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Guo Y, Lin Z, Fan Z, Tian X. Epileptic brain network mechanisms and neuroimaging techniques for the brain network. Neural Regen Res 2024; 19:2637-2648. [PMID: 38595282 PMCID: PMC11168515 DOI: 10.4103/1673-5374.391307] [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: 06/26/2023] [Revised: 09/08/2023] [Accepted: 11/22/2023] [Indexed: 04/11/2024] Open
Abstract
Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.
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Affiliation(s)
- Yi Guo
- Department of Neurology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
| | - Zhonghua Lin
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
| | - Zhen Fan
- Department of Geriatrics, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
| | - Xin Tian
- Department of Neurology, Chongqing Key Laboratory of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Nelson BK, Farah LN, Grier A, Su W, Chen J, Sossi V, Sekhon MS, Stoessl AJ, Wellington C, Honer WG, Lang D, Silverberg ND, Panenka WJ. Differences in brain structure and cognitive performance between patients with long-COVID and those with normal recovery. Neuroimage 2024; 300:120859. [PMID: 39317274 DOI: 10.1016/j.neuroimage.2024.120859] [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: 06/17/2024] [Revised: 09/14/2024] [Accepted: 09/17/2024] [Indexed: 09/26/2024] Open
Abstract
BACKGROUND The pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing. METHODS Individuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons. RESULTS There were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all β<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05). CONCLUSIONS Differences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found.
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Affiliation(s)
- Breanna K Nelson
- University of British Columbia, Department of Psychiatry, 2255 Wesbrook Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada
| | - Lea N Farah
- University of British Columbia, Department of Psychiatry, 2255 Wesbrook Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada
| | - Ava Grier
- University of British Columbia, Department of Radiology, 2775 Laurel Street Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada
| | - Wayne Su
- University of British Columbia, Department of Psychiatry, 2255 Wesbrook Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada
| | - Johnson Chen
- Vancouver General Hospital, British Columbia, 899 West 12th Ave Vancouver, BC Canada
| | - Vesna Sossi
- University of British Columbia, Department of Physics and Astronomy, 325-6224 Agricultural Road Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - Mypinder S Sekhon
- University of British Columbia, Department of Medicine, 2775 Laurel Street Vancouver, BC Canada; Vancouver General Hospital, British Columbia, 899 West 12th Ave Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - A Jon Stoessl
- University of British Columbia, Department of Medicine, 2775 Laurel Street Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - Cheryl Wellington
- University of British Columbia, Department of Pathology and Laboratory Medicine, 317 - 2194 Health Sciences Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - William G Honer
- University of British Columbia, Department of Psychiatry, 2255 Wesbrook Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada
| | - Donna Lang
- University of British Columbia, Department of Radiology, 2775 Laurel Street Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - Noah D Silverberg
- University of British Columbia, Department of Psychology, 2136 West Mall Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada
| | - William J Panenka
- University of British Columbia, Department of Psychiatry, 2255 Wesbrook Mall Vancouver, BC Canada; British Columbia Children's Hospital Research Institute, 938 West 28th Ave Vancouver, BC Canada; British Columbia Mental Health and Substance Use Services Research Institute, 938 West 28th Ave Vancouver, BC Canada; Djavad Mowafaghian Center for Brain Health, 2215 Wesbrook Mall Vancouver, BC Canada.
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Xu Q, Chen Y, Miller S, Bajaj K, Santana J, Badawy M, Lyu H, Liu Y, He N, Yan F, Haacke EM. In Vivo visualization of white matter fiber tracts in the brainstem using low flip angle double echo 3D gradient echo imaging at 3T. Neuroimage 2024; 300:120857. [PMID: 39299660 DOI: 10.1016/j.neuroimage.2024.120857] [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: 07/15/2024] [Revised: 09/11/2024] [Accepted: 09/17/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND White matter (WM) fiber tracts in the brainstem communicate with various regions in the cerebrum, cerebellum, and spinal cord. Clinically, small lesions, malformations, or histopathological changes in the brainstem can cause severe neurological disorders. A direct and non-invasive assessment approach could bring valuable information about the intricate anatomical variations of the white matter fiber tracts and nuclei. Although tractography from diffusion tensor imaging has been commonly used to map the WM fiber tracts connectivity, it is difficult to differentiate the complex WM tracts anatomically. Both high field MRI methods and ultrahigh-field MRI methods at 7T and 11.7 T have been used to enhance the contrast of WM fiber tracts. Despite their promising results, it is still challenging to achieve wide clinical adoption at 3T. In this study, we explored a clinically feasible method using a proton density weighted (PDW) 3D gradient echo (GRE) sequence to directly image the WM fiber tracts in the brainstem at 3T in vivo. METHODS We optimized a 3D high resolution, double echo, short TR, PDW GRE sequence on 5 healthy volunteers using a clinical 3T scanner to visualize the complicated anatomy of WM fiber tracts in the brain stem. Tissue properties including T1, proton density and T2* from in vivo quantitative MRI data were used for simulations to determine the optimal flip angle for the sequence. The visualization of multiple WM fiber tracts in the brainstem was assessed qualitatively and quantitatively using relative contrast and contrast-to-noise ratio (CNR). To improve the CNR, the final images were created by averaging over all echoes from two consecutive scans at the optimal flip angle. The results were compared to anatomical atlases and histology sections to identify the major fiber tracts. All the identified major fiber tracts were labeled on axial, sagittal and coronal slices. RESULTS The WM fiber tracts were found to have distinct hypointense signal throughout the brainstem and most of the major WM fiber tracts, such as the corticospinal tract, medial lemniscus, medial longitudinal fasciculus, and central tegmental tract, in the brainstem up to and including the thalamus were identified in all subjects. Both qualitative and quantitative evaluations showed that the 3° scan offered the best contrast for WM fiber tracts for a TR of 20 ms. The average over the first two echo times and two consecutive 3° scans gave a CNR of 47.8 ± 6.2 for the pyramidal tracts in particular and CNRs values greater than 6.5 ± 2.4 for the rest of the fiber tracts. CONCLUSIONS All the major fiber tracts in the brainstem could be visualized. Given the reasonably short scan time of 10 min at 3T, double echo PDW GRE sequence is a very practical approach for clinical adoption.
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Affiliation(s)
- Qiuyun Xu
- Department of Radiology, Wayne State University, 3990 John R, 4201 St Antoine, Detroit Receiving Hospital 3L-8, Detroit, MI, 48201, USA
| | - Yongsheng Chen
- Department of Neurology, Detroit Medical Center, Wayne State University, University Health Center-8th floor, 4201 St Antoine, Detroit, MI, 48201, USA
| | - Stephan Miller
- Department of Radiology, Detroit Medical Center, Wayne State University School of Medicine, 3901 Beaubien Boulevard, Detroit, MI, 48201, USA
| | - Kunal Bajaj
- Department of Radiology, Detroit Medical Center, Wayne State University School of Medicine, 3901 Beaubien Boulevard, Detroit, MI, 48201, USA
| | - Jairo Santana
- Department of Radiology, Detroit Medical Center, Wayne State University School of Medicine, 3901 Beaubien Boulevard, Detroit, MI, 48201, USA
| | - Mohamed Badawy
- Department of Radiology, Detroit Medical Center, Wayne State University School of Medicine, 3901 Beaubien Boulevard, Detroit, MI, 48201, USA
| | - Haiying Lyu
- Department of Radiology, Ruijin Hospital, No. 197 Ruijin Er Road, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yu Liu
- Department of Radiology, Ruijin Hospital, No. 197 Ruijin Er Road, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, No. 197 Ruijin Er Road, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, No. 197 Ruijin Er Road, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - E Mark Haacke
- Department of Radiology, Wayne State University, 3990 John R, 4201 St Antoine, Detroit Receiving Hospital 3L-8, Detroit, MI, 48201, USA; Department of Neurology, Detroit Medical Center, Wayne State University, University Health Center-8th floor, 4201 St Antoine, Detroit, MI, 48201, USA; Department of Radiology, Ruijin Hospital, No. 197 Ruijin Er Road, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Department of Biomedical Engineering, Wayne State University, 3990 John R, 4201 St Antoine, Detroit Receiving Hospital 3L-8, Detroit, MI, 48201, USA.
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Hoffman LJ, Foley JM, Leong JK, Sullivan-Toole H, Elliott BL, Olson IR. A Virtual In Vivo Dissection and Analysis of Socioaffective Symptoms Related to Cerebellum-Midbrain Reward Circuitry in Humans. J Neurosci 2024; 44:e1031242024. [PMID: 39256045 PMCID: PMC11466071 DOI: 10.1523/jneurosci.1031-24.2024] [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: 06/03/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/12/2024] Open
Abstract
Emerging research in nonhuman animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white matter connectivity in a cohort of men and women using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections between the cerebellum and VTA predominantly originate in the right cerebellar hemisphere, interposed nucleus, and paravermal cortex and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared with other lobules. We discovered a mediolateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socioaffective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socioaffective regulation.
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Affiliation(s)
- Linda J Hoffman
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Julia M Foley
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Josiah K Leong
- Department of Psychological Science, University of Arkansas, Fayetteville, Arkansas 72701
| | - Holly Sullivan-Toole
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Blake L Elliott
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Ingrid R Olson
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
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5
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Genc S, Schiavi S, Chamberland M, Tax CMW, Raven EP, Daducci A, Jones DK. Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography. Netw Neurosci 2024; 8:946-964. [PMID: 39355444 PMCID: PMC11424039 DOI: 10.1162/netn_a_00378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 04/09/2024] [Indexed: 10/03/2024] Open
Abstract
In response to a growing interest in refining brain connectivity assessments, this study focuses on integrating white matter fiber-specific microstructural properties into structural connectomes. Spanning ages 8-19 years in a developmental sample, it explores age-related patterns of microstructure-informed network properties at both local and global scales. First, the diffusion-weighted signal fraction associated with each tractography-reconstructed streamline was constructed. Subsequently, the convex optimization modeling for microstructure-informed tractography (COMMIT) approach was employed to generate microstructure-informed connectomes from diffusion MRI data. To complete the investigation, network characteristics within eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks) were evaluated. The findings underscore a consistent increase in global efficiency across child and adolescent development within the visual, somatomotor, and default mode networks (p < 0.005). Additionally, mean strength exhibits an upward trend in the somatomotor and visual networks (p < 0.001). Notably, nodes within the dorsal and ventral visual pathways manifest substantial age-dependent changes in local efficiency, aligning with existing evidence of extended maturation in these pathways. The outcomes strongly support the notion of a prolonged developmental trajectory for visual association cortices. This study contributes valuable insights into the nuanced dynamics of microstructure-informed brain connectivity throughout different developmental stages.
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Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children’s Hospital, Parkville, Victoria, Australia
- Developmental Imaging, Clinical Sciences, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Simona Schiavi
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Department of Computer Science, University of Verona, Italy
- ASG Superconductors, Genova, Italy
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Eindhoven University of Technology, Department of Mathematics and Computer Science, Eindhoven, Netherlands
| | - Chantal M. W. Tax
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, United Kingdom
| | - Erika P. Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | | | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
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Wendt J, Neubauer A, Hedderich DM, Schmitz‐Koep B, Ayyildiz S, Schinz D, Hippen R, Daamen M, Boecker H, Zimmer C, Wolke D, Bartmann P, Sorg C, Menegaux A. Human Claustrum Connections: Robust In Vivo Detection by DWI-Based Tractography in Two Large Samples. Hum Brain Mapp 2024; 45:e70042. [PMID: 39397271 PMCID: PMC11471578 DOI: 10.1002/hbm.70042] [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: 01/28/2024] [Revised: 09/24/2024] [Accepted: 09/27/2024] [Indexed: 10/15/2024] Open
Abstract
Despite substantial neuroscience research in the last decade revealing the claustrum's prominent role in mammalian forebrain organization, as evidenced by its extraordinarily widespread connectivity pattern, claustrum studies in humans are rare. This is particularly true for studies focusing on claustrum connections. Two primary reasons may account for this situation: First, the intricate anatomy of the human claustrum located between the external and extreme capsule hinders straightforward and reliable structural delineation. In addition, the few studies that used diffusion-weighted-imaging (DWI)-based tractography could not clarify whether in vivo tractography consistently and reliably identifies claustrum connections in humans across different subjects, cohorts, imaging methods, and connectivity metrics. To address these issues, we combined a recently developed deep-learning-based claustrum segmentation tool with DWI-based tractography in two large adult cohorts: 81 healthy young adults from the human connectome project and 81 further healthy young participants from the Bavarian longitudinal study. Tracts between the claustrum and 13 cortical and 9 subcortical regions were reconstructed in each subject using probabilistic tractography. Probabilistic group average maps and different connectivity metrics were generated to assess the claustrum's connectivity profile as well as consistency and replicability of tractography. We found, across individuals, cohorts, DWI-protocols, and measures, consistent and replicable cortical and subcortical ipsi- and contralateral claustrum connections. This result demonstrates robust in vivo tractography of claustrum connections in humans, providing a base for further examinations of claustrum connectivity in health and disease.
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Affiliation(s)
- Jil Wendt
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Antonia Neubauer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Dennis M. Hedderich
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Benita Schmitz‐Koep
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Sevilay Ayyildiz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - David Schinz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Rebecca Hippen
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Marcel Daamen
- Department of Diagnostic and Interventional Radiology, Clinical Functional Imaging GroupUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Department of Diagnostic and Interventional Radiology, Clinical Functional Imaging GroupUniversity Hospital BonnBonnGermany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
| | - Dieter Wolke
- Department of PsychologyUniversity of WarwickCoventryUK
- Warwick Medical SchoolUniversity of WarwickCoventryUK
| | - Peter Bartmann
- Department of Neonatology and Pediatric Intensive CareUniversity Hospital BonnBonnGermany
| | - Christian Sorg
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
- Department of Psychiatry, School of Medicine and HealthTechnical University of MunichMunichGermany
| | - Aurore Menegaux
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine and HealthTechnical University of MunichMunichGermany
- School of Medicine and Health, TUM‐NIC Neuroimaging CenterTechnical University of MunichMunichGermany
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Lien R, Furlano JA, Witt ST, Xian C, Nagamatsu LS. The effects of a six-month exercise intervention on white matter microstructure in older adults at risk for diabetes. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 7:100369. [PMID: 39345304 PMCID: PMC11437870 DOI: 10.1016/j.cccb.2024.100369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 08/30/2024] [Accepted: 09/05/2024] [Indexed: 10/01/2024]
Abstract
Older adults with prediabetes or obesity (i.e., those at risk for diabetes) exhibit impaired structural brain networks. Given findings that resistance training (RT) can combat brain impairments in many populations, this study aimed to test the effects of this type of exercise on white matter microstructure in older adults at risk for diabetes. Seventeen community-dwelling older adults (mean age 67.8 ± 5.7, 52.9 % female) with prediabetes or obesity were randomly allocated to thrice weekly RT or balance and tone training (BAT; control group) for six months. Diffusion weighted imaging via a 3T scanner was used to assess changes in white matter parameters -fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) - over time. Participants in the RT group showed no significant changes in FA but had increased MD and RD in various regions related to cognitive function including the cingulate gyrus. Participants in the control group had both increased and decreased FA depending on the specific white matter tracts; increased FA was seen in areas related to motor coordination such as the middle cerebellar peduncle. The control group also exhibited decreased MD and RD in areas responsible for motor function (e.g., left anterior limb of the internal capsule). We conclude that both resistance and balance exercises result in changes in white matter microstructure albeit in divergent tracts that may be linked to the specific exercises performed.
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Affiliation(s)
- Ryu Lien
- School of Kinesiology, Faculty of Health Sciences, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Joyla A Furlano
- Neuroscience, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Suzanne T Witt
- BrainsCAN, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Chengqian Xian
- Department of Statistical and Actuarial Sciences, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
| | - Lindsay S Nagamatsu
- School of Kinesiology, Faculty of Health Sciences, Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
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8
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Ding J, Thye M, Edmondson-Stait AJ, Szaflarski JP, Mirman D. Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia. Brain Commun 2024; 6:fcae313. [PMID: 39318782 PMCID: PMC11420983 DOI: 10.1093/braincomms/fcae313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 06/26/2024] [Accepted: 09/11/2024] [Indexed: 09/26/2024] Open
Abstract
Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.
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Affiliation(s)
- Junhua Ding
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Melissa Thye
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | | | - Jerzy P Szaflarski
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Daniel Mirman
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
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Shamir I, Assaf Y. Tutorial: a guide to diffusion MRI and structural connectomics. Nat Protoc 2024:10.1038/s41596-024-01052-5. [PMID: 39232202 DOI: 10.1038/s41596-024-01052-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/09/2024] [Indexed: 09/06/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
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10
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Lissaman R, Rajagopal S, Kearley J, Pasvanis S, Rajah MN. Menopause status- and sex-related differences in age associations with spatial context memory and white matter microstructure at midlife. Neurobiol Aging 2024; 141:151-159. [PMID: 38954878 DOI: 10.1016/j.neurobiolaging.2024.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 05/28/2024] [Accepted: 05/31/2024] [Indexed: 07/04/2024]
Abstract
Decline in spatial context memory emerges in midlife, the time when most females transition from pre- to post-menopause. Recent evidence suggests that, among post-menopausal females, advanced age is associated with functional brain alterations and lower spatial context memory. However, it is unknown whether similar effects are evident for white matter (WM) and, moreover, whether such effects contribute to sex differences at midlife. To address this, we conducted a study on 96 cognitively unimpaired middle-aged adults (30 males, 32 pre-menopausal females, 34 post-menopausal females). Spatial context memory was assessed using a face-location memory paradigm, while WM microstructure was assessed using diffusion tensor imaging. Behaviorally, advanced age was associated with lower spatial context memory in post-menopausal females but not pre-menopausal females or males. Additionally, advanced age was associated with microstructural variability in predominantly frontal WM (e.g., anterior corona radiata, genu of corpus callosum), which was related to lower spatial context memory among post-menopausal females. Our findings suggest that post-menopausal status enhances vulnerability to age effects on the brain's WM and episodic memory.
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Affiliation(s)
- Rikki Lissaman
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
| | | | - Julia Kearley
- Department of Psychology, McGill University, Montreal, QC, Canada
| | | | - Maria Natasha Rajah
- Department of Psychiatry, McGill University, Montreal, QC, Canada; Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada
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11
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Janko M, Santaniello SD, Brockmann C, Wolf M, Grauhan NF, Schöffling VI, Dimova V, Ponto K, Hoffmann EM, Kleinekofort W, Othman AE, Brockmann MA, Kronfeld A. Comparison of T1-weighted landmark placement and ROI transfer onto diffusion-weighted EPI sequences for targeted tractography tasks in the optic nerve. Eur J Neurosci 2024; 60:4987-4999. [PMID: 39085986 DOI: 10.1111/ejn.16490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/11/2024] [Accepted: 07/20/2024] [Indexed: 08/02/2024]
Abstract
Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.
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Affiliation(s)
- Markus Janko
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sascha D Santaniello
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Carolin Brockmann
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Marcel Wolf
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Nils F Grauhan
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Vanessa I Schöffling
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Violeta Dimova
- Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Katharina Ponto
- Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Esther M Hoffmann
- Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | | | - Ahmed E Othman
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Marc A Brockmann
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Andrea Kronfeld
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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MacIver CL, Jones D, Green K, Szewczyk-Krolikowski K, Doring A, Tax CMW, Peall KJ. White Matter Microstructural Changes Using Ultra-Strong Diffusion Gradient MRI in Adult-Onset Idiopathic Focal Cervical Dystonia. Neurology 2024; 103:e209695. [PMID: 39110927 PMCID: PMC11319067 DOI: 10.1212/wnl.0000000000209695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 05/28/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Adult-onset idiopathic focal cervical dystonia (AOIFCD) involves abnormal posturing of the cervical musculature and, in some individuals, an associated head tremor. Existing neuroimaging studies have implicated key motor networks. However, measures used to date lack specificity toward underlying pathophysiologic differences. We aim to assess white matter motor pathways for localized, microstructural differences, which may aid in understanding underlying mechanisms. METHODS Individuals diagnosed with AOIFCD and an age- and sex-matched control group were prospectively recruited through the Welsh Movement Disorders Research Network. All participants underwent in-depth clinical phenotyping and MRI (structural and diffusion sequences) using ultra-strong diffusion gradients. Tractography (whole-tract median values) and tractometry (along tract profiling) were performed for key white matter motor pathways assessing diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and standard model parameters. Groups were compared using linear model analysis with Bonferroni multiple comparison correction. RESULTS Fifty participants with AOIFCD and 30 healthy control participants were recruited, with 46 with AOIFCD and 30 healthy controls included for analysis (33 without head tremor, 13 with head tremor). Significant differences were observed in the anterior thalamic radiations (lower mid-tract fractional anisotropy [estimate = -0.046, p = 3.07 × 10-3], radial kurtosis [estimate = -0.165, p = 1.42 × 10-4], f-intra-axonal signal fraction [estimate = -0.044, p = 2.78 × 10-3], p2 orientation coherence [estimate = -0.043, p = 1.64 × 10-3], higher Orientation Dispersion Index [ODI, estimate = 0.023, p = 2.22 × 10-3]) and thalamopremotor tracts (higher mid-tract mean kurtosis [estimate = 0.064, p = 7.56 × 10-4], lower Neurite Density Index [estimate = 0.062, p = 2.1 × 10-3], higher distal tract ODI [estimate = 0.062, p = 3.1 × 10-3], lower f [estimate = -0.1, p = 2.3 × 10-3], and striatopremotor tracts [proximal lower f: estimate = -0.075, p = 1.06 × 10-3]). These measures correlated with clinical measures: dystonia duration (right thalamopremotor distal ODI: r = -0.9, p = 1.29 × 10-14), psychiatric symptoms (obsessive compulsive symptoms: left anterior thalamic radiation p2 r = 0.92, p = 2.797 × 10-11), sleep quality (Sleep Disorders Questionnaire Score: left anterior thalamic radiation ODI: r = -0.84, p = 4.84 × 10-11), pain (left anterior thalamic radiation ODI: r = -0.89, p = 1.4 × 10-13), and cognitive functioning (paired associated learning task p2, r = 0.94, p = 6.68 × 10-20). DISCUSSION Overall, localized microstructural differences were identified within tracts linking the prefrontal and premotor cortices with thalamic and basal ganglia regions, suggesting pathophysiologic processes involve microstructural aberrances of motor system modulatory pathways, particularly involving intra-axonal and fiber orientation dispersion measures.
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Affiliation(s)
- Claire L MacIver
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Derek Jones
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Katy Green
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Konrad Szewczyk-Krolikowski
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Andre Doring
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Chantal M W Tax
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
| | - Kathryn J Peall
- From the Cardiff University Brain Research Imaging Centre (C.L.M., D.J., K.G., A.D., C.M.W.T.), Cardiff University; Neuroscience and Mental Health Research Institute (C.L.M., K.J.P.), Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine; North Bristol NHS Trust (K.S.-K.), United Kingdom; and Image Sciences Institute (C.M.W.T.), University Medical Center Utrecht, the Netherlands
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13
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Kirby ED, Andrushko JW, Boyd LA, Koschutnig K, D'Arcy RCN. Sex differences in patterns of white matter neuroplasticity after balance training in young adults. Front Hum Neurosci 2024; 18:1432830. [PMID: 39257696 PMCID: PMC11383771 DOI: 10.3389/fnhum.2024.1432830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Accepted: 08/08/2024] [Indexed: 09/12/2024] Open
Abstract
Introduction In past work we demonstrated different patterns of white matter (WM) plasticity in females versus males associated with learning a lab-based unilateral motor skill. However, this work was completed in neurologically intact older adults. The current manuscript sought to replicate and expand upon these WM findings in two ways: (1) we investigated biological sex differences in neurologically intact young adults, and (2) participants learned a dynamic full-body balance task. Methods 24 participants (14 female, 10 male) participated in the balance training intervention, and 28 were matched controls (16 female, 12 male). Correlational tractography was used to analyze changes in WM from pre- to post-training. Results Both females and males demonstrated skill acquisition, yet there were significant differences in measures of WM between females and males. These data support a growing body of evidence suggesting that females exhibit increased WM neuroplasticity changes relative to males despite comparable changes in motor behavior (e.g., balance). Discussion The biological sex differences reported here may represent an important factor to consider in both basic research (e.g., collapsing across females and males) as well as future clinical studies of neuroplasticity associated with motor function (e.g., tailored rehabilitation approaches).
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Affiliation(s)
- Eric D Kirby
- BrainNet, Health and Technology District, Surrey, BC, Canada
- Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, BC, Canada
- Faculty of Science, Simon Fraser University, Burnaby, BC, Canada
| | - Justin W Andrushko
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
- Brain Behavior Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Lara A Boyd
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Brain Behavior Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Karl Koschutnig
- Institute of Psychology, BioTechMed Graz, University of Graz, Graz, Austria
| | - Ryan C N D'Arcy
- BrainNet, Health and Technology District, Surrey, BC, Canada
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Faculty of Applied Sciences, Simon Fraser University, Burnaby, BC, Canada
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14
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Bautin P, Fortier MA, Sean M, Little G, Martel M, Descoteaux M, Léonard G, Tétreault P. What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review. Pain 2024:00006396-990000000-00689. [PMID: 39172945 DOI: 10.1097/j.pain.0000000000003345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/13/2024] [Indexed: 08/24/2024]
Abstract
ABSTRACT Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.
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Affiliation(s)
- Paul Bautin
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Marc-Antoine Fortier
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Monica Sean
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Graham Little
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Marylie Martel
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Guillaume Léonard
- School of Rehabilitation, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Research Centre on Aging du Centre intégré universitaire de santé et de services sociaux de l'Estrie-Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Pascal Tétreault
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Medical Imaging and Radiation Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
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15
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Li Y, Zhu H, Liu Y, Ding Y, Li S, Li L, Zhang J, Jiang J, Shen N, Zhu W. Assessment the Impact of IDH Mutation Status on MRI Assessments of White Matter Integrity in Glioma Patients: Insights From Peak Width of Skeletonized Mean Diffusivity and Free Water Metrics. J Magn Reson Imaging 2024. [PMID: 39165049 DOI: 10.1002/jmri.29561] [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: 04/26/2024] [Revised: 07/24/2024] [Accepted: 07/24/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND Gliomas are highly invasive brain tumors that evade accurate geographic assessment by conventional MRI due to microscopic invasion along white matter (WM) tracts. Advanced diffusion MRI techniques are needed to assess occult WM involvement. PURPOSE To evaluate peak width of skeletonized mean diffusivity (PSMD) and peak width of skeletonized free water (PSFW), and axonal water fraction (AWF) for assessing glioma-induced alterations in normal-appearing WM and their relationship with isocitrate dehydrogenase 1 (IDH1) mutation. STUDY TYPE Retrospective. POPULATION One hundred five glioma patients (46 ± 13 years), 53 healthy controls (HCs) (46 ± 9 years). FIELD STRENGTH/SEQUENCE 3.0 T, T1WI, T1-CE, T2WI, T2FLAIR, and DKI. ASSESSMENT PSMD and PSFW were compared between lesion and contralateral sides in glioma patients and between patients and HCs. The associations between these metrics and clinical variables, including IDH1 mutation, was assessed. Corpus callosum (CC) injury, quantified by the AWF, was evaluated for its mediated effect of IDH1 mutation on contralesional PSMD and PSFW. STATISTICAL TESTS Paired-t tests, ANCOVA, univariate and multivariate linear regression, and mediation analysis with significance set at P < 0.05. RESULTS Contralateral PSMD and PSFW were significantly higher in left-sided gliomas (PSMD: 0.206 ± 0.027 vs. 0.193 ± 0.023; PSFW: 0.119 ± 0.019 vs. 0.106 ± 0.020) than in HCs, with similar increases in right-sided gliomas (PSMD: 0.219 ± 0.036 vs. 0.195 ± 0.023; PSFW: 0.129 ± 0.031 vs. 0.109 ± 0.020). IDH1 wild-type gliomas were associated with higher contralateral PSMD and PSFW (β = -0.302 and -0.412). AWF of CC mediated the impact of IDH1 mutations on contralesional PSMD and PSFW (mediated proportion: 42.7% and 53.7%). DATA CONCLUSION PSMD and PSFW are effective biomarkers for assessing WM integrity in gliomas, significantly associated with IDH1 mutation status. AWF of CC mediates the relationship between IDH1 mutation and contralesional PSMD and PSFW. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yufei Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yujie Ding
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaxuan Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingjing Jiang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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16
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Takemura H, Kaneko T, Sherwood CC, Johnson GA, Axer M, Hecht EE, Ye FQ, Leopold DA. A prominent vertical occipital white matter fasciculus unique to primate brains. Curr Biol 2024; 34:3632-3643.e4. [PMID: 38991613 PMCID: PMC11338705 DOI: 10.1016/j.cub.2024.06.034] [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: 02/18/2024] [Revised: 06/09/2024] [Accepted: 06/11/2024] [Indexed: 07/13/2024]
Abstract
Vision in humans and other primates enlists parallel processing streams in the dorsal and ventral visual cortex, known to support spatial and object processing, respectively. These streams are bridged, however, by a prominent white matter tract, the vertical occipital fasciculus (VOF), identified in both classical neuroanatomy and recent diffusion-weighted magnetic resonance imaging (dMRI) studies. Understanding the evolution of the VOF may shed light on its origin, function, and role in visually guided behaviors. To this end, we acquired high-resolution dMRI data from the brains of select mammalian species, including anthropoid and strepsirrhine primates, a tree shrew, rodents, and carnivores. In each species, we attempted to delineate the VOF after first locating the optic radiations in the occipital white matter. In all primate species examined, the optic radiation was flanked laterally by a prominent and coherent white matter fasciculus recognizable as the VOF. By contrast, the equivalent analysis applied to four non-primate species from the same superorder as primates (tree shrew, ground squirrel, paca, and rat) failed to reveal white matter tracts in the equivalent location. Clear evidence for a VOF was also absent in two larger carnivore species (ferret and fox). Although we cannot rule out the existence of minor or differently organized homologous fiber pathways in the non-primate species, the results suggest that the VOF has greatly expanded, or possibly emerged, in the primate lineage. This adaptation likely facilitated the evolution of unique visually guided behaviors in primates, with direct impacts on manual object manipulation, social interactions, and arboreal locomotion.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki-shi, Aichi 444-8585, Japan; The Graduate Institute for Advanced Studies, SOKENDAI, Shonan Village, Hayama-cho, Kanagawa 240-0193, Japan; Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita-shi, Osaka 565-0871, Japan.
| | - Takaaki Kaneko
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, 41-2 Kanrin, Inuyama-shi, Aichi 484-8506, Japan; Division of Behavioral Development, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki-shi, Aichi, Japan
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, 800 22nd St. NW, Washington, DC 20052, USA
| | - G Allan Johnson
- Department of Radiology, Duke Center for In Vivo Microscopy, Duke Medical Center, 311 Research Drive, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, 101 Science Dive., Durham, NC 27705, USA
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich 52425, Germany; Department of Physics, School of Mathematics and Natural Sciences, University of Wuppertal, Gaußstraße 20 42119, Wuppertal, Germany
| | - Erin E Hecht
- Department of Human Evolutionary Biology, Harvard University, 11 Divinity Avenue, Cambridge, MA 02138, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20814, USA; Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA.
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17
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Karat BG, Genc S, Raven EP, Palombo M, Khan AR, Jones DK. The developing hippocampus: Microstructural evolution through childhood and adolescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.19.608590. [PMID: 39229062 PMCID: PMC11370384 DOI: 10.1101/2024.08.19.608590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.
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Affiliation(s)
- Bradley G Karat
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - Sila Genc
- Department of Neurosurgery, The Royal Children's Hospital, Melbourne, Australia
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | - Ali R Khan
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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18
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Asaridou SS, Cler GJ, Wiedemann A, Krishnan S, Smith HJ, Willis HE, Healy MP, Watkins KE. Microstructural Properties of the Cerebellar Peduncles in Children With Developmental Language Disorder. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:774-794. [PMID: 39175782 PMCID: PMC11338306 DOI: 10.1162/nol_a_00142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 03/13/2024] [Indexed: 08/24/2024]
Abstract
Children with developmental language disorder (DLD) struggle to learn their native language for no apparent reason. While research on the neurobiological underpinnings of the disorder has focused on the role of corticostriatal systems, little is known about the role of the cerebellum in DLD. Corticocerebellar circuits might be involved in the disorder as they contribute to complex sensorimotor skill learning, including the acquisition of spoken language. Here, we used diffusion-weighted imaging data from 77 typically developing and 54 children with DLD and performed probabilistic tractography to identify the cerebellum's white matter tracts: the inferior, middle, and superior cerebellar peduncles. Children with DLD showed lower fractional anisotropy (FA) in the inferior cerebellar peduncles (ICP), fiber tracts that carry motor and sensory input via the inferior olive to the cerebellum. Lower FA in DLD was driven by lower axial diffusivity. Probing this further with more sophisticated modeling of diffusion data, we found higher orientation dispersion but no difference in neurite density in the ICP of children with DLD. Reduced FA is therefore unlikely to be reflecting microstructural differences in myelination, rather the organization of axons in these pathways is disrupted. ICP microstructure was not associated with language or motor coordination performance in our sample. We also found no differences in the middle and superior peduncles, the main pathways connecting the cerebellum with the cortex. To conclude, it is not corticocerebellar but atypical olivocerebellar white matter connections that characterize DLD and suggest the involvement of the olivocerebellar system in speech and language acquisition and development.
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Affiliation(s)
- Salomi S. Asaridou
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Gabriel J. Cler
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Speech & Hearing Sciences, University of Washington, Seattle, WA, USA
| | - Anna Wiedemann
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Saloni Krishnan
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychology, Royal Holloway, University of London, Egham Hill, Surrey, UK
| | - Harriet J. Smith
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Hanna E. Willis
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Máiréad P. Healy
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Kate E. Watkins
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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19
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Kwiatkowski A, Weidler C, Habel U, Coverdale NS, Hirad AA, Manning KY, Rauscher A, Bazarian JJ, Cook DJ, Li DKB, Mahon BZ, Menon RS, Taunton J, Reetz K, Romanzetti S, Huppertz C. Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes. Hum Brain Mapp 2024; 45:e26811. [PMID: 39185683 PMCID: PMC11345636 DOI: 10.1002/hbm.26811] [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: 01/19/2024] [Revised: 07/16/2024] [Accepted: 07/20/2024] [Indexed: 08/27/2024] Open
Abstract
Repetitive subconcussive head impacts (RSHI) are believed to induce sub-clinical brain injuries, potentially resulting in cumulative, long-term brain alterations. This study explores patterns of longitudinal brain white matter changes across sports with RSHI-exposure. A systematic literature search identified 22 datasets with longitudinal diffusion magnetic resonance imaging data. Four datasets were centrally pooled to perform uniform quality control and data preprocessing. A total of 131 non-concussed active athletes (American football, rugby, ice hockey; mean age: 20.06 ± 2.06 years) with baseline and post-season data were included. Nonparametric permutation inference (one-sample t tests, one-sided) was applied to analyze the difference maps of multiple diffusion parameters. The analyses revealed widespread lateralized patterns of sports-season-related increases and decreases in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) across spatially distinct white matter regions. Increases were shown across one MD-cluster (3195 voxels; mean change: 2.34%), one AD-cluster (5740 voxels; mean change: 1.75%), and three RD-clusters (817 total voxels; mean change: 3.11 to 4.70%). Decreases were shown across two MD-clusters (1637 total voxels; mean change: -1.43 to -1.48%), two RD-clusters (1240 total voxels; mean change: -1.92 to -1.93%), and one AD-cluster (724 voxels; mean change: -1.28%). The resulting pattern implies the presence of strain-induced injuries in central and brainstem regions, with comparatively milder physical exercise-induced effects across frontal and superior regions of the left hemisphere, which need further investigation. This article highlights key considerations that need to be addressed in future work to enhance our understanding of the nature of observed white matter changes, improve the comparability of findings across studies, and promote data pooling initiatives to allow more detailed investigations (e.g., exploring sex- and sport-specific effects).
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Affiliation(s)
- Anna Kwiatkowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| | - Carmen Weidler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| | - Ute Habel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
- Institute of Neuroscience and Medicine 10, Research Centre JülichJülichGermany
- JARA‐BRAIN Institute Brain Structure Function Relationship, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | | | - Adnan A. Hirad
- Department of SurgeryUniversity of Rochester Medical CenterRochesterNew YorkUSA
- Department of NeuroscienceUniversity of Rochester Medical CenterRochesterNew YorkUSA
- Del Monte Neuroscience Institute, University of RochesterNew YorkUSA
| | - Kathryn Y. Manning
- Department of RadiologyUniversity of Calgary and Alberta Children's Hospital Research InstituteCalgaryAlbertaCanada
| | - Alexander Rauscher
- Department of Radiology, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Pediatrics, Division of NeurologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- UBC MRI Research Centre, University of British ColumbiaVancouverBritish ColumbiaCanada
| | - Jeffrey J. Bazarian
- Department of Emergency MedicineUniversity of Rochester School of Medicine and DentistryRochesterNew YorkUSA
| | - Douglas J. Cook
- Centre for Neuroscience Studies, Queen's UniversityKingstonOntarioCanada
- Division of Neurosurgery, Department of SurgeryQueen's UniversityKingstonOntarioCanada
| | - David K. B. Li
- Department of Radiology, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Bradford Z. Mahon
- Department of PsychologyCarnegie Mellon UniversityPittsburghPennsylvaniaUSA
- Carnegie Mellon Neuroscience InstitutePittsburghPennsylvaniaUSA
- Department of NeurosurgeryUniversity of Rochester Medical CenterRochesterNew YorkUSA
| | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western OntarioLondonOntarioCanada
| | - Jack Taunton
- Allan McGavin Sports Medicine Centre, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Kathrin Reetz
- Department of Neurology, Medical FacultyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | - Sandro Romanzetti
- Department of Neurology, Medical FacultyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | - Charlotte Huppertz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
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20
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Jossinger S, Yablonski M, Amir O, Ben-Shachar M. The Contributions of the Cerebellar Peduncles and the Frontal Aslant Tract in Mediating Speech Fluency. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:676-700. [PMID: 39175785 PMCID: PMC11338307 DOI: 10.1162/nol_a_00098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 12/23/2022] [Indexed: 08/24/2024]
Abstract
Fluent speech production is a complex task that spans multiple processes, from conceptual framing and lexical access, through phonological encoding, to articulatory control. For the most part, imaging studies portraying the neural correlates of speech fluency tend to examine clinical populations sustaining speech impairments and focus on either lexical access or articulatory control, but not both. Here, we evaluated the contribution of the cerebellar peduncles to speech fluency by measuring the different components of the process in a sample of 45 neurotypical adults. Participants underwent an unstructured interview to assess their natural speaking rate and articulation rate, and completed timed semantic and phonemic fluency tasks to assess their verbal fluency. Diffusion magnetic resonance imaging with probabilistic tractography was used to segment the bilateral cerebellar peduncles (CPs) and frontal aslant tract (FAT), previously associated with speech production in clinical populations. Our results demonstrate distinct patterns of white matter associations with different fluency components. Specifically, verbal fluency is associated with the right superior CP, whereas speaking rate is associated with the right middle CP and bilateral FAT. No association is found with articulation rate in these pathways, in contrast to previous findings in persons who stutter. Our findings support the contribution of the cerebellum to aspects of speech production that go beyond articulatory control, such as lexical access, pragmatic or syntactic generation. Further, we demonstrate that distinct cerebellar pathways dissociate different components of speech fluency in neurotypical speakers.
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Affiliation(s)
- Sivan Jossinger
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Maya Yablonski
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Ofer Amir
- Department of Communication Disorders, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Michal Ben-Shachar
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
- The Department of English Literature and Linguistics, Bar-Ilan University, Ramat-Gan, Israel
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21
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Calixto C, Jaimes C, Soldatelli MD, Warfield SK, Gholipour A, Karimi D. Anatomically constrained tractography of the fetal brain. Neuroimage 2024; 297:120723. [PMID: 39029605 PMCID: PMC11382095 DOI: 10.1016/j.neuroimage.2024.120723] [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: 05/22/2024] [Accepted: 07/03/2024] [Indexed: 07/21/2024] Open
Abstract
Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.
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Affiliation(s)
- Camilo Calixto
- Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
| | - Camilo Jaimes
- Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA
| | | | - Simon K Warfield
- Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
| | - Ali Gholipour
- Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
| | - Davood Karimi
- Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA.
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22
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Tymofiyeva O, Sipes BS, Luks T, Hamlat EJ, Samson TE, Hoffmann TJ, Glidden DV, Jakary A, Li Y, Ngan T, Henje E, Yang TT. Interoceptive brain network mechanisms of mindfulness-based training in healthy adolescents. Front Psychol 2024; 15:1410319. [PMID: 39193038 PMCID: PMC11348390 DOI: 10.3389/fpsyg.2024.1410319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 07/18/2024] [Indexed: 08/29/2024] Open
Abstract
Introduction This study evaluated changes in the white matter of the brain and psychological health variables, resulting from a neuroscience-based mindfulness intervention, the Training for Awareness, Resilience, and Action (TARA), in a population of healthy adolescents. Methods A total of 100 healthy adolescents (57 female, age ranges 14-18 years) were randomized into the 12-week TARA intervention or a waitlist-control group. All participants were imaged with diffusion MRI to quantify white matter connectivity between brain regions. Imaging occurred at baseline/randomization and after 12 weeks of baseline (pre- and post-intervention in the TARA group). We hypothesized that structural connectivity in the striatum and interoceptive networks would increase following the TARA intervention, and that, this increased connectivity would relate to psychological health metrics from the Strengths and Difficulties Questionnaire (SDQ) and the Insomnia Severity Index (ISI). The TARA intervention and all assessments, except for the MRIs, were fully remotely delivered using secure telehealth platforms and online electronic data capture systems. Results The TARA intervention showed high consistency, tolerability, safety, recruitment, fidelity, adherence, and retention. After 12 weeks, the TARA group, but not controls, also demonstrated significantly improved sleep quality (p = 0.02), and changes in the right putamen node strength were related to this improved sleep quality (r = -0.42, p = 0.006). Similarly, the TARA group, but not controls, had significantly increased right insula node strength related to improved emotional well-being (r = -0.31, p = 0.04). Finally, we used the network-based statistics to identify a white matter interoception network that strengthened following TARA (p = 0.009). Discussion These results suggest that the TARA mindfulness-based intervention in healthy adolescents is feasible and safe, and it may act to increase structural connectivity strength in interoceptive brain regions. Furthermore, these white matter changes are associated with improved adolescent sleep quality and emotional well-being. Our results suggest that TARA could be a promising fully remotely delivered intervention for improving psychological well-being in adolescents. As our findings suggest that TARA affects brain regions in healthy adolescents, which are also known to be altered during depression in adolescents, future studies will examine the effects of TARA on depressed adolescents. Clinical trial registration https://clinicaltrials.gov/study/NCT04254796.
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Affiliation(s)
- Olga Tymofiyeva
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Benjamin S. Sipes
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Tracy Luks
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Elissa J. Hamlat
- Division of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, Langley Porter Psychiatric Institute, University of California, San Francisco, San Francisco, CA, United States
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Tara E. Samson
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Thomas J. Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - David V. Glidden
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Angela Jakary
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Yi Li
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Tiffany Ngan
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Eva Henje
- Department of Clinical Science/Child- and Adolescent Psychiatry, Umeå University, Umeå, Sweden
| | - Tony T. Yang
- Division of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, Langley Porter Psychiatric Institute, University of California, San Francisco, San Francisco, CA, United States
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
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23
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Vandergaag ID, Nania C, Timmers I, Simons L, Lebel C, Rasic N, Walker A, Noel M, Miller JV. Sleep disturbances, altered brain microstructure and chronic headache in youth. Brain Imaging Behav 2024; 18:875-883. [PMID: 38558207 DOI: 10.1007/s11682-024-00876-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2024] [Indexed: 04/04/2024]
Abstract
Chronic headache (persistent or recurrent headache for 3-months or longer) is highly prevalent among youth. While sleep disturbances have been associated with headache, their inter-relationship with brain connectivity remains unknown. This observational study examined whether self-report and actigraphy measures of sleep were associated with alterations to white matter tracts (i.e., uncinate fasciculus and cingulum) in youth with chronic headache versus healthy controls. Thirty youth aged 10-18 years with chronic headache and thirty controls underwent an MRI. Diffusion tensor images were obtained and mean fractional anisotropy values of the cingulum and uncinate were extracted. One-week prior to their MRI, youth wore an actigraph to obtain sleep duration, wake after sleep onset and sleep efficiency measures. Moreover, they completed questionnaires regarding their sleep quality and pain symptomatology. Linear regression was applied to examine the relationships between sleep (self-report and actigraphy), fractional anisotropy, and number of headache days per month. Self-report and actigraphy measures of sleep did not differ between patients and controls. However, poorer self-reported sleep quality was associated with lower fractional anisotropy values in the left uncinate (P = 0.05). Lower left uncinate fractional anisotropy was related to increased headache frequency (P = 0.002) in youth with chronic headache. Therefore, alterations to connectivity may be associated with the relationship between altered perceptions of sleep and headache chronicity.
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Affiliation(s)
- Isabella Derij Vandergaag
- Biomedical Engineering, Calgary, AB, Canada
- McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, AB, Canada
| | - Cara Nania
- School and Applied Child Psychology, c Psychology, d Radiology, e Anesthesiology, Perioperative & Pain Medicine, University of Calgary, Calgary, AB, Canada
| | - Inge Timmers
- Medical and Clinical Psychology, Tilburg University, Tilburg, Netherlands
| | | | - Catherine Lebel
- Child Brain & Mental Health Program, i Owerko Centre, Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada
| | - Nivez Rasic
- Child Brain & Mental Health Program, i Owerko Centre, Alberta Children's Hospital Research Institute, Calgary, AB, Canada
| | | | - Melanie Noel
- Child Brain & Mental Health Program, i Owerko Centre, Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada
| | - Jillian Vinall Miller
- Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA, USA.
- Child Brain & Mental Health Program, i Owerko Centre, Alberta Children's Hospital Research Institute, Calgary, AB, Canada.
- Hotchkiss Brain Institute, Mathison Centre for Mental Health Research & Education, Calgary, AB, Canada.
- Department of Anesthesiology, Perioperative and Pain Medicine, 28 Oki Dr NW, Calgary, AB, T3B 6A8, Canada.
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24
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Hacker BJ, Imms PE, Dharani AM, Zhu J, Chowdhury NF, Chaudhari NN, Irimia A. Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning. J Neurotrauma 2024; 41:1883-1900. [PMID: 38482793 DOI: 10.1089/neu.2023.0509] [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] [Indexed: 04/30/2024] Open
Abstract
Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinations are equivocal. Such individuals can benefit from novel accurate assessments that complement clinical diagnostics. We introduce a Bayesian machine learning classifier to identify concussion through cortico-cortical connectome mapping from magnetic resonance imaging in persons with quasi-normal cognition and without neuroradiological findings. Classifier features are generated from connectivity matrices specifying the mean fractional anisotropy of white matter connections linking brain structures. Each connection's saliency to classification was quantified by training individual classifier instantiations using a single feature type. The classifier was tested on a discovery sample of 92 healthy controls (HCs; 26 females, age μ ± σ: 39.8 ± 15.5 years) and 471 adult mTBI patients (158 females, age μ ± σ: 38.4 ± 5.9 years). Results were replicated in an independent validation sample of 256 HCs (149 females, age μ ± σ: 55.3 ± 12.1 years) and 126 patients with concussion (46 females, age μ ± σ: 39.0 ± 17.7 years). Classifier accuracy exceeds 99% in both samples, suggesting robust generalizability to new samples. Notably, 13 bilateral cortico-cortical connection pairs predict diagnostic status with accuracy exceeding 99% in both discovery and validation samples. Many such connection pairs are between prefrontal cortex structures, fronto-limbic and fronto-subcortical structures, and occipito-temporal structures in the ventral ("what") visual stream. This and related connectivity form a highly salient network of brain connections that is particularly vulnerable to concussion. Because these connections are important in mediating cognitive control, memory, and attention, our findings explain the high frequency of cognitive disturbances after concussion. Our classifier was trained and validated on concussed participants with cognitive profiles very similar to those of HCs. This suggests that the classifier can complement current diagnostics by providing independent information in clinical contexts where patients have quasi-normal cognition but where concussion diagnosis stands to benefit from additional evidence.
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Affiliation(s)
- Benjamin J Hacker
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Mork Family Department of Chemical Engineering and Materials Science, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Phoebe E Imms
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Ammar M Dharani
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Jessica Zhu
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Nahian F Chowdhury
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Nikhil N Chaudhari
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Department of Quantitative and Computational Biology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
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25
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Pontillo G, Cepas MB, Broeders TAA, Koubiyr I, Schoonheim MM. Network Analysis in Multiple Sclerosis and Related Disorders. Neuroimaging Clin N Am 2024; 34:375-384. [PMID: 38942522 DOI: 10.1016/j.nic.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease of the central nervous system, commonly featuring disability and cognitive impairment. The pathologic hallmark of MS lies in demyelination and hence impaired structural and functional neuronal pathways. Recent studies have shown that MS shows extensive structural disconnection of key network hub areas like the thalamus, combined with a functional network reorganization that can mostly be related to poorer clinical functioning. As MS can, therefore, be considered a network disorder, this review outlines recent innovations in the field of network neuroscience in MS.
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Affiliation(s)
- Giuseppe Pontillo
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands; MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Mar Barrantes Cepas
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Tommy A A Broeders
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
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Freire IS, Lopes TS, Afonso SG, Pereira DJ. From images to insights: a neuroradiologist's practical guide on white matter fiber tract anatomy and DTI patterns for pre-surgical planning. Neuroradiology 2024; 66:1251-1265. [PMID: 38635028 DOI: 10.1007/s00234-024-03362-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 04/13/2024] [Indexed: 04/19/2024]
Abstract
INTRODUCTION Diffusion tensor imaging (DTI) is a valuable non-invasive imaging modality for mapping white matter tracts and assessing microstructural integrity, and can be used as a "biomarker" in diagnosis, differentiation, and therapeutic monitoring. Although it has gained clinical importance as a marker of neuropathology, limitations in its interpretation underscore the need for caution. METHODS This review provides an overview of the principles and clinical applicability of DTI. We focus on major white matter fiber bundles, detailing their normal anatomy and pathological DTI patterns, with emphasis on tracts routinely requested in our neurosurgical department in the preoperative context (uncinate fasciculus, arcuate fasciculus, pyramidal pathway, optic radiation, and dentatorubrothalamic tract). RESULTS We guide neuroradiologists and neurosurgeons in defining volumes of interest for mapping individual tracts and demonstrating their 3D reconstructions. The intricate trajectories of white matter tracts pose a challenge for accurate fiber orientation recording, with each bundle exhibiting specific characteristics. Tracts adjacent to brain lesions are categorized as displaced, edematous, infiltrated, or disrupted, illustrated with clinical cases of brain neoplasms. To improve structured reporting, we propose a checklist of topics for inclusion in imaging evaluations and MRI reports. CONCLUSION DTI is emerging as a powerful tool for assessing microstructural changes in brain disorders, despite some challenges in standardization and interpretation. This review serves an educational purpose by providing guidance for fiber monitoring and interpretation of pathological patterns observed in clinical cases, highlighting the importance and potential pitfalls of DTI in neuroradiology and surgical planning.
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Affiliation(s)
- Inês S Freire
- Department of Neuroradiology - Centro Hospitalar Universitário de Lisboa Central (CHULC), Rua José António Serrano, 1150-199, Lisbon, Portugal.
- NOVA Medical School, Universidade Nova de Lisboa, Lisbon, Portugal.
| | - Tânia S Lopes
- Institute of Nuclear Sciences Applied to Health (ICNAS), Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Coimbra, Portugal
| | - Sónia G Afonso
- Institute of Nuclear Sciences Applied to Health (ICNAS), Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Coimbra, Portugal
| | - Daniela J Pereira
- Institute of Nuclear Sciences Applied to Health (ICNAS), Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Coimbra, Portugal
- Functional Unit of Neuroradiology - Centro Hospitalar e Universitário de Coimbra (CHUC), Coimbra, Portugal
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Quach M, Ali I, Shultz SR, Casillas-Espinosa PM, Hudson MR, Jones NC, Silva JC, Yamakawa GR, Braine EL, Immonen R, Staba RJ, Tohka J, Harris NG, Gröhn O, O'Brien TJ, Wright DK. ComBating inter-site differences in field strength: harmonizing preclinical traumatic brain injury MRI data. NMR IN BIOMEDICINE 2024; 37:e5142. [PMID: 38494895 DOI: 10.1002/nbm.5142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 12/09/2023] [Accepted: 02/15/2024] [Indexed: 03/19/2024]
Abstract
Integrating datasets from multiple sites and scanners can increase statistical power for neuroimaging studies but can also introduce significant inter-site confounds. We evaluated the effectiveness of ComBat, an empirical Bayes approach, to combine longitudinal preclinical MRI data acquired at 4.7 or 9.4 T at two different sites in Australia. Male Sprague Dawley rats underwent MRI on Days 2, 9, 28, and 150 following moderate/severe traumatic brain injury (TBI) or sham injury as part of Project 1 of the NIH/NINDS-funded Centre Without Walls EpiBioS4Rx project. Diffusion-weighted and multiple-gradient-echo images were acquired, and outcomes included QSM, FA, and ADC. Acute injury measures including apnea and self-righting reflex were consistent between sites. Mixed-effect analysis of ipsilateral and contralateral corpus callosum (CC) summary values revealed a significant effect of site on FA and ADC values, which was removed following ComBat harmonization. Bland-Altman plots for each metric showed reduced variability across sites following ComBat harmonization, including for QSM, despite appearing to be largely unaffected by inter-site differences and no effect of site observed. Following harmonization, the combined inter-site data revealed significant differences in the imaging metrics consistent with previously reported outcomes. TBI resulted in significantly reduced FA and increased susceptibility in the ipsilateral CC, and significantly reduced FA in the contralateral CC compared with sham-injured rats. Additionally, TBI rats also exhibited a reversal in ipsilateral CC ADC values over time with significantly reduced ADC at Day 9, followed by increased ADC 150 days after injury. Our findings demonstrate the need for harmonizing multi-site preclinical MRI data and show that this can be successfully achieved using ComBat while preserving phenotypical changes due to TBI.
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Affiliation(s)
- Mara Quach
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Melbourne, Victoria, Australia
| | - Idrish Ali
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Sandy R Shultz
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
- Health Sciences, Vancouver Island University, Nanaimo, British Columbia, Canada
| | - Pablo M Casillas-Espinosa
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
- Department of Neurology, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Matthew R Hudson
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Nigel C Jones
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Juliana C Silva
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Glenn R Yamakawa
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Emma L Braine
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Riikka Immonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Richard J Staba
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, California, USA
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Neil G Harris
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, California, USA
| | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Terence J O'Brien
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
- Department of Neurology, The Alfred Hospital, Melbourne, Victoria, Australia
| | - David K Wright
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
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Chen X, Roberts N, Zheng Q, Peng Y, Han Y, Luo Q, Feng J, Luo T, Li Y. Comparison of diffusion tensor imaging (DTI) tissue characterization parameters in white matter tracts of patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Eur Radiol 2024; 34:5263-5275. [PMID: 38175221 DOI: 10.1007/s00330-023-10550-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 09/25/2023] [Accepted: 11/11/2023] [Indexed: 01/05/2024]
Abstract
OBJECTIVE To investigate the microstructural properties of T2 lesion and normal-appearing white matter (NAWM) in 20 white matter tracts between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and correlations between the tissue damage and clinical variables. METHODS The white matter (WM) compartment of the brain was segmented for 56 healthy controls (HC), 48 patients with MS, and 38 patients with NMOSD, and for the patients further subdivided into T2 lesion and NAWM. Subsequently, the diffusion tensor imaging (DTI) tissue characterization parameters of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared for 20 principal white matter tracts. The correlation between tissue damage and clinical variables was also investigated. RESULTS The higher T2 lesion volumes of 14 fibers were shown in MS compared to NMOSD. MS showed more microstructure damage in 13 fibers of T2 lesion, but similar microstructure in seven fibers compared to NMOSD. MS and NMOSD had microstructure damage of NAWM in 20 fibers compared to WM in HC, with more damage in 20 fibers in MS compared to NMOSD. MS patients showed higher correlation between the microstructure of T2 lesion areas and NAWM. The T2 lesion microstructure damage was correlated with duration and impaired cognition in MS. CONCLUSIONS Patients with MS and NMOSD show different patterns of microstructural damage in T2 lesion and NAWM areas. The prolonged disease course of MS may aggravate the microstructural damage, and the degree of microstructural damage is further related to cognitive impairment. CLINICAL RELEVANCE STATEMENT Microstructure differences between T2 lesion areas and normal-appearing white matter help distinguish multiple sclerosis and neuromyelitis optica spectrum disorder. In multiple sclerosis, lesions rather than normal-appearing white matter should be a concern, because the degree of lesion severity correlated both with normal-appearing white matter damage and cognitive impairment. KEY POINTS • Multiple sclerosis and neuromyelitis optica spectrum disorder have different damage patterns in T2 lesion and normal-appearing white matter areas. • The microstructure damage of normal-appearing white matter is correlated with the microstructure of T2 lesion in multiple sclerosis and neuromyelitis optica spectrum disorder. • The microstructure damage of T2 lesion in multiple sclerosis is correlated with duration and cognitive impairment.
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Affiliation(s)
- Xiaoya Chen
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Neil Roberts
- Edinburgh Imaging Facility QMRI, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Qiao Zheng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yuling Peng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yongliang Han
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Qi Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jinzhou Feng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Tianyou Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
| | - Yongmei Li
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Obaid S, Guberman GI, St-Onge E, Campbell E, Edde M, Lamsam L, Bouthillier A, Weil AG, Daducci A, Rheault F, Nguyen DK, Descoteaux M. Progressive remodeling of structural networks following surgery for operculo-insular epilepsy. Front Neurol 2024; 15:1400601. [PMID: 39144703 PMCID: PMC11322451 DOI: 10.3389/fneur.2024.1400601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/15/2024] [Indexed: 08/16/2024] Open
Abstract
Introduction Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients. Methods Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling. Results We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1). Discussion To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.
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Affiliation(s)
- Sami Obaid
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
| | - Guido I. Guberman
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Etienne St-Onge
- Department of Computer Science and Engineering, Université du Québec en Outaouais, Montreal, QC, Canada
| | - Emma Campbell
- Department of Psychology, University of Montreal, Montreal, QC, Canada
| | - Manon Edde
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
| | - Layton Lamsam
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Alain Bouthillier
- Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
| | - Alexander G. Weil
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- Division of Pediatric Neurosurgery, Department of Surgery, Sainte Justine Hospital, University of Montreal, Montreal, QC, Canada
| | | | - François Rheault
- Medical Imaging and Neuroimaging (MINi) Lab, Sherbrooke University, Sherbrooke, QC, Canada
| | - Dang K. Nguyen
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Division of Neurology, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
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30
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Genc S, Ball G, Chamberland M, Raven EP, Tax CM, Ward I, Yang JYM, Palombo M, Jones DK. MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.30.605934. [PMID: 39131383 PMCID: PMC11312524 DOI: 10.1101/2024.07.30.605934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss with age. However, the underlying cellular mechanisms remain elusive with conventional neuroimaging. Recent advances in MRI hardware and new biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. This study used ultra-strong gradient MRI to obtain high-resolution, in vivo estimates of cortical neurite and soma microstructure in sample of typically developing children and adolescents. Cortical neurite signal fraction, attributed to neuronal and glial processes, increased with age (mean R2 fneurite=.53, p<3.3e-11, 11.91% increase over age), while apparent soma radius decreased (mean R2 Rsoma=.48, p<4.4e-10, 1% decrease over age) across domain-specific networks. To complement these findings, developmental patterns of cortical gene expression in two independent post-mortem databases were analysed. This revealed increased expression of genes expressed in oligodendrocytes, and excitatory neurons, alongside a relative decrease in expression of genes expressed in astrocyte, microglia and endothelial cell-types. Age-related genes were significantly enriched in cortical oligodendrocytes, oligodendrocyte progenitors and Layer 5-6 neurons (pFDR<.001) and prominently expressed in adolescence and young adulthood. The spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes suggest that ongoing cortical myelination processes contribute to adolescent cortical development. These findings highlight the role of intra-cortical myelination in cortical maturation during adolescence and into adulthood.
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Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, Victoria, Australia
| | - Gareth Ball
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Eindhoven University of Technology, Department of Mathematics and Computer Science, Eindhoven, The Netherlands
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, USA
| | - Chantal Mw Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Isobel Ward
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Data and Analysis for Social Care and Health, Office for National Statistics, Newport, United Kingdom
| | - Joseph Yuan-Mou Yang
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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Cottam NC, Ofori K, Bryant M, Rogge JR, Hekmatyar K, Sun J, Charvet CJ. From circuits to lifespan: translating mouse and human timelines with neuroimaging based tractography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.28.605528. [PMID: 39131378 PMCID: PMC11312435 DOI: 10.1101/2024.07.28.605528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Age is a major predictor of developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging. The timeline of human developmental circuits is well known. It is unclear how such timelines compare to those in mice. We lack age alignments across the lifespan of mice and humans. Here, we build upon our Translating Time resource, which is a tool that equates corresponding ages during development. We collected 477 time points (n=1,132 observations) from age-related changes in body, bone, dental, and brain processes to equate corresponding ages across humans and mice. We acquired high-resolution diffusion MR scans of mouse brains (n=12) at sequential stages of postnatal development (postnatal day 3, 4, 12, 21, 60) to trace the timeline of brain circuit maturation (e.g., olfactory association pathway, corpus callosum). We found heterogeneity in white matter pathway growth. The corpus callosum largely ceases to grow days after birth while the olfactory association pathway grows through P60. We found that a P3 mouse equates to a human at roughly GW24, and a P60 mouse equates to a human in teenage years. Therefore, white matter pathway maturation is extended in mice as it is in humans, but there are species-specific adaptations. For example, olfactory-related wiring is protracted in mice, which is linked to their reliance on olfaction. Our findings underscore the importance of translational tools to map common and species-specific biological processes from model systems to humans.
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Affiliation(s)
- Nicholas C. Cottam
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
| | - Kwadwo Ofori
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
| | - Madison Bryant
- College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Jessica R. Rogge
- College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Khan Hekmatyar
- Center for Biomedical and Brain Imaging Center, University of Delaware, Wilmington, DE, USA
- Advanced Translational Imaging Facility, Georgia State University, Atlanta, GA
| | - Jianli Sun
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
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Matthews TE, Lumaca M, Witek MAG, Penhune VB, Vuust P. Music reward sensitivity is associated with greater information transfer capacity within dorsal and motor white matter networks in musicians. Brain Struct Funct 2024:10.1007/s00429-024-02836-x. [PMID: 39052097 DOI: 10.1007/s00429-024-02836-x] [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: 02/19/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024]
Abstract
There are pronounced differences in the degree to which individuals experience music-induced pleasure which are linked to variations in structural connectivity between auditory and reward areas. However, previous studies exploring the link between white matter structure and music reward sensitivity (MRS) have relied on standard diffusion tensor imaging methods, which present challenges in terms of anatomical accuracy and interpretability. Further, the link between MRS and connectivity in regions outside of auditory-reward networks, as well as the role of musical training, have yet to be investigated. Therefore, we investigated the relation between MRS and structural connectivity in a large number of directly segmented and anatomically verified white matter tracts in musicians (n = 24) and non-musicians (n = 23) using state-of-the-art tract reconstruction and fixel-based analysis. Using a manual tract-of-interest approach, we additionally tested MRS-white matter associations in auditory-reward networks seen in previous studies. Within the musician group, there was a significant positive relation between MRS and fiber density and cross section in the right middle longitudinal fascicle connecting auditory and inferior parietal cortices. There were also positive relations between MRS and fiber-bundle cross-section in tracts connecting the left thalamus to the ventral precentral gyrus and connecting the right thalamus to the right supplementary motor area, however, these did not survive FDR correction. These results suggest that, within musicians, dorsal auditory and motor networks are crucial to MRS, possibly via their roles in top-down predictive processing and auditory-motor transformations.
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Affiliation(s)
- Tomas E Matthews
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark.
| | - Massimo Lumaca
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark
| | - Maria A G Witek
- Department of Music School of Languages, Art History and Music, University of Birmingham, Cultures, Birmingham, B15 2TT, UK
| | - Virginia B Penhune
- Department of Psychology, Concordia University, 7141 Sherbrooke St W, Montreal, QC, H4B 1R6, Canada
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark
- Royal Academy of Music, Skovgaardsgade 2C, Aarhus C, DK-8000, Denmark
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33
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Johnson JF, Schwartze M, Belyk M, Pinheiro AP, Kotz SA. Variability in white matter structure relates to hallucination proneness. Neuroimage Clin 2024; 43:103643. [PMID: 39042953 PMCID: PMC11325372 DOI: 10.1016/j.nicl.2024.103643] [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: 06/22/2024] [Accepted: 07/15/2024] [Indexed: 07/25/2024]
Abstract
Hallucinations are a prominent transdiagnostic psychiatric symptom but are also prevalent in individuals who do not require clinical care. Moreover, persistent psychosis-like experience in otherwise healthy individuals may be related to an increased risk to transition to a psychotic disorder. This suggests a common etiology across clinical and non-clinical individuals along a multidimensional psychosis continuum that may be detectable in structural variations of the brain. The current diffusion tensor imaging study assessed 50 healthy individuals (35 females) to identify possible differences in white matter associated with hallucination proneness (HP). This approach circumvents potential confounds related to medication, hospitalization, and disease progression common in clinical individuals. We determined how HP relates to white matter structure in selected association, commissural, and projection fiber pathways putatively linked to psychosis. Increased HP was associated with enhanced fractional anisotropy (FA) in the right uncinate fasciculus, the right anterior and posterior arcuate fasciculus, and the corpus callosum. These findings support the notion of a psychosis continuum, providing first evidence of structural white matter variability associated with HP in healthy individuals. Furthermore, alterations in the targeted pathways likely indicate an association between HP-related structural variations and the putative salience and attention mechanisms that these pathways subserve.
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Affiliation(s)
- Joseph F Johnson
- Université Libre de Bruxelles, Center for Research in Cognition & Neurosciences, Bruxelles, Belgium; University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands
| | - Michael Schwartze
- University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands
| | - Michel Belyk
- Edge Hill University, Department of Psychology, Ormskirk, United Kingdom
| | - Ana P Pinheiro
- Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal
| | - Sonja A Kotz
- University of Maastricht, Department of Neuropsychology and Psychopharmacology, Maastricht, The Netherlands; Max Planck Institute for Human and Cognitive Sciences, Department of Neuropsychology, Leipzig, Germany.
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Larivière S, Park BY, Royer J, DeKraker J, Ngo A, Sahlas E, Chen J, Rodríguez-Cruces R, Weng Y, Frauscher B, Liu R, Wang Z, Shafiei G, Mišić B, Bernasconi A, Bernasconi N, Fox MD, Zhang Z, Bernhardt BC. Connectome reorganization associated with temporal lobe pathology and its surgical resection. Brain 2024; 147:2483-2495. [PMID: 38701342 PMCID: PMC11224603 DOI: 10.1093/brain/awae141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 03/23/2024] [Accepted: 04/05/2024] [Indexed: 05/05/2024] Open
Abstract
Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.
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Affiliation(s)
- Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard University, Boston, MA 02115, USA
| | - Bo-yong Park
- Department of Data Science, Inha University, Incheon 22212, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 34126, Republic of Korea
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Ella Sahlas
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Judy Chen
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, China
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Ruoting Liu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, China
| | - Zhengge Wang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bratislav Mišić
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard University, Boston, MA 02115, USA
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, China
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
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Takemura H, Kruper JA, Miyata T, Rokem A. Tractometry of Human Visual White Matter Pathways in Health and Disease. Magn Reson Med Sci 2024; 23:316-340. [PMID: 38866532 PMCID: PMC11234945 DOI: 10.2463/mrms.rev.2024-0007] [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] [Indexed: 06/14/2024] Open
Abstract
Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Hayama, Kanagawa, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - John A Kruper
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | - Toshikazu Miyata
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - Ariel Rokem
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
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Millán AP, van Straaten ECW, Stam CJ, Nissen IA, Idema S, Van Mieghem P, Hillebrand A. Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study. Netw Neurosci 2024; 8:437-465. [PMID: 38952815 PMCID: PMC11142635 DOI: 10.1162/netn_a_00361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed a framework of individualized computational models that combines epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). ESSES parameters were fitted in a retrospective study (N = 15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES reproduced the iEEG-recorded seizures, and significantly better so for patients with good (seizure-free, SF) than bad (nonseizure-free, NSF) outcome. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N = 34) with a blind setting (to the resection strategy and surgical outcome) that emulated presurgical conditions. By setting the model parameters in the retrospective study, ESSES could be applied also to patients without iEEG data. ESSES could predict the chances of good outcome after any resection by finding patient-specific model-based optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan overlapped more with the model-based optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated with a fully independent cohort and without the need for iEEG recordings.
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Affiliation(s)
- Ana P. Millán
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Institute “Carlos I” for Theoretical and Computational Physics, and Electromagnetism and Matter Physics Department, University of Granada, Granada, Spain
| | - Elisabeth C. W. van Straaten
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Ida A. Nissen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
| | - Sander Idema
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurosurgery, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Cancer Biology and Immonology, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
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Verschuur AS, Tax CMW, Boomsma MF, Carlson HL, van Wezel-Meijler G, King R, Leemans A, Leijser LM. Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data. FRONTIERS IN RADIOLOGY 2024; 4:1416672. [PMID: 39007078 PMCID: PMC11239519 DOI: 10.3389/fradi.2024.1416672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/10/2024] [Indexed: 07/16/2024]
Abstract
Purpose The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures. Methods For the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures. Results Contrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%. Conclusion Reconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts.
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Affiliation(s)
- Anouk S Verschuur
- Department of Radiology, Isala Hospital, Zwolle, Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
- Department of Pediatrics, Section of Newborn Critical Care, University of Calgary, Calgary, AB, Canada
| | - Chantal M W Tax
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
- CUBRIC, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Martijn F Boomsma
- Department of Radiology, Isala Hospital, Zwolle, Netherlands
- Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Helen L Carlson
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Regan King
- Department of Pediatrics, Section of Newborn Critical Care, University of Calgary, Calgary, AB, Canada
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - Lara M Leijser
- Department of Pediatrics, Section of Newborn Critical Care, University of Calgary, Calgary, AB, Canada
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Marecek S, Krajca T, Krupicka R, Sojka P, Nepozitek J, Varga Z, Mala C, Keller J, Waugh JL, Zogala D, Trnka J, Sonka K, Ruzicka E, Dusek P. Analysis of striatal connectivity corresponding to striosomes and matrix in de novo Parkinson's disease and isolated REM behavior disorder. NPJ Parkinsons Dis 2024; 10:124. [PMID: 38918417 PMCID: PMC11199557 DOI: 10.1038/s41531-024-00736-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 06/07/2024] [Indexed: 06/27/2024] Open
Abstract
Striosomes and matrix are two compartments that comprise the striatum, each having its own distinct immunohistochemical properties, function, and connectivity. It is currently not clear whether prodromal or early manifest Parkinson's disease (PD) is associated with any striatal matrix or striosomal abnormality. Recently, a method of striatal parcellation using probabilistic tractography has been described and validated, using the distinct connectivity of these two compartments to identify voxels with striosome- and matrix-like connectivity. The goal of this study was to use this approach in tandem with DAT-SPECT, a method used to quantify the level of nigrostriatal denervation, to analyze the striatum in populations of de novo diagnosed, treatment-naïve patients with PD, isolated REM behavioral disorder (iRBD) patients, and healthy controls. We discovered a shift in striatal connectivity, which showed correlation with nigrostriatal denervation. Patients with PD exhibited a significantly higher matrix-like volume and associated connectivity than healthy controls and higher matrix-associated connectivity than iRBD patients. In contrast, the side with less pronounced nigrostriatal denervation in PD and iRBD patients showed a decrease in striosome-like volume and associated connectivity indices. These findings could point to a compensatory neuroplastic mechanism in the context of nigrostriatal denervation and open a new avenue in the investigation of the pathophysiology of Parkinson's disease.
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Affiliation(s)
- S Marecek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
| | - T Krajca
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Kladno, Czech Republic
| | - R Krupicka
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Kladno, Czech Republic
| | - P Sojka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - J Nepozitek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Z Varga
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - C Mala
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Kladno, Czech Republic
| | - J Keller
- Department of Radiodiagnostics, Na Homolce Hospital, Prague, Czech Republic
| | - J L Waugh
- Division of Pediatric Neurology, Department of Pediatrics, University of Texas Southwestern, Dallas, TX, USA
| | - D Zogala
- Institute of Nuclear Medicine, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - J Trnka
- Institute of Nuclear Medicine, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - K Sonka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - E Ruzicka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - P Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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Wang HR, Liu ZQ, Nakua H, Hegarty CE, Thies MB, Patel PK, Schleifer CH, Boeck TP, McKinney RA, Currin D, Leathem L, DeRosse P, Bearden CE, Misic B, Karlsgodt KH. Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated With Psychopathology Across Independent Cohorts. Biol Psychiatry 2024:S0006-3223(24)01391-X. [PMID: 38908657 DOI: 10.1016/j.biopsych.2024.06.011] [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: 01/04/2024] [Revised: 05/14/2024] [Accepted: 06/11/2024] [Indexed: 06/24/2024]
Abstract
BACKGROUND Patients with early psychosis (EP) (within 3 years after psychosis onset) show significant variability, which makes predicting outcomes challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, which limits the development of early interventions. METHODS A data-driven approach, partial least squares correlation, was used across 2 independent datasets to examine multivariate relationships between white matter properties and symptomatology and to identify stable and generalizable signatures in EP. The primary cohort included patients with EP from the Human Connectome Project for Early Psychosis (n = 124). The replication cohort included patients with EP from the Feinstein Institute for Medical Research (n = 78) as part of the MEND (Multimodal Evaluation of Neural Disorders) Project. Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. RESULTS In both cohorts, a significant latent component corresponded to a symptom profile that combined negative symptoms, primarily diminished expression, with specific somatic symptoms. Both latent components captured comprehensive features of white matter disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the partial least squares model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. CONCLUSIONS This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural white matter alterations in EP across diagnoses and datasets, showing strong covariance of these alterations with a unique profile of negative and somatic symptoms. These findings suggest the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.
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Affiliation(s)
- Haley R Wang
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Zhen-Qi Liu
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
| | - Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Catherine E Hegarty
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Melanie Blair Thies
- Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Pooja K Patel
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; Desert Pacific Mental Illness Research, Education, and Clinical Center Greater Los Angeles VA Healthcare System, Los Angeles, California
| | - Charles H Schleifer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Thomas P Boeck
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Rachel A McKinney
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Danielle Currin
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Logan Leathem
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Pamela DeRosse
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Carrie E Bearden
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
| | - Katherine H Karlsgodt
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California.
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Neukam PT, Müller DK, Deza-Lougovski YI, Pooseh S, Witt SH, Rietschel M, Smolka MN. Connection Failure: Differences in White Matter Microstructure Are Associated with 5-HTTLPR but Not with Risk Seeking for Losses. Int J Mol Sci 2024; 25:6666. [PMID: 38928372 PMCID: PMC11203796 DOI: 10.3390/ijms25126666] [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: 05/04/2024] [Revised: 06/10/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
S/S carriers of 5-HTTLPR have been found to be more risk seeking for losses compared to L/L carriers. This finding may be the result of reduced top-down control from the frontal cortex due to altered signal pathways involving the amygdala and ventral striatum. The serotonergic system is known to be involved in neurodevelopment and neuroplasticity. Therefore, the aim of this study was to investigate whether structural differences in white matter can explain the differences in risk-seeking behaviour. Lower structural connectivity in S/S compared to L/L carriers and a negative relationship between risk seeking for losses and connectivity were assumed. Diffusion-weighted imaging was used to compute diffusion parameters for the frontostriatal and uncinate tract in 175 genotyped individuals. The results showed no significant relationship between diffusion parameters and risk seeking for losses. Furthermore, we did not find significant differences in diffusion parameters of the S/S vs. L/L group. There were only group differences in the frontostriatal tract showing stronger structural connectivity in the S/L group, which is also reflected in the whole brain approach. Therefore, the data do not support the hypothesis that the association between 5-HTTLPR and risk seeking for losses is related to differences in white matter pathways implicated in decision-making.
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Affiliation(s)
- Philipp T. Neukam
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, 01307 Dresden, Germany;
| | - Dirk K. Müller
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, Germany
| | | | - Shakoor Pooseh
- Center for Interdisciplinary Digital Sciences (CIDS), Technische Universität Dresden, 01069 Dresden, Germany;
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, 68159 Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, 68159 Mannheim, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, 01307 Dresden, Germany;
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Anderson ME, Wind EJ, Robison LS. Exploring the neuroprotective role of physical activity in cerebral small vessel disease. Brain Res 2024; 1833:148884. [PMID: 38527712 DOI: 10.1016/j.brainres.2024.148884] [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: 12/27/2023] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 03/27/2024]
Abstract
Cerebral small vessel disease (cSVD) is a common neurological finding characterized by abnormalities of the small blood vessels in the brain. Previous research has established a strong connection between cSVD and stroke, as well as neurodegenerative disorders, notably Alzheimer's disease (AD) and other dementias. As the search for effective interventions continues, physical activity (PA) has emerged as a potential preventative and therapeutic avenue. This review synthesizes the human and animal literature on the influence of PA on cSVD, highlighting the importance of determining optimal exercise protocols, considering aspects such as intensity, duration, timing, and exercise type. Furthermore, the necessity of widening the age bracket in research samples is discussed, ensuring a holistic understanding of the interventions across varying pathological stages of the disease. The review also suggests the potential of exploring diverse biomarkers and risk profiles associated with clinically significant outcomes. Moreover, we review findings demonstrating the beneficial effects of PA in various rodent models of cSVD, which have uncovered numerous mechanisms of neuroprotection, including increases in neuroplasticity and integrity of the vasculature and white matter; decreases in inflammation, oxidative stress, and mitochondrial dysfunction; and alterations in amyloid processing and neurotransmitter signaling. In conclusion, this review highlights the potential of physical activity as a preventive strategy for addressing cSVD, offering insights into the need for refining exercise parameters, diversifying research populations, and exploring novel biomarkers, while shedding light on the intricate mechanisms through which exercise confers neuroprotection in both humans and animal models.
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Affiliation(s)
- Maria E Anderson
- Department of Psychology, Family, and Justice Studies, University of Saint Joseph, 1678 Asylum Ave, West Hartford, CT 06117, USA
| | - Eleanor J Wind
- Department of Psychology and Neuroscience, Nova Southeastern University, 3300 S. University Drive, Fort Lauderdale, FL 33328, USA
| | - Lisa S Robison
- Department of Psychology and Neuroscience, Nova Southeastern University, 3300 S. University Drive, Fort Lauderdale, FL 33328, USA.
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Skandalakis GP, Linn W, Yeh F, Kazim SF, Komaitis S, Neromyliotis E, Dimopoulos D, Drosos E, Hadjipanayis CG, Kongkham PN, Zadeh G, Stranjalis G, Koutsarnakis C, Kogan M, Evans LT, Kalyvas A. Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways. Hum Brain Mapp 2024; 45:e26771. [PMID: 38925589 PMCID: PMC11199201 DOI: 10.1002/hbm.26771] [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: 10/30/2023] [Revised: 04/17/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024] Open
Abstract
Neuroimaging studies have consistently demonstrated concurrent activation of the human precuneus and temporal pole (TP), both during resting-state conditions and various higher-order cognitive functions. However, the precise underlying structural connectivity between these brain regions remains uncertain despite significant advancements in neuroscience research. In this study, we investigated the connectivity of the precuneus and TP by employing parcellation-based fiber micro-dissections in human brains and fiber tractography techniques in a sample of 1065 human subjects and a sample of 41 rhesus macaques. Our results demonstrate the connectivity between the posterior precuneus area POS2 and the areas 35, 36, and TG of the TP via the fifth subcomponent of the cingulum (CB-V) also known as parahippocampal cingulum. This finding contributes to our understanding of the connections within the posteromedial cortices, facilitating a more comprehensive integration of anatomy and function in both normal and pathological brain processes. PRACTITIONER POINTS: Our investigation delves into the intricate architecture and connectivity patterns of subregions within the precuneus and temporal pole, filling a crucial gap in our knowledge. We revealed a direct axonal connection between the posterior precuneus (POS2) and specific areas (35, 35, and TG) of the temporal pole. The direct connections are part of the CB-V pathway and exhibit a significant association with the cingulum, SRF, forceps major, and ILF. Population-based human tractography and rhesus macaque fiber tractography showed consistent results that support micro-dissection outcomes.
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Affiliation(s)
- Georgios P. Skandalakis
- Section of NeurosurgeryDartmouth Hitchcock Medical CenterLebanonNew HampshireUSA
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Wen‐Jieh Linn
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Fang‐Cheng Yeh
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Syed Faraz Kazim
- Department of NeurosurgeryUniversity of New Mexico HospitalAlbuquerqueNew MexicoUSA
| | - Spyridon Komaitis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Eleftherios Neromyliotis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Dimitrios Dimopoulos
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Evangelos Drosos
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | | | - Paul N. Kongkham
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
| | - Gelareh Zadeh
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
| | - George Stranjalis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Christos Koutsarnakis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Michael Kogan
- Department of NeurosurgeryUniversity of New Mexico HospitalAlbuquerqueNew MexicoUSA
| | - Linton T. Evans
- Section of NeurosurgeryDartmouth Hitchcock Medical CenterLebanonNew HampshireUSA
| | - Aristotelis Kalyvas
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
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Midrigan-Ciochina L, Vodacek KP, Sewell C, Corina DP. A Comparison of White Matter Brain Differences in Monolingual and Highly Proficient Multilingual Speakers. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:497-527. [PMID: 38911457 PMCID: PMC11192512 DOI: 10.1162/nol_a_00144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 03/20/2024] [Indexed: 06/25/2024]
Abstract
Language processing relies on the communication between brain regions that is achieved through several white matter tracts, part of the dorsal, ventral, and medial pathways involved in language processing and control (Coggins et al., 2004; Friederici & Gierhan, 2013; Hickok & Poeppel, 2007; Luk et al., 2011). While changes in white matter tract morphology have been reported as a function of second language learning in bilinguals, little is known about changes that may be present in multilanguage users. Here we investigate white matter morphometry in a group of highly proficient multilinguals, (individuals with proficiency in four or more languages), compared to a group of monolinguals. White matter morphometry was quantified using a fixel-based analysis (Raffelt et al., 2015; Raffelt et al., 2017; Tournier et al., 2007). Higher fiber cross-section and lower fiber density values were observed for the multilinguals, in the dorsal pathways (superior longitudinal fasciculus and arcuate fasciculus) and the ventral pathway, including the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and the uncinate fasciculus. Segments of the corpus callosum, the fornix, and the cortico-spinal tract showed decreases in all three morphometry measures for multilinguals. The findings suggest differential efficiencies in neural communication between domain-specific language regions and domain-general cognitive processes underlying multilingual language use. We discuss the results in relation to the bilingual Anterior to Posterior and Subcortical Shift (BAPSS) hypothesis (Grundy et al., 2017) and the Dynamic Restructuring Model (Pliatsikas, 2020).
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Affiliation(s)
- Ludmila Midrigan-Ciochina
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
- Department of Linguistics and Human Ecology, University of California, Davis, Davis, CA, USA
| | - Kayla P. Vodacek
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
| | - Cristina Sewell
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
| | - David P. Corina
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
- Department of Linguistics and Psychology, University of California, Davis, Davis, CA, USA
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Zhang Z, Wei W, Wang S, Li M, Li X, Li X, Wang Q, Yu H, Zhang Y, Guo W, Ma X, Zhao L, Deng W, Sham PC, Sun Y, Li T. Dynamic structure-function coupling across three major psychiatric disorders. Psychol Med 2024; 54:1629-1640. [PMID: 38084608 DOI: 10.1017/s0033291723003525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
BACKGROUND Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). METHODS We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time. RESULTS The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity. CONCLUSIONS These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.
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Affiliation(s)
- Zhe Zhang
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- School of Physics, Hangzhou Normal University, Hangzhou, China
- Institute of Brain Science, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, China
| | - Wei Wei
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Sujie Wang
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
| | - Mingli Li
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Li
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Xiaoyu Li
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
| | - Hua Yu
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Yamin Zhang
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Wanjun Guo
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Deng
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
| | - Pak C Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong SAR, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Yu Sun
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Li
- Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
- Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
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Duanmu X, Wen J, Qin J, Tan S, Wu C, Yuan W, Zheng Q, Zhou C, Wu H, Chen J, Wang S, Hong H, Guo T, Wu J, Zhu B, Fang Y, Yan Y, Zhao G, Zhang B, Zhang M, Guan X, Xu X. Differential influences of rest tremor on brain fiber architecture in essential tremor and Parkinson's disease. Parkinsonism Relat Disord 2024; 123:106559. [PMID: 38513448 DOI: 10.1016/j.parkreldis.2024.106559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Rest tremor is a movement disorder commonly found in diseases like Parkinson's disease (PD) and essential tremor (ET). Rest tremor typically shows slower progression in PD, but more severe progression in ET. However, the underlying white matter organization of rest tremor behind PD and ET remains unclear. METHODS This study included 57 ET patients (40 without rest tremor (ETWR), 17 with rest tremor (ETRT)), 68 PD patients (34 without rest tremor (PDWR), 34 with rest tremor (PDRT)), and 62 normal controls (NC). Fixel-based analysis was used to evaluate the structural changes of white matter in rest tremor in these different diseases. RESULTS The fiber-bundle cross-section (FC) of the right non-decussating dentato-rubro-thalamic tract and several fibers outside the dentato-rubro-thalamic pathway in ETWR were significantly higher than that in NC. The fiber density and cross-section of the left nigro-pallidal in PDWR is significantly lower than that in NC, while the FC of bilateral nigro-pallidal in PDRT is significantly lower than that in NC. CONCLUSION ET patients with pure action tremor showed over-activation of fiber tracts. However, when superimposed with rest tremor, ET patients no longer exhibited over-activation of fiber tracts, but rather showed a trend of fiber tract damage. Except for the nigro-pallidal degeneration in all PD, PDRT will not experience further deterioration in fiber organization. These results provide important insights into the unique effects of rest tremor on brain fiber architecture in ET and PD.
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Affiliation(s)
- Xiaojie Duanmu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianmei Qin
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Sijia Tan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chenqing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weijin Yuan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qianshi Zheng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haoting Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingwen Chen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bingting Zhu
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Yuelin Fang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Yaping Yan
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Guohua Zhao
- Department of Neurology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China; Joint Laboratory of Clinical Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Nägele FL, Petersen M, Mayer C, Bönstrup M, Schulz R, Gerloff C, Thomalla G, Cheng B. Longitudinal microstructural alterations surrounding subcortical ischemic stroke lesions detected by free-water imaging. Hum Brain Mapp 2024; 45:e26722. [PMID: 38780442 PMCID: PMC11114091 DOI: 10.1002/hbm.26722] [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: 10/29/2023] [Revised: 03/20/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
In this study we explore the spatio-temporal trajectory and clinical relevance of microstructural white matter changes within and beyond subcortical stroke lesions detected by free-water imaging. Twenty-seven patients with subcortical infarct with mean age of 66.73 (SD 11.57) and median initial NIHSS score of 4 (IQR 3-7) received diffusion MRI 3-5 days, 1 month, 3 months, and 12 months after symptom-onset. Extracellular free-water and fractional anisotropy of the tissue (FAT) were averaged within stroke lesions and the surrounding tissue. Linear models showed increased free-water and decreased FAT in the white matter of patients with subcortical stroke (lesion [free-water/FAT, mean relative difference in %, ipsilesional vs. contralesional hemisphere at 3-5 days, 1 month, 3 months, and 12 months after symptom-onset]: +41/-34, +111/-37, +208/-26, +251/-18; perilesional tissue [range in %]: +[5-24]/-[0.2-7], +[2-20]/-[3-16], +[5-43]/-[2-16], +[10-110]/-[2-12]). Microstructural changes were most prominent within the lesion and gradually became less pronounced with increasing distance from the lesion. While free-water elevations continuously increased over time and peaked after 12 months, FAT decreases were most evident 1 month post-stroke, gradually returning to baseline values thereafter. Higher perilesional free-water and higher lesional FAT at baseline were correlated with greater reductions in lesion size (rho = -0.51, p = .03) in unadjusted analyses only, while there were no associations with clinical measures. In summary, we find a characteristic spatio-temporal pattern of extracellular and cellular alterations beyond subcortical stroke lesions, indicating a dynamic parenchymal response to ischemia characterized by vasogenic edema, cellular damage, and white matter atrophy.
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Affiliation(s)
- Felix L. Nägele
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Marvin Petersen
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Carola Mayer
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Marlene Bönstrup
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurologyUniversity of Leipzig Medical CenterLeipzigGermany
| | - Robert Schulz
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Christian Gerloff
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Götz Thomalla
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Bastian Cheng
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
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47
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Smolders L, De Baene W, Rutten GJ, van der Hofstad R, Florack L. Can structure predict function at individual level in the human connectome? Brain Struct Funct 2024; 229:1209-1223. [PMID: 38656375 PMCID: PMC11147846 DOI: 10.1007/s00429-024-02796-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/25/2024] [Indexed: 04/26/2024]
Abstract
Several studies predicting Functional Connectivity (FC) from Structural Connectivity (SC) at individual level have been published in recent years, each promising increased performance and utility. We investigated three of these studies, analyzing whether the results truly represent a meaningful individual-level mapping from SC to FC. Using data from the Human Connectome Project shared accross the three studies, we constructed a predictor by averaging FC of training data and analyzed its performance in the same way. In each case, we found that group average FC is an equivalent or better predictor of individual FC than the predictive models in terms of raw prediction performance. Furthermore, we showed that additional analyses performed by the authors of the three studies, in which they attempt to show that their predicted FC has value beyond raw prediction performance, could also be reproduced using the group average FC predictor. This makes it unclear whether any of the three methods represent a meaningful individual-level predictive model. We conclude that either the methods are not appropriate for the data, that the sample size is too small, or that the data does not contain sufficient information to learn a mapping from SC to FC. We advise future individual-level studies to explicitly report results in comparison to the performance of the group average, and carefully demonstrate that their predictions contain meaningful individual-level information. Finally, we believe that investigating alternatives for the construction of SC and FC may improve the chances of developing a meaningful individual-level mapping from SC to FC.
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Affiliation(s)
- Lars Smolders
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands.
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands.
| | - Wouter De Baene
- Tilburg University, Department of Cognitive Neuropsychology, Warandelaan 2, Tilburg, 5000 LE, Netherlands
| | - Geert-Jan Rutten
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands
| | - Remco van der Hofstad
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
| | - Luc Florack
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
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48
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Kerpel A, Davenport E, Proskovec AL, Xi Y, Berry JD, Yetkin Z, Maldjian J, Yu FF. Antidepressant-related microstructural changes in the external capsule. Brain Imaging Behav 2024:10.1007/s11682-024-00891-w. [PMID: 38814546 DOI: 10.1007/s11682-024-00891-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2024] [Indexed: 05/31/2024]
Abstract
Several magnetic resonance imaging (MRI) studies have reported that antidepressant medications are strongly linked to brain microstructural alterations. Notably, external capsule alterations have been reported to be a biological marker for therapeutic response. However, prior studies did not investigate whether a change in the neurite density or directional coherence of white matter (WM) fibers underlies the observed microstructural alterations. This MRI-based case-control study examined the relationship between patients' current use of antidepressant medications and advanced measurements of external capsule WM microstructure derived from multishell diffusion imaging using neurite orientation dispersion and density imaging (NODDI). The study compared a group of thirty-five participants who were taking antidepressant medications comprising selective serotonin reuptake inhibitors (SSRIs) (n = 25) and serotonin and norepinephrine reuptake inhibitors (SNRIs) with a control group of thirty-five individuals matched in terms of age, sex, race, and atherosclerotic cardiovascular risk factors. All participants were selected from the Dallas Heart Study phase 2, a multi-ethnic, population-based cohort study. A series of multiple linear regression analyses were conducted to predict microstructural characteristics of the bilateral external capsule using age, sex, and antidepressant medications as predictor variables. There was significantly reduced neurite density in the bilateral external capsules of patients taking SSRIs. Increased orientation dispersion in the external capsule was predominantly seen in patients taking SNRIs. Our findings suggest an association between specific external capsule microstructural changes and antidepressant medications, including reduced neurite density for SSRIs and increased orientation dispersion for SNRIs.
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Affiliation(s)
- Ariel Kerpel
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
| | - Elizabeth Davenport
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Amy L Proskovec
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Yin Xi
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jarett D Berry
- Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Zerrin Yetkin
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Joseph Maldjian
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Fang F Yu
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
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49
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Le Grand Q, Tsuchida A, Koch A, Imtiaz MA, Aziz NA, Vigneron C, Zago L, Lathrop M, Dubrac A, Couffinhal T, Crivello F, Matthews PM, Mishra A, Breteler MMB, Tzourio C, Debette S. Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease. Mol Psychiatry 2024:10.1038/s41380-024-02604-7. [PMID: 38811690 DOI: 10.1038/s41380-024-02604-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/31/2024]
Abstract
Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.
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Affiliation(s)
- Quentin Le Grand
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ami Tsuchida
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Alexandra Koch
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Mohammed-Aslam Imtiaz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Chloé Vigneron
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Victor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montreal, QC, H3A 0G1, Canada
| | - Alexandre Dubrac
- Centre de Recherche, CHU Sainte-Justine, Montréal, QC, Canada
- Département de Pathologie et Biologie Cellulaire, Université de Montréal, Montréal, QC, Canada
- Département d'Ophtalmologie, Université de Montréal, Montréal, QC, Canada
| | - Thierry Couffinhal
- University of Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600, Pessac, France
| | - Fabrice Crivello
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Paul M Matthews
- UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK
| | - Aniket Mishra
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Christophe Tzourio
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Bordeaux University Hospital, Department of Medical Informatics, F-33000, Bordeaux, France
| | - Stéphanie Debette
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France.
- Bordeaux University Hospital, Department of Neurology, Institute for Neurodegenerative Diseases, F-33000, Bordeaux, France.
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50
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Baranyi G, Buchanan CR, Conole ELS, Backhouse EV, Maniega SM, Valdés Hernández MDC, Bastin ME, Wardlaw J, Deary IJ, Cox SR, Pearce J. Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936. Mol Psychiatry 2024:10.1038/s41380-024-02591-9. [PMID: 38773266 DOI: 10.1038/s41380-024-02591-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 04/29/2024] [Accepted: 05/02/2024] [Indexed: 05/23/2024]
Abstract
Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.
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Affiliation(s)
- Gergő Baranyi
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK.
| | - Colin R Buchanan
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Eleanor L S Conole
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - María Del C Valdés Hernández
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Joanna Wardlaw
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Jamie Pearce
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
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