] [Indexed: 10/30/2024] Open
Abstract
OBJECTIVE This study examined the relationship between culture and cognitive abilities by comparing WAIS-IV subtests, index scores, and Full-Scale Intelligence Quotient (FSIQ) scores across various age groups in the Taiwanese and U.S. populations. METHOD The Taiwanese and U.S. versions of WAIS-IV are comprehensively compared, examining subtest items, psychometrics, and sample characteristics. Scaled scores are compared by extracting raw scores with a scaled score of 10 from each subtest scale in the Taiwanese version and applying U.S. age norms to acquire U.S. scaled scores. RESULTS Despite the mean FSIQ score closely aligning with the U.S. sample, notable discrepancies are evident in the Taiwanese Verbal Comprehension Index (VCI) score, potentially influenced by cultural fairness of the tests. Significant variations are observed among age cohorts in the Taiwanese sample, with younger individuals excelling in Processing Speed Index, Working Memory Index, Perceptual Reasoning Index, and FSIQ, while maintaining comparable VCI scores to their U.S. counterparts. Conversely, older cohorts demonstrate lower performance across various domains, except for visuospatial reasoning and organizational skills, compared to their U.S. counterparts. These subtest variations robustly correlate with educational disparities between the Taiwanese and U.S. samples. CONCLUSIONS Despite the similarity in factor structures between the Taiwanese and U.S. versions of WAIS-IV, this study reveals cultural bias in both verbal and non-verbal subtests. The study highlights the intricate interplay among cognitive processing styles, cultural influences, and educational factors contributing to performance disparities.
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Affiliation(s)
- Yu-Ling Chang
- Department of Psychology, College of Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (R.O.C.)
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, No. 7, Zhongshang S Rd., Taipei 10002, Taiwan (R.O.C.)
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, No.1, Sec.1, Ren-Ai Rd., Taipei 10051, Taiwan (R.O.C.)
- Neurobiology and Cognitive Science Center, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (R.O.C.)
- Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (R.O.C.)
| | - Wen-Yu Cheng
- Private Practice, 588 Bell St. Unit 2904, Seattle, WA 98121, USA
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Brouillard A, Davignon LM, Vachon-Presseau É, Roy M, Marin MF. Starting the pill during adolescence: Age of onset and duration of use influence morphology of the hippocampus and ventromedial prefrontal cortex. Eur J Neurosci 2024; 60:5876-5899. [PMID: 39245916 DOI: 10.1111/ejn.16509] [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: 09/06/2023] [Revised: 07/29/2024] [Accepted: 07/31/2024] [Indexed: 09/10/2024]
Abstract
From adolescence, women become more likely to experience fear dysregulation. Oral contraceptives (OCs) can modulate the brain regions involved in fear processes. OCs are generally used for years and often initiated during adolescence, a sensitive period where certain brain regions involved in the fear circuitry are still undergoing important reorganization. It remains unknown whether OC use during adolescence may induce long-lasting changes in the fear circuitry. This study aimed to examine whether age of onset moderated the relationship between duration of use and fear-related brain structures. We collected structural MRI data in 98 healthy adult women (61 current users, 37 past users) and extracted grey matter volumes (GMV) and cortical thickness (CT) of key regions of the fear circuitry. Non-linear multiple regressions revealed interaction effects between age of onset and quadratic duration of use on GMV of the right hippocampus and right ventromedial prefrontal cortex (vmPFC). Among women who initiated OCs earlier in adolescence, a short duration of use was associated with smaller hippocampal GMV and thicker vmPFC compared to a longer duration of use. For both GMV and CT of the right vmPFC, women with an early OC onset had more grey matter at a short duration of use than those with a later onset. Our results suggest that OC use earlier in adolescence may induce lasting effects on structural correlates of fear learning and its regulation. These findings support further investigation into the timing of OC use to better comprehend how OCs could disrupt normal brain development processes.
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Affiliation(s)
- Alexandra Brouillard
- Department of Psychology, Université du Québec à Montréal, Montreal, QC, Canada
- Research Center of the Institut universitaire en santé mentale de Montréal, Montreal, QC, Canada
| | - Lisa-Marie Davignon
- Department of Psychology, Université du Québec à Montréal, Montreal, QC, Canada
- Research Center of the Institut universitaire en santé mentale de Montréal, Montreal, QC, Canada
| | - Étienne Vachon-Presseau
- Department of Anesthesia, McGill University, Montreal, QC, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, QC, Canada
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, QC, Canada
| | - Mathieu Roy
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, QC, Canada
- Department of Psychology, McGill University, Montreal, QC, Canada
| | - Marie-France Marin
- Department of Psychology, Université du Québec à Montréal, Montreal, QC, Canada
- Research Center of the Institut universitaire en santé mentale de Montréal, Montreal, QC, Canada
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Zhao X, Wang Y, Wu X, Liu S. An MRI Study of Morphology, Asymmetry, and Sex Differences of Inferior Precentral Sulcus. Brain Topogr 2024; 37:748-763. [PMID: 38374489 PMCID: PMC11393153 DOI: 10.1007/s10548-024-01035-5] [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: 08/23/2023] [Accepted: 01/15/2024] [Indexed: 02/21/2024]
Abstract
Numerous studies utilizing magnetic resonance imaging (MRI) have observed sex and interhemispheric disparities in sulcal morphology, which could potentially underpin certain functional disparities in the human brain. Most of the existing research examines the precentral sulcus comprehensively, with a rare focus on its subsections. To explore the morphology, asymmetry, and sex disparities within the inferior precentral sulcus (IPCS), we acquired 3.0T magnetic resonance images from 92 right-handed Chinese adolescents. Brainvisa was used to reconstruct the IPCS structure and calculate its mean depth (MD). Based on the morphological patterns of IPCS, it was categorized into five distinct types. Additionally, we analyzed four different types of spatial relationships between IPCS and inferior frontal sulcus (IFS). There was a statistically significant sex disparity in the MD of IPCS, primarily observed in the right hemisphere. Females exhibited significantly greater asymmetry in the MD of IPCS compared to males. No statistically significant sex or hemispheric variations were identified in sulcal patterns. Our findings expand the comprehension of inconsistencies in sulcal structure, while also delivering an anatomical foundation for the study of related regions' function.
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Affiliation(s)
- Xinran Zhao
- Department of Clinical Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
- Institute for Sectional Anatomy and Digital Human, Department of Anatomy and Neurobiology, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
- Department of Neurology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yu Wang
- Institute for Sectional Anatomy and Digital Human, Department of Anatomy and Neurobiology, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Xiaokang Wu
- Department of Clinical Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
- Institute for Sectional Anatomy and Digital Human, Department of Anatomy and Neurobiology, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Shuwei Liu
- Institute for Sectional Anatomy and Digital Human, Department of Anatomy and Neurobiology, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China.
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Li Y, Zhang W, Wu Y, Yin L, Zhu C, Chen Y, Cetin-Karayumak S, Cho KIK, Zekelman LR, Rushmore J, Rathi Y, Makris N, O'Donnell LJ, Zhang F. A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations. Sci Data 2024; 11:787. [PMID: 39019877 PMCID: PMC11255335 DOI: 10.1038/s41597-024-03624-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 07/08/2024] [Indexed: 07/19/2024] Open
Abstract
The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population WM atlas and the large site-specific variability of dMRI data. This study presents a dMRI tractography atlas, namely the East-West WM Atlas, for concurrent WM mapping between Eastern and Western populations and creates a large, harmonized dMRI dataset (n=306) based on the Human Connectome Project and the Chinese Human Connectome Project. The curated WM atlas, as well as subject-specific data including the harmonized dMRI data, the whole brain tractography data, and parcellated WM fiber tracts and their diffusion measures, are publicly released. This resource is a valuable addition to facilitating the exploration of brain commonalities and differences across diverse cultural backgrounds.
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Affiliation(s)
- Yijie Li
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Ye Wu
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
| | - Li Yin
- West China Hospital of Medical Science, Sichuan University, Chengdu, China
| | - Ce Zhu
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuqian Chen
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | | | - Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Leo R Zekelman
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Jarrett Rushmore
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Nikos Makris
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Lauren J O'Donnell
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | - Fan Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.
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Safari N, Fang H, Veerareddy A, Xu P, Krueger F. The anatomical structure of sex differences in trust propensity: A voxel-based morphometry study. Cortex 2024; 176:260-273. [PMID: 38677959 DOI: 10.1016/j.cortex.2024.02.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 08/14/2023] [Accepted: 02/28/2024] [Indexed: 04/29/2024]
Abstract
Trust is a key component of human relationships. Sex differences in trust behavior have been elucidated by parental investment theory and social role theory, attributing men's higher trust propensity to their increased engagement in physically and socially risky activities aimed at securing additional resources. Although sex differences in trust behavior exist and the neuropsychological signatures of trust are known, the underlying anatomical structure of sex differences is still unexplored. Our study aimed to investigate the anatomical structure of sex differences in trust behavior toward strangers (i.e., trust propensity, TP) by employing voxel-based morphometry (VBM) in a sample of healthy young adults. We collected behavioral data for TP as measured with participants in the role of trustors completing the one-shot trust game (TG) with anonymous partners as trustees. We conducted primary region of interest (ROI) and exploratory whole-brain (WB) VBM analyses of high-resolution structural images to test for the association between TP and regional gray matter volume (GMV) associated with sex differences. Confirming previous studies, our behavioral results demonstrated that men trusted more than women during the one-shot TG. Our WB analysis showed a greater GMV related to TP in men than women in the precuneus (PreC), whereas our ROI analysis in regions of the default-mode network (dorsomedial prefrontal cortex [dmPFC], PreC, superior temporal gyrus) to simulate the partner's trustworthiness, central-executive network (ventrolateral PFC) to implement a calculus-based trust strategy, and action-perception network (precentral gyrus) to performance cost-benefit calculations, as proposed by a neuropsychoeconomic model of trust. Our findings advance the neuropsychological understanding of sex differences in TP, which has implications for interpersonal partnerships, financial transactions, and societal engagements.
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Affiliation(s)
- Nooshin Safari
- School of Systems Biology, George Mason University, Fairfax, VA, USA
| | - Huihua Fang
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging, China; Department of Psychology, University of Mannheim, Mannheim, Germany
| | | | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China; Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China.
| | - Frank Krueger
- School of Systems Biology, George Mason University, Fairfax, VA, USA; Department of Psychology, University of Mannheim, Mannheim, Germany
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Lee W, Lee S, Park Y, Kim GE, Bae JB, Han JW, Kim KW. Construction and validation of a brain magnetic resonance imaging template for normal older Koreans. BMC Neurol 2024; 24:222. [PMID: 38943101 PMCID: PMC11212263 DOI: 10.1186/s12883-024-03735-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 06/17/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND Spatial normalization to a standardized brain template is a crucial step in magnetic resonance imaging (MRI) studies. Brain templates made from sufficient sample size have low brain variability, improving the accuracy of spatial normalization. Using population-specific template improves accuracy of spatial normalization because brain morphology varies according to ethnicity and age. METHODS We constructed a brain template of normal Korean elderly (KNE200) using MRI scans 100 male and 100 female aged over 60 years old with normal cognition. We compared the deformation after spatial normalization of the KNE200 template to that of the KNE96, constructed from 96 cognitively normal elderly Koreans and to that of the brain template (OCF), constructed from 434 non-demented older Caucasians to examine the effect of sample size and ethnicity on the accuracy of brain template, respectively. We spatially normalized the MRI scans of elderly Koreans and quantified the amount of deformations associated with spatial normalization using the magnitude of displacement and volumetric changes of voxels. RESULTS The KNE200 yielded significantly less displacement and volumetric change in the parahippocampal gyrus, medial and posterior orbital gyrus, fusiform gyrus, gyrus rectus, cerebellum and vermis than the KNE96. The KNE200 also yielded much less displacement in the cerebellum, vermis, hippocampus, parahippocampal gyrus and thalamus and much less volumetric change in the cerebellum, vermis, hippocampus and parahippocampal gyrus than the OCF. CONCLUSION KNE200 had the better accuracy than the KNE96 due to the larger sample size and was far accurate than the template constructed from elderly Caucasians in elderly Koreans.
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Grants
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
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Affiliation(s)
- Wheesung Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Subin Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Yeseung Park
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Grace Eun Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Jong Bin Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ki Woong Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea.
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Koppelmans V, Ruitenberg MF, Schaefer SY, King JB, Jacobo JM, Silvester BP, Mejia AF, van der Geest J, Hoffman JM, Tasdizen T, Duff K. Classification of Mild Cognitive Impairment and Alzheimer's Disease Using Manual Motor Measures. NEURODEGENER DIS 2024; 24:54-70. [PMID: 38865972 PMCID: PMC11381162 DOI: 10.1159/000539800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/09/2024] [Indexed: 06/14/2024] Open
Abstract
INTRODUCTION Manual motor problems have been reported in mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the specific aspects that are affected, their neuropathology, and potential value for classification modeling is unknown. The current study examined if multiple measures of motor strength, dexterity, and speed are affected in MCI and AD, related to AD biomarkers, and are able to classify MCI or AD. METHODS Fifty-three cognitively normal (CN), 33 amnestic MCI, and 28 AD subjects completed five manual motor measures: grip force, Trail Making Test A, spiral tracing, finger tapping, and a simulated feeding task. Analyses included (1) group differences in manual performance; (2) associations between manual function and AD biomarkers (PET amyloid β, hippocampal volume, and APOE ε4 alleles); and (3) group classification accuracy of manual motor function using machine learning. RESULTS Amnestic MCI and AD subjects exhibited slower psychomotor speed and AD subjects had weaker dominant hand grip strength than CN subjects. Performance on these measures was related to amyloid β deposition (both) and hippocampal volume (psychomotor speed only). Support vector classification well-discriminated control and AD subjects (area under the curve of 0.73 and 0.77, respectively) but poorly discriminated MCI from controls or AD. CONCLUSION Grip strength and spiral tracing appear preserved, while psychomotor speed is affected in amnestic MCI and AD. The association of motor performance with amyloid β deposition and atrophy could indicate that this is due to amyloid deposition in and atrophy of motor brain regions, which generally occurs later in the disease process. The promising discriminatory abilities of manual motor measures for AD emphasize their value alongside other cognitive and motor assessment outcomes in classification and prediction models, as well as potential enrichment of outcome variables in AD clinical trials.
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Affiliation(s)
- Vincent Koppelmans
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, UT, USA
| | - Marit F.L. Ruitenberg
- Department of Health, Medical and Neuropsychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Sydney Y. Schaefer
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Jasmine M. Jacobo
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, UT, USA
| | - Benjamin P. Silvester
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, UT, USA
| | - Amanda F. Mejia
- Department of Statistics, University of Indiana, Bloomington, IN, USA
| | | | - John M. Hoffman
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Tolga Tasdizen
- Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
| | - Kevin Duff
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
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Vallejo-Azar MN, Arenaza B, Elizalde Acevedo B, Alba-Ferrara L, Samengo I, Bendersky M, Gonzalez PN. Hemispheric asymmetries in cortical grey matter of gyri and sulci in modern human populations from South America. J Anat 2024; 244:815-830. [PMID: 38183319 PMCID: PMC11021627 DOI: 10.1111/joa.14001] [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: 09/16/2021] [Revised: 12/18/2023] [Accepted: 12/18/2023] [Indexed: 01/08/2024] Open
Abstract
Structural asymmetries of brain regions associated with lateralised functions have been extensively studied. However, there are fewer morphometric analyses of asymmetries of the gyri and sulci of the entire cortex. The current study assessed cortical asymmetries in a sample of healthy adults (N = 175) from an admixed population from South America. Grey matter volume and surface area of 66 gyri and sulci were quantified on T1 magnetic resonance images. The departure from zero of the differences between left and right hemispheres (L-R), a measure of directional asymmetry (DA), the variance of L-R, and an index of fluctuating asymmetry (FA) were evaluated for each region. Significant departures from perfect symmetry were found for most cortical gyri and sulci. Regions showed leftward asymmetry at the population level in the frontal lobe and superior lateral parts of the parietal lobe. Rightward asymmetry was found in the inferior parietal, occipital, frontopolar, and orbital regions, and the cingulate (anterior, middle, and posterior-ventral). Despite this general pattern, several sulci showed the opposite DA compared to the neighbouring gyri, which remarks the need to consider the neurobiological differences in gyral and sulcal development in the study of structural asymmetries. The results also confirm the absence of DA in most parts of the inferior frontal gyrus and the precentral region. This study contributes with data on populations underrepresented in the databases used in neurosciences. Among its findings, there is agreement with previous results obtained in populations of different ancestry and some discrepancies in the middle frontal and medial parietal regions. A significant DA not reported previously was found for the volume of long and short insular gyri and the central sulcus of the insula, frontomarginal, transverse frontopolar, paracentral, and middle and posterior parts of the cingulate gyrus and sulcus, gyrus rectus, occipital pole, and olfactory sulcus, as well as for the volume and area of the transverse collateral sulcus and suborbital sulcus. Also, several parcels displayed significant variability in the left-right differences, which can be partially attributable to developmental instability, a source of FA. Moreover, a few gyri and sulci displayed ideal FA with non-significant departures from perfect symmetry, such as subcentral and posterior cingulate gyri and sulci, inferior frontal and fusiform gyri, and the calcarine, transverse collateral, precentral, and orbital sulci. Overall, these results show that asymmetries are ubiquitous in the cerebral cortex.
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Affiliation(s)
- Mariana N Vallejo-Azar
- Estudios en Neurociencias y Sistemas Complejos, ENyS (CONICET, Universidad Nacional Arturo Jauretche, Hospital El Cruce), Florencio Varela, Argentina
| | - Bautista Arenaza
- Department of Medical Physics and Instituto Balseiro, Centro Atómico Bariloche, CONICET, Bariloche, Argentina
| | - Bautista Elizalde Acevedo
- Estudios en Neurociencias y Sistemas Complejos, ENyS (CONICET, Universidad Nacional Arturo Jauretche, Hospital El Cruce), Florencio Varela, Argentina
- Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET-Universidad Austral, Bariloche, Argentina
| | - Lucía Alba-Ferrara
- Estudios en Neurociencias y Sistemas Complejos, ENyS (CONICET, Universidad Nacional Arturo Jauretche, Hospital El Cruce), Florencio Varela, Argentina
| | - Inés Samengo
- Department of Medical Physics and Instituto Balseiro, Centro Atómico Bariloche, CONICET, Bariloche, Argentina
| | - Mariana Bendersky
- Estudios en Neurociencias y Sistemas Complejos, ENyS (CONICET, Universidad Nacional Arturo Jauretche, Hospital El Cruce), Florencio Varela, Argentina
- Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Paula N Gonzalez
- Estudios en Neurociencias y Sistemas Complejos, ENyS (CONICET, Universidad Nacional Arturo Jauretche, Hospital El Cruce), Florencio Varela, Argentina
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11
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Du F, Zheng S, Shao K, Yang Y, Chen W, Bai X, Hua Y. Specific-CT brain template construction and retrospective dosimetric comparison study in brain for nasopharyngeal carcinoma patients treated with IMRT or VMAT. Am J Cancer Res 2024; 14:1662-1674. [PMID: 38726278 PMCID: PMC11076250 DOI: 10.62347/hacn9549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 03/12/2024] [Indexed: 05/12/2024] Open
Abstract
The current Radiotherapy (RT) technology still inevitably irradiated normal brain tissue, causing implicit radiation-induced injury. This study investigates the precise localization and the corresponding radiation dosage of brain regions susceptible to damage in nasopharyngeal carcinoma (NPC) patients following RT. Utilizing the Advanced Normalization Tools (ANTs) package, a computed tomography (CT) brain template was created in the standard Montreal Neurological Institute (MNI) space, based on 803 Chinese NPC patients (T0~T4) who underwent RT. With this template, all patients' CT and RTdose data were registered to the MNI space, and the RTdose distribution characteristics in normal brain tissues were compared for NPC patients treated with Intensity-modulated radiotherapy (IMRT) or Volumetric Modulated Arc Therapy (VMAT), with patients' age and gender as covariates. Analysis of the average dosages indicated that certain areas within the Limbic, Temporal, and Posterior Lobes, the Brainstem, and the Cerebellum Posterior Lobe were exposed to doses exceeding 50 Gy. Inter-group analysis revealed that IMRT delivered higher doses than VMAT to brain regions anterior to the nasopharyngeal tumor, whereas VMAT affected the posterior regions more. Interestingly, VMAT showed a drawback in preserving the normal brain tissues for T4-stage patients. This revealed that the two treatment modalities have unique characteristics in preserving normal brain tissue, each with advantages. With better localization precision, the created CT brain template in MNI space may be beneficial for NPC patients' toxicity and dosimetric analyses.
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Affiliation(s)
- Fenglei Du
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
| | - Shuang Zheng
- School of Media and Design, Hangzhou Dianzi UniversityHangzhou 310018, Zhejiang, China
| | - Kainan Shao
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
- Department of Radiation Oncology, Zhejiang Provincial People’s HospitalHangzhou 314408, Zhejiang, China
| | - Yiwei Yang
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
| | - Wei Chen
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
- School of Nuclear Science and Technology, University of South ChinaHengyang 421001, Hunan, China
| | - Xue Bai
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
| | - Yonghong Hua
- Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesHangzhou 310022, Zhejiang, China
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12
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Geng X, Chan PH, Lam HS, Chu WC, Wong PC. Brain templates for Chinese babies from newborn to three months of age. Neuroimage 2024; 289:120536. [PMID: 38346529 DOI: 10.1016/j.neuroimage.2024.120536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/20/2024] [Accepted: 02/08/2024] [Indexed: 02/22/2024] Open
Abstract
The infant brain develops rapidly and this area of research has great clinical implications. Neurodevelopmental disorders such as autism and developmental delay have their origins, potentially, in abnormal early brain maturation. Searching for potential early neural markers requires a priori knowledge about infant brain development and anatomy. One of the most common methods of characterizing brain features requires normalization of individual images into a standard stereotactic space and conduct of group-based analyses in this space. A population representative brain template is critical for these population-based studies. Little research is available on constructing brain templates for typical developing Chinese infants. In the present work, a total of 120 babies from 5 to 89 days of age were included with high resolution structural magnetic resonance imaging scans. T1-weighted and T2-weighted templates were constructed using an unbiased registration approach for babies from newborn to 3 months of age. Age-specific templates were also estimated for babies aged at 0, 1, 2 and 3 months old. Then we conducted a series of evaluations and statistical analyses over whole tissue segmentations and brain parcellations. Compared to the use of population mismatched templates, using our established templates resulted in lower deformation energy to transform individual images into the template space and produced a smaller registration error, i.e., smaller standard deviation of the registered images. Significant volumetric growth was observed across total brain tissues and most of the brain regions within the first three months of age. The total brain tissues exhibited larger volumes in baby boys compared to baby girls. To the best of our knowledge, this is the first study focusing on the construction of Chinese infant brain templates. These templates can be used for investigating birth related conditions such as preterm birth, detecting neural biomarkers for neurological and neurodevelopmental disorders in Chinese populations, and exploring genetic and cultural effects on the brain.
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Affiliation(s)
- Xiujuan Geng
- Brain and Mind Institute The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Peggy Hy Chan
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Hugh Simon Lam
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Winnie Cw Chu
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China.
| | - Patrick Cm Wong
- Brain and Mind Institute The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China.
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13
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Barber N, Valoumas I, Leger KR, Chang YL, Huang CM, Goh JOS, Gutchess A. Culture, prefrontal volume, and memory. PLoS One 2024; 19:e0298235. [PMID: 38551909 PMCID: PMC10980194 DOI: 10.1371/journal.pone.0298235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 01/19/2024] [Indexed: 04/01/2024] Open
Abstract
Prior cross-cultural studies have demonstrated differences among Eastern and Western cultures in memory and cognition along with variation in neuroanatomy and functional engagement. We further probed cultural neuroanatomical variability in terms of its relationship with memory performance. Specifically, we investigated how memory performance related to gray matter volume in several prefrontal lobe structures, including across cultures. For 58 American and 57 Taiwanese young adults, memory performance was measured with the California Verbal Learning Test (CVLT) using performance on learning trial 1, on which Americans had higher scores than the Taiwanese, and the long delayed free recall task, on which groups performed similarly. MRI data were reconstructed using FreeSurfer. Across both cultures, we observed that larger volumes of the bilateral rostral anterior cingulate were associated with lower scores on both CVLT tasks. In terms of effects of culture, the relationship between learning trial 1 scores and gray matter volumes in the right superior frontal gyrus had a trend for a positive relationship in Taiwanese but not in Americans. In addition to the a priori analysis of select frontal volumes, an exploratory whole-brain analysis compared volumes-without considering CVLT performance-across the two cultural groups in order to assess convergence with prior research. Several cultural differences were found, such that Americans had larger volumes in the bilateral superior frontal and lateral occipital cortex, whereas Taiwanese had larger volumes in the bilateral rostral middle frontal and inferior temporal cortex, and the right precuneus.
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Affiliation(s)
- Nicolette Barber
- Department of Psychology, Brandeis University, Waltham, MA, United States of America
| | - Ioannis Valoumas
- Department of Psychology, Brandeis University, Waltham, MA, United States of America
| | - Krystal R. Leger
- Department of Psychology, Brandeis University, Waltham, MA, United States of America
| | - Yu-Ling Chang
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
- Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, Taiwan
- Volen National Center for Complex Systems, Brandeis University, Waltham, MA, United States of America
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Joshua Oon Soo Goh
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
- Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, Taiwan
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Angela Gutchess
- Department of Psychology, Brandeis University, Waltham, MA, United States of America
- Volen National Center for Complex Systems, Brandeis University, Waltham, MA, United States of America
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14
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Wu Y, Chen Y, Yang Y, Lin C, Su S, Zhao J, Wu S, Wu G, Liu H, Liu X, Yang Z, Zhang J, Huang B. Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population. Cereb Cortex 2024; 34:bhae030. [PMID: 38342684 DOI: 10.1093/cercor/bhae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 02/13/2024] Open
Abstract
As a biomarker of human brain health during development, brain age is estimated based on subtle differences in brain structure from those under typical developmental. Magnetic resonance imaging (MRI) is a routine diagnostic method in neuroimaging. Brain age prediction based on MRI has been widely studied. However, few studies based on Chinese population have been reported. This study aimed to construct a brain age predictive model for the Chinese population across its lifespan. We developed a partition prediction method based on transfer learning and atlas attention enhancement. The participants were separated into four age groups, and a deep learning model was trained for each group to identify the brain regions most critical for brain age prediction. The Atlas attention-enhancement method was also used to help the models focus only on critical brain regions. The proposed method was validated using 354 participants from domestic datasets. For prediction performance in the testing sets, the mean absolute error was 2.218 ± 1.801 years, and the Pearson correlation coefficient (r) was 0.969, exceeding previous results for wide-range brain age prediction. In conclusion, the proposed method could provide brain age estimation to assist in assessing the status of brain health.
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Affiliation(s)
- Yingtong Wu
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Paul C Lauterbur Research Center for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, Guangdong Province, China
| | - Yingqian Chen
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Yang Yang
- Department of Radiology, Suining Central Hospital, 127 Desheng West Road, Suining 629099, Sichuan Province, China
- Medical Imaging Center of Guizhou Province, Department of Radiology, The Affiliated Hospital of Zunyi Medical University, 149 Dalian Road, Zunyi 563000, Guizhou Province, China
| | - Chuxuan Lin
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Shu Su
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Jing Zhao
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Songxiong Wu
- Radiology Department, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Guangyao Wu
- Radiology Department, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Heng Liu
- Medical Imaging Center of Guizhou Province, Department of Radiology, The Affiliated Hospital of Zunyi Medical University, 149 Dalian Road, Zunyi 563000, Guizhou Province, China
| | - Xia Liu
- Department of Radiology, Shenzhen Mental Health Center, Shenzhen Kangning Hospital, 1080 Cuizhu Road, Shenzhen 518118, Guangdong Province, China
| | - Zhiyun Yang
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Jian Zhang
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, 1068 Xueyuan Avenue, Shenzhen 518055, Guangdong Province, China
- School of Pharmaceutical Sciences, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
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15
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Choi YY, Lee JJ, Te Nijenhuis J, Choi KY, Park J, Ok J, Choo IH, Kim H, Song MK, Choi SM, Cho SH, Choe Y, Kim BC, Lee KH. Multi-Ethnic Norms for Volumes of Subcortical and Lobar Brain Structures Measured by Neuro I: Ethnicity May Improve the Diagnosis of Alzheimer's Disease1. J Alzheimers Dis 2024; 99:223-240. [PMID: 38640153 DOI: 10.3233/jad-231182] [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] [Indexed: 04/21/2024]
Abstract
Background We previously demonstrated the validity of a regression model that included ethnicity as a novel predictor for predicting normative brain volumes in old age. The model was optimized using brain volumes measured with a standard tool FreeSurfer. Objective Here we further verified the prediction model using newly estimated brain volumes from Neuro I, a quantitative brain analysis system developed for Korean populations. Methods Lobar and subcortical volumes were estimated from MRI images of 1,629 normal Korean and 786 Caucasian subjects (age range 59-89) and were predicted in linear regression from ethnicity, age, sex, intracranial volume, magnetic field strength, and scanner manufacturers. Results In the regression model predicting the new volumes, ethnicity was again a substantial predictor in most regions. Additionally, the model-based z-scores of regions were calculated for 428 AD patients and the matched controls, and then employed for diagnostic classification. When the AD classifier adopted the z-scores adjusted for ethnicity, the diagnostic accuracy has noticeably improved (AUC = 0.85, ΔAUC = + 0.04, D = 4.10, p < 0.001). Conclusions Our results suggest that the prediction model remains robust across different measurement tool, and ethnicity significantly contributes to the establishment of norms for brain volumes and the development of a diagnostic system for neurodegenerative diseases.
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Affiliation(s)
- Yu Yong Choi
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Jang Jae Lee
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Jan Te Nijenhuis
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | | | | | - Il Han Choo
- Department of Neuropsychiatry, Chosun University School of Medicine and Hospital, Gwangju, Republic of Korea
| | - Hoowon Kim
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Neurology, Chosun University School of Medicine and Hospital, Gwangju, Republic of Korea
| | - Min-Kyung Song
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Seong-Min Choi
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
- Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Soo Hyun Cho
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
- Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Youngshik Choe
- Korea Brain Research Institute, Daegu, Republic of Korea
| | - Byeong C Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
- Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Neurozen Inc., Seoul, Republic of Korea
- Korea Brain Research Institute, Daegu, Republic of Korea
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
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16
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Xie JQ, Tian Y, Hu J, Yin MZ, Sun YD, Shan YJ, Chen K, Feng G, Qiu J. The neural correlates of value hierarchies: a prospective typology based on personal value profiles of emerging adults. Front Psychol 2023; 14:1224911. [PMID: 38164257 PMCID: PMC10758175 DOI: 10.3389/fpsyg.2023.1224911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 11/28/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Value hierarchies, as motivational goals anchored in the self-schema, may be correlated with spontaneous activity in the resting brain, especially those involving self-relevance. This study aims to investigate the neural correlates of value hierarchies from the perspective of typology. Methods A total of 610 Chinese college students (30.31% women), aged 18 to 23, completed the personal values questionnaire and underwent resting-state functional magnetic resonance imaging. Results The latent profile analysis revealed three personal value profiles: traditional social orientation, modernized orientation, and undifferentiated orientation. Neuroimaging results revealed that individuals with modernized orientation prioritized openness to change value, and this personal-focus is related to the higher low-frequency amplitude of the posterior insula; individuals with traditional social orientation prioritized self-transcendence and conservation values, and this social-focus is related to the stronger functional connectivity of the middle insula with the inferior temporal gyrus, temporal gyrus, posterior occipital cortex, and basal ganglia, as well as weaker functional connections within the right middle insula. Discussion Taken together, these findings potentially indicate the intra-generational differentiation of contemporary Chinese emerging adults' value hierarchies. At the neural level, these are correlated with brain activities involved in processing self- and other-relevance.
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Affiliation(s)
- Jia-Qiong Xie
- Faculty of Social Sciences, Chongqing University, Chongqing, China
| | - Yun Tian
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - Jia Hu
- Institute for Advanced Studies in Humanities and Social Sciences, Chongqing University, Chongqing, China
| | - Ming-Ze Yin
- Faculty of Education, Southwest University, Chongqing, China
- Office of Social Sciences, Chongqing University, Chongqing, China
| | - Ya-Dong Sun
- Faculty of Social Sciences, Chongqing University, Chongqing, China
| | - Yan-Jie Shan
- Faculty of Social Sciences, Chongqing University, Chongqing, China
| | - Ke Chen
- Faculty of Social Sciences, Chongqing University, Chongqing, China
| | - Gang Feng
- School of Marxism, Beijing Normal University, Beijing, China
| | - Jiang Qiu
- Faculty of Psychology, Southwest University, Chongqing, China
- Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality at Beijing Normal University, Beijing, China
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17
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Dempsey DA, Deardorff R, Wu YC, Yu M, Apostolova LG, Brosch J, Clark DG, Farlow MR, Gao S, Wang S, Saykin AJ, Risacher SL. BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.05.23299222. [PMID: 38106123 PMCID: PMC10723496 DOI: 10.1101/2023.12.05.23299222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The BrainAGE method is used to estimate biological brain age using structural neuroimaging. However, the stability of the model across different scan parameters and races/ethnicities has not been thoroughly investigated. Estimated brain age was compared within- and across- MRI field strength and across voxel sizes. Estimated brain age gap (BAG) was compared across demographically matched groups of different self-reported races and ethnicities in ADNI and IMAS cohorts. Longitudinal ComBat was used to correct for potential scanner effects. The brain age method was stable within field strength, but less stable across different field strengths. The method was stable across voxel sizes. There was a significant difference in BAG between races, but not ethnicities. Correction procedures are suggested to eliminate variation across scanner field strength while maintaining accurate brain age estimation. Further studies are warranted to determine the factors contributing to racial differences in BAG.
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Affiliation(s)
- Desarae A. Dempsey
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Rachael Deardorff
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Meichen Yu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Liana G. Apostolova
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Jared Brosch
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - David G. Clark
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Martin R. Farlow
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Sujuan Gao
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Sophia Wang
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
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18
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Veerareddy A, Fang H, Safari N, Xu P, Krueger F. Cognitive empathy mediates the relationship between gray matter volume size of dorsomedial prefrontal cortex and social network size: A voxel-based morphometry study. Cortex 2023; 169:279-289. [PMID: 37972460 DOI: 10.1016/j.cortex.2023.09.015] [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: 11/25/2022] [Revised: 07/19/2023] [Accepted: 09/26/2023] [Indexed: 11/19/2023]
Abstract
Social networks are an important factor in developing and maintaining social relationships. The social brain network comprises brain regions that differ in terms of their location, structure, and functioning, and these differences tend to vary among individuals with different social network sizes. However, it remains unknown how social cognitive abilities such as empathy can affect social network size. The goal of our study was to examine the relationship between brain regions in the social brain network, empathy, and individual social network size by using the Social Network Index, which measures social network diversity, size, and complexity by assessing 12 different types of relationships. We performed voxel-based morphometry and mediation analyses using data from questionnaires and structural magnetic resonance imaging data in a sample of 204 young adults. Our findings showed that the gray matter volume of the dorsomedial prefrontal cortex (dmPFC) was inversely associated with social network size and cognitive empathy mediated this association, suggesting that decreased gray matter volume in the dmPFC is associated with greater utilization of cognitive empathy, which, in turn, seems to increase social network size. A potential mechanism explaining this inverse relationship could be cognitive pruning, a phenomenon that occurs in the brain between early adolescence and adulthood, but future longitudinal studies are needed. In conclusion, our findings provide information about the neurocognitive mechanisms involved in the formation and maintenance of social networks.
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Affiliation(s)
| | - Huihua Fang
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China; Department of Psychology, University of Mannheim, Mannheim, Germany
| | - Nooshin Safari
- School of Systems Biology, George Mason University, Fairfax, VA, USA
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China; Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China.
| | - Frank Krueger
- School of Systems Biology, George Mason University, Fairfax, VA, USA; Department of Psychology, University of Mannheim, Mannheim, Germany
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19
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Panta OB, Gurung B, Giri SR, Adhikari A, Ghimire RK. Mean Intracranial Volume of Brain among Patients with Normal Magnetic Resonance Imaging Referred to the Department of Radiology and Imaging of a Tertiary Care Centre. JNMA J Nepal Med Assoc 2023; 61:934-937. [PMID: 38289763 PMCID: PMC10792718 DOI: 10.31729/jnma.8357] [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: 11/29/2023] [Indexed: 02/01/2024] Open
Abstract
Introduction The measurement of brain volume is an important aspect of the assessment of brain structure and function. However, limited data is available on brain volumetry in the Nepalese population. The study aimed to find the mean intracranial volume of the brain among patients with normal magnetic resonance imaging referred to the Department of Radiology and Imaging of a tertiary care centre. Methods A descriptive cross-sectional study was conducted among patients with normal magnetic resonance imaging referred to the Department of Radiology and Imaging in a tertiary care centre. All magnetic resonance imaging of the brain during the study period was reviewed by a radiologist. Magnetic resonance imaging with abnormal findings, clinical signs of neurological deficit, dementia and psychiatric symptoms were excluded from the study. A convenience sampling method was used. The point estimate was calculated at a 95% Confidence Interval. Results Among 285 Magnetic Resonance Imaging datasets, the mean intracranial volume was 1286.30±129.88 cc (1271.22-1301.38, 95% of Confidence Interval). The mean cerebral volume was 985.06±106.4 cc, cerebellar volume was 126.99±13.05 cc and brain stem volume was 19.97±2.54 cc. Conclusions The mean intracranial volume of the brain among patients with normal magnetic resonance imaging was found to be lower than other studies done in similar settings. Keywords brainstem; cerebellum; cerebrum; magnetic resonance imaging.
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Affiliation(s)
- Om Biju Panta
- Department of Radiology and Imaging, Nepal Mediciti Hospital, Bhaisepati, Lalitpur, Nepal
| | - Bibek Gurung
- Department of Radiology and Imaging, Nepal Mediciti Hospital, Bhaisepati, Lalitpur, Nepal
| | - Shahjan Raj Giri
- Department of Radiology and Imaging, Nepal Mediciti Hospital, Bhaisepati, Lalitpur, Nepal
| | - Abhishek Adhikari
- Department of Radiology and Imaging, Nepal Mediciti Hospital, Bhaisepati, Lalitpur, Nepal
| | - Ram Kumar Ghimire
- Department of Radiology and Imaging, Nepal Mediciti Hospital, Bhaisepati, Lalitpur, Nepal
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20
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Kim HB, Kim SH, Um YH, Wang SM, Kim REY, Choe YS, Lee J, Kim D, Lim HK, Lee CU, Kang DW. Modulation of associations between education years and cortical volume in Alzheimer's disease vulnerable brain regions by Aβ deposition and APOE ε4 carrier status in cognitively normal older adults. Front Aging Neurosci 2023; 15:1248531. [PMID: 37829142 PMCID: PMC10565031 DOI: 10.3389/fnagi.2023.1248531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/05/2023] [Indexed: 10/14/2023] Open
Abstract
Background Education years, as a measure of cognitive reserve, have been shown to affect the progression of Alzheimer's disease (AD), both pathologically and clinically. However, inconsistent results have been reported regarding the association between years of education and intermediate structural changes in AD-vulnerable brain regions, particularly when AD risk factors were not considered during the preclinical phase. Objective This study aimed to examine how Aβ deposition and APOE ε4 carrier status moderate the relationship between years of education and cortical volume in AD-vulnerable regions among cognitively normal older adults. Methods A total of 121 participants underwent structural MRI, [18F] flutemetamol PET-CT imaging, and neuropsychological battery assessment. Multiple regression analysis was conducted to examine the interaction between years of education and the effects of potential modifiers on cortical volume. The associations between cortical volume and neuropsychological performance were further explored in subgroups categorized based on AD risk factors. Results The cortical volume of the left lateral occipital cortex and bilateral fusiform gyrus demonstrated a significant differential association with years of education, depending on the presence of Aβ deposition and APOE ε4 carrier status. Furthermore, a significant relationship between the cortical volume of the bilateral fusiform gyrus and AD-nonspecific cognitive function was predominantly observed in individuals without AD risk factors. Conclusion AD risk factors exerted varying influences on the association between years of education and cortical volume during the preclinical phase. Further investigations into the long-term implications of these findings would enhance our understanding of cognitive reserves in the preclinical stages of AD.
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Affiliation(s)
- Hak-Bin Kim
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung-Hwan Kim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | - Yeong Sim Choe
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Jiyeon Lee
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Donghyeon Kim
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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21
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Shen Y, Cai H, Mo F, Yao S, Yu Y, Zhu J. Functional connectivity gradients of the cingulate cortex. Commun Biol 2023; 6:650. [PMID: 37337086 PMCID: PMC10279697 DOI: 10.1038/s42003-023-05029-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/08/2023] [Indexed: 06/21/2023] Open
Abstract
Heterogeneity of the cingulate cortex is evident in multiple dimensions including anatomy, function, connectivity, and involvement in networks and diseases. Using the recently developed functional connectivity gradient approach and resting-state functional MRI data, we found three functional connectivity gradients that captured distinct dimensions of cingulate hierarchical organization. The principal gradient exhibited a radiating organization with transitions from the middle toward both anterior and posterior parts of the cingulate cortex and was related to canonical functional networks and corresponding behavioral domains. The second gradient showed an anterior-posterior axis across the cingulate cortex and had prominent geometric distance dependence. The third gradient displayed a marked differentiation of subgenual and caudal middle with other parts of the cingulate cortex and was associated with cortical morphology. Aside from providing an updated framework for understanding the multifaceted nature of cingulate heterogeneity, the observed hierarchical organization of the cingulate cortex may constitute a novel research agenda with potential applications in basic and clinical neuroscience.
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Affiliation(s)
- Yuhao Shen
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Fan Mo
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Shanwen Yao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China.
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China.
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China.
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China.
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
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22
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Shao K, Zheng S, Wang Y, Bai X, Luo H, Du F. A detailed dosimetric comparative study of IMRT and VMAT in normal brain tissues for nasopharyngeal carcinoma patients treated with radiotherapy. FRONTIERS IN RADIOLOGY 2023; 3:1190763. [PMID: 37492390 PMCID: PMC10365280 DOI: 10.3389/fradi.2023.1190763] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 04/27/2023] [Indexed: 07/27/2023]
Abstract
Background Radiotherapy (RT) is the primary treatment for nasopharyngeal carcinoma (NPC). However, it can cause implicit RT-induced injury by irradiating normal brain tissue. To date, there have been no detailed reports on the radiated exact location in the brain, the corresponding radiation dose, and their relationship. Methods We analyzed 803 Chinese NPC patients treated with RT and used a CT brain template in a Montreal Neurological Institute (MNI) space to compare the group differences in RT dose distribution for different RT technologies (IMRT or VMAT). Results Brain regions that received high doses (>50 Gy) of radiation were mainly located in parts of the temporal and limbic lobes, where radioactive damage often occurs. Brain regions that accepted higher doses with IMRT were mainly located near the anterior region of the nasopharyngeal tumor, while brain regions that accepted higher doses with VMAT were mainly located near the posterior region of the tumor. No significant difference was detected between IMRT and VMAT for T1 stage patients. For T2 stage patients, differences were widely distributed, with VMAT showing a significant dose advantage in protecting the normal brain tissue. For T3 stage patients, VMAT showed an advantage in the superior temporal gyrus and limbic lobe, while IMRT showed an advantage in the posterior cerebellum. For T4 stage patients, VMAT showed a disadvantage in protecting the normal brain tissue. These results indicate that IMRT and VMAT have their own advantages in sparing different organs at risk (OARs) in the brain for different T stages of NPC patients treated with RT. Conclusion Our approach for analyzing dosimetric characteristics in a standard MNI space for Chinese NPC patients provides greater convenience in toxicity and dosimetry analysis with superior localization accuracy. Using this method, we found interesting differences from previous reports: VMAT showed a disadvantage in protecting the normal brain tissue for T4 stage NPC patients.
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Affiliation(s)
- Kainan Shao
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, China
| | - Shuang Zheng
- School of Media and Design, Hangzhou Dianzi University, Hangzhou, China
| | - Yajuan Wang
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, China
| | - Xue Bai
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, China
| | - Hongying Luo
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, China
- Faculty of Nuclear Science and Technology, University of South China, Hengyang, China
| | - Fenglei Du
- Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, China
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23
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Yang G, Bozek J, Noble S, Han M, Wu X, Xue M, Kang J, Jia T, Fu J, Ge J, Cui Z, Li X, Feng J, Gao JH. Global diversity in individualized cortical network topography. Cereb Cortex 2023:6992941. [PMID: 36657772 DOI: 10.1093/cercor/bhad002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 12/24/2022] [Accepted: 12/27/2022] [Indexed: 01/21/2023] Open
Abstract
Individualized cortical network topography (ICNT) varies between people and exhibits great variability in the association networks in the human brain. However, these findings were mainly discovered in Western populations. It remains unclear whether and how ICNT is shaped by the non-Western populations. Here, we leveraged a multisession hierarchical Bayesian model to define individualized functional networks in White American and Han Chinese populations with data from both US and Chinese Human Connectome Projects. We found that both the size and spatial topography of individualized functional networks differed between White American and Han Chinese groups, especially in the heteromodal association cortex (including the ventral attention, control, language, dorsal attention, and default mode networks). Employing a support vector machine, we then demonstrated that ethnicity-related ICNT diversity can be used to identify an individual's ethnicity with high accuracy (74%, pperm < 0.0001), with heteromodal networks contributing most to the classification. This finding was further validated through mass-univariate analyses with generalized additive models. Moreover, we reveal that the spatial heterogeneity of ethnic diversity in ICNT correlated with fundamental properties of cortical organization, including evolutionary cortical expansion, brain myelination, and cerebral blood flow. Altogether, this case study highlights a need for more globally diverse and publicly available neuroimaging datasets.
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Affiliation(s)
- Guoyuan Yang
- Advanced Research Institute of Multidisciplinary Sciences, School of Medical Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Jelena Bozek
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb 10000, Croatia
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Meizhen Han
- McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xinyu Wu
- Advanced Research Institute of Multidisciplinary Sciences, School of Medical Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Mufan Xue
- Advanced Research Institute of Multidisciplinary Sciences, School of Medical Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai 200433, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai 200433, China.,Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London SE5 8AF, United Kingdom
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300203, China
| | - Jianqiao Ge
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Xuesong Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai 200433, China.,Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,McGovern Institute for Brain Research, Peking University, Beijing 100871, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
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24
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Vallejo-Azar MN, Alba-Ferrara L, Bouzigues A, Princich JP, Markov M, Bendersky M, Gonzalez PN. Influence of accessory sulci of the frontoparietal operculum on gray matter quantification. Front Neuroanat 2023; 16:1022758. [PMID: 37089581 PMCID: PMC10117380 DOI: 10.3389/fnana.2022.1022758] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 12/29/2022] [Indexed: 01/21/2023] Open
Abstract
Introduction: The perisylvian region is the cortical core of language and speech. Several accessory sulci have been described in this area, whose presence could modify the results of the automatic quantification of gray matter by popularly used software. This study aimed to assess the expression of accessory sulci in the frontoparietal operculum (FPO) and to evaluate their influence on the gray matter volume estimated by an automatic parcellation of cortical gyri and sulci. Methods: Brain MRI scans of 100 healthy adult volunteers were visually analyzed. The existence of the triangular and diagonal sulci, and the number of accessory sulci in the frontoparietal operculum, were assessed on T1 images. Also, the gray matter volume of gyri and sulci was quantified by an automatized parcellation method. Interhemispheric differences in accessory sulci were evaluated with Chi-square and Wilcoxon paired tests. The effects of the hemisphere, sex, age, total intracranial volume, and accessory sulci on morphometric variables were assessed by linear models. Results: These sulci were found in more than half of the subjects, mostly in the left hemisphere, and showed a significant effect on the gray matter content of the FPO. In particular, the volume of the inferior frontal sulcus, pars opercularis of the inferior frontal gyrus, horizontal ramus of the lateral sulcus, angular gyrus, and postcentral gyrus showed a significant influence on the presence of accessory sulci. Discussion: The prevalence of tertiary sulci in the FPO is high, although their meaning is not yet known. Therefore, they should be considered to reduce the risk of misclassifications of normal variation.
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Affiliation(s)
- Mariana N. Vallejo-Azar
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
| | - Lucia Alba-Ferrara
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
| | - Arabella Bouzigues
- INSERM U1127, Institut du cerveau, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Juan P. Princich
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
| | - Martin Markov
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
| | - Mariana Bendersky
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
- Laboratorio de Anatomía Viviente, Facultad de Medicina, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Paula N. Gonzalez
- Unidad de Estudios en Neurociencias y Sistemas Complejos, CONICET, Hospital El Cruce Dr, “Néstor C. Kirchner”, Universidad Arturo Jauretche, Buenos Aires, Argentina
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25
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Malinowska JK, Żuradzki T. Towards the multileveled and processual conceptualisation of racialised individuals in biomedical research. SYNTHESE 2022; 201:11. [PMID: 36591336 PMCID: PMC9795162 DOI: 10.1007/s11229-022-04004-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
In this paper, we discuss the processes of racialisation on the example of biomedical research. We argue that applying the concept of racialisation in biomedical research can be much more precise, informative and suitable than currently used categories, such as race and ethnicity. For this purpose, we construct a model of the different processes affecting and co-shaping the racialisation of an individual, and consider these in relation to biomedical research, particularly to studies on hypertension. We finish with a discussion on the potential application of our proposition to institutional guidelines on the use of racial categories in biomedical research.
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Affiliation(s)
| | - Tomasz Żuradzki
- Institute of Philosophy & Interdisciplinary Centre for Ethics, Jagiellonian University, ul. Grodzka 52, 31-044 Kraków, Poland
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26
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Lim EC, Choi US, Choi KY, Lee JJ, Sung YW, Ogawa S, Kim BC, Lee KH, Gim J. DeepParcellation: A novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians. Front Aging Neurosci 2022; 14:1027857. [PMID: 36570529 PMCID: PMC9783623 DOI: 10.3389/fnagi.2022.1027857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 11/15/2022] [Indexed: 12/13/2022] Open
Abstract
Accurate parcellation of cortical regions is crucial for distinguishing morphometric changes in aged brains, particularly in degenerative brain diseases. Normal aging and neurodegeneration precipitate brain structural changes, leading to distinct tissue contrast and shape in people aged >60 years. Manual parcellation by trained radiologists can yield a highly accurate outline of the brain; however, analyzing large datasets is laborious and expensive. Alternatively, newly-developed computational models can quickly and accurately conduct brain parcellation, although thus far only for the brains of Caucasian individuals. To develop a computational model for the brain parcellation of older East Asians, we trained magnetic resonance images of dimensions 256 × 256 × 256 on 5,035 brains of older East Asians (Gwangju Alzheimer's and Related Dementia) and 2,535 brains of Caucasians. The novel N-way strategy combining three memory reduction techniques inception blocks, dilated convolutions, and attention gates was adopted for our model to overcome the intrinsic memory requirement problem. Our method proved to be compatible with the commonly used parcellation model for Caucasians and showed higher similarity and robust reliability in older aged and East Asian groups. In addition, several brain regions showing the superiority of the parcellation suggest that DeepParcellation has a great potential for applications in neurodegenerative diseases such as Alzheimer's disease.
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Affiliation(s)
- Eun-Cheon Lim
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Uk-Su Choi
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea,BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, South Korea,Neurozen Inc., Seoul, South Korea,Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, South Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Jang Jae Lee
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Yul-Wan Sung
- Kansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Miyagi, Japan
| | - Seiji Ogawa
- Kansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Miyagi, Japan
| | - Byeong Chae Kim
- Department of Neurology, Chonnam National University Medical School, Gwangju, South Korea
| | - Kun Ho Lee
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea,BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, South Korea,Neurozen Inc., Seoul, South Korea,Department of Biomedical Science, Chosun University, Gwangju, South Korea,Korea Brain Research Institute, Daegu, South Korea,*Correspondence: Kun Ho Lee,
| | - Jungsoo Gim
- Gwangju Alzheimer’s and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea,BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, South Korea,Department of Biomedical Science, Chosun University, Gwangju, South Korea,Jungsoo Gim,
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27
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Chen R, Sun C, Liu T, Liao Y, Wang J, Sun Y, Zhang Y, Wang G, Wu D. Deciphering the developmental order and microstructural patterns of early white matter pathways in a diffusion MRI based fetal brain atlas. Neuroimage 2022; 264:119700. [PMID: 36270621 DOI: 10.1016/j.neuroimage.2022.119700] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 10/14/2022] [Accepted: 10/18/2022] [Indexed: 11/09/2022] Open
Abstract
White matter (WM) of the fetal brain undergoes rapid development to form early structural connections. Diffusion magnetic resonance imaging (dMRI) has shown to be a useful tool to depict fetal brain WM in utero, and many studies have observed increasing fractional anisotropy and decreasing diffusivity in the fetal brain during the second-to-third trimester, whereas others reported non-monotonic changes. Unbiased dMRI atlases of the fetal brain are important for characterizing the developmental trajectories of WM and providing normative references for in utero diagnosis of prenatal abnormalities. To date, the sole fetal brain dMRI atlas was collected from a Caucasian/mixed population and was constructed based on the diffusion tensor model with limited spatial resolution. In this work, we proposed a fiber orientation distribution (FOD) based pipeline for generating fetal brain dMRI atlases, which showed better registration accuracy than a diffusion tensor based pipeline. Based on the FOD-based pipeline, we constructed the first Chinese fetal brain dMRI atlas using 89 dMRI scans of normal fetuses at gestational age between 24 and 38 weeks. Complex non-monotonic trends of tensor- and FOD-derived microstructural parameters in eight WM tracts were observed, which jointly pointed to different phases of microstructural development. Specifically, we speculated that the turning point of the diffusivity trajectory may correspond to the starting point of pre-myelination, based on which, the developmental order of WM tracts can be mapped and the order was in agreement with the order of myelination from histological studies. The normative atlas also provided a reference for the detection of abnormal WM development, such as that in congenital heart disease. Therefore, the established high-order fetal brain dMRI atlas depicted the spatiotemporal pattern of early WM development, and findings may help decipher the distinct microstructural events in utero.
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Affiliation(s)
- Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuhao Liao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | | | - Yi Sun
- MR Collaboration, Siemens Healthineers Ltd., Shanghai, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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28
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Pirazzoli L, Sullivan E, Xie W, Richards JE, Bulgarelli C, Lloyd-Fox S, Shama T, Kakon SH, Haque R, Petri WAJ, Nelson CA. Association of psychosocial adversity and social information processing in children raised in a low-resource setting: an fNIRS study. Dev Cogn Neurosci 2022; 56:101125. [PMID: 35763916 PMCID: PMC9241055 DOI: 10.1016/j.dcn.2022.101125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 06/02/2022] [Accepted: 06/13/2022] [Indexed: 01/01/2023] Open
Abstract
Social cognition skills and socioemotional development are compromised in children growing up in low SES contexts, however, the mechanisms underlying this association remain unknown. Exposure to psychosocial risk factors early in life alters the child's social milieu and in turn, could lead to atypical processing of social stimuli. In this study, we used functional Near Infrared Spectroscopy (fNIRS) to measure cortical responses to a social discrimination task in children raised in a low-resource setting at 6, 24, and 36 months. In addition, we assessed the relation between cortical responses to social and non-social information with psychosocial risk factors assessed using the Childhood Psychosocial Adversity Scale (CPAS). In line with previous findings, we observed specialization to social stimuli in cortical regions in all age groups. In addition, we found that risk factors were associated with social discrimination at 24 months (intimate partner violence and verbal abuse and family conflict) and 36 months (verbal abuse and family conflict and maternal depression) but not at 6 months. Overall, the results show that exposure to psychosocial adversity has more impact on social information processing in toddlerhood than earlier in infancy.
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Affiliation(s)
- Laura Pirazzoli
- Labs of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Eileen Sullivan
- Labs of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Graduate School of Education, Cambridge, MA, USA
| | - Wanze Xie
- School of Psychological and Cognitive Sciences, Peking University, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, China
| | | | - Chiara Bulgarelli
- Birkbeck, University of London, UK; University College London, London, UK
| | | | | | | | | | | | - Charles A Nelson
- Labs of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard Graduate School of Education, Cambridge, MA, USA
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29
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Yap KH, Abdul Manan H, Yahya N, Azmin S, Mohamed Mukari SA, Mohamed Ibrahim N. Magnetic Resonance Imaging and Its Clinical Correlation in Spinocerebellar Ataxia Type 3: A Systematic Review. Front Neurosci 2022; 16:859651. [PMID: 35757531 PMCID: PMC9226753 DOI: 10.3389/fnins.2022.859651] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/10/2022] [Indexed: 12/14/2022] Open
Abstract
Background Spinocerebellar ataxia type 3 (SCA3) is a complex cerebrocerebellar disease primarily characterized by ataxia symptoms alongside motor and cognitive impairments. The heterogeneous clinical presentation of SCA3 necessitates correlations between magnetic resonance imaging (MRI) and clinical findings in reflecting progressive disease changes. At present, an attempt to systematically examine the brain-behavior relationship in SCA3, specifically, the correlation between MRI and clinical findings, is lacking. Objective We investigated the association strength between MRI abnormality and each clinical symptom to understand the brain-behavior relationship in SCA3. Methods We conducted a systematic review on Medline and Scopus to review studies evaluating the brain MRI profile of SCA3 using structural MRI (volumetric, voxel-based morphometry, surface analysis), magnetic resonance spectroscopy, and diffusion tensor imaging, including their correlations with clinical outcomes. Results Of 1,767 articles identified, 29 articles met the eligibility criteria. According to the National Institutes of Health quality assessment tool for case-control studies, all articles were of excellent quality. This systematic review found that SCA3 neuropathology contributes to widespread brain degeneration, affecting the cerebellum and brainstem. The disease gradually impedes the cerebral cortex and basal ganglia in the late stages of SCA3. Most findings reported moderate correlations (r = 0.30–0.49) between MRI features in several regions and clinical findings. Regardless of the MRI techniques, most studies focused on the brainstem and cerebellum. Conclusions Clinical findings suggest that rather than individual brain regions, the connectivity between different brain regions in distributed networks (i.e., cerebellar-cerebral network) may be responsible for motor and neurocognitive function in SCA3. This review highlights the importance of evaluating the progressive changes of the cerebellar-cerebral networks in SCA3 patients, specifically the functional connectivity. Given the relative lack of knowledge about functional connectivity on SCA3, future studies should investigate possible functional connectivity abnormalities in SCA3 using fMRI.
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Affiliation(s)
- Kah Hui Yap
- Department of Medicine, Universiti Kebangsaan Malaysia (UKM) Medical Centre, Kuala Lumpur, Malaysia
| | - Hanani Abdul Manan
- Makmal Pemprosesan Imej Kefungsian, Department of Radiology, Universiti Kebangsaan Malaysia (UKM) Medical Centre, Kuala Lumpur, Malaysia.,Department of Radiology and Intervency, Hospital Pakar Kanan-Kanak, Children Specialist Hospital, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur, Malaysia
| | - Noorazrul Yahya
- School of Diagnostic and Applied Health Sciences, Faculty of Health Sciences, National University of Malaysia, Kuala Lumpur, Malaysia
| | - Shahrul Azmin
- Department of Medicine, Universiti Kebangsaan Malaysia (UKM) Medical Centre, Kuala Lumpur, Malaysia
| | - Shahizon Azura Mohamed Mukari
- Makmal Pemprosesan Imej Kefungsian, Department of Radiology, Universiti Kebangsaan Malaysia (UKM) Medical Centre, Kuala Lumpur, Malaysia
| | - Norlinah Mohamed Ibrahim
- Department of Medicine, Universiti Kebangsaan Malaysia (UKM) Medical Centre, Kuala Lumpur, Malaysia
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30
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Gao P, Dong HM, Liu SM, Fan XR, Jiang C, Wang YS, Margulies D, Li HF, Zuo XN. A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping. Sci Data 2022; 9:286. [PMID: 35680932 PMCID: PMC9184635 DOI: 10.1038/s41597-022-01413-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 05/24/2022] [Indexed: 11/09/2022] Open
Abstract
The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It is important for the community to realize that such open science effort must protect personal, especially facial information when raw neuroimaging data are shared. An ideal tool for the face anonymization should not disturb subsequent brain tissue extraction and further morphological measurements. Using the high-resolution head images from magnetic resonance imaging (MRI) of 215 healthy Chinese, we discovered and validated a template effect on the face anonymization. Improved facial anonymization was achieved when the Chinese head templates but not the Western templates were applied to obscure the faces of Chinese brain images. This finding has critical implications for international brain imaging data-sharing. To facilitate the further investigation of potential culture-related impacts on and increase diversity of data-sharing for the human brain mapping, we released the 215 Chinese multi-modal MRI data into a database for imaging Chinese young brains, namely'I See your Brains (ISYB)', to the public via the Science Data Bank ( https://doi.org/10.11922/sciencedb.00740 ).
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Affiliation(s)
- Peng Gao
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030024, China
| | - Hao-Ming Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- National Basic Science Data Center, Beijing, 100109, China
| | - Si-Man Liu
- Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xue-Ru Fan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Chao Jiang
- School of Psychology, Capital Normal University, Beijing, 100048, China
| | - Yin-Shan Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Daniel Margulies
- Centre National de la Recherche Scientifique, Frontlab, Brain and Spinal Cord Institute, Paris, UMR 7225, France
| | - Hai-Fang Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030024, China.
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- National Basic Science Data Center, Beijing, 100109, China.
- Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, 530001, China.
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31
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Wang Y, Xu F, Zhou W, Hou L, Tang Y, Liu S. Morphological and hemispheric and sex differences of the anterior ascending ramus and the horizontal ascending ramus of the lateral sulcus. Brain Struct Funct 2022; 227:1949-1961. [PMID: 35441988 PMCID: PMC9232435 DOI: 10.1007/s00429-022-02482-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/13/2022] [Indexed: 11/30/2022]
Abstract
Broca’s area is composed of the pars opercularis (PO) and the pars triangularis (PTR) of the inferior frontal gyrus; the anterior ascending ramus of the lateral sulcus (aals) separates the PO from the PTR, and the horizontal ascending ramus of the lateral sulcus (hals) separates the PTR from the pars orbitalis. The morphometry of these two sulci maybe has potential effects on the various functions of Broca’s area. Exploring the morphological variations, hemispheric differences and sex differences of these two sulci contributed to a better localization of Broca's area. BrainVISA was used to reconstruct and parameterize these two sulci based on data from 3D MR images of 90 healthy right-handed subjects. The 3D anatomic morphologies of these two sulci were investigated using 4 sulcal parameters: average depth (AD), average width (AW), outer length (OL) and inner length (IL). The aals and hals could be identified in 98.89% and 98.33%, respectively, of the hemispheres evaluated. The morphological patterns of these two sulci were categorized into four typical types. There were no statistically significant interhemispheric or sex differences in the frequency of the morphological patterns. There was statistically significant interhemispheric difference in the IL of the aals. Significant sex differences were found in the AD and the IL of the aals and OL of the hals. Our results not only provide a structural basis for functional studies related to Broca’s area but also are helpful in determining the precise position of Broca’s area in neurosurgery.
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Affiliation(s)
- Yu Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Wenjuan Zhou
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Lanwei Hou
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China. .,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, 250012, Shandong, China.
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32
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Lin T, Zhang X, Fields EC, Sekuler R, Gutchess A. Spatial frequency impacts perceptual and attentional ERP components across cultures. Brain Cogn 2022; 157:105834. [PMID: 34999289 PMCID: PMC8792318 DOI: 10.1016/j.bandc.2021.105834] [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: 07/14/2021] [Revised: 12/21/2021] [Accepted: 12/21/2021] [Indexed: 11/22/2022]
Abstract
Culture impacts visual perception in several ways.To identify stages of perceptual processing that differ between cultures, we usedelectroencephalography measures of perceptual and attentional responses to simple visual stimuli.Gabor patches of higher or lower spatialfrequencywere presented at high contrast to 25 American and 31 East Asian participants while they were watching for the onset of aninfrequent, oddball stimulus. Region of interest and mass univariate analyses assessed how cultural background and stimuli spatial frequency affected the visual evoked response potentials. Across both groups, the Gabor of lower spatial frequency produced stronger evoked response potentials in the anterior N1 and P3 than did the higher frequency Gabor. The mass univariate analyses also revealed effects of spatial frequency, including a frontal negativity around 150 ms and a widespread posterior positivity around 300 ms. The effects of spatial frequency generally differed little across cultures; although there was some evidence for cultural differences in the P3 response to different frequencies at the Pz electrode, this effect did not emerge in the mass univariate analyses. We discuss these results in relation to those from previous studies, and explore the potential advantages of mass univariate analyses for cultural neuroscience.
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Affiliation(s)
- Tong Lin
- Brandeis University, United States
| | | | - Eric C Fields
- Brandeis University, United States; Boston College, United States; Westminster College, United States
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33
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Ma X, Kang J, Li X, Maurer U, Cao X, Sommer W. Does learning different script systems affect configural visual processing? ERP evidence from early readers of Chinese and German. Psychophysiology 2022; 59:e14006. [PMID: 35150451 DOI: 10.1111/psyp.14006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/17/2021] [Accepted: 01/02/2022] [Indexed: 11/27/2022]
Affiliation(s)
- Xiaoli Ma
- Institut für Psychologie, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jing Kang
- Department of Psychology, Zhejiang Normal University, Jin Hua, China
| | - Xinran Li
- Institut für Psychologie, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Urs Maurer
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China.,Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - Xiaohua Cao
- Department of Psychology, Zhejiang Normal University, Jin Hua, China
| | - Werner Sommer
- Institut für Psychologie, Humboldt-Universität zu Berlin, Berlin, Germany.,Department of Psychology, Zhejiang Normal University, Jin Hua, China
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34
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Xu J, Liu X, Li Q, Goldblatt R, Qin W, Liu F, Chu C, Luo Q, Ing A, Guo L, Liu N, Liu H, Huang C, Cheng J, Wang M, Geng Z, Zhu W, Zhang B, Liao W, Qiu S, Zhang H, Xu X, Yu Y, Gao B, Han T, Cui G, Chen F, Xian J, Li J, Zhang J, Zuo XN, Wang D, Shen W, Miao Y, Yuan F, Lui S, Zhang X, Xu K, Zhang L, Ye Z, Banaschewski T, Barker GJ, Bokde ALW, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Robinson L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Winterer J, Patrick K, Calhoun V, Li MJ, Liang M, Gong P, Barker ED, Clinton N, Marquand A, Yu L, Yu C, Schumann G. Global urbanicity is associated with brain and behaviour in young people. Nat Hum Behav 2022; 6:279-293. [PMID: 34711977 DOI: 10.1038/s41562-021-01204-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 08/26/2021] [Indexed: 02/05/2023]
Abstract
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.
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Affiliation(s)
- Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Xiaoxuan Liu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Qiaojun Li
- College of Information Engineering, Tianjin University of Commerce, Tianjin, P. R. China
| | | | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Congying Chu
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Fudan University, Shanghai, China
| | - Alex Ing
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Conghong Huang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China
| | - Zuojun Geng
- Department of Medical Imaging, Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Shijun Qiu
- Department of Medical Imaging, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hui Zhang
- Department of Radiology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiaojun Xu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Yongqiang Yu
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bo Gao
- Department of Radiology, Affliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province and Department of Radiology, Tangdu Hospital, Military Medical University of PLA Airforce (Fourth Military Medical University), Xi'an, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital, Haikou, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jiance Li
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, Tianjin, China
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Fei Yuan
- Department of Radiology, Pingjin Hospital, Logistics University of Chinese People's Armed Police Forces, Tianjin, China
| | - Su Lui
- Department of Radiology, Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaochu Zhang
- Department of Radiology, First Affiliated Hospital of USTC, Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China
| | - Kai Xu
- Department of Radiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Longjiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Department of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, CNRS, Centre Borelli, INSERM U1299 "Trajectoires Développementales & Psychiatrie", Gif-sur-Yvette, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 Neuroimaging and Psychiatry, University Paris Sud, University Paris Descartes - Sorbonne Paris Cité; Psychiatry Department 91G16, Orsay Hospital, Orsay, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Herve Lemaitre
- Institute National de la Santé et de la Recherche Médicale, UMR 992 INSERM, CEA, Faculté de médecine, Université Paris-Sud, Université Paris-Saclay NeuroSpin, Gif-sur-Yvette, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Lauren Robinson
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jeanne Winterer
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Kevin Patrick
- Center for Wireless and Population Health Systems, Department of Family and Preventive Medicine and Calit2's Qualcomm Institute, University of California San Diego, La Jolla, CA, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Mulin Jun Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, P. R. China
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, P. R. China
| | - Peng Gong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
- Department of Geography and Department of Earth Sciences, University of Hong Kong, Hong Kong, China
| | - Edward D Barker
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Andre Marquand
- Predictive Clinical Neuroscience Group at the Donders Institute, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Le Yu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, P. R. China.
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology of Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, P. R. China.
- Centre for Population Neuroscience and Stratified Medicine (PONS), Charite Mental Health, Dept. of Psychiatry and Psychotherapy, CCM, Charite Universitätsmedizin Berlin, Berlin, Germany.
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35
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Goto M, Abe O, Hagiwara A, Fujita S, Kamagata K, Hori M, Aoki S, Osada T, Konishi S, Masutani Y, Sakamoto H, Sakano Y, Kyogoku S, Daida H. Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications. Magn Reson Med Sci 2022; 21:41-57. [PMID: 35185061 PMCID: PMC9199978 DOI: 10.2463/mrms.rev.2021-0096] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls. In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).
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Affiliation(s)
- Masami Goto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo
| | | | - Shohei Fujita
- Department of Radiology, Graduate School of Medicine, The University of Tokyo
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine
| | - Takahiro Osada
- Department of Neurophysiology, Juntendo University School of Medicine
| | - Seiki Konishi
- Department of Neurophysiology, Juntendo University School of Medicine
| | | | - Hajime Sakamoto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | - Yasuaki Sakano
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | - Shinsuke Kyogoku
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | - Hiroyuki Daida
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
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36
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Baecker L, Garcia-Dias R, Vieira S, Scarpazza C, Mechelli A. Machine learning for brain age prediction: Introduction to methods and clinical applications. EBioMedicine 2021; 72:103600. [PMID: 34614461 PMCID: PMC8498228 DOI: 10.1016/j.ebiom.2021.103600] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 12/19/2022] Open
Abstract
The rise of machine learning has unlocked new ways of analysing structural neuroimaging data, including brain age prediction. In this state-of-the-art review, we provide an introduction to the methods and potential clinical applications of brain age prediction. Studies on brain age typically involve the creation of a regression machine learning model of age-related neuroanatomical changes in healthy people. This model is then applied to new subjects to predict their brain age. The difference between predicted brain age and chronological age in a given individual is known as ‘brain-age gap’. This value is thought to reflect neuroanatomical abnormalities and may be a marker of overall brain health. It may aid early detection of brain-based disorders and support differential diagnosis, prognosis, and treatment choices. These applications could lead to more timely and more targeted interventions in age-related disorders.
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Affiliation(s)
- Lea Baecker
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Rafael Garcia-Dias
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Department of General Psychology, University of Padua, Italy
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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37
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Choi YY, Lee JJ, Choi KY, Choi US, Seo EH, Choo IH, Kim H, Song MK, Choi SM, Cho SH, Choe Y, Kim BC, Lee KH. Multi-Racial Normative Data for Lobar and Subcortical Brain Volumes in Old Age: Korean and Caucasian Norms May Be Incompatible With Each Other †. Front Aging Neurosci 2021; 13:675016. [PMID: 34413763 PMCID: PMC8369368 DOI: 10.3389/fnagi.2021.675016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/15/2021] [Indexed: 11/17/2022] Open
Abstract
Brain aging is becoming an increasingly important topic, and the norms of brain structures are essential for diagnosing neurodegenerative diseases. However, previous studies of the aging brain have mostly focused on Caucasians, not East Asians. The aim of this paper was to examine ethnic differences in the aging process of brain structures or to determine to what extent ethnicity affects the normative values of lobar and subcortical volumes in clinically normal elderly and the diagnosis in multi-racial patients with Alzheimer's disease (AD). Lobar and subcortical volumes were measured using FreeSurfer from MRI data of 1,686 normal Koreans (age range 59–89) and 851 Caucasian, non-Hispanic subjects in the ADNI and OASIS datasets. The regression models were designed to predict brain volumes, including ethnicity, age, sex, intracranial volume (ICV), magnetic field strength (MFS), and MRI scanner manufacturers as independent variables. Ethnicity had a significant effect for all lobar (|β| > 0.20, p < 0.001) and subcortical regions (|β| > 0.08, p < 0.001) except left pallidus and bilateral ventricles. To demonstrate the validity of the z-score for AD diagnosis, 420 patients and 420 normal controls were selected evenly from the Korean and Caucasian datasets. The four validation groups divided by race and diagnosis were matched on age and sex using a propensity score matching. We analyzed whether and to what extent the ethnicity adjustment improved the diagnostic power of the logistic regression model that was built using the only z-scores of six regions: bilateral temporal cortices, hippocampi, and amygdalae. The performance of the classifier after ethnicity adjustment was significantly improved compared with the classifier before ethnicity adjustment (ΔAUC = 0.10, D = 7.80, p < 0.001; AUC comparison test using bootstrap). Korean AD dementia patients may not be classified by Caucasian norms of brain volumes because the brain regions vulnerable to AD dementia are bigger in normal Korean elderly peoples. Therefore, ethnicity is an essential factor in establishing normative data for regional volumes in brain aging and applying it to the diagnosis of neurodegenerative diseases.
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Affiliation(s)
- Yu Yong Choi
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea.,Biomedical Technology Center, Chosun University Hospital, Gwangju, South Korea
| | - Jang Jae Lee
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Uk-Su Choi
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Eun Hyun Seo
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Il Han Choo
- Department of Neuropsychiatry, Chosun University School of Medicine and Hospital, Gwangju, South Korea
| | - Hoowon Kim
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea.,Biomedical Technology Center, Chosun University Hospital, Gwangju, South Korea.,Department of Neurology, Chosun University School of Medicine and Hospital, Gwangju, South Korea
| | - Min-Kyung Song
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Seong-Min Choi
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Soo Hyun Cho
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | | | - Byeong C Kim
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, South Korea.,Korea Brain Research Institute, Daegu, South Korea.,Department of Biomedical Science, Chosun University, Gwangju, South Korea.,Neurozen Inc., Seoul, South Korea
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38
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Williams CM, Peyre H, Toro R, Ramus F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum Brain Mapp 2021; 42:4623-4642. [PMID: 34268815 PMCID: PMC8410561 DOI: 10.1002/hbm.25572] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/18/2022] Open
Abstract
Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, Paris, France.,Center for Research and Interdisciplinarity (CRI), INSERM U1284, Paris, France.,Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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39
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Personalized prediction of transcranial magnetic stimulation clinical response in patients with treatment-refractory depression using neuroimaging biomarkers and machine learning. J Affect Disord 2021; 290:261-271. [PMID: 34010751 DOI: 10.1016/j.jad.2021.04.081] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 01/13/2021] [Accepted: 04/23/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND Functional connectivity between the left dorsolateral prefrontal cortex (DLPFC) and subgenual cingulate (sgACC) may serve as a biomarker for transcranial magnetic stimulation (rTMS) treatment response. The first aim was to establish whether this finding is veridical or artifactually induced by the pre-processing method. Furthermore, alternative biomarkers were identified and the clinical utility for personalized medicine was examined. METHODS Resting-state fMRI data were collected in medication-refractory depressed patients (n = 70, 16 males) before undergoing neuronavigated left DLPFC rTMS. Seed-based analyses were performed with and without global signal regression pre-processing to identify biomarkers of short-term and long-term treatment response. Receiver Operating Characteristic curve and supervised machine learning analyses were applied to assess the clinical utility of these biomarkers for the classification of categorical rTMS response. RESULTS Regardless of the pre-processing method, DLPFC-sgACC connectivity was not associated with treatment outcome. Instead, poorer connectivity between the sgACC and three clusters (peak locations: frontal pole, superior parietal lobule, occipital cortex) and DLPFC-central opercular cortex were observed in long-term nonresponders. The identified connections could serve as acceptable to excellent markers. Combining the features using supervised machine learning reached accuracy rates of 95.35% (CI=82.94-100.00) and 88.89% (CI=63.96-100.00) in the cross-validation and test dataset, respectively. LIMITATIONS The sample size was moderate, and features for machine learning were based on group differences. CONCLUSIONS Long-term nonresponders showed greater disrupted connectivity in regions involving the central executive network. Our findings may aid the development of personalized medicine for medication-refractory depression.
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40
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Han S, Chen Y, Zheng R, Li S, Jiang Y, Wang C, Fang K, Yang Z, Liu L, Zhou B, Wei Y, Pang J, Li H, Zhang Y, Cheng J. The stage-specifically accelerated brain aging in never-treated first-episode patients with depression. Hum Brain Mapp 2021; 42:3656-3666. [PMID: 33932251 PMCID: PMC8249899 DOI: 10.1002/hbm.25460] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 04/02/2021] [Accepted: 04/15/2021] [Indexed: 12/29/2022] Open
Abstract
Depression associated with structural brain abnormalities is hypothesized to be related with accelerated brain aging. However, there is far from a unified conclusion because of clinical variations such as medication status, cumulative illness burden. To explore whether brain age is accelerated in never‐treated first‐episode patients with depression and its association with clinical characteristics, we constructed a prediction model where gray matter volumes measured by voxel‐based morphometry derived from T1‐weighted MRI scans were treated as features. The prediction model was first validated using healthy controls (HCs) in two Chinese Han datasets (Dataset 1, N = 130 for HCs and N = 195 for patients with depression; Dataset 2, N = 270 for HCs) separately or jointly, then the trained prediction model using HCs (N = 400) was applied to never‐treated first‐episode patients with depression (N = 195). The brain‐predicted age difference (brain‐PAD) scores defined as the difference between predicted brain age and chronological age, were calculated for all participants and compared between patients with age‐, gender‐, educational level‐matched HCs in Dataset 1. Overall, patients presented higher brain‐PAD scores suggesting patients with depression having an “older” brain than expected. More specially, this difference occurred at illness onset (illness duration <3 months) and following 2 years then disappeared as the illness further advanced (>2 years) in patients. This phenomenon was verified by another data‐driven method and significant correlation between brain‐PAD scores and illness duration in patients. Our results reveal that accelerated brain aging occurs at illness onset and suggest it is a stage‐dependent phenomenon in depression.
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Affiliation(s)
- Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Keke Fang
- Phase I Clinical Research Center, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Zhengui Yang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Liang Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfen Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province
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41
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Interdependent self-construal predicts increased gray matter volume of scene processing regions in the brain. Biol Psychol 2021; 161:108050. [PMID: 33592270 DOI: 10.1016/j.biopsycho.2021.108050] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 02/08/2021] [Accepted: 02/09/2021] [Indexed: 12/21/2022]
Abstract
Interdependent self-construal (SC) is thought to lead to a more holistic cognitive style that emphasizes the processing of the background scene of a focal object. At present, little is known about whether the structural properties of the brain might underlie this functional relationship. Here, we examined the gray matter (GM) volume of three cortical regions involved in scene processing -- a cornerstone of contextual processing. Study 1 tested 78 European American non-student adults and found that interdependent (vs. independent) SC predicts higher GM volume in the parahippocampal place area (PPA), one of the three target regions. Testing both European American and East Asian college students (total N = 126), Study 2 replicated this association. Moreover, the GM volume of all the three target regions was greater for East Asians than for European Americans. Our findings suggest that there is a structural neural underpinning for the cultural variation in cognitive style.
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Zhang Z, Wang Y, Gao Y, Li Z, Zhang S, Lin X, Hou Z, Yu Q, Wang X, Liu S. Morphological changes in the central sulcus of children with isolated growth hormone deficiency versus idiopathic short stature. Dev Neurobiol 2020; 81:36-46. [PMID: 33277816 DOI: 10.1002/dneu.22797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 08/25/2020] [Accepted: 11/27/2020] [Indexed: 11/10/2022]
Abstract
In this study, the morphological changes in the central sulcus between children with isolated growth hormone deficiency (IGHD) and those with idiopathic short stature (ISS) were analyzed. Thirty children with IGHD (peak growth hormone < 5 µg/L) and 30 children with ISS (peak growth hormone > 10.0 µg/L) were included. Morphological measurements of the central sulcus were obtained from T1-weighted MRIs using BrainVISA, including the average sulcal width, maximum depth, average depth, top length, bottom length, and depth position-based profiles (DPPs). The bilateral average width of the central sulci was significantly wider, while the left maximum depth and right average depth of the central sulcus were significantly smaller, in children with IGHD than in children with ISS. There were no significant differences in the right maximum depth, left average depth, or bilateral top length and bottom length of the central sulcus between groups. The DPPs of the middle part of both central sulci (corresponding to the hand motor activation area) and the inferior part of the right central sulcus (corresponding to the oral movement area) near the Sylvian fissure were significantly smaller in children with IGHD than in controls before false discovery rate (FDR) correction. However, all the above significant DPP sites disappeared after FDR correction. There were significant morphological changes in the three-dimensional structure of the central sulcus in children with IGHD, which were the outcome of other more essential cortical or subcortical changes, resulting in their relatively slower development in motor, cognitive, and linguistic functional performance.
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Affiliation(s)
- Zhonghe Zhang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China.,Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Yu Wang
- Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Yue Gao
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Zhuoran Li
- Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Shuhan Zhang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Xiangtao Lin
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China.,Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Zhongyu Hou
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China.,Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China.,Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Ximing Wang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China.,Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Shuwei Liu
- Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
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Zhang Z, Wang Y, Gao Y, Li Z, Zhang S, Lin X, Hou Z, Yu Q, Wang X, Liu S. Morphological changes of the cerebral cortex between children with isolated growth hormone deficiency and idiopathic short stature. Brain Res 2020; 1748:147081. [PMID: 32882231 DOI: 10.1016/j.brainres.2020.147081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 08/12/2020] [Accepted: 08/23/2020] [Indexed: 10/23/2022]
Abstract
The growth hormone (GH)-insulin-like growth factor-I (IGF-I) axis plays an important role in normal brain development, and GH deficiency inevitably affects the growth of the cerebral cortex. This study was designed to analyze morphological differences in gray matter volume, cortical surface area, and gray matter thickness between children with isolated growth hormone deficiency (IGHD) and children with idiopathic short stature (ISS). Twenty-four children with IGHD (mean age 9.42 years, peak GH < 5 μg/l) and 24 controls with ISS (mean age 9.21 years, peak GH > 10 μg/l) were included. High-resolution three-dimensional T1-weighted MRIs were acquired at participants' first visit. Measurements of gray matter volume, cortical surface area and gray matter thickness were obtained using FreeSurfer. The total and regional differences between groups were statistically analyzed. Correlations between the FreeSurfer results and GH and IGF-I levels were also obtained. The gray matter volume, cortical surface area and gray matter thickness of the total brain and of the bilateral hemispheres of children with IGHD were significantly smaller than those of children with ISS (all P values < 0.05). All the measurements had similar cortical distributions between groups but varied across regions. Cortical regions with significant differences in the mean gray matter volume and surface area were mainly distributed around the bilateral central sulci and the lateral and basal parts of the temporal lobes (all P values < 0.05). There were negative correlations between gray matter volume, cortical surface area and GH levels, and the right hemispheric and total cortical surface area correlated significantly with GH levels (all P values < 0.05) in children with IGHD. There were significant positive correlations between gray matter volume, cortical surface area and IGF-I levels (all P values < 0.05) in both groups, except for in left hemispheric gray matter volume in children with ISS. Children with IGHD have significant morphological changes in the cerebral cortex, which were partially influenced by GH and IGF-I levels. These cortical changes may be related to deficits in their relatively slower development in intelligence, motor performance, and other functions.
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Affiliation(s)
- Zhonghe Zhang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China; Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China.
| | - Yu Wang
- Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
| | - Yue Gao
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Zhuoran Li
- Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
| | - Shuhan Zhang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Xiangtao Lin
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China; Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
| | - Zhongyu Hou
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China; Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China; Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
| | - Ximing Wang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong University, Shandong, China; Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong, China
| | - Shuwei Liu
- Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, Shandong, China
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Kang DW, Wang SM, Na HR, Park SY, Kim NY, Lee CU, Kim D, Son SJ, Lim HK. Differences in cortical structure between cognitively normal East Asian and Caucasian older adults: a surface-based morphometry study. Sci Rep 2020; 10:20905. [PMID: 33262399 PMCID: PMC7708477 DOI: 10.1038/s41598-020-77848-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 10/19/2020] [Indexed: 11/30/2022] Open
Abstract
There is a growing literature on the impact of ethnicity on brain structure and function. Despite the regional heterogeneity in age-related changes and non-uniformity across brain morphometry measurements in the aging process, paucity of studies investigated the difference in cortical anatomy between the East Asian and Caucasian older adults. The present study aimed to compare cortical anatomy measurements, including cortical thickness, volume and surface area, between cognitively normal East Asian (n = 171) and Caucasian (n = 178) older adults, using surface-based morphometry and vertex-wise group analysis of high-dimensional structural magnetic resonance imaging (MRI) data. The East Asian group showed greater cortical thickness and larger cortical volume in the right superior temporal gyrus, postcentral gyrus, bilateral inferior temporal gyrus, and inferior parietal cortex. The Caucasian group showed thicker and larger cortex in the left transverse temporal cortex, lingual gyrus, right lateral occipital cortex, and precentral gyrus. Additionally, the difference in surface area was discordant with that in cortical thickness. Differences in brain structure between the East Asian and Caucasian might reflect differences in language and information processing, but further studies using standardized methods for assessing racial characteristics are needed. The research results represent a further step towards developing a comprehensive understanding of differences in brain structure between ethnicities of older adults, and this would enrich clinical research on aging and neurodegenerative diseases.
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Affiliation(s)
- Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hae-Ran Na
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sonya Youngju Park
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Nak Young Kim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | | | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
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Čeněk J, Tsai JL, Šašinka Č. Cultural variations in global and local attention and eye-movement patterns during the perception of complex visual scenes: Comparison of Czech and Taiwanese university students. PLoS One 2020; 15:e0242501. [PMID: 33196671 PMCID: PMC7668589 DOI: 10.1371/journal.pone.0242501] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 11/03/2020] [Indexed: 11/19/2022] Open
Abstract
Previous research on cross-cultural differences in visual attention has been inconclusive. Some studies have suggested the existence of systematic differences in global and local attention and context sensitivity, while others have produced negative or mixed results. The objective in this study was to examine the similarities and differences in holistic and analytic cognitive styles in a sample of Czech and Taiwanese university students. Two cognitive tasks were conducted: a Compound Figures Test and a free-viewing scene perception task which manipulated several focal objects and measured eye-movement patterns. An analysis of the reaction times in the Compound Figures Test showed no clear differences between either sample. An analysis of eye-movement metrics showed certain differences between the samples. While Czechs tended to focus relatively more on the focal objects measured by the number of fixations, the Taiwanese subjects spent more time fixating on the background. The results were consistent for scenes with one or two focal objects. The results of a correlation analysis of both tasks showed that they were unrelated. These results showed certain differences between the samples in visual perception but were not as systematic as the theory of holistic and analytic cognitive styles would suggest. An alternative model of cross-cultural differences in cognition and perception is discussed.
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Affiliation(s)
- Jiří Čeněk
- Department of Social Studies, Faculty of Regional Development and International Studies, Mendel University in Brno, Brno, Czech Republic
- * E-mail:
| | - Jie-Li Tsai
- Laboratory of Eye-Movements and Reading, Centre for the Mind, Brain and Learning, Department of Psychology, National Chengchi University, Taipei, Taiwan (R.O.C.)
| | - Čeněk Šašinka
- Division of Information and Library Studies, Faculty of Arts, Masaryk University, Brno, Czech Republic
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Choi YY, Lee JJ, Choi KY, Seo EH, Choo ILH, Kim H, Song MK, Choi SM, Cho SH, Kim BC, Lee KH. The Aging Slopes of Brain Structures Vary by Ethnicity and Sex: Evidence From a Large Magnetic Resonance Imaging Dataset From a Single Scanner of Cognitively Healthy Elderly People in Korea. Front Aging Neurosci 2020; 12:233. [PMID: 32903525 PMCID: PMC7437271 DOI: 10.3389/fnagi.2020.00233] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 07/03/2020] [Indexed: 01/12/2023] Open
Abstract
The aging of the brain is a well-investigated topic, but existing analyses have mainly focused on Caucasian samples. To investigate brain aging in East Asians, we measured cortical and subcortical volumes from magnetic resonance imaging (MRI) scans of 1,008 cognitively normal elderly Koreans from the Gwangju Alzheimer's and Related Dementia cohort and 342 Caucasians from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. To determine whether the aging effect varies with ethnicity and sex, beta coefficients of age and confidence intervals (CIs) were estimated in each ethnicity-sex group using a bootstrap method and a regression analysis using the relative volume to intracranial volume as predicted. The betas or aging slopes largely were not significantly different between ethnicity and sex groups in most types of brain structures. However, ethnic differences between the two female groups were found in the brain, most cortical regions, and a few subcortical regions. Ethnic differences in brain aging are likely due in large part to genetic factors; thus, we compared carriers and non-carriers of a gene relevant to longevity and neurodegenerative diseases, such as apolipoprotein E (APOE) ε4. The regions with ethnic differences in women also showed significant differences between Korean APOE ε4 non-carriers and Caucasian APOE ε4 carriers. Furthermore, Caucasian women showed significant APOE ε4 effects in the largest number of regions. These results illustrate that much of the ethnic differences in females may be explained by synergistic effects of ethnic background and APOE ε4 carrier status. Our results suggest that sex-dependent differences of aging between ethnic backgrounds may be due to ethnicity-dependent effects of genetic risk factors, such as APOE ε4. We also presented the normative information on volume estimates of the brain structures of the elderly Korean people in the subdivided age groups. This normative information of the aging brain stratified by ethnicity provides the age-related reference ranges quantified to replace visual judgment and facilitate precise clinical decision-making.
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Affiliation(s)
- Yu Yong Choi
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
- Biomedical Technology Center, Chosun University Hospital, Gwangju, South Korea
| | - Jang Jae Lee
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
| | - Eun Hyun Seo
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
- Biomedical Technology Center, Chosun University Hospital, Gwangju, South Korea
| | - IL Han Choo
- Department of Neuropsychiatry, Chosun University School of Medicine and Hospital, Gwangju, South Korea
| | - Hoowon Kim
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
- Biomedical Technology Center, Chosun University Hospital, Gwangju, South Korea
- Department of Neurology, Chosun University School of Medicine and Hospital, Gwangju, South Korea
| | - Min-Kyung Song
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Seong-Min Choi
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Soo Hyun Cho
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Byeong C. Kim
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Kun Ho Lee
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju, South Korea
- Department of Biomedical Science, Chosun University, Gwangju, South Korea
- Dementia Research Group, Korea Brain Research Institute, Daegu, South Korea
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Yang G, Bozek J, Han M, Gao J. Constructing and evaluating a cortical surface atlas and analyzing cortical sex differences in young Chinese adults. Hum Brain Mapp 2020; 41:2495-2513. [PMID: 32141680 PMCID: PMC7267952 DOI: 10.1002/hbm.24960] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 01/29/2020] [Accepted: 02/11/2020] [Indexed: 12/17/2022] Open
Abstract
Cortical surface templates are an important standardized coordinate frame for cortical structure and function analysis in magnetic resonance (MR) imaging studies. The widely used adult cortical surface templates (e.g., fsaverage, Conte69, and the HCP-MMP atlas) are based on the Caucasian population. Neuroanatomical differences related to environmental and genetic factors between Chinese and Caucasian populations make these templates unideal for analysis of the cortex in the Chinese population. We used a multimodal surface matching algorithm in an iterative procedure to create Chinese (sCN200) and Caucasian (sUS200) cortical surface atlases based on 200 demographically matched high-quality T1- and T2-weighted (T1w and T2w, respectively) MR images from the Chinese Human Connectome Project (CHCP) and the Human Connectome Project (HCP), respectively. Templates for anatomical cortical surfaces (white matter, pial, midthickness) and cortical feature maps of sulcal depth, curvature, thickness, T1w/T2w myelin, and cortical labels were generated. Using independent subsets from the CHCP and the HCP, we quantified the accuracy of cortical registration when using population-matched and mismatched atlases. The performance of the cortical registration and accuracy of curvature alignment when using population-matched atlases was significantly improved, thereby demonstrating the importance of using the sCN200 cortical surface atlas for Chinese adult population studies. Finally, we analyzed female and male cortical differences within the Chinese and Caucasian populations. We identified significant between-sex differences in cortical curvature, sulcal depth, thickness, and T1w/T2w myelin maps in the frontal, temporal, parietal, occipital, and insular lobes as well as the cingulate cortices.
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Affiliation(s)
- Guoyuan Yang
- Beijing City Key Lab for Medical Physics and EngineeringInstitute of Heavy Ion Physics, School of Physics, Peking UniversityBeijingChina
- Center for MRI Research, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
- McGovern Institute for Brain Research, Peking UniversityBeijingChina
| | - Jelena Bozek
- Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia
| | - Meizhen Han
- Beijing City Key Lab for Medical Physics and EngineeringInstitute of Heavy Ion Physics, School of Physics, Peking UniversityBeijingChina
- Center for MRI Research, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
- McGovern Institute for Brain Research, Peking UniversityBeijingChina
| | - Jia‐Hong Gao
- Beijing City Key Lab for Medical Physics and EngineeringInstitute of Heavy Ion Physics, School of Physics, Peking UniversityBeijingChina
- Center for MRI Research, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
- McGovern Institute for Brain Research, Peking UniversityBeijingChina
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Xu Q, Guo L, Cheng J, Wang M, Geng Z, Zhu W, Zhang B, Liao W, Qiu S, Zhang H, Xu X, Yu Y, Gao B, Han T, Yao Z, Cui G, Liu F, Qin W, Zhang Q, Li MJ, Liang M, Chen F, Xian J, Li J, Zhang J, Zuo XN, Wang D, Shen W, Miao Y, Yuan F, Lui S, Zhang X, Xu K, Zhang LJ, Ye Z, Yu C. CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research. Mol Psychiatry 2020; 25:517-529. [PMID: 31827248 PMCID: PMC7042768 DOI: 10.1038/s41380-019-0627-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 11/21/2019] [Accepted: 11/27/2019] [Indexed: 02/05/2023]
Abstract
The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.
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Affiliation(s)
- Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, 450003, Zhengzhou, China
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, 450003, Zhengzhou, China
| | - Zuojun Geng
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, 050000, Shijiazhuang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, 210008, Nanjing, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, 410008, Changsha, China
- National Clinical Research Center for Geriatric Disorder, 410008, Changsha, China
| | - Shijun Qiu
- Department of Medical Imaging, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 510405, Guangzhou, China
| | - Hui Zhang
- Department of Radiology, The First Hospital of Shanxi Medical University, 030001, Taiyuan, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, 310009, Hangzhou, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
| | - Bo Gao
- Department of Radiology, Yantai Yuhuangding Hospital, 264000, Yantai, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, 300350, Tianjin, China
- Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, 300350, Tianjin, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hosptial, Fudan University, 200040, Shanghai, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province & Department of Radiology, Tangdu Hospital, The Military Medical University of PLA Airforce (Fourth Military Medical University), 710038, Xi'an, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Quan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Mulin Jun Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, 300070, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, 300203, Tianjin, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital, 570311, Haikou, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, 100730, Beijing, China
| | - Jiance Li
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, 325000, Wenzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, 730050, Lanzhou, China
| | - Xi-Nian Zuo
- Department of Psychology, University of Chinese Academy of Sciences (CAS), 100049, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, 250012, Jinan, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, 300192, Tianjin, China
| | - Yanwei Miao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, 116011, Dalian, China
| | - Fei Yuan
- Department of Radiology, Pingjin Hospital, Logistics University of Chinese People's Armed Police Forces, 300162, Tianjin, China
| | - Su Lui
- Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, 610041, Chengdu, China
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325000, Wenzhou, China
| | - Xiaochu Zhang
- CAS Key Laboratory of Brain Function and Disease, University of Science and Technology of China, 230026, Hefei, China
- School of Life Sciences, University of Science & Technology of China, 230026, Hefei, China
| | - Kai Xu
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, 221006, Xuzhou, China
- School of Medical Imaging, Xuzhou Medical University, 221004, Xuzhou, China
| | - Long Jiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 210002, Nanjing, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, 300060, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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49
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Yang G, Zhou S, Bozek J, Dong HM, Han M, Zuo XN, Liu H, Gao JH. Sample sizes and population differences in brain template construction. Neuroimage 2020; 206:116318. [PMID: 31689538 PMCID: PMC6980905 DOI: 10.1016/j.neuroimage.2019.116318] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 10/01/2019] [Accepted: 10/26/2019] [Indexed: 12/23/2022] Open
Abstract
Spatial normalization or deformation to a standard brain template is routinely used as a key module in various pipelines for the processing of magnetic resonance imaging (MRI) data. Brain templates are often constructed using MRI data from a limited number of subjects. Individual brains show significant variabilities in their morphology; thus, sample sizes and population differences are two key factors that influence brain template construction. To address these influences, we employed two independent groups from the Human Connectome Project (HCP) and the Chinese Human Connectome Project (CHCP) to quantify the impacts of sample sizes and population on brain template construction. We first assessed the effect of sample size on the construction of volumetric brain templates using data subsets from the HCP and CHCP datasets. We applied a voxel-wise index of the deformation variability and a logarithmically transformed Jacobian determinant to quantify the variability associated with the template construction and modeled the brain template variability as a power function of the sample size. At the system level, the frontoparietal control network and dorsal attention network demonstrated higher deformation variability and logged Jacobian determinants, whereas other primary networks showed lower variability. To investigate the population differences, we constructed Caucasian and Chinese standard brain atlases (namely, US200 and CN200). The two demographically matched templates, particularly the language-related areas, exhibited dramatic bilaterally in supramarginal gyri and inferior frontal gyri differences in their deformation variability and logged Jacobian determinant. Using independent data from the HCP and CHCP, we examined the segmentation and registration accuracy and observed significant reduction in the performance of the brain segmentation and registration when the population-mismatched templates were used in the spatial normalization. Our findings provide evidence to support the use of population-matched templates in human brain mapping studies. The US200 and CN200 templates have been released on the Neuroimage Informatics Tools and Resources Clearinghouse (NITRC) website (https://www.nitrc.org/projects/us200_cn200/).
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Affiliation(s)
- Guoyuan Yang
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Sizhong Zhou
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Jelena Bozek
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Hao-Ming Dong
- Department of Psychology, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Meizhen Han
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Xi-Nian Zuo
- Department of Psychology, University of Chinese Academy of Sciences (UCAS), Beijing, China; CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China; Key Laboratory of Brain and Education, Nanning Normal University, Nanning, China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.
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50
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Tkachev A, Stepanova V, Zhang L, Khrameeva E, Zubkov D, Giavalisco P, Khaitovich P. Differences in lipidome and metabolome organization of prefrontal cortex among human populations. Sci Rep 2019; 9:18348. [PMID: 31797944 PMCID: PMC6893025 DOI: 10.1038/s41598-019-53762-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 10/31/2019] [Indexed: 12/11/2022] Open
Abstract
Human populations, despite their overwhelming similarity, contain some distinct phenotypic, genetic, epigenetic, and gene expression features. In this study, we explore population differences at yet another level of molecular phenotype: the abundance of non-polar and polar low molecular weight compounds, lipids and metabolites in the prefrontal cortical region of the brain. We assessed the abundance of 1,670 lipids and 258 metabolites in 146 Han Chinese, 97 Western European, and 60 African American individuals of varying ages, covering most of the lifespan. The statistical analysis and logistic regression models both demonstrated extensive lipid and metabolic divergence of the Han Chinese individuals from the other two populations. This divergence was age-dependent, peaking in young adults, and involved metabolites and lipids clustering in specific metabolic pathways.
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Affiliation(s)
- Anna Tkachev
- Skolkovo Institute of Science and Technology, 121205, Moscow, Russia
- Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoy Karetny Per. 19/1, 127051, Moscow, Russia
| | - Vita Stepanova
- Skolkovo Institute of Science and Technology, 121205, Moscow, Russia
- Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoy Karetny Per. 19/1, 127051, Moscow, Russia
| | - Lei Zhang
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, 200031, Shanghai, China
| | | | - Dmitry Zubkov
- Skolkovo Institute of Science and Technology, 121205, Moscow, Russia
| | - Patrick Giavalisco
- Max Planck Institute for Biology of Ageing, Joseph-Stelzmann-Straße 9B, 50931, Cologne, Germany.
| | - Philipp Khaitovich
- Skolkovo Institute of Science and Technology, 121205, Moscow, Russia.
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, 200031, Shanghai, China.
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany.
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