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Nishat E, Scratch SE, Ameis SH, Wheeler AL. Disrupted Maturation of White Matter Microstructure After Concussion Is Associated With Internalizing Behavior Scores in Female Children. Biol Psychiatry 2024:S0006-3223(24)00031-3. [PMID: 38237797 DOI: 10.1016/j.biopsych.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 12/08/2023] [Accepted: 01/08/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Some children who experience concussions, particularly females, develop long-lasting emotional and behavioral problems. Establishing the potential contribution of preexisting behavioral problems and disrupted white matter maturation has been challenging due to a lack of preinjury data. METHODS From the Adolescent Brain Cognitive Development cohort, 239 (90 female) children age 12.1 ± 0.6 years who experienced a concussion after study entry at 10.0 ± 0.6 years were compared to 6438 (3245 female) children without head injuries who were age 9.9 ± 0.6 years at baseline and 12.0 ± 0.6 years at follow-up. The Child Behavior Checklist was used to assess internalizing and externalizing behavior at study entry and follow-up. In the children with magnetic resonance imaging data available (concussion n = 134, comparison n = 3520), deep and superficial white matter was characterized by neurite density from restriction spectrum image modeling of diffusion magnetic resonance imaging. Longitudinal ComBat harmonization removed scanner effects. Linear regressions modeled 1) behavior problems at follow-up controlling for baseline behavior, 2) impact of concussion on white matter maturation, and 3) contribution of deviations in white matter maturation to postconcussion behavior problems. RESULTS Only female children with concussion had higher internalizing behavior problem scores. The youngest children with concussion showed less change in superficial white matter neurite density over 2 years than children with no concussion. In females with concussion, less change in superficial white matter neurite density was correlated with increased internalizing behavior problem scores. CONCLUSIONS Concussions in female children are associated with emotional problems beyond preinjury levels. Injury to superficial white matter may contribute to persistent internalizing behavior problems in females.
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Affiliation(s)
- Eman Nishat
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Shannon E Scratch
- Department of Paediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
| | - Stephanie H Ameis
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Cundill Centre for Child and Youth Depression, Margaret and Wallace McCain Centre for Child, Youth and Family Mental Health, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Anne L Wheeler
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.
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2
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Chauvel M, Uszynski I, Herlin B, Popov A, Leprince Y, Mangin JF, Hopkins WD, Poupon C. In vivo mapping of the deep and superficial white matter connectivity in the chimpanzee brain. Neuroimage 2023; 282:120362. [PMID: 37722605 DOI: 10.1016/j.neuroimage.2023.120362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/27/2023] [Accepted: 09/03/2023] [Indexed: 09/20/2023] Open
Abstract
Mapping the chimpanzee brain connectome and comparing it to that of humans is key to our understanding of similarities and differences in primate evolution that occurred after the split from their common ancestor around 6 million years ago. In contrast to studies on macaque species' brains, fewer studies have specifically addressed the structural connectivity of the chimpanzee brain and its comparison with the human brain. Most comparative studies in the literature focus on the anatomy of the cortex and deep nuclei to evaluate how their morphology and asymmetry differ from that of the human brain, and some studies have emerged concerning the study of brain connectivity among humans, monkeys, and apes. In this work, we established a new white matter atlas of the deep and superficial white matter structural connectivity in chimpanzees. In vivo anatomical and diffusion-weighted magnetic resonance imaging (MRI) data were collected on a 3-Tesla MRI system from 39 chimpanzees. These datasets were subsequently processed using a novel fiber clustering pipeline adapted to the chimpanzee brain, enabling us to create two novel deep and superficial white matter connectivity atlases representative of the chimpanzee brain. These atlases provide the scientific community with an important and novel set of reference data for understanding the commonalities and differences in structural connectivity between the human and chimpanzee brains. We believe this study to be innovative both in its novel approach and in mapping the superficial white matter bundles in the chimpanzee brain, which will contribute to a better understanding of hominin brain evolution.
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Affiliation(s)
- Maëlig Chauvel
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France.
| | - Ivy Uszynski
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - Bastien Herlin
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France; Hôpital de la Pitié-Salpêtrière, 47-83 Boulevard de l'Hôpital, 75013 Paris, France
| | - Alexandros Popov
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - Yann Leprince
- UNIACT, NeuroSpin, Université Paris-Saclay, CEA, Gif-sur-Yvette, France
| | - Jean-François Mangin
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - William D Hopkins
- Department of Comparative Medicine, Michale E Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, United States of America
| | - Cyril Poupon
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France.
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3
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Zhu J, Margulies D, Qiu A. White matter functional gradients and their formation in adolescence. Cereb Cortex 2023; 33:10770-10783. [PMID: 37727985 DOI: 10.1093/cercor/bhad319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 09/21/2023] Open
Abstract
It is well known that functional magnetic resonance imaging (fMRI) is a widely used tool for studying brain activity. Recent research has shown that fluctuations in fMRI data can reflect functionally meaningful patterns of brain activity within the white matter. We leveraged resting-state fMRI from an adolescent population to characterize large-scale white matter functional gradients and their formation during adolescence. The white matter showed gray-matter-like unimodal-to-transmodal and sensorimotor-to-visual gradients with specific cognitive associations and a unique superficial-to-deep gradient with nonspecific cognitive associations. We propose two mechanisms for their formation in adolescence. One is a "function-molded" mechanism that may mediate the maturation of the transmodal white matter via the transmodal gray matter. The other is a "structure-root" mechanism that may support the mutual mediation roles of the unimodal and transmodal white matter maturation during adolescence. Thus, the spatial layout of the white matter functional gradients is in concert with the gray matter functional organization. The formation of the white matter functional gradients may be driven by brain anatomical wiring and functional needs.
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Affiliation(s)
- Jingwen Zhu
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
| | - Daniel Margulies
- Integrative Neuroscience and Cognition Center, Centre National de la Recherche Scientifique (CNRS) and Université de Paris, 45 Rue des Saint-Pères, 75006 Paris, France
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- NUS (Suzhou) Research Institute, National University of Singapore, No. 377 Linquan Street, Suzhou 215000, China
- The N.1 Institute for Health, National University of Singapore, 28 Medical Dr, Singapore 117456, Singapore
- Institute of Data Science, National University of Singapore, 3 Research Link, #04-06, Singapore 117602, Singapore
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Kowloon, Hong Kong
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
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4
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Schilling KG, Archer D, Rheault F, Lyu I, Huo Y, Cai LY, Bunge SA, Weiner KS, Gore JC, Anderson AW, Landman BA. Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features. Brain Struct Funct 2023; 228:1019-1031. [PMID: 37074446 PMCID: PMC10320929 DOI: 10.1007/s00429-023-02642-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 04/08/2023] [Indexed: 04/20/2023]
Abstract
Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA.
| | - Derek Archer
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yuankai Huo
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Silvia A Bunge
- Department of Psychology, University of California at Berkeley, Berkeley, USA
| | - Kevin S Weiner
- Department of Psychology, University of California at Berkeley, Berkeley, USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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Xue T, Zhang F, Zhang C, Chen Y, Song Y, Golby AJ, Makris N, Rathi Y, Cai W, O'Donnell LJ. Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions. Med Image Anal 2023; 85:102759. [PMID: 36706638 PMCID: PMC9975054 DOI: 10.1016/j.media.2023.102759] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 01/05/2023] [Accepted: 01/20/2023] [Indexed: 01/24/2023]
Abstract
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts. It enables quantification and visualization of whole-brain tractography. Currently, most parcellation methods focus on the deep white matter (DWM), whereas fewer methods address the superficial white matter (SWM) due to its complexity. We propose a novel two-stage deep-learning-based framework, Superficial White Matter Analysis (SupWMA), that performs an efficient and consistent parcellation of 198 SWM clusters from whole-brain tractography. A point-cloud-based network is adapted to our SWM parcellation task, and supervised contrastive learning enables more discriminative representations between plausible streamlines and outliers for SWM. We train our model on a large-scale tractography dataset including streamline samples from labeled long- and medium-range (over 40 mm) SWM clusters and anatomically implausible streamline samples, and we perform testing on six independently acquired datasets of different ages and health conditions (including neonates and patients with space-occupying brain tumors). Compared to several state-of-the-art methods, SupWMA obtains highly consistent and accurate SWM parcellation results on all datasets, showing good generalization across the lifespan in health and disease. In addition, the computational speed of SupWMA is much faster than other methods.
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Affiliation(s)
- Tengfei Xue
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA; School of Computer Science, University of Sydney, Sydney, Australia
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | - Chaoyi Zhang
- School of Computer Science, University of Sydney, Sydney, Australia
| | - Yuqian Chen
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA; School of Computer Science, University of Sydney, Sydney, Australia
| | - Yang Song
- School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
| | | | - Nikos Makris
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA; Center for Morphometric Analysis, Massachusetts General Hospital, Boston, USA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Weidong Cai
- School of Computer Science, University of Sydney, Sydney, Australia
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Gagnon A, Grenier G, Bocti C, Gillet V, Lepage JF, Baccarelli AA, Posner J, Descoteaux M, Takser L. White matter microstructural variability linked to differential attentional skills and impulsive behavior in a pediatric population. Cereb Cortex 2023; 33:1895-1912. [PMID: 35535719 PMCID: PMC9977366 DOI: 10.1093/cercor/bhac180] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 11/14/2022] Open
Abstract
Structural and functional magnetic resonance imaging (MRI) studies have suggested a neuroanatomical basis that may underly attention-deficit-hyperactivity disorder (ADHD), but the anatomical ground truth remains unknown. In addition, the role of the white matter (WM) microstructure related to attention and impulsivity in a general pediatric population is still not well understood. Using a state-of-the-art structural connectivity pipeline based on the Brainnetome atlas extracting WM connections and its subsections, we applied dimensionality reduction techniques to obtain biologically interpretable WM measures. We selected the top 10 connections-of-interests (located in frontal, parietal, occipital, and basal ganglia regions) with robust anatomical and statistical criteria. We correlated WM measures with psychometric test metrics (Conner's Continuous Performance Test 3) in 171 children (27 Dx ADHD, 3Dx ASD, 9-13 years old) from the population-based GESTation and Environment cohort. We found that children with lower microstructural complexity and lower axonal density show a higher impulsive behavior on these connections. When segmenting each connection in subsections, we report WM alterations localized in one or both endpoints reflecting a specific localization of WM alterations along each connection. These results provide new insight in understanding the neurophysiology of attention and impulsivity in a general population.
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Affiliation(s)
- Anthony Gagnon
- Department of Pediatrics, University of Sherbrooke, Sherbrooke, Quebec, Canada
| | - Gabrielle Grenier
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Christian Bocti
- Department of Medicine, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Research Center on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, Quebec, Canada
| | - Virginie Gillet
- Department of Pediatrics, University of Sherbrooke, Sherbrooke, Quebec, Canada
| | | | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | | | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Imeka Solutions Inc, Sherbrooke, QC, Canada
| | - Larissa Takser
- Department of Pediatrics, University of Sherbrooke, Sherbrooke, Quebec, Canada
- Department of Psychiatry, University of Sherbrooke, Sherbrooke, Québec, Canada
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Oyefiade A, Parthab N, Skocic J, Moxon-Emre I, Tabori U, Bouffet E, Ramaswamy V, Laughlin S, Mabbott DJ. Insult to Short-Range White Matter Connectivity in Childhood Brain Tumor Survivors. Int J Radiat Oncol Biol Phys 2023:S0360-3016(23)00068-8. [PMID: 36706870 DOI: 10.1016/j.ijrobp.2023.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 01/10/2023] [Accepted: 01/16/2023] [Indexed: 01/26/2023]
Abstract
PURPOSE Children treated for brain tumors are at an increased risk for cognitive impairments due to the effect of radiation therapy on developing white matter (WM). Although damage to long-range WM is well documented in pediatric brain tumor survivors, the effect of radiation therapy on short-range WM remains unelucidated. We sought to clarify whether radiation treatment affects short-range WM by completing a virtual dissection of these connections and comparing their microstructural properties between brain tumor survivors and typically developing children. METHODS AND MATERIALS T1-weighted and diffusion-weighted magnetic resonance images were acquired for 26 brain tumor survivors and 26 typically developing children. Short-range WM was delineated using a novel, whole-brain approach. A random forest classifier was used to identify short-range connections with the largest differences in microstructure between patients and typically developing children. RESULTS The random forest classifier identified differences in short-range WM microstructure across the brain with an accuracy of 87.5%. Nine connections showed the largest differences in short-range WM between patients and typically developing children. For these connections, fractional anisotropy and axial diffusivity were significantly lower in patients. Short-range connections in the posterior fossa were disproportionately affected, suggesting that greater radiation exposure to the posterior fossa was more injurious to short-range WM. Lower craniospinal radiation dose did not predict reduced toxicity to short-range WM. CONCLUSIONS Our findings indicate that treatment for medulloblastoma resulted in changes in short-range WM in patients. Lower fractional anisotropy and axial diffusivity may reflect altered microstructural organization and coherence of these connections, especially in the posterior fossa. Short-range WM may be especially sensitive to the effect of craniospinal radiation therapy, resulting in compromise to these connections regardless of dose.
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Affiliation(s)
- Adeoye Oyefiade
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Nadeem Parthab
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jovanka Skocic
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Iska Moxon-Emre
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Uri Tabori
- Divisions of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Eric Bouffet
- Divisions of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Vijay Ramaswamy
- Divisions of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Susanne Laughlin
- Divisions of Radiology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Donald J Mabbott
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychology, University of Toronto, Toronto, Ontario, Canada.
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Pietrasik W, Cribben I, Olsen F, Malykhin N. Diffusion tensor imaging of superficial prefrontal white matter in healthy aging. Brain Res 2023; 1799:148152. [PMID: 36343726 DOI: 10.1016/j.brainres.2022.148152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/27/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.
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Affiliation(s)
- Wojciech Pietrasik
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Ivor Cribben
- Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Department of Accounting & Business Analytics, Alberta School of Business, University of Alberta, Edmonton, Alberta, Canada
| | - Fraser Olsen
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Nikolai Malykhin
- Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada.
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9
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Schilling KG, Archer D, Yeh FC, Rheault F, Cai LY, Shafer A, Resnick SM, Hohman T, Jefferson A, Anderson AW, Kang H, Landman BA. Short superficial white matter and aging: a longitudinal multi-site study of 1293 subjects and 2711 sessions. Aging Brain 2023; 3:100067. [PMID: 36817413 PMCID: PMC9937516 DOI: 10.1016/j.nbas.2023.100067] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
It is estimated that short association fibers running immediately beneath the cortex may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in superficial white matter (SWM) tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several SWM systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in SWM throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of SWM volume and length decrease with age in a heterogenous manner across the brain, with different rates of change in inter-gyri and intra-gyri SWM, and at slower rates than well-studied long-range white matter pathways. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Derek Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Leon Y Cai
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Andrea Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Timothy Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Angela Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam W Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN, United States
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
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Oyefiade A, Moxon-Emre I, Beera K, Bouffet E, Taylor M, Ramaswamy V, Laughlin S, Skocic J, Mabbott D. Abnormalities of Structural Brain Connectivity in Pediatric Brain Tumor Survivors. Neurooncol Adv 2022; 4:vdac064. [PMID: 35875689 PMCID: PMC9297943 DOI: 10.1093/noajnl/vdac064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Background Pediatric brain tumor survivors are at an increased risk for white matter (WM) injury. However, damage to whole-brain structural connectivity is unelucidated. The impact of treatment on WM connectivity was investigated. Methods Whole-brain WM networks were derived from diffusion tensor imaging data acquired for 28 irradiated patients (radiotherapy, RT) (mean age = 13.74 ± 3.32 years), 13 patients not irradiated (No RT) (mean age = 12.57 ± 2.87), and 41 typically developing children (TDC) (mean age = 13.32 ± 2.92 years). Differences in network properties were analyzed using robust regressions. Results Participation coefficient was lower in both patient groups (RT: adj. P = .015; No RT: adj. P = .042). Compared to TDC, RT had greater clustering (adj. P = .015), local efficiency (adj. P = .003), and modularity (adj. P = .000003). WM traced from hubs was damaged in patients: left hemisphere pericallosal sulcus (FA [F = 4.97; q < 0.01]; MD [F = 11.02; q < 0.0001]; AD [F = 10.00; q < 0.0001]; RD [F = 8.53; q < 0.0001]), right hemisphere pericallosal sulcus (FA [F = 8.87; q < 0.0001]; RD [F = 8.27; q < 0.001]), and right hemisphere parietooccipital sulcus (MD [F = 5.78; q < 0.05]; RD [F = 5.12; q < 0.05]). Conclusions Findings indicate greater segregation of WM networks after RT. Intermodular connectivity was lower after treatment with and without RT. No significant network differences were observed between patient groups. Our results are discussed in the context of a network approach that emphasizes interactions between brain regions.
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Affiliation(s)
- Adeoye Oyefiade
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
- Department of Psychology, University of Toronto, Toronto, Ontario
| | - Iska Moxon-Emre
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Kiran Beera
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Eric Bouffet
- Division of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario
| | - Michael Taylor
- Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario
| | - Vijay Ramaswamy
- Division of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario
| | - Suzanne Laughlin
- Division of Radiology, The Hospital for Sick Children, Toronto, Ontario
| | - Jovanka Skocic
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Donald Mabbott
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
- Division of Hematology/Oncology, The Hospital for Sick Children, Toronto, Ontario
- Department of Psychology, University of Toronto, Toronto, Ontario
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11
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Guevara M, Sun ZY, Guevara P, Rivière D, Grigis A, Poupon C, Mangin JF. Disentangling the variability of the superficial white matter organization using regional-tractogram-based population stratification. Neuroimage 2022; 255:119197. [PMID: 35417753 DOI: 10.1016/j.neuroimage.2022.119197] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 03/10/2022] [Accepted: 04/07/2022] [Indexed: 11/22/2022] Open
Abstract
Each variation of the cortical folding pattern implies a particular rearrangement of the geometry of the fibers of the underlying white matter. While this rearrangement only impacts the ends of the long pathways, it may affect most of the trajectory of the short bundles. Therefore, mapping the short fibers of the human brain using diffusion-based tractography requires a dedicated strategy to overcome the variability of the folding patterns. In this paper, we propose a fiber-based stratification strategy splitting the population into homogeneous groups for disentangling the superficial white matter bundle organization. This strategy introduces a new refined fiber distance which includes angular considerations for inferring fine-grained atlases of the short bundles surrounding a specific sulcus and a subtractogram distance that quantifies the similitude between fiber sets of two different subjects. The stratification splits the population into groups with similar regional fiber organization using manifold learning. We first successfully test the hypothesis that the main source of variability of the regional fiber organization is the variability of the regional folding pattern. Then, in each group, we proceed with the automatic identification of the most stable bundles, at a higher granularity level than what can be achieved with the non-stratified whole population, enabling the disentanglement of the very variable configuration of the short fibers. Finally, the method searches for bundle correspondence across groups to build a population level atlas. As a proof of concept, the atlas refinement achieved by this strategy is illustrated for the fibers that surround the central sulcus and the superior temporal sulcus using the HCP dataset.
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12
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Yuan S, Liu M, Kim S, Yang J, Barkovich AJ, Xu D, Kim H. Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates. Cereb Cortex 2022; 33:357-373. [PMID: 35235643 PMCID: PMC9837610 DOI: 10.1093/cercor/bhac071] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/19/2023] Open
Abstract
The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.
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Affiliation(s)
| | | | | | - Jingda Yang
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Anthony James Barkovich
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hosung Kim
- Corresponding author: 2025 Zonal Ave, Los Angeles, CA 90033, USA.
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13
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Zhao Y, Li Q, Du J, He H, Liang P, Lu J, Li K. Exploring the Relationship between Gray and White Matter in Healthy Adults: A Hybrid Research of Cortical Reconstruction and Tractography. Biomed Res Int 2021; 2021:6628506. [PMID: 33778072 DOI: 10.1155/2021/6628506] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 02/15/2021] [Accepted: 03/04/2021] [Indexed: 11/18/2022]
Abstract
The gray matter (GM) and white matter (WM) are structurally and functionally related in the human brain. Among the numerous neuroimaging studies, yet only a few have investigated these two structures in the same sample. So, there is limited and inconsistent information about how they are correlated in the brain of healthy adults. In this study, we combined cortical reconstruction with diffusion spectrum imaging (DSI) tractography to investigate the relationship between cortical morphology and microstructural properties of major WM tracts in 163 healthy young adults. The results showed that cortical thickness (CTh) was positively correlated with the coherent tract-wise fractional anisotropy (FA) value, and the correlation was stronger in the dorsal areas than in the ventral areas. For other diffusion parameters, CTh was positively correlated with axial diffusivity (AD) of coherent fibers in the frontal areas and negatively correlated with radial diffusivity (RD) of coherent fibers in the dorsal areas. These findings suggest that the correlation between GM and WM is inhomogeneity and could be interpreted with different mechanisms in different brain regions. We hope our research could provide new insights into the studies of diseases in which the GM and WM are both affected.
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14
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Rodriguez-Vieitez E, Montal V, Sepulcre J, Lois C, Hanseeuw B, Vilaplana E, Schultz AP, Properzi MJ, Scott MR, Amariglio R, Papp KV, Marshall GA, Fortea J, Johnson KA, Sperling RA, Vannini P. Association of cortical microstructure with amyloid-β and tau: impact on cognitive decline, neurodegeneration, and clinical progression in older adults. Mol Psychiatry 2021; 26:7813-7822. [PMID: 34588623 PMCID: PMC8873001 DOI: 10.1038/s41380-021-01290-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 08/16/2021] [Accepted: 09/03/2021] [Indexed: 02/07/2023]
Abstract
Noninvasive biomarkers of early neuronal injury may help identify cognitively normal individuals at risk of developing Alzheimer's disease (AD). A recent diffusion-weighted imaging (DWI) method allows assessing cortical microstructure via cortical mean diffusivity (cMD), suggested to be more sensitive than macrostructural neurodegeneration. Here, we aimed to investigate the association of cMD with amyloid-β and tau pathology in older adults, and whether cMD predicts longitudinal cognitive decline, neurodegeneration and clinical progression. The study sample comprised n = 196 cognitively normal older adults (mean[SD] 72.5 [9.4] years; 114 women [58.2%]) from the Harvard Aging Brain Study. At baseline, all participants underwent structural MRI, DWI, 11C-Pittsburgh compound-B-PET, 18F-flortaucipir-PET imaging, and cognitive assessments. Longitudinal measures of Preclinical Alzheimer Cognitive Composite-5 were available for n = 186 individuals over 3.72 (1.96)-year follow-up. Prospective clinical follow-up was available for n = 163 individuals over 3.2 (1.7) years. Surface-based image analysis assessed vertex-wise relationships between cMD, global amyloid-β, and entorhinal and inferior-temporal tau. Multivariable regression, mixed effects models and Cox proportional hazards regression assessed longitudinal cognition, brain structural changes and clinical progression. Tau, but not amyloid-β, was positively associated with cMD in AD-vulnerable regions. Correcting for baseline demographics and cognition, increased cMD predicted steeper cognitive decline, which remained significant after correcting for amyloid-β, thickness, and entorhinal tau; there was a synergistic interaction between cMD and both amyloid-β and tau on cognitive slope. Regional cMD predicted hippocampal atrophy rate, independently from amyloid-β, tau, and thickness. Elevated cMD predicted progression to mild cognitive impairment. Cortical microstructure is a noninvasive biomarker that independently predicts subsequent cognitive decline, neurodegeneration and clinical progression, suggesting utility in clinical trials.
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Affiliation(s)
- Elena Rodriguez-Vieitez
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.4714.60000 0004 1937 0626Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Victor Montal
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jorge Sepulcre
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Cristina Lois
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Bernard Hanseeuw
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA ,grid.7942.80000 0001 2294 713XSaint Luc University Hospital, Université Catholique de Louvain, Brussels, Belgium
| | - Eduard Vilaplana
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Aaron P. Schultz
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA
| | - Michael J. Properzi
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Matthew R. Scott
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA
| | - Rebecca Amariglio
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Kathryn V. Papp
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Gad A. Marshall
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Juan Fortea
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Keith A. Johnson
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Reisa A. Sperling
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Patrizia Vannini
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA. .,Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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15
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Säisänen L, Könönen M, Niskanen E, Lakka T, Lintu N, Vanninen R, Julkunen P, Määttä S. Primary hand motor representation areas in healthy children, preadolescents, adolescents, and adults. Neuroimage 2020; 228:117702. [PMID: 33385558 DOI: 10.1016/j.neuroimage.2020.117702] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 12/16/2020] [Accepted: 12/19/2020] [Indexed: 01/28/2023] Open
Abstract
The development of the organization of the motor representation areas in children and adolescents is not well-known. This cross-sectional study aimed to provide an understanding for the development of the functional motor areas of the upper extremity muscles by studying healthy right-handed children (6-9 years, n = 10), preadolescents (10-12 years, n = 13), adolescents (15-17 years, n = 12), and adults (22-34 years, n = 12). The optimal representation site and resting motor threshold (rMT) for the abductor pollicis brevis (APB) were assessed in both hemispheres using navigated transcranial magnetic stimulation (nTMS). Motor mapping was performed at 110% of the rMT while recording the EMG of six upper limb muscles in the hand and forearm. The association between the motor map and manual dexterity (box and block test, BBT) was examined. The mapping was well-tolerated and feasible in all but the youngest participant whose rMT exceeded the maximum stimulator output. The centers-of-gravity (CoG) for individual muscles were scattered to the greatest extent in the group of preadolescents and centered and became more focused with age. In preadolescents, the CoGs in the left hemisphere were located more laterally, and they shifted medially with age. The proportion of hand compared to arm representation increased with age (p = 0.001); in the right hemisphere, this was associated with greater fine motor ability. Similarly, there was less overlap between hand and forearm muscles representations in children compared to adults (p<0.001). There was a posterior-anterior shift in the APB hotspot coordinate with age, and the APB coordinate in the left hemisphere exhibited a lateral to medial shift with age from adolescence to adulthood (p = 0.006). Our results contribute to the elucidation of the developmental course in the organization of the motor cortex and its associations with fine motor skills. It was shown that nTMS motor mapping in relaxed muscles is feasible in developmental studies in children older than seven years of age.
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Affiliation(s)
- Laura Säisänen
- Department of Clinical Neurophysiology, Kuopio University Hospital, P.O. Box 100, 70029 KYS, Kuopio, Finland; Institute of Clinical Medicine, University of Eastern Finland, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
| | - Mervi Könönen
- Department of Clinical Neurophysiology, Kuopio University Hospital, P.O. Box 100, 70029 KYS, Kuopio, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Eini Niskanen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Timo Lakka
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Finland; Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Niina Lintu
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Finland
| | - Ritva Vanninen
- Institute of Clinical Medicine, University of Eastern Finland, Finland; Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Petro Julkunen
- Department of Clinical Neurophysiology, Kuopio University Hospital, P.O. Box 100, 70029 KYS, Kuopio, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Sara Määttä
- Department of Clinical Neurophysiology, Kuopio University Hospital, P.O. Box 100, 70029 KYS, Kuopio, Finland
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16
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Hong J, Feng Z, Wang SH, Peet A, Zhang YD, Sun Y, Yang M. Brain Age Prediction of Children Using Routine Brain MR Images via Deep Learning. Front Neurol 2020; 11:584682. [PMID: 33193046 PMCID: PMC7604456 DOI: 10.3389/fneur.2020.584682] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 09/04/2020] [Indexed: 01/26/2023] Open
Abstract
Predicting brain age of children accurately and quantitatively can give help in brain development analysis and brain disease diagnosis. Traditional methods to estimate brain age based on 3D magnetic resonance (MR), T1 weighted imaging (T1WI), and diffusion tensor imaging (DTI) need complex preprocessing and extra scanning time, decreasing clinical practice, especially in children. This research aims at proposing an end-to-end AI system based on deep learning to predict the brain age based on routine brain MR imaging. We spent over 5 years enrolling 220 stacked 2D routine clinical brain MR T1-weighted images of healthy children aged 0 to 5 years old and randomly divided those images into training data including 176 subjects and test data including 44 subjects. Data augmentation technology, which includes scaling, image rotation, translation, and gamma correction, was employed to extend the training data. A 10-layer 3D convolutional neural network (CNN) was designed for predicting the brain age of children and it achieved reliable and accurate results on test data with a mean absolute deviation (MAE) of 67.6 days, a root mean squared error (RMSE) of 96.1 days, a mean relative error (MRE) of 8.2%, a correlation coefficient (R) of 0.985, and a coefficient of determination (R 2) of 0.971. Specially, the performance on predicting the age of children under 2 years old with a MAE of 28.9 days, a RMSE of 37.0 days, a MRE of 7.8%, a R of 0.983, and a R 2 of 0.967 is much better than that over 2 with a MAE of 110.0 days, a RMSE of 133.5 days, a MRE of 8.2%, a R of 0.883, and a R 2 of 0.780.
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Affiliation(s)
- Jin Hong
- School of Informatics, University of Leicester, Leicester, United Kingdom
- Department of Radiology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Zhangzhi Feng
- Department of Radiology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Shui-Hua Wang
- School of Architecture Building and Civil Engineering, Loughborough University, Loughborough, United Kingdom
- School of Mathematics and Actuarial Science, University of Leicester, Leicester, United Kingdom
| | - Andrew Peet
- Institute of Cancer & Genomic Science, University of Birmingham, Birmingham, United Kingdom
| | - Yu-Dong Zhang
- School of Informatics, University of Leicester, Leicester, United Kingdom
- Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Yu Sun
- Institute of Cancer & Genomic Science, University of Birmingham, Birmingham, United Kingdom
- International Laboratory for Children's Medical Imaging Research, School of Biology Science and Medical Engineering, Southeast University, Nanjing, China
| | - Ming Yang
- Department of Radiology, Children's Hospital of Nanjing Medical University, Nanjing, China
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17
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Hong SJ, Hyung B, Paquola C, Bernhardt BC. The Superficial White Matter in Autism and Its Role in Connectivity Anomalies and Symptom Severity. Cereb Cortex 2020; 29:4415-4425. [PMID: 30566613 DOI: 10.1093/cercor/bhy321] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/11/2018] [Accepted: 11/26/2018] [Indexed: 12/29/2022] Open
Abstract
In autism spectrum disorders (ASDs), the majority of neuroimaging studies have focused on the analysis of cortical morphology. White matter changes remain less understood, particularly their association to cortical structure and function. Here, we focused on region that has gained only little attention in ASD neuroimaging: the superficial white matter (SWM) immediately beneath the cortical interface, a compartment playing a prominent role in corticogenesis that incorporates long- and short-range fibers implicated in corticocortical connectivity. Studying a multicentric dataset of ASD and neurotypical controls, we harnessed surface-based techniques to aggregate microstructural SWM diffusion features. Multivariate analysis revealed SWM anomalies in ASD compared with controls in medial parietal and temporoparietal regions. Effects were similar in children and adolescents/adults and consistent across sites. Although SWM anomalies were more confined when correcting for cortical thickness and surface area, findings were overall robust. Diffusion anomalies modulated functional connectivity reductions in ASD and related to symptom severity. Furthermore, mediation models indicated a link between SWM changes, functional connectivity, and symptom load. Analyses targeting the SWM offer a novel perspective on the interplay between structural and functional network perturbations in ASD, highlighting a potentially important neurobiological substrate contributing to its diverse behavioral phenotype.
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Affiliation(s)
- Seok-Jun Hong
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada.,Center for the Developing Brain, Child Mind Institute, 101 E 56th St, New York, NY 10022, USA
| | - Brian Hyung
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
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18
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Guevara M, Guevara P, Román C, Mangin JF. Superficial white matter: A review on the dMRI analysis methods and applications. Neuroimage 2020; 212:116673. [DOI: 10.1016/j.neuroimage.2020.116673] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 02/17/2020] [Accepted: 02/19/2020] [Indexed: 12/12/2022] Open
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Vilaplana E, Rodriguez-Vieitez E, Ferreira D, Montal V, Almkvist O, Wall A, Lleó A, Westman E, Graff C, Fortea J, Nordberg A. Cortical microstructural correlates of astrocytosis in autosomal-dominant Alzheimer disease. Neurology 2020; 94:e2026-e2036. [PMID: 32291295 PMCID: PMC7282881 DOI: 10.1212/wnl.0000000000009405] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 11/18/2019] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE To study the macrostructural and microstructural MRI correlates of brain astrocytosis, measured with 11C-deuterium-L-deprenyl (11C-DED)-PET, in familial autosomal-dominant Alzheimer disease (ADAD). METHODS The total sample (n = 31) comprised ADAD mutation carriers (n = 10 presymptomatic, 39.2 ± 10.6 years old; n = 3 symptomatic, 55.5 ± 2.0 years old) and noncarriers (n = 18, 44.0 ± 13.7 years old) belonging to families with mutations in either the presenilin-1 or amyloid precursor protein genes. All participants underwent structural and diffusion MRI and neuropsychological assessment, and 20 participants (6 presymptomatic and 3 symptomatic mutation carriers and 11 noncarriers) also underwent 11C-DED-PET. RESULTS Vertex-wise interaction analyses revealed a differential relationship between carriers and noncarriers in the association between 11C-DED binding and estimated years to onset (EYO) and between cortical mean diffusivity (MD) and EYO. These differences were due to higher 11C-DED binding in presymptomatic carriers, with lower binding in symptomatic carriers compared to noncarriers, and to lower cortical MD in presymptomatic carriers, with higher MD in symptomatic carriers compared to noncarriers. Using a vertex-wise local correlation approach, 11C-DED binding was negatively correlated with cortical MD and positively correlated with cortical thickness. CONCLUSIONS Our proof-of-concept study is the first to show that microstructural and macrostructural changes can reflect underlying neuroinflammatory mechanisms in early stages of Alzheimer disease (AD). The findings support a role for neuroinflammation in AD pathogenesis, with potential implications for the correct interpretation of neuroimaging biomarkers as surrogate endpoints in clinical trials.
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Affiliation(s)
- Eduard Vilaplana
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Elena Rodriguez-Vieitez
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Daniel Ferreira
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Victor Montal
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Ove Almkvist
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Anders Wall
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Alberto Lleó
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Eric Westman
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Caroline Graff
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Juan Fortea
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Agneta Nordberg
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
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20
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Movahedian Attar F, Kirilina E, Haenelt D, Pine KJ, Trampel R, Edwards LJ, Weiskopf N. Mapping Short Association Fibers in the Early Cortical Visual Processing Stream Using In Vivo Diffusion Tractography. Cereb Cortex 2020; 30:4496-4514. [PMID: 32297628 PMCID: PMC7325803 DOI: 10.1093/cercor/bhaa049] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Short association fibers (U-fibers) connect proximal cortical areas and constitute the majority of white matter connections in the human brain. U-fibers play an important role in brain development, function, and pathology but are underrepresented in current descriptions of the human brain connectome, primarily due to methodological challenges in diffusion magnetic resonance imaging (dMRI) of these fibers. High spatial resolution and dedicated fiber and tractography models are required to reliably map the U-fibers. Moreover, limited quantitative knowledge of their geometry and distribution makes validation of U-fiber tractography challenging. Submillimeter resolution diffusion MRI—facilitated by a cutting-edge MRI scanner with 300 mT/m maximum gradient amplitude—was used to map U-fiber connectivity between primary and secondary visual cortical areas (V1 and V2, respectively) in vivo. V1 and V2 retinotopic maps were obtained using functional MRI at 7T. The mapped V1–V2 connectivity was retinotopically organized, demonstrating higher connectivity for retinotopically corresponding areas in V1 and V2 as expected. The results were highly reproducible, as demonstrated by repeated measurements in the same participants and by an independent replication group study. This study demonstrates a robust U-fiber connectivity mapping in vivo and is an important step toward construction of a more complete human brain connectome.
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Affiliation(s)
- Fakhereh Movahedian Attar
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany.,Department of Education and Psychology, Center for Cognitive Neuroscience Berlin, Free University Berlin, 14195 Berlin, Germany
| | - Daniel Haenelt
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany.,Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, 04109 Leipzig, Germany
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21
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Lynch KM, Cabeen RP, Toga AW, Clark KA. Magnitude and timing of major white matter tract maturation from infancy through adolescence with NODDI. Neuroimage 2020; 212:116672. [PMID: 32092432 PMCID: PMC7224237 DOI: 10.1016/j.neuroimage.2020.116672] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 01/19/2020] [Accepted: 02/18/2020] [Indexed: 01/11/2023] Open
Abstract
White matter maturation is a nonlinear and heterogeneous phenomenon characterized by axonal packing, increased axon caliber, and a prolonged period of myelination. While current in vivo diffusion MRI (dMRI) methods, like diffusion tensor imaging (DTI), have successfully characterized the gross structure of major white matter tracts, these measures lack the specificity required to unravel the distinct processes that contribute to microstructural development. Neurite orientation dispersion and density imaging (NODDI) is a dMRI approach that probes tissue compartments and provides biologically meaningful measures that quantify neurite density index (NDI) and orientation dispersion index (ODI). The purpose of this study was to characterize the magnitude and timing of major white matter tract maturation with NODDI from infancy through adolescence in a cross-sectional cohort of 104 subjects (0.6–18.8 years). To probe the regional nature of white matter development, we use an along-tract approach that partitions tracts to enable more fine-grained analysis. Major white matter tracts showed exponential age-related changes in NDI with distinct maturational patterns. Overall, analyses revealed callosal fibers developed before association fibers. Our along-tract analyses elucidate spatially varying patterns of maturation with NDI that are distinct from those obtained with DTI. ODI was not significantly associated with age in the majority of tracts. Our results support the conclusion that white matter tract maturation is heterochronous process and, furthermore, we demonstrate regional variability in the developmental timing within major white matter tracts. Together, these results help to disentangle the distinct processes that contribute to and more specifically define the time course of white matter maturation.
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Affiliation(s)
- Kirsten M Lynch
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kristi A Clark
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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22
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Beer AL, Plank T, Greenlee MW. Aging and central vision loss: Relationship between the cortical macro-structure and micro-structure. Neuroimage 2020; 212:116670. [PMID: 32088318 DOI: 10.1016/j.neuroimage.2020.116670] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 02/13/2020] [Accepted: 02/17/2020] [Indexed: 12/17/2022] Open
Abstract
Aging and central vision loss are associated with cortical atrophies, but little is known about the relationship between cortical thinning and the underlying cellular structure. We compared the macro- and micro-structure of the cortical gray and superficial white matter of 38 patients with juvenile (JMD) or age-related (AMD) macular degeneration and 38 healthy humans (19-84 years) by multimodal MRI including diffusion-tensor imaging (DTI). A factor analysis showed that cortical thickness, tissue-dependent measures, and DTI-based measures were sensitive to distinct components of brain structure. Age-related cortical thinning and increased diffusion were observed across most of the cortex, but increased T1-weighted intensities (frontal), reduced T2-weighted intensities (occipital), and reduced anisotropy (medial) were limited to confined cortical regions. Vision loss was associated with cortical thinning and enhanced diffusion in the gray matter (less in the white matter) of the occipital central visual field representation. Moreover, AMD (but not JMD) patients showed enhanced diffusion in lateral occipito-temporal cortex and cortical thinning in the posterior cingulum. These findings demonstrate that changes in brain structure are best quantified by multimodal imaging. They further suggest that age-related brain atrophies (cortical thinning) reflect diverse micro-structural etiologies. Moreover, juvenile and age-related macular degeneration are associated with distinct patterns of micro-structural alterations.
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Affiliation(s)
- Anton L Beer
- Institut für Psychologie, Universität Regensburg, Regensburg, Germany.
| | - Tina Plank
- Institut für Psychologie, Universität Regensburg, Regensburg, Germany
| | - Mark W Greenlee
- Institut für Psychologie, Universität Regensburg, Regensburg, Germany
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23
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Gahm JK, Shi Y. Surface-based Tracking of U-fibers in the Superficial White Matter. Med Image Comput Comput Assist Interv 2019; 11766:538-546. [PMID: 33860288 PMCID: PMC8046261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The superficial white matter (SWM) lies directly underneath the cortical ribbon and contains the short association fibers, or U-fibers, that connect neighboring gyri. Connectivity of these U-fibers is important for various neuroscientific research from the development to the aging of the brain. Nonetheless, conventional tractography methods can only provide a partial representation of these connections. Moreover, previous studies on U-fibers mainly extract tracts based on their shape characteristics without imposing the biologically critical condition that they should tightly follow the cortical surface. In this work we leverage the high resolution diffusion imaging data from the Human Connectome Project (HCP), and develop a novel surface-based framework for reconstructing the U-fibers. Guided by the projected fiber orientation distributions (FODs) on cortical surfaces, our method tracks the U-fibers from sulcal seed regions to neighboring gyrus on the triangular mesh representation of the cortex. Compared to volume-based tractography, the main advantage of our method is that it is intrinsic to the cortical geometry. More specifically, we define a novel approach for measuring the change of angles on the tangent space of the surface and use them to determine the U-fiber passing through a sulcal seed point. In experimental results, we compare our surface-based method with state-of-the-art FOD-based tractography from MRtrix on a large-scale dataset of 484 HCP subjects, and demonstrate that our method clearly achieves superior performance on the reconstruction of U-fibers between the precentral and postcentral gyrus.
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24
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Han F, Perrin RJ, Wang Q, Wang Y, Perlmutter JS, Morris JC, Benzinger TLS, Xu J. Neuroinflammation and Myelin Status in Alzheimer's Disease, Parkinson's Disease, and Normal Aging Brains: A Small Sample Study. Parkinsons Dis 2019; 2019:7975407. [PMID: 31354934 PMCID: PMC6637678 DOI: 10.1155/2019/7975407] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/06/2019] [Accepted: 06/12/2019] [Indexed: 11/18/2022]
Abstract
Microglia and astrocytes play important roles in mediating the immune processes and nutritional support in the central nervous system (CNS). Neuroinflammation has been indicated in the progression of neurodegenerative diseases Alzheimer's disease (AD) and Parkinson's disease (PD). Chronic neuroinflammation with sustained activation of microglia and astrocytes may affect white matter tracts and disrupt communication between neurons. Recent studies indicate astrogliosis may inhibit remyelination in demyelinating disorders such as multiple sclerosis. In this study, we investigated the relationship between neuroinflammation and myelin status in postmortem human brain tissue (n = 15 including 6 AD, 5 PD, and 4 age-matched, neurologically normal controls (NC)). We conducted systematic and quantitative immunohistochemistry for glial fibrillary acidic protein (GFAP), ionized calcium-binding adaptor molecule 1 (Iba1), amyloid beta, and highly phosphorylated tau (tauopathy). White matter intactness was evaluated by myelin and axon staining in adjacent brain tissue sections. Eight of 15 cases (4 AD, 3 PD, and 1 NC) showed increased immunoreactivity for microglia and astrocytes in the white matter that connects striatum and cortex. Quantitative analysis of these 8 cases showed a significant negative correlation between GFAP (but not Iba-1) and myelin (but not axon) staining in white matter (r 2 = 0.78, p < 0.005). Tau, but not amyloid beta plaques, is significantly higher in AD vs. PD and NC. Tau burden increases with age in AD cases. These observations indicate that astrocytosis in white matter is associated with loss of myelin in AD, PD, and normal aging and that tau is a potent biomarker for AD.
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Affiliation(s)
- Fei Han
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Richard J. Perrin
- Department of Pathology & Immunology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Qing Wang
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Yong Wang
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Joel S. Perlmutter
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
- Department of Neuroscience, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
- Department of Physical Therapy, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
- Department of Occupational Therapy, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Tammie L. S. Benzinger
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Jinbin Xu
- Department of Radiology, Washington University School of Medicine, 510 S, Kingshighway Blvd, St. Louis, MO 63110, USA
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25
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Määttä S, Säisänen L, Kallioniemi E, Lakka TA, Lintu N, Haapala EA, Koskenkorva P, Niskanen E, Ferreri F, Könönen M. Maturation changes the excitability and effective connectivity of the frontal lobe: A developmental TMS-EEG study. Hum Brain Mapp 2019; 40:2320-2335. [PMID: 30648321 DOI: 10.1002/hbm.24525] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2018] [Revised: 12/07/2018] [Accepted: 01/07/2019] [Indexed: 12/22/2022] Open
Abstract
The combination of transcranial magnetic stimulation with simultaneous electroencephalography (TMS-EEG) offers direct neurophysiological insight into excitability and connectivity within neural circuits. However, there have been few developmental TMS-EEG studies to date, and they all have focused on primary motor cortex stimulation. In the present study, we used navigated high-density TMS-EEG to investigate the maturation of the superior frontal cortex (dorsal premotor cortex [PMd]), which is involved in a broad range of motor and cognitive functions known to develop with age. We demonstrated that reactivity to frontal cortex TMS decreases with development. We also showed that although frontal cortex TMS elicits an equally complex TEP waveform in all age groups, the statistically significant between-group differences in the topography of the TMS-evoked peaks and differences in current density maps suggest changes in effective connectivity of the right PMd with maturation. More generally, our results indicate that direct study of the brain's excitability and effective connectivity via TMS-EEG co-registration can also be applied to pediatric populations outside the primary motor cortex, and may provide useful information for developmental studies and studies on developmental neuropsychiatric disorders.
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Affiliation(s)
- Sara Määttä
- Faculty of Health Sciences, Department of Clinical Neurophysiology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio Campus, Finland.,Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Laura Säisänen
- Faculty of Health Sciences, Department of Clinical Neurophysiology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio Campus, Finland.,Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Elisa Kallioniemi
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Timo A Lakka
- Faculty of Health Sciences, Institute of Biomedicine, University of Eastern Finland, Kuopio Campus, Finland.,Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland.,Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Niina Lintu
- Faculty of Health Sciences, Institute of Biomedicine, University of Eastern Finland, Kuopio Campus, Finland
| | - Eero A Haapala
- Faculty of Health Sciences, Institute of Biomedicine, University of Eastern Finland, Kuopio Campus, Finland.,Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Päivi Koskenkorva
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Eini Niskanen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Florinda Ferreri
- Department of Neuroscience, Unit of Neurology and Neurophysiology, University of Padua, Padua, Italy
| | - Mervi Könönen
- Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
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26
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Lebel C, Treit S, Beaulieu C. A review of diffusion MRI of typical white matter development from early childhood to young adulthood. NMR Biomed 2019; 32:e3778. [PMID: 28886240 DOI: 10.1002/nbm.3778] [Citation(s) in RCA: 204] [Impact Index Per Article: 40.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 05/24/2017] [Accepted: 07/05/2017] [Indexed: 05/05/2023]
Abstract
Understanding typical, healthy brain development provides a baseline from which to detect and characterize brain anomalies associated with various neurological or psychiatric disorders and diseases. Diffusion MRI is well suited to study white matter development, as it can virtually extract individual tracts and yield parameters that may reflect alterations in the underlying neural micro-structure (e.g. myelination, axon density, fiber coherence), though it is limited by its lack of specificity and other methodological concerns. This review summarizes the last decade of diffusion imaging studies of healthy white matter development spanning childhood to early adulthood (4-35 years). Conclusions about anatomical location, rates, and timing of white matter development with age are discussed, as well as the influence of image acquisition, analysis, age range/sample size, and statistical model. Despite methodological variability between studies, some consistent findings have emerged from the literature. Specifically, diffusion studies of neurodevelopment overwhelmingly demonstrate regionally varying increases of fractional anisotropy and decreases of mean diffusivity during childhood and adolescence, some of which continue into adulthood. While most studies use linear fits to model age-related changes, studies with sufficient sample sizes and age range provide clear evidence that white matter development (as indicated by diffusion) is non-linear. Several studies further suggest that maturation in association tracts with frontal-temporal connections continues later than commissural and projection tracts. The emerging contributions of more advanced diffusion methods are also discussed, as they may reveal new aspects of white matter development. Although non-specific, diffusion changes may reflect increases of myelination, axonal packing, and/or coherence with age that may be associated with changes in cognition.
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Affiliation(s)
- Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
| | - Sarah Treit
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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Abstract
Brain maturation across childhood and adolescence is characterized by cortical thickness (CT) and volume contraction, and early expansion of surface area (SA). These processes occur asynchronously across the cortical surface, with functional, topographic, and network-based organizing principles proposed to account for developmental patterns. Characterizing regions undergoing synchronized development can help determine whether "maturational networks" overlap with well-described functional networks, and whether they are targeted by neurodevelopmental and psychiatric disorders. In the present study, we modeled changes with age in CT, SA, and volume from 335 typically developing subjects in the NIH MRI study of normal brain development, with 262 followed longitudinally for a total of 724 scans. Vertices showing similar maturation between 5 and 22 years were grouped together using data-driven clustering. Patterns of CT development distinguished sensory and motor regions from association regions, and were vastly different from SA patterns, which separated anterior from posterior regions. Developmental modules showed little similarity to networks derived from resting-state functional connectivity. Our findings present a novel perspective on maturational changes across the cortex, showing that several proposed organizing principles of cortical development co-exist, albeit in different structural parameters, and enable visualization of developmental trends occurring in parallel at remote cortical sites.
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Affiliation(s)
- Mark Krongold
- Child and Adolescent Imaging Research Program, Alberta Children's Hospital, Calgary, AB, Canada T3B 6A8.,Alberta Children's Hospital Research Institute, Calgary, AB, Canada T3B 6A8.,Biomedical Engineering Graduate Program
| | - Cassandra Cooper
- Child and Adolescent Imaging Research Program, Alberta Children's Hospital, Calgary, AB, Canada T3B 6A8.,Alberta Children's Hospital Research Institute, Calgary, AB, Canada T3B 6A8
| | - Signe Bray
- Child and Adolescent Imaging Research Program, Alberta Children's Hospital, Calgary, AB, Canada T3B 6A8.,Alberta Children's Hospital Research Institute, Calgary, AB, Canada T3B 6A8.,Department of Radiology, Cumming School of Medicine.,Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada T2N 1N4
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28
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Marzilli E, Cerniglia L, Cimino S. A narrative review of binge eating disorder in adolescence: prevalence, impact, and psychological treatment strategies. Adolesc Health Med Ther 2018; 9:17-30. [PMID: 29379325 PMCID: PMC5759856 DOI: 10.2147/ahmt.s148050] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Binge eating disorder (BED) represents one of the most problematic clinical conditions among youths. Research has shown that the developmental stage of adolescence is a critical stage for the onset of eating disorders (EDs), with a peak prevalence of BED at the age of 16–17 years. Several studies among adults with BED have underlined that it is associated with a broad spectrum of negative consequences, including higher concern about shape and weight, difficulties in social functioning, and emotional-behavioral problems. This review aimed to examine studies focused on the prevalence of BED in the adolescent population, its impact in terms of physical, social, and psychological outcomes, and possible strategies of psychological intervention. The review of international literature was made on paper material and electronic databases ProQuest, PsycArticles, and PsycInfo, and the Scopus index were used to verify the scientific relevance of the papers. Epidemiological research that examined the prevalence of BED in adolescent samples in accordance with Diagnostic and Statistical Manual of Mental Disorders, 4th Edition showed a prevalence ranging from 1% to 4%. More recently, only a few studies have investigated the prevalence of BED, in accordance with the Diagnostic and Statistical Manual of Disorders, Fifth Edition criteria, reporting a prevalence of ~1%–5%. Studies that focused on the possible impact that BED may have on physical, psychological, and social functioning showed that adolescents with BED have an increased risk of developing various adverse consequences, including obesity, social problems, substance use, suicidality, and other psychological difficulties, especially in the internalizing area. Despite the evidence, to date, reviews on possible and effective psychological treatment for BED among young population are rare and focused primarily on adolescent females.
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Affiliation(s)
- Eleonora Marzilli
- Department of Dynamic and Clinical Psychology, Psychology and Medicine Faculty, Sapienza - University of Rome
| | - Luca Cerniglia
- Department of Psychology, Psychology Faculty, International Telematic University Uninettuno, Rome, Italy
| | - Silvia Cimino
- Department of Dynamic and Clinical Psychology, Psychology and Medicine Faculty, Sapienza - University of Rome
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29
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Deng F, Zhao L, Liu C, Lu M, Zhang S, Huang H, Chen L, Wu X, Niu C, He Y, Wang J, Huang R. Plasticity in deep and superficial white matter: a DTI study in world class gymnasts. Brain Struct Funct 2017; 223:1849-1862. [PMID: 29250703 DOI: 10.1007/s00429-017-1594-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 12/12/2017] [Indexed: 12/20/2022]
Abstract
Brain white matter (WM) could be generally categorized into two types, deep and superficial WM. Studies combining these two types WM are important for a better understanding of brain plasticity induced by motor training. In this study, we applied both univariate and multivariate approaches to study gymnastic training-induced plasticity in brain WM. Specifically, we acquired diffusion tensor imaging data from 13 world class gymnasts and 14 non-athlete normal controls, reconstructed brain deep and superficial WM tracts, estimated and compared their fractional anisotropy (FA) difference between the two groups. Taking FA values as the features, we applied logistic regression and support vector machine to distinguish the gymnasts from the controls. Compared to the controls, the gymnasts showed lower FA in four regional deep WM tracts, including the occipital lobe portion of left inferior fronto-occipital fasciculus (IFOF.L), occipital and temporal lobe portion of right inferior longitudinal fasciculus (ILF.R), insular cortex portion of right uncinate fasciculus (UF.R), and parietal lobe portion of right arcuate fasciculus (AF.R). Meanwhile, we found lower FA in the superficial U-shaped tracts within the frontal lobe in the gymnasts compared to the controls. In addition, we detected that mean FA in either the AF.R or the U-shaped tracts connecting the left pars triangularis and superior frontal gyrus was negatively correlated with years of training in the gymnasts. Classification analyses indicated FA in deep WM hold higher potential to distinguish the gymnasts from the controls. Overall, our findings provide a more complete picture of training-induced plasticity in brain WM.
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Affiliation(s)
- Feng Deng
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Ling Zhao
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, 94720, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA
| | - Min Lu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, People's Republic of China
| | - Shufei Zhang
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Huiyuan Huang
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Lixiang Chen
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Xiaoyan Wu
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Chen Niu
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Yuan He
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Jun Wang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, People's Republic of China
| | - Ruiwang Huang
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China.
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30
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Tamnes CK, Roalf DR, Goddings AL, Lebel C. Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress. Dev Cogn Neurosci 2017; 33:161-175. [PMID: 29229299 PMCID: PMC6969268 DOI: 10.1016/j.dcn.2017.12.002] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 05/18/2017] [Accepted: 12/04/2017] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) continues to grow in popularity as a useful neuroimaging method to study brain development, and longitudinal studies that track the same individuals over time are emerging. Over the last decade, seminal work using dMRI has provided new insights into the development of brain white matter (WM) microstructure, connections and networks throughout childhood and adolescence. This review provides an introduction to dMRI, both diffusion tensor imaging (DTI) and other dMRI models, as well as common acquisition and analysis approaches. We highlight the difficulties associated with ascribing these imaging measurements and their changes over time to specific underlying cellular and molecular events. We also discuss selected methodological challenges that are of particular relevance for studies of development, including critical choices related to image acquisition, image analysis, quality control assessment, and the within-subject and longitudinal reliability of dMRI measurements. Next, we review the exciting progress in the characterization and understanding of brain development that has resulted from dMRI studies in childhood and adolescence, including brief overviews and discussions of studies focusing on sex and individual differences. Finally, we outline future directions that will be beneficial to the field.
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Affiliation(s)
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Catherine Lebel
- Department of Radiology, Cumming School of Medicine, and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
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31
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Montal V, Vilaplana E, Alcolea D, Pegueroles J, Pasternak O, González-Ortiz S, Clarimón J, Carmona-Iragui M, Illán-Gala I, Morenas-Rodríguez E, Ribosa-Nogué R, Sala I, Sánchez-Saudinós MB, García-Sebastian M, Villanúa J, Izagirre A, Estanga A, Ecay-Torres M, Iriondo A, Clerigue M, Tainta M, Pozueta A, González A, Martínez-Heras E, Llufriu S, Blesa R, Sanchez-Juan P, Martínez-Lage P, Lleó A, Fortea J. Cortical microstructural changes along the Alzheimer's disease continuum. Alzheimers Dement 2017; 14:340-351. [PMID: 29080407 DOI: 10.1016/j.jalz.2017.09.013] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Revised: 09/14/2017] [Accepted: 09/20/2017] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Cortical mean diffusivity (MD) and free water fraction (FW) changes are proposed biomarkers for Alzheimer's disease (AD). METHODS We included healthy control subjects (N = 254), mild cognitive impairment (N = 41), and AD dementia (N = 31) patients. Participants underwent a lumbar puncture and a 3 T magnetic resonance imaging. Healthy control subjects were classified following National Institute on Aging-Alzheimer's Association stages (stage 0, N = 220; stage 1, N = 25; and stage 2/3, N = 9). We assessed the cortical MD, cortical FW, and cortical thickness (CTh) changes along the AD continuum. RESULTS Microstructural and macrostructural changes show a biphasic trajectory. Stage 1 subjects showed increased CTh and decreased MD and FW with respect the stage 0 subjects. Stage 2/3 subjects showed decreased CTh and increased cortical MD and FW, changes that were more widespread in symptomatic stages. DISCUSSION These results support a biphasic model of changes in AD, which could affect the selection of patients for clinical trials and the use of magnetic resonance imaging as a surrogate marker of disease modification.
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Affiliation(s)
- Victor Montal
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Eduard Vilaplana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Daniel Alcolea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Jordi Pegueroles
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Jordi Clarimón
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - María Carmona-Iragui
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Ignacio Illán-Gala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Estrella Morenas-Rodríguez
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Roser Ribosa-Nogué
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Isabel Sala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - María-Belén Sánchez-Saudinós
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Maite García-Sebastian
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Jorge Villanúa
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain; Donostia Unit, Osatek SA, Donostia University Hospital, San Sebastian, Spain
| | - Andrea Izagirre
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Ainara Estanga
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Mirian Ecay-Torres
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Ane Iriondo
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Montserrat Clerigue
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Ana Pozueta
- Servicio de Neurología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Andrea González
- Servicio de Neurología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Eloy Martínez-Heras
- Center for Neuroimmunology, Hospital Clinic Barcelona, IDIBAPS, Barcelona, Spain
| | - Sara Llufriu
- Center for Neuroimmunology, Hospital Clinic Barcelona, IDIBAPS, Barcelona, Spain
| | - Rafael Blesa
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Pascual Sanchez-Juan
- Servicio de Neurología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Pablo Martínez-Lage
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain; Center for Research and Advanced Therapies and Memory Clinic, Fundacion CITA-Alzheimer Fundazioa, Donostia/San Sebastian, Spain
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain.
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32
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Oyefiade AA, Ameis S, Lerch JP, Rockel C, Szulc KU, Scantlebury N, Decker A, Jefferson J, Spichak S, Mabbott DJ. Development of short-range white matter in healthy children and adolescents. Hum Brain Mapp 2017; 39:204-217. [PMID: 29030921 DOI: 10.1002/hbm.23836] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Revised: 09/14/2017] [Accepted: 09/25/2017] [Indexed: 12/14/2022] Open
Abstract
Neural communication is facilitated by intricate networks of white matter (WM) comprised of both long and short range connections. The maturation of long range WM connections has been extensively characterized, with projection, commissural, and association tracts showing unique trajectories with age. There, however, remains a limited understanding of age-related changes occurring within short range WM connections, or U-fibers. These connections are important for local connectivity within lobes and facilitate regional cortical function and greater network economy. Recent studies have explored the maturation of U-fibers primarily using cross-sectional study designs. Here, we analyzed diffusion tensor imaging (DTI) data for healthy children and adolescents in both a cross-sectional (n = 78; mean age = 13.04 ± 3.27 years) and a primarily longitudinal (n = 26; mean age = 10.78 ± 2.69 years) cohort. We found significant age-related differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) across the frontal, parietal, and temporal lobes of participants within the cross-sectional cohort. By contrast, we report significant age-related differences in only FA for participants within the longitudinal cohort. Specifically, larger FA values were observed with age in frontal, parietal, and temporal lobes of the left hemisphere. Our results extend previous findings restricted to long range WM to demonstrate regional changes in the microstructure of short range WM during childhood and adolescence. These changes possibly reflect continued myelination and axonal organization of short range WM with increasing age in more anterior regions of the left hemisphere. Hum Brain Mapp 39:204-217, 2018. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Adeoye A Oyefiade
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario.,Department of Psychology, University of Toronto, Toronto, Ontario
| | - Stephanie Ameis
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario.,Campbell Family Mental Health Research Institute, The Center for Addictions and Mental Health, Toronto, Ontario
| | - Jason P Lerch
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Conrad Rockel
- Department of Medical Biophysics, Western University, London, Ontario
| | - Kamila U Szulc
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Nadia Scantlebury
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Alexandra Decker
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Jaleel Jefferson
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario
| | - Simon Spichak
- Department of Human Biology, University of Toronto, Toronto, Ontario
| | - Donald J Mabbott
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario.,Department of Psychology, University of Toronto, Toronto, Ontario
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33
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Ouyang M, Kang H, Detre JA, Roberts TPL, Huang H. Short-range connections in the developmental connectome during typical and atypical brain maturation. Neurosci Biobehav Rev 2017; 83:109-122. [PMID: 29024679 DOI: 10.1016/j.neubiorev.2017.10.007] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Revised: 09/09/2017] [Accepted: 10/06/2017] [Indexed: 01/10/2023]
Abstract
The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long-range connectivity has been focused on in most research, short-range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short-range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting-state functional MRI (rs-fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short-range connectivity possible in pediatric populations. This review summarizes findings on the development of short-range functional and structural connections at the macroscale. These findings suggest an inverted U-shaped pattern of maturation from primary to higher-order brain regions, and possible "hyper-" and "hypo-" short-range connections in autism and schizophrenia, respectively. The precisely balanced short- and long-range connections contribute to the integration and segregation of the connectome during development. The mechanistic relationship among short-range connectivity maturation, the developmental connectome and emerging brain functions needs further investigation, including the refinement of methodological approaches.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Huiying Kang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Timothy P L Roberts
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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34
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Corporaal SHA, Gooijers J, Chalavi S, Cheval B, Swinnen SP, Boisgontier MP. Neural predictors of motor control and impact of visuo-proprioceptive information in youth. Hum Brain Mapp 2017; 38:5628-5647. [PMID: 28782899 DOI: 10.1002/hbm.23754] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 07/10/2017] [Accepted: 07/24/2017] [Indexed: 01/15/2023] Open
Abstract
For successful motor control, the central nervous system is required to combine information from the environment and the current body state, which is provided by vision and proprioception respectively. We investigated the relative contribution of visual and proprioceptive information to upper limb motor control and the extent to which structural brain measures predict this performance in youth (n = 40; age range 9-18 years). Participants performed a manual tracking task, adopting in-phase and anti-phase coordination modes. Results showed that, in contrast to older participants, younger participants performed the task with lower accuracy in general and poorer performance in anti-phase than in-phase modes. However, a proprioceptive advantage was found at all ages, that is, tracking accuracy was higher when proprioceptive information was available during both in- and anti-phase modes at all ages. The microstructural organization of interhemispheric connections between homologous dorsolateral prefrontal cortices, and the cortical thickness of the primary motor cortex were associated with sensory-specific accuracy of tracking performance. Overall, the findings suggest that manual tracking performance in youth does not only rely on brain regions involved in sensorimotor processing, but also on prefrontal regions involved in attention and working memory. Hum Brain Mapp 38:5628-5647, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Sharissa H A Corporaal
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Jolien Gooijers
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Sima Chalavi
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Boris Cheval
- Department of General Internal Medicine, Rehabilitation and Geriatrics, University of Geneva, Geneva, Switzerland.,Swiss NCCR "LIVES - Overcoming Vulnerability: Life Course Perspectives", University of Geneva, Geneva, Switzerland
| | - Stephan P Swinnen
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Matthieu P Boisgontier
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
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35
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Felton A, Vazquez D, Ramos-Nunez AI, Greene MR, McDowell A, Hernandez AE, Chiarello C. Bilingualism Influences Structural Indices of Interhemispheric Organization. J Neurolinguistics 2017; 42:1-11. [PMID: 28579694 PMCID: PMC5450970 DOI: 10.1016/j.jneuroling.2016.10.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Bilingualism represents an interesting model of possible experience-dependent alterations in brain structure. The current study examines whether interhemispheric adaptations in brain structure are associated with bilingualism. Corpus callosum volume and cortical thickness asymmetry across 13 regions of interest (selected to include critical language and bilingual cognitive control areas) were measured in a sample of Spanish-English bilinguals and age- and gender-matched monolingual individuals (N = 39 per group). Cortical thickness asymmetry of the anterior cingulate region differed across groups, with thicker right than left cortex for bilinguals and the reverse for monolinguals. In addition, two adjacent regions of the corpus callosum (mid-anterior and central) had greater volume in bilinguals. The findings suggest that structural indices of interhemispheric organization in a critical cognitive control region are sensitive to variations in language experience.
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Affiliation(s)
- Adam Felton
- University of California, Riverside, 900 University Ave., Riverside, CA, USA 92521
| | - David Vazquez
- University of California, Riverside, 900 University Ave., Riverside, CA, USA 92521
| | | | - Maya R. Greene
- University of Houston, 4800 Calhoun Rd., Houston, TX, USA 77004
| | - Alessandra McDowell
- University of California, Riverside, 900 University Ave., Riverside, CA, USA 92521
| | | | - Christine Chiarello
- University of California, Riverside, 900 University Ave., Riverside, CA, USA 92521
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36
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Määttä S, Könönen M, Kallioniemi E, Lakka T, Lintu N, Lindi V, Ferreri F, Ponzo D, Säisänen L. Development of cortical motor circuits between childhood and adulthood: A navigated TMS-HdEEG study. Hum Brain Mapp 2017; 38:2599-2615. [PMID: 28218489 DOI: 10.1002/hbm.23545] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 02/08/2017] [Accepted: 02/09/2017] [Indexed: 12/18/2022] Open
Abstract
Motor functions improve during childhood and adolescence, but little is still known about the development of cortical motor circuits during early life. To elucidate the neurophysiological hallmarks of motor cortex development, we investigated the differences in motor cortical excitability and connectivity between healthy children, adolescents, and adults by means of navigated suprathreshold motor cortex transcranial magnetic stimulation (TMS) combined with high-density electroencephalography (EEG). We demonstrated that with development, the excitability of the motor system increases, the TMS-evoked EEG waveform increases in complexity, the magnitude of induced activation decreases, and signal spreading increases. Furthermore, the phase of the oscillatory response to TMS becomes less consistent with age. These changes parallel an improvement in manual dexterity and may reflect developmental changes in functional connectivity. Hum Brain Mapp 38:2599-2615, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Sara Määttä
- Department of Clinical Neurophysiology, Institute of Clinical Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Mervi Könönen
- Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Elisa Kallioniemi
- Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.,Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Timo Lakka
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland.,Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Niina Lintu
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Virpi Lindi
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Florinda Ferreri
- Department of Clinical Neurophysiology, Institute of Clinical Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, University Campus Biomedico, Rome, Italy
| | - David Ponzo
- Department of Neurology, University Campus Biomedico, Rome, Italy
| | - Laura Säisänen
- Department of Clinical Neurophysiology, Institute of Clinical Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
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37
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Vetreno RP, Yaxley R, Paniagua B, Crews FT. Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction. Addict Biol 2016; 21:939-53. [PMID: 25678360 DOI: 10.1111/adb.12232] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction.
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Affiliation(s)
- Ryan P. Vetreno
- The Bowles Center for Alcohol Studies; Department of Psychiatry; The University of North Carolina at Chapel Hill; Chapel Hill NC USA
| | - Richard Yaxley
- The Bowles Center for Alcohol Studies; Department of Psychiatry; The University of North Carolina at Chapel Hill; Chapel Hill NC USA
| | - Beatriz Paniagua
- The Bowles Center for Alcohol Studies; Department of Psychiatry; The University of North Carolina at Chapel Hill; Chapel Hill NC USA
| | - Fulton T. Crews
- The Bowles Center for Alcohol Studies; Department of Psychiatry; The University of North Carolina at Chapel Hill; Chapel Hill NC USA
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38
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Liu M, Bernhardt BC, Hong SJ, Caldairou B, Bernasconi A, Bernasconi N. The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions. Brain 2016; 139:2431-40. [PMID: 27357350 DOI: 10.1093/brain/aww167] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 05/31/2016] [Indexed: 01/08/2023] Open
Abstract
Drug-resistant temporal lobe epilepsy is increasingly recognized as a system-level disorder affecting the structure and function of large-scale grey matter networks. While diffusion magnetic resonance imaging studies have demonstrated deep fibre tract alterations, the superficial white matter immediately below the cortex has so far been neglected despite its proximity to neocortical regions and key role in maintaining cortico-cortical connectivity. Using multi-modal 3 T magnetic resonance imaging, we mapped the topography of superficial white matter diffusion alterations in 61 consecutive temporal lobe epilepsy patients relative to 38 healthy controls and studied the relationship to large-scale structural as well as functional networks. Our approach continuously sampled mean diffusivity and fractional anisotropy along surfaces running 2 mm below the cortex. Multivariate statistics mapped superficial white matter diffusion anomalies in patients relative to controls, while correlation and mediation analyses evaluated their relationship to structural (cortical thickness, mesiotemporal volumetry) and functional parameters (resting state functional magnetic resonance imaging amplitude) and clinical variables. Patients presented with overlapping anomalies in mean diffusivity and anisotropy, particularly in ipsilateral temporo-limbic regions. Diffusion anomalies did not relate to cortical thinning; conversely, they mediated large-scale functional amplitude decreases in patients relative to controls in default mode hub regions (i.e. anterior and posterior midline regions, lateral temporo-parietal cortices), and were themselves mediated by hippocampal atrophy. With respect to clinical variables, we observed more marked diffusion anomalies in patients with a history of febrile convulsions and those with longer disease duration. Similarly, more marked diffusion alterations were associated with seizure-free outcome. Bootstrap analyses indicated high reproducibility of our findings, suggesting generalizability. The temporo-limbic distribution of superficial white matter anomalies, together with the mediation-level findings, suggests that this so far neglected region serves a key link between the hippocampal atrophy and large-scale default mode network alterations in temporal lobe epilepsy.
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Affiliation(s)
- Min Liu
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Boris C Bernhardt
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Seok-Jun Hong
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Shen KK, Doré V, Rose S, Fripp J, McMahon KL, de Zubicaray GI, Martin NG, Thompson PM, Wright MJ, Salvado O. Heritability and genetic correlation between the cerebral cortex and associated white matter connections. Hum Brain Mapp 2016; 37:2331-47. [PMID: 27006297 DOI: 10.1002/hbm.23177] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Revised: 02/22/2016] [Accepted: 02/25/2016] [Indexed: 02/06/2023] Open
Abstract
The aim of this study is to investigate the genetic influence on the cerebral cortex, based on the analyses of heritability and genetic correlation between grey matter (GM) thickness, derived from structural MR images (sMRI), and associated white matter (WM) connections obtained from diffusion MRI (dMRI). We measured on sMRI the cortical thickness (CT) from a large twin imaging cohort using a surface-based approach (N = 308, average age 22.8 ± 2.3 SD). An ACE model was employed to compute the heritability of CT. WM connections were estimated based on probabilistic tractography using fiber orientation distributions (FOD) from dMRI. We then fitted the ACE model to estimate the heritability of CT and FOD peak measures along WM fiber tracts. The WM fiber tracts where genetic influence was detected were mapped onto the cortical surface. Bivariate genetic modeling was performed to estimate the cross-trait genetic correlation between the CT and the FOD-based connectivity of the tracts associated with the cortical regions. We found some cortical regions displaying heritable and genetically correlated GM thickness and WM connectivity, forming networks under stronger genetic influence. Significant heritability and genetic correlations between the CT and WM connectivity were found in regions including the right postcentral gyrus, left posterior cingulate gyrus, right middle temporal gyri, suggesting common genetic factors influencing both GM and WM. Hum Brain Mapp 37:2331-2347, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Kai-Kai Shen
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia
| | - Vincent Doré
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia
| | - Stephen Rose
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Greig I de Zubicaray
- Faculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | | | - Paul M Thompson
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California
| | - Margaret J Wright
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Olivier Salvado
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia
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40
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Wu M, Kumar A, Yang S. Development and aging of superficial white matter myelin from young adulthood to old age: Mapping by vertex-based surface statistics (VBSS). Hum Brain Mapp 2016; 37:1759-69. [PMID: 26955787 DOI: 10.1002/hbm.23134] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2015] [Revised: 01/07/2016] [Accepted: 01/26/2016] [Indexed: 11/06/2022] Open
Abstract
Superficial white matter (SWM) lies immediately beneath cortical gray matter and consists primarily of short association fibers. The characteristics of SWM and its development and aging were seldom examined in the literature and warrant further investigation. Magnetization transfer imaging is sensitive to myelin changes in the white matter. Using an innovative multimodal imaging analysis approach, vertex-based surface statistics (VBSS), the current study vertexwise mapped age-related changes of magnetization transfer ratio (MTR) in SWM from young adulthood to old age (30-85 years, N = 66). Results demonstrated regionally selective and temporally heterochronologic changes of SWM MTR with age, including (1) inverted U-shaped trajectories of SWM MTR in the rostral middle frontal, medial temporal, and temporoparietal regions, suggesting continuing myelination and protracted maturation till age 40-50 years and accelerating demyelination at age 60 and beyond, (2) linear decline of SWM MTR in the middle and superior temporal, and pericalcarine areas, indicating early maturation and less acceleration in age-related degeneration, and (3) no significant changes of SWM MTR in the primary motor, somatosensory and auditory regions, suggesting resistance to age-related deterioration. We did not observe similar patterns of changes in cortical thickness in our sample, suggesting the observed SWM MTR changes are not due to cortical atrophy. Hum Brain Mapp 37:1759-1769, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Minjie Wu
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Anand Kumar
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Shaolin Yang
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois.,Department of Radiology, University of Illinois at Chicago, Chicago, Illinois.,Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois
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41
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Najt P, Wang F, Spencer L, Johnston JAY, Cox Lippard ET, Pittman BP, Lacadie C, Staib LH, Papademetris X, Blumberg HP. Anterior Cortical Development During Adolescence in Bipolar Disorder. Biol Psychiatry 2016; 79:303-10. [PMID: 26033826 PMCID: PMC4595154 DOI: 10.1016/j.biopsych.2015.03.026] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 03/25/2015] [Accepted: 03/29/2015] [Indexed: 12/23/2022]
Abstract
BACKGROUND Increasing evidence supports a neurodevelopmental model for bipolar disorder (BD), with adolescence as a critical period in its development. Developmental abnormalities of anterior paralimbic and heteromodal frontal cortices, key structures in emotional regulation processes and central in BD, are implicated. However, few longitudinal studies have been conducted, limiting understanding of trajectory alterations in BD. In this study, we performed longitudinal neuroimaging of adolescents with and without BD and assessed volume changes over time, including changes in tissue overall and within gray and white matter. Larger decreases over time in anterior cortical volumes in the adolescents with BD were hypothesized. Gray matter decreases and white matter increases are typically observed during adolescence in anterior cortices. It was hypothesized that volume decreases over time in BD would reflect alterations in those processes, showing larger gray matter contraction and decreased white matter expansion. METHODS Two high-resolution magnetic resonance imaging scans were obtained approximately 2 years apart for 35 adolescents with bipolar I disorder (BDI) and 37 healthy adolescents. Differences over time between groups were investigated for volume overall and specifically for gray and white matter. RESULTS Relative to healthy adolescents, adolescents with BDI showed greater volume contraction over time in a region including insula and orbitofrontal, rostral, and dorsolateral prefrontal cortices (p < .05, corrected), including greater gray matter contraction and decreased white matter expansion over time, in the BD compared with the healthy group. CONCLUSIONS The findings support neurodevelopmental abnormalities during adolescence in BDI in anterior cortices, including altered developmental trajectories of anterior gray and white matter.
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Affiliation(s)
- Pablo Najt
- Departments of Psychiatry, New Haven, Connecticut
| | - Fei Wang
- Departments of Psychiatry, New Haven, Connecticut
| | | | | | | | | | | | - Lawrence H Staib
- Diagnostic Radiology, New Haven, Connecticut.; Electrical Engineering, New Haven, Connecticut
| | - Xenophon Papademetris
- Diagnostic Radiology, New Haven, Connecticut.; Biomedical Engineering, New Haven, Connecticut
| | - Hilary P Blumberg
- Departments of Psychiatry, New Haven, Connecticut.; Diagnostic Radiology, New Haven, Connecticut.; Child Study Center, Yale School of Medicine, New Haven, Connecticut..
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42
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Jeon T, Mishra V, Ouyang M, Chen M, Huang H. Synchronous Changes of Cortical Thickness and Corresponding White Matter Microstructure During Brain Development Accessed by Diffusion MRI Tractography from Parcellated Cortex. Front Neuroanat 2015; 9:158. [PMID: 26696839 PMCID: PMC4667005 DOI: 10.3389/fnana.2015.00158] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Accepted: 11/18/2015] [Indexed: 12/30/2022] Open
Abstract
Cortical thickness (CT) changes during normal brain development is associated with complicated cellular and molecular processes including synaptic pruning and apoptosis. In parallel, the microstructural enhancement of developmental white matter (WM) axons with their neuronal bodies in the cerebral cortex has been widely reported with measurements of metrics derived from diffusion tensor imaging (DTI), especially fractional anisotropy (FA). We hypothesized that the changes of CT and microstructural enhancement of corresponding axons are highly interacted during development. DTI and T1-weighted images of 50 healthy children and adolescents between the ages of 7 and 25 years were acquired. With the parcellated cortical gyri transformed from T1-weighted images to DTI space as the tractography seeds, probabilistic tracking was performed to delineate the WM fibers traced from specific parcellated cortical regions. CT was measured at certain cortical regions and FA was measured from the WM fibers traced from same cortical regions. The CT of all frontal cortical gyri, including Brodmann areas 4, 6, 8, 9, 10, 11, 44, 45, 46, and 47, decreased significantly and heterogeneously; concurrently, significant, and heterogeneous increases of FA of WM traced from corresponding regions were found. We further revealed significant correlation between the slopes of the CT decrease and the slopes of corresponding WM FA increase in all frontal cortical gyri, suggesting coherent cortical pruning and corresponding WM microstructural enhancement. Such correlation was not found in cortical regions other than frontal cortex. The molecular and cellular mechanisms of these synchronous changes may be associated with overlapping signaling pathways of axonal guidance, synaptic pruning, neuronal apoptosis, and more prevalent interstitial neurons in the prefrontal cortex. Revealing the coherence of cortical and WM structural changes during development may open a new window for understanding the underlying mechanisms of developing brain circuits and structural abnormality associated with mental disorders.
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Affiliation(s)
- Tina Jeon
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia PA, USA ; Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas TX, USA
| | - Virendra Mishra
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas TX, USA ; Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas NV, USA
| | - Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia PA, USA ; Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas TX, USA
| | - Min Chen
- Department of Mathematical Sciences, University of Texas at Dallas, Richardson TX, USA
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia PA, USA ; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA, USA
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Vorona GA, Berman JI. Review of diffusion tensor imaging and its application in children. Pediatr Radiol 2015; 45 Suppl 3:S375-81. [PMID: 26346143 DOI: 10.1007/s00247-015-3277-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Revised: 11/04/2014] [Accepted: 01/06/2015] [Indexed: 12/26/2022]
Abstract
Diffusion MRI is an imaging technique that uses the random motion of water to probe tissue microstructure. Diffusion tensor imaging (DTI) can quantitatively depict the organization and connectivity of white matter. Given the non-invasiveness of the technique, DTI has become a widely used tool for researchers and clinicians to examine the white matter of children. This review covers the basics of diffusion-weighted imaging and diffusion tensor imaging and discusses examples of their clinical application in children.
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44
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Truong TK, Song AW, Chen NK. Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging. Biomed Res Int 2015; 2015:185026. [PMID: 26413505 DOI: 10.1155/2015/185026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2014] [Accepted: 10/13/2014] [Indexed: 01/09/2023]
Abstract
In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T2∗-weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.
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45
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Bray S, Krongold M, Cooper C, Lebel C. Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence. eNeuro 2015; 2:ENEURO. [PMID: 26464999 DOI: 10.1523/ENEURO.0003-15.2015] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2015] [Revised: 03/25/2015] [Accepted: 04/30/2015] [Indexed: 12/21/2022] Open
Abstract
The human brain develops with a nonlinear contraction of gray matter across late childhood and adolescence with a concomitant increase in white matter volume. Across the adult population, properties of cortical gray matter covary within networks that may represent organizational units for development and degeneration. Although gray matter covariance may be strongest within structurally connected networks, the relationship to volume changes in white matter remains poorly characterized. In the present study we examined age-related trends in white and gray matter volume using T1-weighted MR images from 360 human participants from the NIH MRI study of Normal Brain Development. Images were processed through a voxel-based morphometry pipeline. Linear effects of age on white and gray matter volume were modeled within four age bins, spanning 4-18 years, each including 90 participants (45 male). White and gray matter age-slope maps were separately entered into k-means clustering to identify regions with similar age-related variability across the four age bins. Four white matter clusters were identified, each with a dominant direction of underlying fibers: anterior-posterior, left-right, and two clusters with superior-inferior directions. Corresponding, spatially proximal, gray matter clusters encompassed largely cerebellar, fronto-insular, posterior, and sensorimotor regions, respectively. Pairs of gray and white matter clusters followed parallel slope trajectories, with white matter changes generally positive from 8 years onward (indicating volume increases) and gray matter negative (decreases). As developmental disorders likely target networks rather than individual regions, characterizing typical coordination of white and gray matter development can provide a normative benchmark for understanding atypical development.
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46
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Blackmon K. Structural MRI biomarkers of shared pathogenesis in autism spectrum disorder and epilepsy. Epilepsy Behav 2015; 47:172-82. [PMID: 25812936 DOI: 10.1016/j.yebeh.2015.02.017] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2014] [Revised: 02/11/2015] [Accepted: 02/16/2015] [Indexed: 01/28/2023]
Abstract
Etiological factors that contribute to a high comorbidity between autism spectrum disorder (ASD) and epilepsy are the subject of much debate. Does epilepsy cause ASD or are there common underlying brain abnormalities that increase the risk of developing both disorders? This review summarizes evidence from quantitative MRI studies to suggest that abnormalities of brain structure are not necessarily the consequence of ASD and epilepsy but are antecedent to disease expression. Abnormal gray and white matter volumes are present prior to onset of ASD and evident at the time of onset in pediatric epilepsy. Aberrant brain growth trajectories are also common in both disorders, as evidenced by blunted gray matter maturation and white matter maturation. Although the etiological factors that explain these abnormalities are unclear, high heritability estimates for gray matter volume and white matter microstructure demonstrate that genetic factors assert a strong influence on brain structure. In addition, histopathological studies of ASD and epilepsy brain tissue reveal elevated rates of malformations of cortical development (MCDs), such as focal cortical dysplasia and heterotopias, which supports disruption of neuronal migration as a contributing factor. Although MCDs are not always visible on MRI with conventional radiological analysis, quantitative MRI detection methods show high sensitivity to subtle malformations in epilepsy and can be potentially applied to MCD detection in ASD. Such an approach is critical for establishing quantitative neuroanatomic endophenotypes that can be used in genetic research. In the context of emerging drug treatments for seizures and autism symptoms, such as rapamycin and rapalogs, in vivo neuroimaging markers of subtle structural brain abnormalities could improve sample stratification in human clinical trials and potentially extend the range of patients that might benefit from treatment. This article is part of a Special Issue entitled "Autism and Epilepsy".
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Affiliation(s)
- Karen Blackmon
- Comprehensive Epilepsy Center, Department of Neurology, New York University School of Medicine, New York, NY 10016, USA; Center for Mind/Brain Sciences, University of Trento, Rovereto, Trento 38068, Italy.
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Bauer IE, Ouyang A, Mwangi B, Sanches M, Zunta-Soares GB, Keefe RSE, Huang H, Soares JC. Reduced white matter integrity and verbal fluency impairment in young adults with bipolar disorder: a diffusion tensor imaging study. J Psychiatr Res 2015; 62:115-22. [PMID: 25684152 PMCID: PMC4355300 DOI: 10.1016/j.jpsychires.2015.01.008] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 01/13/2015] [Accepted: 01/15/2015] [Indexed: 11/23/2022]
Abstract
BACKGROUND Clinical evidence shows that bipolar disorder (BD) is characterized by white matter (WM) microstructural abnormalities. However, little is known about the biological mechanisms associated with these abnormalities and their relationship with cognitive functioning. METHODS 49 adult BD patients ((M±SD): 29.27 ± 7.92 years; 17 males, 32 females; 34 BD-I, 10 BD-II, and 5 BD-NOS) and 28 age-matched normal subjects ((M±SD): 29.19 ± 7.35 years; 10 males and 18 females) underwent diffusion tensor imaging (DTI) imaging. DTI metrics were computed using whole-brain tract-based spatial statistics (TBSS) as part of the FMRIB Software Library. Measures of WM coherence (fractional anisotropy - FA) and axonal structure (mean, axial and radial diffusivity - MD, AD and RD) were employed to characterize the microstructural alterations in the limbic, commissural, association and projection fiber tracts. All participants performed the Brief Assessment of Cognition for Affective disorders (BAC-A). RESULTS BD patients performed poorly on verbal fluency tasks and exhibited large clusters of altered FA, RD and MD values within the retrolenticular part of the internal capsule, the superior and anterior corona radiata, and the corpus callosum. Increased FA values in the left IFOF and the forceps minor correlated positively with verbal fluency scores. Altered RD parameters in the corticospinal tract and the forceps minor were associated with reduced visuomotor abilities. CONCLUSIONS The reported verbal fluency deficits and FA, RD and MD alterations in WM structures are potential cognitive and neural markers of BD. Abnormal RD values may be associated with progressive demyelination.
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Affiliation(s)
- Isabelle E Bauer
- University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 77054 Houston, TX, United States.
| | - Austin Ouyang
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Benson Mwangi
- University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 77054 Houston, TX, United States
| | - Marsal Sanches
- University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 77054 Houston, TX, United States
| | - Giovana B Zunta-Soares
- University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 77054 Houston, TX, United States
| | - Richard S E Keefe
- Division of Medical Psychology, Duke University, Medical Centre, 27710 Durham, NC, United States
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania PA, United States
| | - Jair C Soares
- University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 77054 Houston, TX, United States
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Kates WR, Olszewski AK, Gnirke MH, Kikinis Z, Nelson J, Antshel KM, Fremont W, Radoeva PD, Middleton FA, Shenton ME, Coman IL. White matter microstructural abnormalities of the cingulum bundle in youths with 22q11.2 deletion syndrome: associations with medication, neuropsychological function, and prodromal symptoms of psychosis. Schizophr Res 2015; 161:76-84. [PMID: 25066496 PMCID: PMC4277733 DOI: 10.1016/j.schres.2014.07.010] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 07/02/2014] [Accepted: 07/03/2014] [Indexed: 11/17/2022]
Abstract
BACKGROUND The 22q11.2 deletion syndrome (22q11.2DS) is regarded as an etiologically homogenous model for understanding neuroanatomic disruptions associated with a high risk for schizophrenia. This study utilized diffusion tensor imaging (DTI) to analyze white matter microstructure in individuals with 22q11.2DS. We focused on the cingulum bundle (CB), previously shown to be disrupted in patients with schizophrenia and associated with symptoms of psychosis. METHODS White matter microstructure was assessed in the anterior, superior, and posterior CB using the tractography algorithm in DTIStudio. Neuropsychological function, presence of prodromal symptoms of psychosis, and medication history were assessed in all participants. RESULTS Relative to controls, young adults with 22q11.2DS showed alterations in most DTI metrics of the CB. Alterations were associated with positive prodromal symptoms of psychosis. However, when individuals with 22q11.2DS were divided by usage of antipsychotics/mood stabilizers, the medicated and non-medicated groups differed significantly in axial diffusivity of the anterior CB and in fractional anisotropy of the superior CB. DTI metrics did not differ between the medicated group and the control group. CONCLUSIONS Results suggest that the microstructure of the CB is altered in individuals with 22q11.2DS, and that those alterations may underlie positive prodromal symptoms of psychosis. Our findings further provide preliminary evidence that antipsychotic/mood stabilizer usage may have a reparative effect on white matter microstructure in prodromal 22q11.2DS, independent of the potential effects of psychosis. Future studies of white matter pathology in individuals with 22q11.2DS should test for potential effects of medication on white matter microstructure.
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Affiliation(s)
- Wendy R Kates
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States.
| | - Amy K Olszewski
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Matthew H Gnirke
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Zora Kikinis
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Joshua Nelson
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Kevin M Antshel
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States; Department of Psychology, Syracuse University, Syracuse, NY, United States
| | - Wanda Fremont
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Petya D Radoeva
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Frank A Middleton
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States; Department of Neuroscience and Physiology, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; VA Boston Healthcare System, Brockton Division, Brockton, MA, United States
| | - Ioana L Coman
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
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Zhou D, Lebel C, Treit S, Evans A, Beaulieu C. Accelerated longitudinal cortical thinning in adolescence. Neuroimage 2015; 104:138-45. [DOI: 10.1016/j.neuroimage.2014.10.005] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2014] [Revised: 09/26/2014] [Accepted: 10/02/2014] [Indexed: 01/26/2023] Open
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50
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Worbe Y, Marrakchi-Kacem L, Lecomte S, Valabregue R, Poupon F, Guevara P, Tucholka A, Mangin JF, Vidailhet M, Lehericy S, Hartmann A, Poupon C. Altered structural connectivity of cortico-striato-pallido-thalamic networks in Gilles de la Tourette syndrome. ACTA ACUST UNITED AC 2014; 138:472-82. [PMID: 25392196 PMCID: PMC4306818 DOI: 10.1093/brain/awu311] [Citation(s) in RCA: 148] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
See Jackson (doi:10.1093/brain/awu338) for a scientific commentary on this article. The neural substrate of Gilles de la Tourette syndrome is unknown. Worbe et al. use probabilistic tractography to demonstrate widespread structural abnormalities in cortico-striato-pallido-thalamic white matter pathways—likely arising from abnormal brain development—in patients with this syndrome. Gilles de la Tourette syndrome is a childhood-onset syndrome characterized by the presence and persistence of motor and vocal tics. A dysfunction of cortico-striato-pallido-thalamo-cortical networks in this syndrome has been supported by convergent data from neuro-pathological, electrophysiological as well as structural and functional neuroimaging studies. Here, we addressed the question of structural integration of cortico-striato-pallido-thalamo-cortical networks in Gilles de la Tourette syndrome. We specifically tested the hypothesis that deviant brain development in Gilles de la Tourette syndrome could affect structural connectivity within the input and output basal ganglia structures and thalamus. To this aim, we acquired data on 49 adult patients and 28 gender and age-matched control subjects on a 3 T magnetic resonance imaging scanner. We used and further implemented streamline probabilistic tractography algorithms that allowed us to quantify the structural integration of cortico-striato-pallido-thalamo-cortical networks. To further investigate the microstructure of white matter in patients with Gilles de la Tourette syndrome, we also evaluated fractional anisotropy and radial diffusivity in these pathways, which are both sensitive to axonal package and to myelin ensheathment. In patients with Gilles de la Tourette syndrome compared to control subjects, we found white matter abnormalities in neuronal pathways connecting the cerebral cortex, the basal ganglia and the thalamus. Specifically, striatum and thalamus had abnormally enhanced structural connectivity with primary motor and sensory cortices, as well as paracentral lobule, supplementary motor area and parietal cortices. This enhanced connectivity of motor cortex positively correlated with severity of tics measured by the Yale Global Tics Severity Scale and was not influenced by current medication status, age or gender of patients. Independently of the severity of tics, lateral and medial orbito-frontal cortex, inferior frontal, temporo-parietal junction, medial temporal and frontal pole also had enhanced structural connectivity with the striatum and thalamus in patients with Gilles de la Tourette syndrome. In addition, the cortico-striatal pathways were characterized by elevated fractional anisotropy and diminished radial diffusivity, suggesting microstructural axonal abnormalities of white matter in Gilles de la Tourette syndrome. These changes were more prominent in females with Gilles de la Tourette syndrome compared to males and were not related to the current medication status. Taken together, our data showed widespread structural abnormalities in cortico-striato-pallido-thalamic white matter pathways in patients with Gilles de la Tourette, which likely result from abnormal brain development in this syndrome.
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Affiliation(s)
- Yulia Worbe
- 1 Centre de Référence National Maladie Rare 'Syndrome Gilles de la Tourette', Pôle des Maladies du Système Nerveux, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 3 Assistance Publique Hôpitaux de Paris (APHP), INSERM, ICM, Centre d'Investigation Clinique Pitié Neurosciences, CIC-1422, Département des Maladies du Système Nerveux, Hôpital Pitié-Salpêtrière, Paris, France
| | - Linda Marrakchi-Kacem
- 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 4 NeuroSpin, CEA, Gif-Sur-Yvette, France 5 Inria, Aramis project-team, Centre Paris-Rocquencourt, France
| | - Sophie Lecomte
- 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 4 NeuroSpin, CEA, Gif-Sur-Yvette, France 5 Inria, Aramis project-team, Centre Paris-Rocquencourt, France
| | - Romain Valabregue
- 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 6 Centre de NeuroImagerie de Recherche - CENIR, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | | | | | | | | | - Marie Vidailhet
- 1 Centre de Référence National Maladie Rare 'Syndrome Gilles de la Tourette', Pôle des Maladies du Système Nerveux, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 3 Assistance Publique Hôpitaux de Paris (APHP), INSERM, ICM, Centre d'Investigation Clinique Pitié Neurosciences, CIC-1422, Département des Maladies du Système Nerveux, Hôpital Pitié-Salpêtrière, Paris, France
| | - Stephane Lehericy
- 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 6 Centre de NeuroImagerie de Recherche - CENIR, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Andreas Hartmann
- 1 Centre de Référence National Maladie Rare 'Syndrome Gilles de la Tourette', Pôle des Maladies du Système Nerveux, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France 2 Sorbonne Universités, UPMC Université Paris 06, UM 75, ICM, F-75013 Paris, France 3 Assistance Publique Hôpitaux de Paris (APHP), INSERM, ICM, Centre d'Investigation Clinique Pitié Neurosciences, CIC-1422, Département des Maladies du Système Nerveux, Hôpital Pitié-Salpêtrière, Paris, France
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