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Alexander S, Kairalla JA, Gupta S, Hibbitts E, Weisman H, Anghelescu D, Winick NJ, Krull KR, Salzer WL, Burke MJ, Gore L, Devidas M, Embry L, Raetz EA, Hunger SP, Loh ML, Hardy KK. Impact of Propofol Exposure on Neurocognitive Outcomes in Children With High-Risk B ALL: A Children's Oncology Group Study. J Clin Oncol 2024:JCO2301989. [PMID: 38603641 DOI: 10.1200/jco.23.01989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 01/11/2024] [Accepted: 02/08/2024] [Indexed: 04/13/2024] Open
Abstract
PURPOSE Many children treated for ALL develop long-term neurocognitive impairments. Increased risk of these impairments is associated with treatment and demographic factors. Exposure to anesthesia is an additional possible risk factor. This study evaluated the impact of cumulative exposure to anesthesia on neurocognitive outcomes among a multicenter cohort of children with ALL. METHODS This study was embedded in AALL1131, a Children's Oncology Group phase III trial for patients with high-risk B-ALL. In consenting patients age 6-12 years, prospective uniform assessments of neurocognitive function were performed during and at 1 year after completion of therapy. Exposure to all episodes of anesthetic agents was abstracted. Multivariable linear regression models determined associations of cumulative anesthetic agents with the primary neurocognitive outcome reaction time/processing speed (age-normed) at 1 year off therapy, adjusting for baseline neurocognitive score, age, sex, race/ethnicity, insurance status (as a proxy for socioeconomic status), and leukemia risk group. RESULTS One hundred and forty-four children, 76 (52.8%) males, mean age of 9.1 (min-max, 6.0-12.0) years at diagnosis, underwent a median of 27 anesthetic episodes (min-max, 1-37). Almost all patients were exposed to propofol (140/144, 97.2%), with a mean cumulative dose of 112.3 mg/kg. One year after therapy, the proportion of children with impairment (Z-score ≤-1.5) was significantly higher compared with a normative sample. In covariate-adjusted multivariable analysis, cumulative exposure to propofol was associated with a 0.05 Z-score decrease in reaction time/processing speed per each 10 mg/kg propofol exposure (P = .03). CONCLUSION In a multicenter and uniformly treated cohort of children with B-ALL, cumulative exposure to propofol was an independent risk factor for impairment in reaction time/processing speed 1 year after therapy. Anesthesia exposure is a modifiable risk, and opportunities to minimize propofol use should be considered.
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Affiliation(s)
- Sarah Alexander
- Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, ON, Canada
| | - John A Kairalla
- Department of Biostatistics, University of Florida, Children's Oncology Group, Gainesville, FL
| | - Sumit Gupta
- Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Emily Hibbitts
- Department of Biostatistics, University of Florida, Children's Oncology Group, Gainesville, FL
| | | | - Doralina Anghelescu
- Division of Anesthesiology, St Jude Children's Research Hospital, Memphis, TN
| | - Naomi J Winick
- Department of Pediatric Hematology Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Kevin R Krull
- Department of Psychology and Biobehavioral Sciences, St Jude Children's Research Hospital, Memphis, TN
| | - Wanda L Salzer
- Uniformed Services University, F. Edward Hebert School of Medicine, Bethesda, MD
| | - Michael J Burke
- Department of Pediatrics, The Medical College of Wisconsin Inc, Milwaukee, WI
| | - Lia Gore
- Children's Hospital Colorado, University of Colorado, Aurora, CO
| | - Meenakshi Devidas
- Department of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, TN
| | - Leanne Embry
- University of Texas Health at San Antonio, San Antonia, TX
| | - Elizabeth A Raetz
- Department of Pediatrics, Perlmutter Cancer Center, NYU Langone Hospital, New York, NY
| | - Stephen P Hunger
- Department of Pediatrics, Division of Oncology and the Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Mignon L Loh
- Department of Pediatrics, The Ben Towne Center for Childhood Cancer Research, Seattle Children's Hospital, University of Washington, Seattle, WA
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Yang B, Zheng W, Wang L, Jia Y, Qi Q, Xin H, Wang Y, Liang T, Chen X, Chen Q, Li B, Du J, Hu Y, Lu J, Chen N. Specific Alterations in Brain White Matter Networks and Their Impact on Clinical Function in Pediatric Patients With Thoracolumbar Spinal Cord Injury. J Magn Reson Imaging 2024. [PMID: 38243392 DOI: 10.1002/jmri.29231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/26/2023] [Accepted: 12/27/2023] [Indexed: 01/21/2024] Open
Abstract
BACKGROUND The alternation of brain white matter (WM) network has been studied in adult spinal cord injury (SCI) patients. However, the WM network alterations in pediatric SCI patients remain unclear. PURPOSE To evaluate WM network changes and their functional impact in children with thoracolumbar SCI (TSCI). STUDY TYPE Prospective. SUBJECTS Thirty-five pediatric patients with TSCI (8.94 ± 1.86 years, 8/27 males/females) and 34 age- and gender-matched healthy controls (HCs) participated in this study. FIELD STRENGTH/SEQUENCE 3.0 T/DTI imaging using spin-echo echo-planar and T1-weighted imaging using 3D T1-weighted magnetization-prepared rapid gradient-echo sequence. ASSESSMENT Pediatric SCI patients were evaluated for motor and sensory scores, injury level, time since injury, and age at injury. The WM network was constructed using a continuous tracing method, resulting in a 90 × 90 matrix. The global and regional metrics were obtained to investigate the alterations of the WM structural network. topology. STATISTICAL TESTS Two-sample independent t-tests, chi-squared test, Mann-Whitney U-test, and Spearman correlation. Statistical significance was set at P < 0.05. RESULTS Compared with HCs, pediatric TSCI patients displayed decreased shortest path length (Lp = 1.080 ± 0.130) and normalized Lp (λ = 5.020 ± 0.363), and increased global efficiency (Eg = 0.200 ± 0.015). Notably, these patients also demonstrated heightened regional properties in the orbitofrontal cortex, limbic system, default mode network, and several audio-visual-related regions. Moreover, the λ and Lp values negatively correlated with sensory scores. Conversely, nodal efficiency values in the right calcarine fissure and surrounding cortex positively correlated with sensory scores. The age at injury positively correlated with node degree in the left parahippocampal gyrus and nodal efficiency in the right posterior cingulate gyrus. DATA CONCLUSION Reorganization of the WM networks in pediatric SCI patients is indicated by increased global and nodal efficiency, which may provide promising neuroimaging biomarkers for functional assessment of pediatric SCI. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Beining Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Weimin Zheng
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Ling Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yulong Jia
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qunya Qi
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Haotian Xin
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yu Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Tengfei Liang
- Department of Medical Imaging, Affiliated Hospital of Hebei Engineering University, Handan, China
| | - Xin Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Baowei Li
- Department of Medical Imaging, Affiliated Hospital of Hebei Engineering University, Handan, China
| | - Jubao Du
- Department of Rehabilitation Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yongsheng Hu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Nan Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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Aggarwal N, Oler JA, Tromp DPM, Roseboom PH, Riedel MK, Elam VR, Brotman MA, Kalin NH. A preliminary study of the effects of an antimuscarinic agent on anxious behaviors and white matter microarchitecture in nonhuman primates. Neuropsychopharmacology 2024; 49:405-413. [PMID: 37516801 PMCID: PMC10724160 DOI: 10.1038/s41386-023-01686-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 07/31/2023]
Abstract
Myelination subserves efficient neuronal communication, and alterations in white matter (WM) microstructure have been implicated in numerous psychiatric disorders, including pathological anxiety. Recent work in rodents suggests that muscarinic antagonists may enhance myelination with behavioral benefits; however, the neural and behavioral effects of muscarinic antagonists have yet to be explored in non-human primates (NHP). Here, as a potentially translatable therapeutic strategy for human pathological anxiety, we present data from a first-in-primate study exploring the effects of the muscarinic receptor antagonist solifenacin on anxious behaviors and WM microstructure. 12 preadolescent rhesus macaques (6 vehicle control, 6 experimental; 8F, 4M) were included in a pre-test/post-test between-group study design. The experimental group received solifenacin succinate for ~60 days. Subjects underwent pre- and post-assessments of: 1) anxious temperament (AT)-related behaviors in the potentially threatening no-eye-contact (NEC) paradigm (30-min); and 2) WM and regional brain metabolism imaging metrics, including diffusion tensor imaging (DTI), quantitative relaxometry (QR), and FDG-PET. In relation to anxiety-related behaviors expressed during the NEC, significant Group (vehicle control vs. solifenacin) by Session (pre vs. post) interactions were found for freezing, cooing, and locomotion. Compared to vehicle controls, solifenacin-treated subjects exhibited effects consistent with reduced anxiety, specifically decreased freezing duration, increased locomotion duration, and increased cooing frequency. Furthermore, the Group-by-Session-by-Sex interaction indicated that these effects occurred predominantly in the males. Exploratory whole-brain voxelwise analyses of post-minus-pre differences in DTI, QR, and FDG-PET metrics revealed some solifenacin-related changes in WM microstructure and brain metabolism. These findings in NHPs support the further investigation of the utility of antimuscarinic agents in targeting WM microstructure as a means to treat pathological anxiety.
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Affiliation(s)
- Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA.
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Patrick H Roseboom
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Marissa K Riedel
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Victoria R Elam
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Melissa A Brotman
- Neuroscience and Novel Therapeutics Unit, National Institute of Mental Health, Bethesda, MD, 20892, USA
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
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Bagautdinova J, Bourque J, Sydnor VJ, Cieslak M, Alexander-Bloch AF, Bertolero MA, Cook PA, Gur RE, Gur RC, Hu F, Larsen B, Moore TM, Radhakrishnan H, Roalf DR, Shinohara RT, Tapera TM, Zhao C, Sotiras A, Davatzikos C, Satterthwaite TD. Development of white matter fiber covariance networks supports executive function in youth. Cell Rep 2023; 42:113487. [PMID: 37995188 PMCID: PMC10795769 DOI: 10.1016/j.celrep.2023.113487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 10/05/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023] Open
Abstract
During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.
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Affiliation(s)
- Joëlle Bagautdinova
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Josiane Bourque
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Philip A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hamsanandini Radhakrishnan
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russel T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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Tansey R, Graff K, Rohr CS, Dimond D, Ip A, Yin S, Dewey D, Bray S. Functional MRI responses to naturalistic stimuli are increasingly typical across early childhood. Dev Cogn Neurosci 2023; 62:101268. [PMID: 37327695 PMCID: PMC10275704 DOI: 10.1016/j.dcn.2023.101268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 04/05/2023] [Accepted: 06/12/2023] [Indexed: 06/18/2023] Open
Abstract
While findings show that throughout development, there are child- and age-specific patterns of brain functioning, there is also evidence for significantly greater inter-individual response variability in young children relative to adults. It is currently unclear whether this increase in functional "typicality" (i.e., inter-individual similarity) is a developmental process that occurs across early childhood, and what changes in BOLD response may be driving changes in typicality. We collected fMRI data from 81 typically developing 4-8-year-old children during passive viewing of age-appropriate television clips and asked whether there is increasing typicality of brain response across this age range. We found that the "increasing typicality" hypothesis was supported across many regions engaged by passive viewing. Post hoc analyses showed that in a priori ROIs related to language and face processing, the strength of the group-average shared component of activity increased with age, with no concomitant decline in residual signal or change in spatial extent or variability. Together, this suggests that increasing inter-individual similarity of functional responses to audiovisual stimuli is an important feature of early childhood functional brain development.
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Affiliation(s)
- Ryann Tansey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
| | - Kirk Graff
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Christiane S Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Shelly Yin
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Owerko Centre at the Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Sa de Almeida J, Baud O, Fau S, Barcos-Munoz F, Courvoisier S, Lordier L, Lazeyras F, Hüppi PS. Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study. Dev Cogn Neurosci 2023; 61:101254. [PMID: 37182337 DOI: 10.1016/j.dcn.2023.101254] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/25/2023] [Accepted: 05/09/2023] [Indexed: 05/16/2023] Open
Abstract
Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.
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Affiliation(s)
- Joana Sa de Almeida
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland.
| | - Olivier Baud
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Sebastien Fau
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Francisca Barcos-Munoz
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Sebastien Courvoisier
- Center of BioMedical Imaging (CIBM), University of Geneva, Geneva, Switzerland; Department of Radiology and Medical Informatics, Geneva, Switzerland
| | - Lara Lordier
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - François Lazeyras
- Center of BioMedical Imaging (CIBM), University of Geneva, Geneva, Switzerland; Department of Radiology and Medical Informatics, Geneva, Switzerland
| | - Petra S Hüppi
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
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Perdue MV, DeMayo MM, Bell TK, Boudes E, Bagshawe M, Harris AD, Lebel C. Changes in brain metabolite levels across childhood. Neuroimage 2023; 274:120087. [PMID: 37080345 DOI: 10.1016/j.neuroimage.2023.120087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/05/2023] [Accepted: 04/03/2023] [Indexed: 04/22/2023] Open
Abstract
Metabolites play important roles in brain development and their levels change rapidly in the prenatal period and during infancy. Metabolite levels are thought to stabilize during childhood, but the development of neurochemistry across early-middle childhood remains understudied. We examined the developmental changes of key metabolites (total N-acetylaspartate, tNAA; total choline, tCho; total creatine, tCr; glutamate+glutamine, Glx; and myo-inositol, mI) using short echo-time magnetic resonance spectroscopy (MRS) in the anterior cingulate cortex (ACC) and the left temporo-parietal cortex (LTP) using a mixed cross-sectional/longitudinal design in children aged 2-11 years (ACC: N=101 children, 112 observations; LTP: N=95 children, 318 observations). We found age-related effects for all metabolites. tNAA increased with age in both regions, while tCho decreased with age in both regions. tCr increased with age in the LTP only, and mI decreased with age in the ACC only. Glx did not show linear age effects in either region, but a follow-up analysis in only participants with ≥3 datapoints in the LTP revealed a quadratic effect of age following an inverted U-shape. These substantial changes in neurochemistry throughout childhood likely underlie various processes of structural and functional brain development.
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Affiliation(s)
- Meaghan V Perdue
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | - Marilena M DeMayo
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary; Mathison Centre for Mental Health Research and Education; Department of Psychiatry, University of Calgary
| | - Tiffany K Bell
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | | | - Mercedes Bagshawe
- Alberta Children's Hospital Research Institute; Werklund School of Education, University of Calgary
| | - Ashley D Harris
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | - Catherine Lebel
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary.
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8
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Martinelli D, Catesini G, Greco B, Guarnera A, Parrillo C, Maines E, Longo D, Napolitano A, De Nictolis F, Cairoli S, Liccardo D, Caviglia S, Sidorina A, Olivieri G, Siri B, Bianchi R, Spagnoletti G, Dello Strologo L, Spada M, Dionisi-Vici C. Neurologic outcome following liver transplantation for methylmalonic aciduria. J Inherit Metab Dis 2023; 46:450-465. [PMID: 36861405 DOI: 10.1002/jimd.12599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023]
Abstract
Liver and liver/kidney transplantation are increasingly used in methylmalonic aciduria, but little is known on their impact on CNS. The effect of transplantation on neurological outcome was prospectively assessed in six patients pre- and post-transplant by clinical evaluation and by measuring disease biomarkers in plasma and CSF, in combination with psychometric tests and brain MRI studies. Primary (methylmalonic- and methylcitric acid) and secondary biomarkers (glycine and glutamine) significantly improved in plasma, while they remained unchanged in CSF. Differently, biomarkers of mitochondrial dysfunction (lactate, alanine, and related ratios) significantly decreased in CSF. Neurocognitive evaluation documented significant higher post-transplant developmental/cognitive scores and maturation of executive functions corresponding to improvement of brain atrophy, cortical thickness, and white matter maturation indexes at MRI. Three patients presented post-transplantation reversible neurological events, which were differentiated, by means of biochemical and neuroradiological evaluations, into calcineurin inhibitor-induced neurotoxicity and metabolic stroke-like episode. Our study shows that transplantation has a beneficial impact on neurological outcome in methylmalonic aciduria. Early transplantation is recommended due to the high risk of long-term complications, high disease burden, and low quality of life.
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Affiliation(s)
- Diego Martinelli
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Giulio Catesini
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Benedetta Greco
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
- Clinical Psychology Unit, Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Alessia Guarnera
- Neuroradiology Unit, Imaging Department, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Chiara Parrillo
- Medical Physics Unit, Risk Management Enterprise, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Evelina Maines
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
- Pediatric Department, S.Chiara Hospital of Trento, Trento, Italy
| | - Daniela Longo
- Neuroradiology Unit, Imaging Department, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Antonio Napolitano
- Medical Physics Unit, Risk Management Enterprise, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Francesca De Nictolis
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Sara Cairoli
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Daniela Liccardo
- Division of Hepatology, Gastroenterology and Nutrition, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Stefania Caviglia
- Clinical Psychology Unit, Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Anna Sidorina
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Giorgia Olivieri
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Barbara Siri
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
| | - Roberto Bianchi
- Department of Anesthesiology, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Gionata Spagnoletti
- Unit of Hepato-Biliary-Pancreatic Surgery, Department of Surgery, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Luca Dello Strologo
- Renal Transplant Unit, Bambino Gesù, Children's Hospital, IRCCS, Rome, Italy
| | - Marco Spada
- Unit of Hepato-Biliary-Pancreatic Surgery, Department of Surgery, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Carlo Dionisi-Vici
- Division of Metabolism, Department of Pediatric Subspecialties, Bambino Gesù Children's Hospital, Rome, Italy
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9
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Bagautdinova J, Bourque J, Sydnor VJ, Cieslak M, Alexander-Bloch AF, Bertolero MA, Cook PA, Gur RC, Gur RE, Larsen B, Moore TM, Radhakrishnan H, Roalf DR, Shinohara RT, Tapera TM, Zhao C, Sotiras A, Davatzikos C, Satterthwaite TD. Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.09.527696. [PMID: 36798354 PMCID: PMC9934602 DOI: 10.1101/2023.02.09.527696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
The white matter architecture of the human brain undergoes substantial development throughout childhood and adolescence, allowing for more efficient signaling between brain regions that support executive function. Increasingly, the field understands grey matter development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. While white matter development also appears asynchronous, previous studies have largely relied on anatomical atlases to characterize white matter tracts, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Here, we leveraged advances in diffusion modeling and unsupervised machine learning to delineate white matter fiber covariance networks comprised of structurally similar areas of white matter in a cross-sectional sample of 939 youth aged 8-22 years. We then evaluated associations between fiber covariance network structural properties with both age and executive function using generalized additive models. The identified fiber covariance networks aligned with the known architecture of white matter while simultaneously capturing novel spatial patterns of coordinated maturation. Fiber covariance networks showed heterochronous increases in fiber density and cross section that generally followed hierarchically organized temporal patterns of cortical development, with the greatest increases in unimodal sensorimotor networks and the most prolonged increases in superior and anterior transmodal networks. Notably, we found that executive function was associated with structural features of limbic and association networks. Taken together, this study delineates data-driven patterns of white matter network development that support cognition and align with major axes of brain maturation.
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Affiliation(s)
- Joëlle Bagautdinova
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Josiane Bourque
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matt Cieslak
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Max A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Phil A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hamsi Radhakrishnan
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russel T Shinohara
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St.Louis, 63130 MO, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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10
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Meisler SL, Gabrieli JDE. Fiber-specific structural properties relate to reading skills in children and adolescents. eLife 2022; 11:e82088. [PMID: 36576253 PMCID: PMC9815823 DOI: 10.7554/elife.82088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/21/2022] [Indexed: 12/29/2022] Open
Abstract
Recent studies suggest that the cross-sectional relationship between reading skills and white matter microstructure, as indexed by fractional anisotropy, is not as robust as previously thought. Fixel-based analyses yield fiber-specific micro- and macrostructural measures, overcoming several shortcomings of the traditional diffusion tensor model. We ran a whole-brain analysis investigating whether the product of fiber density and cross-section (FDC) related to single-word reading skills in a large, open, quality-controlled dataset of 983 children and adolescents ages 6-18. We also compared FDC between participants with (n = 102) and without (n = 570) reading disabilities. We found that FDC positively related to reading skills throughout the brain, especially in left temporoparietal and cerebellar white matter, but did not differ between reading proficiency groups. Exploratory analyses revealed that among metrics from other diffusion models - diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging - only the orientation dispersion and neurite density indexes from NODDI were associated (inversely) with reading skills. The present findings further support the importance of left-hemisphere dorsal temporoparietal white matter tracts in reading. Additionally, these results suggest that future DWI studies of reading and dyslexia should be designed to benefit from advanced diffusion models, include cerebellar coverage, and consider continuous analyses that account for individual differences in reading skill.
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Affiliation(s)
- Steven Lee Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard Medical SchoolBostonUnited States
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11
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Hoffman LJ, Ngo CT, Canada KL, Pasternak O, Zhang F, Riggins T, Olson IR. The fornix supports episodic memory during childhood. Cereb Cortex 2022; 32:5388-5403. [PMID: 35169831 PMCID: PMC9712741 DOI: 10.1093/cercor/bhac022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 12/27/2022] Open
Abstract
Episodic memory relies on the coordination of widespread brain regions that reconstruct spatiotemporal details of an episode. These topologically dispersed brain regions can rapidly communicate through structural pathways. Research in animal and human lesion studies implicate the fornix-the major output pathway of the hippocampus-in supporting various aspects of episodic memory. Because episodic memory undergoes marked changes in early childhood, we tested the link between the fornix and episodic memory in an age window of robust memory development (ages 4-8 years). Children were tested on the stories subtest from the Children's Memory Scale, a temporal order memory task, and a source memory task. Fornix streamlines were reconstructed using probabilistic tractography to estimate fornix microstructure. In addition, we measured fornix macrostructure and computed free water. To assess selectivity of our findings, we also reconstructed the uncinate fasciculus. Findings show that children's memory increases from ages 4 to 8 and that fornix micro- and macrostructure increases between ages 4 and 8. Children's memory performance across nearly every memory task correlated with individual differences in fornix, but not uncinate fasciculus, white matter. These findings suggest that the fornix plays an important role in supporting the development of episodic memory, and potentially semantic memory, in early childhood.
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Affiliation(s)
- Linda J Hoffman
- Department of Psychology, Temple University, 1701 North 13th St., Philadelphia, PA 19122, USA
| | - Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Kelsey L Canada
- Institute of Gerontology, Wayne State University, 87 East Ferry St., Detroit, MI 48202, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA 02115, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston MA 02115, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston MA 02115, USA
| | - Tracy Riggins
- Department of Psychology, University of Maryland, 4094 Campus Dr., College Park, MD, 20742, USA
| | - Ingrid R Olson
- Department of Psychology, Temple University, 1701 North 13th St., Philadelphia, PA 19122, USA
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12
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Singh M, Skippen P, He J, Thomson P, Fuelscher I, Caeyenberghs K, Anderson V, Nicholson JM, Hyde C, Silk TJ. Longitudinal developmental trajectories of inhibition and white-matter maturation of the fronto-basal-ganglia circuits. Dev Cogn Neurosci 2022; 58:101171. [PMID: 36372005 PMCID: PMC9660590 DOI: 10.1016/j.dcn.2022.101171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/06/2022] [Accepted: 10/29/2022] [Indexed: 01/13/2023] Open
Abstract
Response inhibition refers to the cancelling of planned (or restraining of ongoing) actions and is required in much of our everyday life. Response inhibition appears to improve dramatically in early development and plateau in adolescence. The fronto-basal-ganglia network has long been shown to predict individual differences in the ability to enact response inhibition. In the current study, we examined whether developmental trajectories of fiber-specific white matter properties of the fronto-basal-ganglia network was predictive of parallel developmental trajectories of response inhibition. 138 children aged 9-14 completed the stop-signal task (SST). A subsample of 73 children underwent high-angular resolution diffusion MRI data for up to three time points. Performance on the SST was assessed using a parametric race modelling approach. White matter organization of the fronto-basal-ganglia circuit was estimated using fixel-based analysis. Contrary to predictions, we did not find any significant associations between maturational trajectories of fronto-basal-ganglia white matter and developmental improvements in SST performance. Findings suggest that the development of white matter organization of the fronto-basal-ganglia and development of stopping performance follow distinct maturational trajectories.
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Affiliation(s)
- Mervyn Singh
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia.
| | - Patrick Skippen
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
| | - Jason He
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Phoebe Thomson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Vicki Anderson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia; The Royal Children's Hospital, Melbourne, Australia
| | - Jan M Nicholson
- Judith Lumley Centre, La Trobe University, Melbourne, Australia
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Timothy J Silk
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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13
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Morphological similarity of amygdala-ventral prefrontal pathways represents trait anxiety in younger and older adults. Proc Natl Acad Sci U S A 2022; 119:e2205162119. [PMID: 36215497 PMCID: PMC9586323 DOI: 10.1073/pnas.2205162119] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Stronger amygdala-ventral prefrontal white matter connectivity has been associated with lower trait anxiety, possibly reflecting an increased capacity for efficient communication between the two regions. However, there are also reports arguing against this brain-anxiety association. To address these inconsistencies in the literature, we tested the possibility that idiosyncratic tract morphology may account for meaningful individual differences in trait anxiety, even among those with comparable microstructural integrity. Here, we adopted intersubject representational similarity analysis, an analytic framework that captures multivariate patterns of similarity, to analyze the morphological similarity of amygdala-ventral prefrontal pathways. Data drawn from the Leipzig Study for Mind-Body-Emotion Interactions dataset showed that younger adults (20 to 35 y of age) with low trait anxiety, in contrast to trait-anxious individuals, had consistently similar morphological configurations in their left amygdala-ventral prefrontal pathways. Additional tests on an independent sample of older adults (60 to 75 y of age) validated this finding. Our study reveals a generalizable pattern of brain-anxiety association that is embedded within the shared geometries between fiber tract morphology and trait anxiety data.
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14
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Liu T, Wu J, Zhao Z, Li M, Lv Y, Li M, Gao F, You Y, Zhang H, Ji C, Wu D. Developmental pattern of association fibers and their interaction with associated cortical microstructures in 0-5-month-old infants. Neuroimage 2022; 261:119525. [PMID: 35908606 DOI: 10.1016/j.neuroimage.2022.119525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 11/19/2022] Open
Abstract
Association fibers connect the cortical regions and experience rapid development involving myelination and axonal growth during infancy. Yet, the spatiotemporal patterns of microstructural changes along these tracts, as well as the developmental interaction between the white matter (WM) tracts and the cortical gray matter (cGM) connected to them, are mostly unknown during infancy. In this study, we performed a diffusion MRI-based tractography and microstructure study in a cohort of 89 healthy preterm-born infants with gestational age at birth between 28.1∼36.4 weeks and postmenstrual age at scan between 39.9∼59.9 weeks. Results revealed that several C-shaped fibers, such as the arcuate fasciculus, cingulum, and uncinate fasciculus, demonstrated symmetrical along-tract profiles; and the horizontally oriented running fibers, including the inferior fronto-occipital fasciculus and the inferior longitudinal fasciculus, demonstrated an anterior-posterior developmental gradient. This study characterized the along-tract profiles using fixel-based analysis and revealed that the fiber cross-section (FC) of all five association fibers demonstrated a fluctuating increase with age, while the fiber density (FD) monotonically increase with age. NODDI was utilized to analyze the microstructural development of cGM and indicated cGM connected to the anterior end of the association fibers developed faster than that of the posterior end during 0-5 months. Notably, a mediation analysis was used to explore the relation between the development of WM and associated cGM, and demonstrated a partial mediation effect of FD in WM on the development of intracellular volume (ICV) in cGM and a full mediation effect of ICV on the growth of FD in most fibers, suggesting a predominant mediation of cGM on the WM development. Furthermore, for assessing whether those results were biased by prematurity, we compared preterm- and term-born neonates with matched scan age, gender, and multiple births from the developing human connectome project (dHCP) dataset to assess the effect of preterm-birth, and the results indicated a similar developmental pattern of the association fibers and their attached cGM. These findings presented a comprehensive picture of the major association fibers during early infancy and deciphered the developmental interaction between WM and cGM in this period.
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Affiliation(s)
- Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Jiani Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Ying Lv
- Department of Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mingyan Li
- Department of Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fusheng Gao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuqing You
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hongxi Zhang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chai Ji
- Department of Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China.
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15
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Kaur S, Espenhahn S, Bell T, Godfrey KJ, Nwaroh C, Giuffre A, Cole L, Beltrano W, Yan T, Stokoe M, Haynes L, Hou TY, Tommerdahl M, Bray S, Harris AD. Nonlinear age effects in tactile processing from early childhood to adulthood. Brain Behav 2022; 12:e2644. [PMID: 35676225 PMCID: PMC9304836 DOI: 10.1002/brb3.2644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 05/10/2022] [Accepted: 05/12/2022] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Tactile processing plays a pivotal role in the early stages of human development; however, little is known about tactile function in young children. An understanding of how tactile processing changes with age from early childhood to adulthood is fundamental in understanding altered tactile experiences in neurodevelopmental disorders, such as autism spectrum disorder. METHODS In this cross-sectional study, 142 children and adults aged 3-23 years completed a vibrotactile testing battery consisting of 5 tasks, which rely on different cortical and cognitive mechanisms. The battery was designed to be suitable for testing in young children to investigate how tactile processing changes from early childhood to adulthood. RESULTS Our results suggest a pattern of rapid, age-related changes in tactile processing toward lower discrimination thresholds (lower discrimination thresholds = greater sensitivity) across early childhood, though we acknowledge limitations with cross-sectional data. Differences in the rate of change across tasks were observed, with tactile performance reaching adult-like levels at a younger age on some tasks compared to others. CONCLUSIONS While it is known that early childhood is a period of profound development including tactile processing, our data provides evidence for subtle differences in the developmental rate of the various underlying cortical, physical, and cognitive processes. Further, we are the first to show the feasibility of vibrotactile testing in early childhood (<6 years). The results of this work provide estimates of age-related differences in performance, which could have important implications as a reference for investigating altered tactile processing in developmental disorders.
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Affiliation(s)
- Sakshi Kaur
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Svenja Espenhahn
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Tiffany Bell
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Kate J Godfrey
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Neuroscience, University of Calgary, Calgary, Alberta, Canada
| | - Chidera Nwaroh
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Adrianna Giuffre
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Neuroscience, University of Calgary, Calgary, Alberta, Canada
| | - Lauran Cole
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Neuroscience, University of Calgary, Calgary, Alberta, Canada
| | - Winnica Beltrano
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Tingting Yan
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Mehak Stokoe
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Logan Haynes
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Tasha Yuntao Hou
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Mark Tommerdahl
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Signe Bray
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ashley D Harris
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.,Child and Adolescent Imaging Research (CAIR) Program, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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16
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Sydnor VJ, Cieslak M, Duprat R, Deluisi J, Flounders MW, Long H, Scully M, Balderston NL, Sheline YI, Bassett DS, Satterthwaite TD, Oathes DJ. Cortical-subcortical structural connections support transcranial magnetic stimulation engagement of the amygdala. SCIENCE ADVANCES 2022; 8:eabn5803. [PMID: 35731882 PMCID: PMC9217085 DOI: 10.1126/sciadv.abn5803] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 05/04/2022] [Indexed: 05/31/2023]
Abstract
The amygdala processes valenced stimuli, influences emotion, and exhibits aberrant activity across anxiety disorders, depression, and PTSD. Interventions modulating amygdala activity hold promise as transdiagnostic psychiatric treatments. In 45 healthy participants, we investigated whether transcranial magnetic stimulation (TMS) elicits indirect changes in amygdala activity when applied to ventrolateral prefrontal cortex (vlPFC), a region important for emotion regulation. Harnessing in-scanner interleaved TMS/functional MRI (fMRI), we reveal that vlPFC neurostimulation evoked acute and focal modulations of amygdala fMRI BOLD signal. Larger TMS-evoked changes in the amygdala were associated with higher fiber density in a vlPFC-amygdala white matter pathway when stimulating vlPFC but not an anatomical control, suggesting this pathway facilitated stimulation-induced communication between cortex and subcortex. This work provides evidence of amygdala engagement by TMS, highlighting stimulation of vlPFC-amygdala circuits as a candidate treatment for transdiagnostic psychopathology. More broadly, it indicates that targeting cortical-subcortical structural connections may enhance the impact of TMS on subcortical neural activity and, by extension, subcortex-subserved behaviors.
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Affiliation(s)
- Valerie J. Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Romain Duprat
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joseph Deluisi
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew W. Flounders
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hannah Long
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Morgan Scully
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nicholas L. Balderston
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yvette I. Sheline
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S. Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Theodore D. Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Desmond J. Oathes
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Brain Science, Translation, Innovation, and Modulation Center (brainSTIM), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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17
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Graff K, Tansey R, Rai S, Ip A, Rohr C, Dimond D, Dewey D, Bray S. Functional connectomes become more longitudinally self-stable, but not more distinct from others, across early childhood. Neuroimage 2022; 258:119367. [PMID: 35716841 DOI: 10.1016/j.neuroimage.2022.119367] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 06/06/2022] [Accepted: 06/08/2022] [Indexed: 11/17/2022] Open
Abstract
Functional connectomes, as measured with functional magnetic resonance imaging (fMRI), are highly individualized, and evidence suggests this individualization may increase across childhood. A connectome can become more individualized either by increasing self-stability or decreasing between-subject-similarity. Here we used a longitudinal early childhood dataset to investigate age associations with connectome self-stability, between-subject-similarity, and developmental individualization, defined as an individual's self-stability across a 12-month interval relative to their between-subject-similarity. fMRI data were collected during an 18-minute passive viewing scan from 73 typically developing children aged 4-7 years, at baseline and 12-month follow-up. We found that young children had highly individualized connectomes, with sufficient self-stability across 12-months for 98% identification accuracy. Linear models showed a significant relationship between age and developmental individualization across the whole brain and in most networks. This association appeared to be largely driven by an increase in self-stability with age, with only weak evidence for relationships between age and similarity across participants. Together our findings suggest that children's connectomes become more individualized across early childhood, and that this effect is driven by increasing self-stability rather than decreasing between-subject-similarity.
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Affiliation(s)
- Kirk Graff
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada.
| | - Ryann Tansey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Shefali Rai
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Christiane Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, University of Calgary, Calgary, AB, Canada; Community Health Science, University of Calgary, Calgary, AB, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada
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18
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Bells S, Longoni G, Berenbaum T, de Medeiros CB, Narayanan S, Banwell BL, Arnold DL, Mabbott DJ, Ann Yeh E. Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders. Neuroimage Clin 2022; 34:103001. [PMID: 35381508 PMCID: PMC8980471 DOI: 10.1016/j.nicl.2022.103001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022]
Abstract
A multi-modal approach was used to evaluate the visual pathway from anterior (retina) to posterior (visual cortex) in both paediatric MOGAD and MS patients. MS patients exhibited more widespread white matter abnormalities; MOGAD patients exhibited white matter changes primarily within the optic radiation. The pattern of cortical thinning differed in MS and MOGAD patients. Reduced RNFLT was associated with lower axonal density in MOGAD and tortuosity in MS.
The impact of multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) - associated disorders (MOGAD) on brain structure in youth remains poorly understood. Reductions in cortical mantle thickness on structural MRI and abnormal diffusion-based white matter metrics (e.g., diffusion tensor parameters) have been well documented in MS but not in MOGAD. Characterizing structural abnormalities found in children with these disorders can help clarify the differences and similarities in their impact on neuroanatomy. Importantly, while MS and MOGAD affect the entire CNS, the visual pathway is of particular interest in both groups, as most patients have evidence for clinical or subclinical involvement of the anterior visual pathway. Thus, the visual pathway is of key interest in analyses of structural abnormalities in these disorders and may distinguish MOGAD from MS patients. In this study we collected MRI data on 18 MS patients, 14 MOGAD patients and 26 age- and sex-matched typically developing children (TDC). Full-brain group differences in fixel diffusion measures (fibre-bundle populations) and cortical thickness measures were tested using age and sex as covariates. Visual pathway analysis was performed by extracting mean diffusion measures within lesion free optic radiations, cortical thickness within the visual cortex, and retinal nerve fibre layer (RNFL) and ganglion cell layer thickness measures from optical coherence tomography (OCT). Fixel based analysis (FBA) revealed MS patients have widespread abnormal white matter within the corticospinal tract, inferior longitudinal fasciculus, and optic radiations, while within MOGAD patients, non-lesional impact on white matter was found primarily in the right optic radiation. Cortical thickness measures were reduced predominately in the temporal and parietal lobes in MS patients and in frontal, cingulate and visual cortices in MOGAD patients. Additionally, our findings of associations between reduced RNFLT and axonal density in MOGAD and TORT in MS patients in the optic radiations imply widespread axonal and myelin damage in the visual pathway, respectively. Overall, our approach of combining FBA, cortical thickness and OCT measures has helped evaluate similarities and differences in brain structure in MS and MOGAD patients in comparison to TDC.
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Affiliation(s)
- Sonya Bells
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Pediatric Neurology, Spectrum Health Helen Devos Children's Hospital, Grand Rapids, USA; Department of Pediatrics and Human Development, Michigan State University, East Lansing, USA
| | - Giulia Longoni
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada
| | - Tara Berenbaum
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Cynthia B de Medeiros
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Sridar Narayanan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Brenda L Banwell
- Division of Child Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, USA
| | - Douglas L Arnold
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Donald J Mabbott
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada
| | - E Ann Yeh
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada.
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19
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Guerrero-Gonzalez J, Surgent O, Adluru N, Kirk GR, Dean III DC, Kecskemeti SR, Alexander AL, Travers BG. Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem. Front Integr Neurosci 2022; 16:804743. [PMID: 35310466 PMCID: PMC8928227 DOI: 10.3389/fnint.2022.804743] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/31/2022] [Indexed: 11/24/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging. Here, we implement a method for achieving increased apparent spatial resolution in pediatric dMRI that hinges on accurate geometric distortion correction and on high fidelity within subject image registration between dMRI and magnetization prepared rapid acquisition gradient echo (MPnRAGE) images. We call this post-processing pipeline T1 weighted-diffusion fused, or "TiDi-Fused". Data used in this work consists of dMRI data (2.4 mm resolution, corrected using FSL's Topup) and T1-weighted (T1w) MPnRAGE anatomical data (1 mm resolution) acquired from 128 autistic and non-autistic children (ages 6-10 years old). Accurate correction of geometric distortion permitted for a further increase in apparent resolution of the dMRI scan via boundary-based registration to the MPnRAGE T1w. Estimation of fiber orientation distributions and further analyses were carried out in the T1w space. Data processed with the TiDi-Fused method were qualitatively and quantitatively compared to data processed with conventional dMRI processing methods. Results show the advantages of the TiDi-Fused pipeline including sharper brainstem gray-white matter tissue contrast, improved inter-subject spatial alignment for group analyses of dMRI based measures, accurate spatial alignment with histology-based imaging of the brainstem, reduced variability in brainstem-cerebellar white matter tracts, and more robust biologically plausible relationships between age and brainstem-cerebellar white matter tracts. Overall, this work identifies a promising pipeline for achieving high-resolution imaging of brainstem structures in pediatric and clinical populations who may not be able to endure long scan times. This pipeline may serve as a gateway for feasibly elucidating brainstem contributions to autism and other conditions.
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Affiliation(s)
- Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean III
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Occupational Therapy Program in the Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
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20
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OUP accepted manuscript. Cereb Cortex 2022; 32:4684-4697. [DOI: 10.1093/cercor/bhab510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 12/13/2021] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
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21
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Darayi M, Hoffman ME, Sayut J, Wang S, Demirci N, Consolini J, Holland MA. Computational models of cortical folding: A review of common approaches. J Biomech 2021; 139:110851. [PMID: 34802706 DOI: 10.1016/j.jbiomech.2021.110851] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 08/09/2021] [Accepted: 10/26/2021] [Indexed: 11/29/2022]
Abstract
The process of gyrification, by which the brain develops the intricate pattern of gyral hills and sulcal valleys, is the result of interactions between biological and mechanical processes during brain development. Researchers have developed a vast array of computational models in order to investigate cortical folding. This review aims to summarize these studies, focusing on five essential elements of the brain that affect development and gyrification and how they are represented in computational models: (i) the constraints of skull, meninges, and cerebrospinal fluid; (ii) heterogeneity of cortical layers and regions; (iii) anisotropic behavior of subcortical fiber tracts; (iv) material properties of brain tissue; and (v) the complex geometry of the brain. Finally, we highlight areas of need for future simulations of brain development.
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Affiliation(s)
- Mohsen Darayi
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Mia E Hoffman
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - John Sayut
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Shuolun Wang
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Nagehan Demirci
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Jack Consolini
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Maria A Holland
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA.
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22
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Samson AD, Rohr CS, Park S, Arora A, Ip A, Tansey R, Comessotti T, Madigan S, Dewey D, Bray S. Videogame exposure positively associates with selective attention in a cross-sectional sample of young children. PLoS One 2021; 16:e0257877. [PMID: 34570826 PMCID: PMC8476027 DOI: 10.1371/journal.pone.0257877] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 09/13/2021] [Indexed: 11/18/2022] Open
Abstract
There is growing interest in how exposure to videogames is associated with young children's development. While videogames may displace time from developmentally important activities and have been related to lower reading skills, work in older children and adolescents has suggested that experience with attention-demanding/fast-reaction games positively associates with attention and visuomotor skills. In the current study, we assessed 154 children aged 4-7 years (77 male; mean age 5.38) whose parents reported average daily weekday recreational videogame time, including information about which videogames were played. We investigated associations between videogame exposure and children's sustained, selective, and executive attention skills. We found that videogame time was significantly positively associated only with selective attention. Longitudinal studies are needed to elucidate the directional association between time spent playing recreational videogames and attention skills.
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Affiliation(s)
- Alexandria D. Samson
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Christiane S. Rohr
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Suhyeon Park
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Anish Arora
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Amanda Ip
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Ryann Tansey
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Tiana Comessotti
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Sheri Madigan
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Deborah Dewey
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Signe Bray
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- * E-mail:
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23
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Sydnor VJ, Larsen B, Bassett DS, Alexander-Bloch A, Fair DA, Liston C, Mackey AP, Milham MP, Pines A, Roalf DR, Seidlitz J, Xu T, Raznahan A, Satterthwaite TD. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron 2021; 109:2820-2846. [PMID: 34270921 PMCID: PMC8448958 DOI: 10.1016/j.neuron.2021.06.016] [Citation(s) in RCA: 204] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/24/2021] [Accepted: 06/11/2021] [Indexed: 12/11/2022]
Abstract
The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY 10962, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, NIMH Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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24
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Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities. Neuroimage 2021; 241:118417. [PMID: 34298083 DOI: 10.1016/j.neuroimage.2021.118417] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 07/11/2021] [Accepted: 07/20/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.
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25
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Andica C, Kamagata K, Saito Y, Uchida W, Fujita S, Hagiwara A, Akashi T, Wada A, Ogawa T, Hatano T, Hattori N, Aoki S. Fiber-specific white matter alterations in early-stage tremor-dominant Parkinson's disease. NPJ PARKINSONS DISEASE 2021; 7:51. [PMID: 34172728 PMCID: PMC8233424 DOI: 10.1038/s41531-021-00197-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/04/2021] [Indexed: 12/14/2022]
Abstract
Using a fixel-based analysis (FBA), we assessed the fiber-specific white matter (WM) alterations in nonmedicated patients with early-stage Parkinson's disease (PD) with tremor-dominant (TD; n = 53; mean age, 61.7 ± 8.7 years) and postural instability and gait disorder (PIGD; n = 27; mean age, 57.8 ± 8.1 years) motor subtypes and age- and sex-matched healthy controls (HC; n = 43; mean age, 61.6 ± 9.2 years) from Parkinson's Progression Markers Initiative dataset. FBA revealed significantly increased macrostructural fiber cross section and a combination of fiber density and cross section metrics within the corticospinal tract in patients with TD-PD compared with HC. Nonetheless, no significant changes in FBA-derived metrics were found in patients with PIGD-PD compared with HC or patients with TD-PD. Our results may provide evidence of WM neural compensation mechanisms in patients with TD-PD marked by increases in fiber bundle size and the ability to relay information between brain regions.
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Affiliation(s)
- Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akihiko Wada
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takashi Ogawa
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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26
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Clemente A, Domínguez D JF, Imms P, Burmester A, Dhollander T, Wilson PH, Poudel G, Caeyenberghs K. Individual differences in attentional lapses are associated with fiber-specific white matter microstructure in healthy adults. Psychophysiology 2021; 58:e13871. [PMID: 34096075 DOI: 10.1111/psyp.13871] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 04/21/2021] [Accepted: 04/21/2021] [Indexed: 11/30/2022]
Abstract
Attentional lapses interfere with goal-directed behaviors, which may result in harmless (e.g., not hearing instructions) or severe (e.g., fatal car accident) consequences. Task-related functional MRI (fMRI) studies have shown a link between attentional lapses and activity in the frontoparietal network. Activity in this network is likely to be mediated by the organization of the white matter fiber pathways that connect the regions implicated in the network, such as the superior longitudinal fasciculus I (SLF-I). In the present study, we investigate the relationship between susceptibility to attentional lapses and relevant white matter pathways in 36 healthy adults (23 females, Mage = 31.56 years). Participants underwent a diffusion MRI (dMRI) scan and completed the global-local task to measure attentional lapses, similar to previous fMRI studies. Applying the fixel-based analysis framework for fiber-specific analysis of dMRI data, we investigated the association between attentional lapses and variability in microstructural fiber density (FD) and macrostructural (morphological) fiber-bundle cross section (FC) in the SLF-I. Our results revealed a significant negative association between higher total number of attentional lapses and lower FD in the left SLF-I. This finding indicates that the variation in the microstructure of a key frontoparietal white matter tract is associated with attentional lapses and may provide a trait-like biomarker in the general population. However, SLF-I microstructure alone does not explain propensity for attentional lapses, as other factors such as sleep deprivation or underlying psychological conditions (e.g., sleep disorders) may also lead to higher susceptibility in both healthy people and those with neurological disorders.
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Affiliation(s)
- Adam Clemente
- Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Juan F Domínguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Phoebe Imms
- Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Alex Burmester
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Peter H Wilson
- Healthy Brain and Mind Research Centre, School of Behavioural, Health and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Govinda Poudel
- Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
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27
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Alves JM, Angelo BC, Zink J, Chow T, Yunker AG, Clark K, Luo S, Belcher BR, Herting MM, Dieli-Conwright CM, Xiang AH, Page KA. Child physical activity as a modifier of the relationship between prenatal exposure to maternal overweight/obesity and neurocognitive outcomes in offspring. Int J Obes (Lond) 2021; 45:1310-1320. [PMID: 33731834 PMCID: PMC8164988 DOI: 10.1038/s41366-021-00794-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 01/04/2021] [Accepted: 02/11/2021] [Indexed: 11/12/2022]
Abstract
BACKGROUND/OBJECTIVES With rising obesity rates among pregnant women, more children are exposed in utero to maternal obesity. In prior epidemiological studies, exposure to maternal obesity was associated with lower intelligence quotient (IQ) scores and worse cognitive abilities in offspring. Further studies have shown that offspring exposed to maternal obesity, exhibit differences in the white matter microstructure properties, fractional anisotropy (FA) and mean diffusivity (MD). In contrast, physical activity was shown to improve cognition and white matter microstructure during childhood. We examined if child physical activity levels modify the relationship between prenatal exposure to maternal obesity with IQ and white matter microstructure in offspring. SUBJECTS/METHODS One hundred children (59% girls) age 7-11 years underwent brain magnetic resonance imaging and IQ testing. Maternal pre-pregnancy BMI was abstracted from electronic medical records. White matter was assessed using diffusion tensor imaging with the measures, global FA, MD. The 3-day physical activity recall was used to measure moderate-to-vigorous physical activity and vigorous physical activity (VPA). Linear regression was used to test for interactions between prenatal exposure to maternal overweight/obesity and child PA levels on child IQ and global FA/MD. RESULTS The relationship between prenatal exposure to maternal overweight/obesity and child IQ and global FA varied by child VPA levels. Children exposed to mothers with overweight/obesity who engaged in more VPA had higher IQ scores and global FA compared to exposed children who engaged in less VPA. Associations were independent of child age, sex, BMI Z-score and socioeconomic status. Children born to normal-weight mothers did not differ in either IQ or global FA by time in VPA. CONCLUSIONS Our findings support findings in rodent models and suggest that VPA during childhood modifies the relationship between prenatal exposure to maternal obesity and child IQ and white matter microstructure.
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Affiliation(s)
- Jasmin M Alves
- Division of Endocrinology, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Brendan C Angelo
- Division of Endocrinology, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Jennifer Zink
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Ting Chow
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, 91101, USA
| | - Alexandra G Yunker
- Division of Endocrinology, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Kristi Clark
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Shan Luo
- Division of Endocrinology, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Britni Ryan Belcher
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Megan M Herting
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Christina M Dieli-Conwright
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, 91101, USA
| | - Kathleen A Page
- Division of Endocrinology, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA.
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA.
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28
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Longitudinal diffusion MRI analysis using Segis-Net: A single-step deep-learning framework for simultaneous segmentation and registration. Neuroimage 2021; 235:118004. [PMID: 33794359 DOI: 10.1016/j.neuroimage.2021.118004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 03/12/2021] [Accepted: 03/19/2021] [Indexed: 01/02/2023] Open
Abstract
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolutional neural network and optimized simultaneously for their mutual benefit. An objective function that optimizes spatial correspondence for the segmented structures across time-points is proposed. We applied Segis-Net to the analysis of white matter tracts from N=8045 longitudinal brain MRI datasets of 3249 elderly individuals. Segis-Net approach showed a significant increase in registration accuracy, spatio-temporal segmentation consistency, and reproducibility compared with two multistage pipelines. This also led to a significant reduction in the sample-size that would be required to achieve the same statistical power in analyzing tract-specific measures. Thus, we expect that Segis-Net can serve as a new reliable tool to support longitudinal imaging studies to investigate macro- and microstructural brain changes over time.
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29
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Fuelscher I, Hyde C, Anderson V, Silk TJ. White matter tract signatures of fiber density and morphology in ADHD. Cortex 2021; 138:329-340. [PMID: 33784515 DOI: 10.1016/j.cortex.2021.02.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/22/2021] [Accepted: 02/17/2021] [Indexed: 01/01/2023]
Abstract
Previous studies investigating white matter organization in attention deficit hyperactivity disorder (ADHD) have adopted diffusion tensor imaging (DTI). However, attempts to derive pathophysiological models from this research have had limited success, possibly reflecting limitations of the DTI method. This study investigated the organization of white matter tracts in ADHD using fixel based analysis (FBA), a fiber specific analysis framework that is well placed to provide novel insights into the pathophysiology of ADHD. High angular diffusion weighted imaging and clinical data were collected in a large paediatric cohort (N = 144; 76 with ADHD; age range 9-11 years). White matter tractography and FBA were performed across 14 white matter tracts. Permutation based inference testing (using FBA derived measures of fiber density and morphology) assessed differences in white matter tract profiles between children with and without ADHD. Analysis further examined the association between white matter properties and ADHD symptom severity. Relative to controls, children with ADHD showed reduced white matter connectivity along association and projection pathways considered critical to behavioral control and motor function. Increased ADHD symptom severity was associated with reduced white matter organization in fronto-pontine fibers projecting to and from the supplementary motor area. Providing novel insight into the neurobiological foundations of ADHD, this is the first research to uncover fiber specific white matter alterations across a comprehensive set of white matter tracts in ADHD using FBA. Findings inform pathophysiological models of ADHD and hold great promise for the consistent identification and systematic replication of brain differences in this disorder.
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Affiliation(s)
- Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Vicki Anderson
- Clinical Sciences, Murdoch Children's Research Institute, Parkville, Australia; The Royal Children's Hospital, Parkville, Australia
| | - Timothy J Silk
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Developmental Imaging, Murdoch Children's Research Institute, Parkville, Australia
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30
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Carandini T, Mancini M, Bogdan I, Rae CL, Barritt AW, Sethi A, Harrison N, Rashid W, Scarpini E, Galimberti D, Bozzali M, Cercignani M. Disruption of brainstem monoaminergic fibre tracts in multiple sclerosis as a putative mechanism for cognitive fatigue: a fixel-based analysis. NEUROIMAGE-CLINICAL 2021; 30:102587. [PMID: 33610097 PMCID: PMC7903010 DOI: 10.1016/j.nicl.2021.102587] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 01/31/2021] [Accepted: 02/01/2021] [Indexed: 12/13/2022]
Abstract
In multiple sclerosis (MS), monoaminergic systems are altered as a result of both inflammation-dependent reduced synthesis and direct structural damage. Aberrant monoaminergic neurotransmission is increasingly considered a major contributor to fatigue pathophysiology. In this study, we aimed to compare the integrity of the monoaminergic white matter fibre tracts projecting from brainstem nuclei in a group of patients with MS (n = 68) and healthy controls (n = 34), and to investigate its association with fatigue. Fibre tracts integrity was assessed with the novel fixel-based analysis that simultaneously estimates axonal density, by means of 'fibre density', and white matter atrophy, by means of fibre 'cross section'. We focused on ventral tegmental area, locus coeruleus, and raphe nuclei as the main source of dopaminergic, noradrenergic, and serotoninergic fibres within the brainstem, respectively. Fourteen tracts of interest projecting from these brainstem nuclei were reconstructed using diffusion tractography, and compared by means of the product of fibre-density and cross-section (FDC). Finally, correlations of monoaminergic axonal damage with the modified fatigue impact scale scores were evaluated in MS. Fixel-based analysis revealed significant axonal damage - as measured by FDC reduction - within selective monoaminergic fibre-tracts projecting from brainstem nuclei in MS patients, in comparison to healthy controls; particularly within the dopaminergic-mesolimbic pathway, the noradrenergic-projections to prefrontal cortex, and serotoninergic-projections to cerebellum. Moreover, we observed significant correlations between severity of cognitive fatigue and axonal damage within the mesocorticolimbic tracts projecting from ventral tegmental area, as well as within the locus coeruleus projections to prefrontal cortex, suggesting a potential contribution of dopaminergic and noradrenergic pathways to central fatigue in MS. Our findings support the hypothesis that axonal damage along monoaminergic pathways contributes to the reduction/dysfunction of monoamines in MS and add new information on the mechanisms by which monoaminergic systems contribute to MS pathogenesis and fatigue. This supports the need for further research into monoamines as therapeutic targets aiming to combat and alleviate fatigue in MS.
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Affiliation(s)
- Tiziana Carandini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; NeuroPoly Lab, Polytechnique Montreal, Montreal, Canada; CUBRIC, Cardiff University, Cardiff, UK
| | - Iulia Bogdan
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK
| | | | - Andrew W Barritt
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK
| | - Arjun Sethi
- Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Neil Harrison
- Department of Psychology and Department of Medicine, Cardiff, UK
| | - Waqar Rashid
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Dino Ferrari Center, Milan, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Dino Ferrari Center, Milan, Italy
| | - Marco Bozzali
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Rita Levi Montalcini Department of Neuroscience, University of Torino, Turin, Italy
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Neuroimaging Laboratory, Santa Lucia Foundation IRCCS, Rome, Italy
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31
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Aggarwal N, Moody JF, Dean DC, Tromp DPM, Kecskemeti SR, Oler JA, Alexander AL, Kalin NH. Spatiotemporal dynamics of nonhuman primate white matter development during the first year of life. Neuroimage 2021; 231:117825. [PMID: 33549752 DOI: 10.1016/j.neuroimage.2021.117825] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/22/2021] [Accepted: 01/27/2021] [Indexed: 11/15/2022] Open
Abstract
White matter (WM) development early in life is a critical component of brain development that facilitates the coordinated function of neuronal pathways. Additionally, alterations in WM have been implicated in various neurodevelopmental disorders, including psychiatric disorders. Because of the need to understand WM development in the weeks immediately following birth, we characterized changes in WM microstructure throughout the postnatal macaque brain during the first year of life. This is a period in primates during which genetic, developmental, and environmental factors may have long-lasting impacts on WM microstructure. Studies in nonhuman primates (NHPs) are particularly valuable as a model for understanding human brain development because of their evolutionary relatedness to humans. Here, 34 rhesus monkeys (23 females, 11 males) were imaged longitudinally at 3, 7, 13, 25, and 53 weeks of age with T1-weighted (MPnRAGE) and diffusion tensor imaging (DTI). With linear mixed-effects (LME) modeling, we demonstrated robust logarithmic growth in FA, MD, and RD trajectories extracted from 18 WM tracts across the brain. Estimated rate of change curves for FA, MD, and RD exhibited an initial 10-week period of exceedingly rapid WM development, followed by a precipitous decline in growth rates. K-means clustering of raw DTI trajectories and rank ordering of LME model parameters revealed distinct posterior-to-anterior and medial-to-lateral gradients in WM maturation. Finally, we found that individual differences in WM microstructure assessed at 3 weeks of age were significantly related to those at 1 year of age. This study provides a quantitative characterization of very early WM growth in NHPs and lays the foundation for future work focused on the impact of alterations in early WM developmental trajectories in relation to human psychopathology.
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Affiliation(s)
- Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States.
| | - Jason F Moody
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States
| | - Douglas C Dean
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Department of Pediatrics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Steve R Kecskemeti
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Andy L Alexander
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States; Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
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Chahal R, Kirshenbaum JS, Ho TC, Mastrovito D, Gotlib IH. Greater age-related changes in white matter morphometry following early life stress: Associations with internalizing problems in adolescence. Dev Cogn Neurosci 2021; 47:100899. [PMID: 33340790 PMCID: PMC7750321 DOI: 10.1016/j.dcn.2020.100899] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 10/21/2020] [Accepted: 12/01/2020] [Indexed: 12/29/2022] Open
Abstract
Early life stress (ELS) is associated with increased risk for internalizing disorders and variations in gray matter development. It is unclear, however, whether ELS affects normative age-related changes in white matter (WM) morphology, and if such maturational differences are associated with risk for internalizing psychopathology. We conducted comprehensive interviews in a cross-sectional sample of young adolescents (N = 156; 89 F; Ages 9-14) to assess lifetime exposure to stress and objective cumulative ELS severity. We used diffusion-weighted imaging to measure WM fixel-based morphometry and tested the effects of age and ELS on WM fiber density and cross-section (FDC), and associations between WM FDC and internalizing problems. Age was positively associated with FDC in all WM tracts; greater ELS severity was related to stronger age-WM associations in several association tracts connecting the frontal lobes with limbic, parietal, and occipital regions, including bilateral superior and inferior longitudinal and uncinate fasciculi (UF). Among older adolescents with greater ELS severity, a higher UF FDC was associated with fewer internalizing problems. Greater ELS severity predicted more mature WM morphometry in tracts implicated in emotion regulation and cognitive processing. More phenotypically mature UF WM may be adaptive against internalizing psychopathology in adolescents exposed to ELS.
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Affiliation(s)
- Rajpreet Chahal
- Department of Psychology, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, United States.
| | - Jaclyn S Kirshenbaum
- Department of Psychology, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, United States
| | - Tiffany C Ho
- Department of Psychiatry & Behavioral Sciences and Weill Institute for Neurosciences, University of California, 401 Parnassus Avenue, San Francisco, CA, 94143, United States
| | - Dana Mastrovito
- Department of Psychology, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, United States
| | - Ian H Gotlib
- Department of Psychology, Stanford University, 450 Jane Stanford Way, Stanford, CA, 94305, United States.
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Verhelst H, Dhollander T, Gerrits R, Vingerhoets G. Fibre-specific laterality of white matter in left and right language dominant people. Neuroimage 2021; 230:117812. [PMID: 33524578 DOI: 10.1016/j.neuroimage.2021.117812] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/23/2020] [Accepted: 01/20/2021] [Indexed: 12/13/2022] Open
Abstract
Language is the most commonly described lateralised cognitive function, relying more on the left hemisphere compared to the right hemisphere in over 90% of the population. Most research examining the structure-function relationship of language lateralisation only included people showing a left language hemisphere dominance. In this work, we applied a state-of-the-art "fixel-based" analysis approach, allowing statistical analysis of white matter micro- and macrostructure on a fibre-specific level in a sample of participants with left and right language dominance (LLD and RLD). Both groups showed a similar extensive pattern of white matter lateralisation including a comparable leftwards lateralisation of the arcuate fasciculus, regardless of their functional language lateralisation. These results suggest that lateralisation of language functioning and the arcuate fasciculus are driven by independent biases. Finally, a significant group difference of lateralisation was detected in the forceps minor, with a leftwards lateralisation in LLD and rightwards lateralisation for the RLD group.
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Affiliation(s)
- Helena Verhelst
- Department of Experimental Psychology, Ghent University, Belgium.
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Robin Gerrits
- Department of Experimental Psychology, Ghent University, Belgium
| | - Guy Vingerhoets
- Department of Experimental Psychology, Ghent University, Belgium
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Fuelscher I, Hyde C, Efron D, Silk TJ. Manual dexterity in late childhood is associated with maturation of the corticospinal tract. Neuroimage 2020; 226:117583. [PMID: 33221438 DOI: 10.1016/j.neuroimage.2020.117583] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 11/05/2020] [Accepted: 11/09/2020] [Indexed: 12/21/2022] Open
Abstract
PURPOSE Despite the important role of manual dexterity in child development, the neurobiological mechanisms associated with manual dexterity in childhood remain unclear. We leveraged fixel-based analysis (FBA) to examine the longitudinal association between manual dexterity and the development of white matter structural properties in the corticospinal tract (CST). METHODS High angular diffusion weighted imaging (HARDI) data were acquired for 44 right-handed typically developing children (22 female) aged 9-13 across two timepoints (timepoint 1: mean age 10.5 years ± 0.5 years, timepoint 2: 11.8 ± 0.5 years). Manual dexterity was assessed using the Grooved Pegboard Test, a widely used measure of manual dexterity. FBA-derived measures of fiber density and morphology were generated for the CST at each timepoint. Connectivity-based fixel enhancement and mixed linear modelling were used to examine the longitudinal association between manual dexterity and white matter structural properties of the CST. RESULTS Longitudinal mixed effects models showed that greater manual dexterity of the dominant hand was associated with increased fiber cross-section in the contralateral CST. Analyses further demonstrated that the rate of improvement in manual dexterity was associated with the rate of increase in fiber cross-section in the contralateral CST between the two timepoints. CONCLUSION Our longitudinal data suggest that the development of manual dexterity in late childhood is associated with maturation of the CST. These findings significantly enhance our understanding of the neurobiological systems that subserve fine motor development and provide an important step toward mapping normative trajectories of fine motor function against microstructural and morphological development in childhood.
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Affiliation(s)
- Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Daryl Efron
- The Royal Children's Hospital, Parkville, Australia; Murdoch Children's Research Institute, Parkville, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Timothy J Silk
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Parkville, Australia
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Dimond D, Heo S, Ip A, Rohr CS, Tansey R, Graff K, Dhollander T, Smith RE, Lebel C, Dewey D, Connelly A, Bray S. Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood. Neuroimage 2020; 221:117168. [DOI: 10.1016/j.neuroimage.2020.117168] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 06/15/2020] [Accepted: 07/12/2020] [Indexed: 12/13/2022] Open
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Kimpton JA, Batalle D, Barnett ML, Hughes EJ, Chew ATM, Falconer S, Tournier JD, Alexander D, Zhang H, Edwards AD, Counsell SJ. Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates. Neuroradiology 2020; 63:573-583. [PMID: 33123752 PMCID: PMC7966229 DOI: 10.1007/s00234-020-02584-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 10/13/2020] [Indexed: 02/03/2023]
Abstract
Purpose Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics. Methods Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32+1 weeks (24+2–36+4) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35+2 weeks (25+3–43+1). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development. Results PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.). Conclusion We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone. Supplementary Information The online version of this article (10.1007/s00234-020-02584-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- J A Kimpton
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - D Batalle
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK.,Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M L Barnett
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - E J Hughes
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - A T M Chew
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - S Falconer
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - J D Tournier
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - D Alexander
- Department of Computer Science and Centre for Medical Imaging Computing, University College London, London, UK
| | - H Zhang
- Department of Computer Science and Centre for Medical Imaging Computing, University College London, London, UK
| | - A D Edwards
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - S J Counsell
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK.
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Mito R, Dhollander T, Xia Y, Raffelt D, Salvado O, Churilov L, Rowe CC, Brodtmann A, Villemagne VL, Connelly A. In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data. Neuroimage Clin 2020; 28:102479. [PMID: 33395971 PMCID: PMC7652769 DOI: 10.1016/j.nicl.2020.102479] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 09/25/2020] [Accepted: 10/19/2020] [Indexed: 12/13/2022]
Abstract
White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.
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Affiliation(s)
- Remika Mito
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
| | - Thijs Dhollander
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Ying Xia
- CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
| | - David Raffelt
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Olivier Salvado
- CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia; CSIRO Data61, Sydney, New South Wales, Australia
| | - Leonid Churilov
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia
| | - Christopher C Rowe
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Eastern Clinical Research Unit, Monash University, Box Hill Hospital, Melbourne, Victoria, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Alan Connelly
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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Haynes L, Ip A, Cho IYK, Dimond D, Rohr CS, Bagshawe M, Dewey D, Lebel C, Bray S. Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines. Dev Cogn Neurosci 2020; 46:100875. [PMID: 33166899 PMCID: PMC7652784 DOI: 10.1016/j.dcn.2020.100875] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/10/2020] [Accepted: 10/21/2020] [Indexed: 10/30/2022] Open
Abstract
Early childhood is an important period of sensory, motor, cognitive and socio-emotional maturation, yet relatively little is known about the brain changes specific to this period. Voxel-based morphometry (VBM) is a technique to estimate regional brain volumes from magnetic resonance (MR) images. The default VBM processing pipeline can be customized to increase accuracy of segmentation and normalization, yet the impact of customizations on analyses in young children are not clear. Here, we assessed the impact of different preprocessing steps on T1-weighted MR images from typically developing children in two separate cohorts. Data were processed with the Computational Anatomy Toolbox (CAT12), using seven different VBM pipelines with distinct combinations of tissue probability maps (TPMs) and DARTEL templates created using the Template-O-Matic, and CerebroMatic. The first cohort comprised female children aged 3.9-7.9 years (N = 62) and the second included boys and girls aged 2.7-8 years (N = 74). We found that pipelines differed significantly in their tendency to classify voxels as grey or white matter and the conclusions about some age effects were pipeline-dependent. Our study helps to both understand age-associations in grey and white matter volume across early childhood and elucidate the impact of VBM customization on brain volumes in this age range.
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Affiliation(s)
- Logan Haynes
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Ivy Y K Cho
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Christiane S Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Mercedes Bagshawe
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Canada; Owerko Centre, University of Calgary, Calgary, Canada
| | - Catherine Lebel
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.
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Corpus Callosum Agenesis: An Insight into the Etiology and Spectrum of Symptoms. Brain Sci 2020; 10:brainsci10090625. [PMID: 32916978 PMCID: PMC7565833 DOI: 10.3390/brainsci10090625] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 09/06/2020] [Accepted: 09/07/2020] [Indexed: 12/22/2022] Open
Abstract
Brain hemispheres are connected by commissural structures, which consist of white matter fiber tracts that spread excitatory stimuli to various regions of the cortex. This allows an interaction between the two cerebral halves. The largest commissure is the corpus callosum (CC) which is located inferior to the longitudinal fissure, serving as its lower border. Sometimes this structure is not completely developed, which results in the condition known as agenesis of the corpus callosum (ACC). The aim of this paper was to review the latest discoveries related to the genetic and metabolic background of ACC, including the genotype/phenotype correlations as well as the clinical and imaging symptomatology. Due to various factors, including genetic defects and metabolic diseases, the development of CC may be impaired in many ways, which results in complete or partial ACC. This creates several clinical implications, depending on the specificity of the malformation and other defects in patients. Epilepsy, motor impairment and intellectual disability are the most prevalent. However, an asymptomatic course of the disease is even more common. ACC presents with characteristic images on ultrasound and magnetic resonance imaging (MRI).
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40
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Danielsen VM, Vidal-Piñeiro D, Mowinckel AM, Sederevicius D, Fjell AM, Walhovd KB, Westerhausen R. Lifespan trajectories of relative corpus callosum thickness: Regional differences and cognitive relevance. Cortex 2020; 130:127-141. [PMID: 32652340 DOI: 10.1016/j.cortex.2020.05.020] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 05/11/2020] [Accepted: 05/25/2020] [Indexed: 02/03/2023]
Abstract
The cerebral hemispheres are specialized for different cognitive functions and receive divergent information from the sensory organs, so that the interaction between the hemispheres is a crucial aspect of perception and cognition. At the same time, the major fiber tract responsible for this interaction, the corpus callosum, shows a structural development across the lifespan which is over-proportional. That is, compared to changes in overall forebrain volume, the corpus callosum shows an accentuated growth during childhood, adolescence, and early adulthood, as well as pronounced decline in older age. However, this over-proportionality of growth and decline along with potential consequences for cognition, have been largely overlooked in empirical research. In the present study we systematically address the proportionality of callosal development in a large mixed cross-sectional and longitudinal sample (1867 datasets from 1014 unique participants), covering the human lifespan (age range 4-93 years), and examine the cognitive consequences of the observed changes. Relative corpus callosum thickness was measured at 60 segments along the midsagittal surface, and lifespan trajectories were clustered to identify callosal subsections of comparable lifespan development. While confirming the expected inverted u-shaped lifespan trajectories, we also found substantial regional variation. Compared with anterior clusters, the most posterior sections exhibited an accentuated growth during development which extends well into the third decade of life, and a protracted decline in older age which is delayed by about 10 years (starting mid to late 50s). We further showed that the observed longitudinal changes in relative thickness of the mid splenium significantly mediates age-related changes in tests assessing verbal knowledge and non-verbal visual-spatial abilities across the lifespan. In summary, we demonstrate that analyzing the proportionality of callosal growth and decline offers valuable insight into lifespan development of structural connectivity between the hemispheres, and suggests consequences for the cognitive development of perception and cognition.
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Affiliation(s)
- V M Danielsen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - D Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - A M Mowinckel
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - D Sederevicius
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - A M Fjell
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - K B Walhovd
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - R Westerhausen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway.
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