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Monchi O, Pinilla-Monsalve GD, Almgren H, Ghahremani M, Kibreab M, Maarouf N, Kathol I, Boré A, Rheault F, Descoteaux M, Ismail Z. White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease. Mov Disord 2024. [PMID: 38661496 DOI: 10.1002/mds.29804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/13/2024] [Accepted: 03/18/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood. OBJECTIVE The aim was to explore the changes in white matter microstructure linked to MBI and mild cognitive impairment (MCI) in early- to mid-stage PD using diffusion magnetic resonance imaging (dMRI). METHODS A total of 91 PD patients and 36 healthy participants were recruited and underwent anatomical MRI and dMRI, a comprehensive neuropsychological battery, and the completion of the Mild Behavioral Impairment-Checklist. Metrics of white matter integrity included tissue fractional anisotropy (FAt) and radial diffusivity (RDt), free water (FW), and fixel-based apparent fiber density (AFD). RESULTS The connection between the left amygdala and the putamen was disrupted when comparing PD patients with MBI (PD-MBI) to PD-non-MBI, as evidenced by increased RDt (η2 = 0.09, P = 0.004) and both decreased AFD (η2 = 0.05, P = 0.048) and FAt (η2 = 0.12, P = 0.014). Compared to controls, PD patients with both MBI and MCI demonstrated increased FW for the connection between the left orbitofrontal gyrus (OrG) and the hippocampus (η2 = 0.22, P = 0.008), augmented RDt between the right OrG and the amygdala (η2 = 0.14, P = 0.008), and increased RDt (η2 = 0.25, P = 0.028) with decreased AFD (η2 = 0.10, P = 0.046) between the right OrG and the caudate nucleus. CONCLUSION MBI is associated with abnormal microstructure of connections involving the orbitofrontal cortex, putamen, and amygdala. To our knowledge, this is the first assessment of the white matter microstructure in PD-MBI using dMRI. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Oury Monchi
- Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Montreal, Quebec, Canada
- Département de radiologie, radio-oncologie et médicine nucléaire, Université de Montréal, Montreal, Quebec, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Gabriel D Pinilla-Monsalve
- Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Montreal, Quebec, Canada
- Département de radiologie, radio-oncologie et médicine nucléaire, Université de Montréal, Montreal, Quebec, Canada
| | - Hannes Almgren
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Maryam Ghahremani
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Departments of Psychiatry and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Mekale Kibreab
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Nadia Maarouf
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Iris Kathol
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Arnaud Boré
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - François Rheault
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Maxime Descoteaux
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Departments of Psychiatry and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
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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 2024:10.1007/s00234-024-03362-7. [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] [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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Rosberg A, Merisaari H, Lewis JD, Hashempour N, Lukkarinen M, Rasmussen JM, Scheinin NM, Karlsson L, Karlsson H, Tuulari JJ. Associations between maternal pre-pregnancy BMI and infant striatal mean diffusivity. BMC Med 2024; 22:140. [PMID: 38528552 DOI: 10.1186/s12916-024-03340-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 03/05/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND It is well-established that parental obesity is a strong risk factor for offspring obesity. Further, a converging body of evidence now suggests that maternal weight profiles may affect the developing offspring's brain in a manner that confers future obesity risk. Here, we investigated how pre-pregnancy maternal weight status influences the reward-related striatal areas of the offspring's brain during in utero development. METHODS We used diffusion tensor imaging to quantify the microstructure of the striatal brain regions of interest in neonates (N = 116 [66 males, 50 females], mean gestational weeks at birth [39.88], SD = 1.14; at scan [43.56], SD = 1.05). Linear regression was used to test the associations between maternal pre-pregnancy body mass index (BMI) and infant striatal mean diffusivity. RESULTS High maternal pre-pregnancy BMI was associated with higher mean MD values in the infant's left caudate nucleus. Results remained unchanged after the adjustment for covariates. CONCLUSIONS In utero exposure to maternal adiposity might have a growth-impairing impact on the mean diffusivity of the infant's left caudate nucleus. Considering the involvement of the caudate nucleus in regulating eating behavior and food-related reward processing later in life, this finding calls for further investigations to define the prognostic relevance of early-life caudate nucleus development and weight trajectories of the offspring.
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Affiliation(s)
- Aylin Rosberg
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.
- Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Diagnostic Radiology, Turku University Hospital, Turku, Finland
| | - John D Lewis
- The Hospital for Sick Children (SickKids) Research Institute, Toronto, ON, Canada
| | - Niloofar Hashempour
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Minna Lukkarinen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | | | - Noora M Scheinin
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, University of Turku and Satakunta Wellbeing Services County, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
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Ruiz-Rizzo AL, Finke K, Archila-Meléndez ME. Diffusion Tensor Imaging in Alzheimer's Studies. Methods Mol Biol 2024; 2785:105-113. [PMID: 38427191 DOI: 10.1007/978-1-0716-3774-6_8] [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: 03/02/2024]
Abstract
In this chapter, we describe the use of quantitative metrics of white matter obtained from the diffusion tensor model based on diffusion-weighted imaging in Alzheimer's disease (AD). Our description synthesizes insights not only from patient populations with AD dementia but also from participants at risk for AD dementia (e.g., amnestic mild cognitive impairment, subjective cognitive decline, or familial AD mutation carriers). A reference to studies examining correlations with behavioral variables is also included. Our main message is to caution against the overinterpretation of diffusion metrics and to favor analyses that focus on regions of interest or major white matter tracts for biomarker studies in AD.
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Affiliation(s)
| | - Kathrin Finke
- Department of Neurology, Jena University Hospital, Jena, Germany
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Spalek K, Coynel D, de Quervain D, Milnik A. Sex-dependent differences in connectivity patterns are related to episodic memory recall. Hum Brain Mapp 2023; 44:5612-5623. [PMID: 37647201 PMCID: PMC10619411 DOI: 10.1002/hbm.26465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/12/2023] [Accepted: 08/08/2023] [Indexed: 09/01/2023] Open
Abstract
Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.
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Affiliation(s)
- Klara Spalek
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Division of Molecular NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Hoekzema Lab, Adult PsychiatryUniversity Medical Centre AmsterdamAmsterdamNetherlands
| | - David Coynel
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Research Cluster Molecular and Cognitive NeurosciencesUniversity of BaselBaselSwitzerland
| | - Dominique de Quervain
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Research Cluster Molecular and Cognitive NeurosciencesUniversity of BaselBaselSwitzerland
- Psychiatric University Clinics, University of BaselBaselSwitzerland
| | - Annette Milnik
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Division of Molecular NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Psychiatric University Clinics, University of BaselBaselSwitzerland
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Kim CW, Kim Y, Kim HH, Choi JY. The aspect of structural connectivity in relation to age-related gait performance. PSYCHORADIOLOGY 2023; 3:kkad028. [PMID: 38666123 PMCID: PMC10917373 DOI: 10.1093/psyrad/kkad028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/05/2023] [Accepted: 11/24/2023] [Indexed: 04/28/2024]
Affiliation(s)
- Cheol-Woon Kim
- Department of Physical Education, Korea University,, 02841, Seoul, Republic of Korea
| | - Yechan Kim
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
| | - Hyun-Ho Kim
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
| | - Joon Yul Choi
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
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Ghini V, Meoni G, Vignoli A, Di Cesare F, Tenori L, Turano P, Luchinat C. Fingerprinting and profiling in metabolomics of biosamples. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:105-135. [PMID: 38065666 DOI: 10.1016/j.pnmrs.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 12/18/2023]
Abstract
This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.
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Affiliation(s)
- Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy.
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy; Giotto Biotech S.r.l., Sesto Fiorentino, Italy.
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Minosse S, Picchi E, Conti A, di Giuliano F, di Ciò F, Sarmati L, Teti E, de Santis S, Andreoni M, Floris R, Guerrisi M, Garaci F, Toschi N. Multishell diffusion MRI reveals whole-brain white matter changes in HIV. Hum Brain Mapp 2023; 44:5113-5124. [PMID: 37647214 PMCID: PMC10502617 DOI: 10.1002/hbm.26448] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 07/15/2023] [Accepted: 07/26/2023] [Indexed: 09/01/2023] Open
Abstract
Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) have been previously used to explore white matter related to human immunodeficiency virus (HIV) infection. While DTI and DKI suffer from low specificity, the Combined Hindered and Restricted Model of Diffusion (CHARMED) provides additional microstructural specificity. We used these three models to evaluate microstructural differences between 35 HIV-positive patients without neurological impairment and 20 healthy controls who underwent diffusion-weighted imaging using three b-values. While significant group effects were found in all diffusion metrics, CHARMED and DKI analyses uncovered wider involvement (80% vs. 20%) of all white matter tracts in HIV infection compared with DTI. In restricted fraction (FR) analysis, we found significant differences in the left corticospinal tract, middle cerebellar peduncle, right inferior cerebellar peduncle, right corticospinal tract, splenium of the corpus callosum, left superior cerebellar peduncle, left superior cerebellar peduncle, pontine crossing tract, left posterior limb of the internal capsule, and left/right medial lemniscus. These are involved in language, motor, equilibrium, behavior, and proprioception, supporting the functional integration that is frequently impaired in HIV-positivity. Additionally, we employed a machine learning algorithm (XGBoost) to discriminate HIV-positive patients from healthy controls using DTI and CHARMED metrics on an ROIwise basis, and unique contributions to this discrimination were examined using Shapley Explanation values. The CHARMED and DKI estimates produced the best performance. Our results suggest that biophysical multishell imaging, combining additional sensitivity and built-in specificity, provides further information about the brain microstructural changes in multimodal areas involved in attentive, emotional and memory networks often impaired in HIV patients.
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Affiliation(s)
- Silvia Minosse
- Diagnostic Imaging UnitUniversity Hospital Rome Tor VergataRomeItaly
| | - Eliseo Picchi
- Diagnostic Imaging UnitUniversity Hospital Rome Tor VergataRomeItaly
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
| | - Allegra Conti
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
| | - Francesca di Giuliano
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
- Neuroradiology UnitUniversity Hospital of Rome Tor VergataRomeItaly
| | - Francesco di Ciò
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
| | - Loredana Sarmati
- Clinical Infectious Diseases UnitUniversity Hospital of Rome Tor VergataRomeItaly
- Department of Systems MedicineUniversity of Rome Tor VergataRomeItaly
| | - Elisabetta Teti
- Clinical Infectious Diseases UnitUniversity Hospital of Rome Tor VergataRomeItaly
| | - Silvia de Santis
- Instituto de NeurocienciasConsejo Superior de Investigaciones Científicas and Universidad Miguel HernándezSant Joan d'AlacantSpain
| | - Massimo Andreoni
- Clinical Infectious Diseases UnitUniversity Hospital of Rome Tor VergataRomeItaly
- Department of Systems MedicineUniversity of Rome Tor VergataRomeItaly
| | - Roberto Floris
- Diagnostic Imaging UnitUniversity Hospital Rome Tor VergataRomeItaly
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
| | - Maria Guerrisi
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
| | - Francesco Garaci
- Department of Biomedicine and PreventionUniversity of Rome Tor VergataRomeItaly
- Neuroradiology UnitUniversity Hospital of Rome Tor VergataRomeItaly
- IRCSS San Raffaele CassinoFrosinoneItaly
| | - Nicola Toschi
- Neuroradiology UnitUniversity Hospital of Rome Tor VergataRomeItaly
- Athinoula A. Martinos Center for Biomedical ImagingHarvard Medical SchoolBostonMassachusettsUSA
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Hain A, Jörgens D, Moreno R. Randomized iterative spherical-deconvolution informed tractogram filtering. Neuroimage 2023; 278:120248. [PMID: 37423271 DOI: 10.1016/j.neuroimage.2023.120248] [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: 02/12/2023] [Revised: 06/15/2023] [Accepted: 06/23/2023] [Indexed: 07/11/2023] Open
Abstract
Tractography has become an indispensable part of brain connectivity studies. However, it is currently facing problems with reliability. In particular, a substantial amount of nerve fiber reconstructions (streamlines) in tractograms produced by state-of-the-art tractography methods are anatomically implausible. To address this problem, tractogram filtering methods have been developed to remove faulty connections in a postprocessing step. This study takes a closer look at one such method, Spherical-deconvolution Informed Filtering of Tractograms (SIFT), which uses a global optimization approach to improve the agreement between the remaining streamlines after filtering and the underlying diffusion magnetic resonance imaging data. SIFT is not suitable for judging the compliance of individual streamlines with the acquired data since its results depend on the size and composition of the surrounding tractogram. To tackle this problem, we propose applying SIFT to randomly selected tractogram subsets in order to retrieve multiple assessments for each streamline. This approach makes it possible to identify streamlines with very consistent filtering results, which were used as pseudo-ground truths for training classifiers. The trained classifier is able to distinguish the obtained groups of complying and non-complying streamlines with the acquired data with an accuracy above 80%.
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Affiliation(s)
- Antonia Hain
- Saarland University, Faculty of Mathematics and Computer Science, Campus E1.7, Saarbruecken, 66041, Saarland, Germany.
| | - Daniel Jörgens
- Division of Brain, Imaging, and Behaviour, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada; KTH Royal Institute of Technology, Department of Biomedical Engineering and Health Systems, Hälsovägen 11C, Huddinge, 14157, Stockholm, Sweden.
| | - Rodrigo Moreno
- KTH Royal Institute of Technology, Department of Biomedical Engineering and Health Systems, Hälsovägen 11C, Huddinge, 14157, Stockholm, Sweden.
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Mahmoodi AL, Landers MJF, Rutten GJM, Brouwers HB. Characterization and Classification of Spatial White Matter Tract Alteration Patterns in Glioma Patients Using Magnetic Resonance Tractography: A Systematic Review and Meta-Analysis. Cancers (Basel) 2023; 15:3631. [PMID: 37509291 PMCID: PMC10377290 DOI: 10.3390/cancers15143631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/03/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
INTRODUCTION Magnetic resonance (MR) tractography can be used to study the spatial relations between gliomas and white matter (WM) tracts. Various spatial patterns of WM tract alterations have been described in the literature. We reviewed classification systems of these patterns, and investigated whether low-grade gliomas (LGGs) and high-grade gliomas (HGGs) demonstrate distinct spatial WM tract alteration patterns. METHODS We conducted a systematic review and meta-analysis to summarize the evidence regarding MR tractography studies that investigated spatial WM tract alteration patterns in glioma patients. RESULTS Eleven studies were included. Overall, four spatial WM tract alteration patterns were reported in the current literature: displacement, infiltration, disruption/destruction and edematous. There was a considerable heterogeneity in the operational definitions of these terms. In a subset of studies, sufficient homogeneity in the classification systems was found to analyze pooled results for the displacement and infiltration patterns. Our meta-analyses suggested that LGGs displaced WM tracts significantly more often than HGGs (n = 259 patients, RR: 1.79, 95% CI [1.14, 2.79], I2 = 51%). No significant differences between LGGs and HGGs were found for WM tract infiltration (n = 196 patients, RR: 1.19, 95% CI [0.95, 1.50], I2 = 4%). CONCLUSIONS The low number of included studies and their considerable methodological heterogeneity emphasize the need for a more uniform classification system to study spatial WM tract alteration patterns using MR tractography. This review provides a first step towards such a classification system, by showing that the current literature is inconclusive and that the ability of fractional anisotropy (FA) to define spatial WM tract alteration patterns should be critically evaluated. We found variations in spatial WM tract alteration patterns between LGGs and HGGs, when specifically examining displacement and infiltration in a subset of the included studies.
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Affiliation(s)
- Arash L Mahmoodi
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands
| | - Maud J F Landers
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands
| | - Geert-Jan M Rutten
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands
| | - H Bart Brouwers
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands
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11
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Gast H, Horowitz A, Krupnik R, Barazany D, Lifshits S, Ben-Amitay S, Assaf Y. A Method for In-Vivo Mapping of Axonal Diameter Distributions in the Human Brain Using Diffusion-Based Axonal Spectrum Imaging (AxSI). Neuroinformatics 2023; 21:469-482. [PMID: 37036548 PMCID: PMC10406702 DOI: 10.1007/s12021-023-09630-w] [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: 03/24/2023] [Indexed: 04/11/2023]
Abstract
In this paper we demonstrate a generalized and simplified pipeline called axonal spectrum imaging (AxSI) for in-vivo estimation of axonal characteristics in the human brain. Whole-brain estimation of the axon diameter, in-vivo and non-invasively, across all fiber systems will allow exploring uncharted aspects of brain structure and function relations with emphasis on connectivity and connectome analysis. While axon diameter mapping is important in and of itself, its correlation with conduction velocity will allow, for the first time, the explorations of information transfer mechanisms within the brain. We demonstrate various well-known aspects of axonal morphometry (e.g., the corpus callosum axon diameter variation) as well as other aspects that are less explored (e.g., axon diameter-based separation of the superior longitudinal fasciculus into segments). Moreover, we have created an MNI based mean axon diameter map over the entire brain for a large cohort of subjects providing the reference basis for future studies exploring relation between axon properties, its connectome representation, and other functional and behavioral aspects of the brain.
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Affiliation(s)
- Hila Gast
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
| | - Assaf Horowitz
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Ronnie Krupnik
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Daniel Barazany
- The Strauss center for neuroimaging, Tel Aviv University, Tel Aviv, Israel
| | - Shlomi Lifshits
- Department of Statistics and Operations Research, Faculty of Exact Sciences, Tel Aviv University, Tel-Aviv, Israel
| | - Shani Ben-Amitay
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- The Strauss center for neuroimaging, Tel Aviv University, Tel Aviv, Israel
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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12
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Shamir I, Assaf Y. Expanding connectomics to the laminar level: A perspective. Netw Neurosci 2023; 7:377-388. [PMID: 37397881 PMCID: PMC10312257 DOI: 10.1162/netn_a_00304] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 12/15/2022] [Indexed: 11/10/2023] Open
Abstract
Despite great progress in uncovering the complex connectivity patterns of the human brain over the last two decades, the field of connectomics still experiences a bias in its viewpoint of the cerebral cortex. Due to a lack of information regarding exact end points of fiber tracts inside cortical gray matter, the cortex is commonly reduced to a single homogenous unit. Concurrently, substantial developments have been made over the past decade in the use of relaxometry and particularly inversion recovery imaging for exploring the laminar microstructure of cortical gray matter. In recent years, these developments have culminated in an automated framework for cortical laminar composition analysis and visualization, followed by studies of cortical dyslamination in epilepsy patients and age-related differences in laminar composition in healthy subjects. This perspective summarizes the developments and remaining challenges of multi-T1 weighted imaging of cortical laminar substructure, the current limitations in structural connectomics, and the recent progress in integrating these fields into a new model-based subfield termed 'laminar connectomics'. In the coming years, we predict an increased use of similar generalizable, data-driven models in connectomics with the purpose of integrating multimodal MRI datasets and providing a more nuanced and detailed characterization of brain connectivity.
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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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13
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Antonenko D, Fromm AE, Thams F, Grittner U, Meinzer M, Flöel A. Microstructural and functional plasticity following repeated brain stimulation during cognitive training in older adults. Nat Commun 2023; 14:3184. [PMID: 37268628 DOI: 10.1038/s41467-023-38910-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/18/2023] [Indexed: 06/04/2023] Open
Abstract
The combination of repeated behavioral training with transcranial direct current stimulation (tDCS) holds promise to exert beneficial effects on brain function beyond the trained task. However, little is known about the underlying mechanisms. We performed a monocenter, single-blind randomized, placebo-controlled trial comparing cognitive training to concurrent anodal tDCS (target intervention) with cognitive training to concurrent sham tDCS (control intervention), registered at ClinicalTrial.gov (Identifier NCT03838211). The primary outcome (performance in trained task) and secondary behavioral outcomes (performance on transfer tasks) were reported elsewhere. Here, underlying mechanisms were addressed by pre-specified analyses of multimodal magnetic resonance imaging before and after a three-week executive function training with prefrontal anodal tDCS in 48 older adults. Results demonstrate that training combined with active tDCS modulated prefrontal white matter microstructure which predicted individual transfer task performance gain. Training-plus-tDCS also resulted in microstructural grey matter alterations at the stimulation site, and increased prefrontal functional connectivity. We provide insight into the mechanisms underlying neuromodulatory interventions, suggesting tDCS-induced changes in fiber organization and myelin formation, glia-related and synaptic processes in the target region, and synchronization within targeted functional networks. These findings advance the mechanistic understanding of neural tDCS effects, thereby contributing to more targeted neural network modulation in future experimental and translation tDCS applications.
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Affiliation(s)
- Daria Antonenko
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany.
| | | | - Friederike Thams
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Ulrike Grittner
- Berlin Institute of Health (BIH), Berlin, Germany
- Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Institute of Biometry and Clinical Epidemiology, Berlin, Germany
| | - Marcus Meinzer
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, Greifswald, Germany
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14
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Takemura H, Liu W, Kuribayashi H, Miyata T, Kida I. Evaluation of simultaneous multi-slice readout-segmented diffusion-weighted MRI acquisition in human optic nerve measurements. Magn Reson Imaging 2023; 102:103-114. [PMID: 37149064 DOI: 10.1016/j.mri.2023.05.001] [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: 03/31/2022] [Revised: 05/02/2023] [Accepted: 05/02/2023] [Indexed: 05/08/2023]
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) is the only available method to measure the tissue properties of white matter tracts in living human brains and has opened avenues for neuroscientific and clinical studies on human white matter. However, dMRI using conventional simultaneous multi-slice (SMS) single-shot echo planar imaging (ssEPI) still presents challenges in the analyses of some specific white matter tracts, such as the optic nerve, which are heavily affected by susceptibility-induced artifacts. In this study, we evaluated dMRI data acquired by using SMS readout-segmented EPI (rsEPI), which aims to reduce susceptibility-induced artifacts by dividing the acquisition space into multiple segments along the readout direction to reduce echo spacing. To this end, we acquired dMRI data from 11 healthy volunteers by using SMS ssEPI and SMS rsEPI, and then compared the dMRI data of the human optic nerve between the SMS ssEPI and SMS rsEPI datasets by visual inspection of the datasets and statistical comparisons of fractional anisotropy (FA) values. In comparison with the SMS ssEPI data, the SMS rsEPI data showed smaller susceptibility-induced distortion and exhibited a significantly higher FA along the optic nerve. In summary, this study demonstrates that despite its prolonged acquisition time, SMS rsEPI is a promising approach for measuring the tissue properties of the optic nerve in living humans and will be useful for future neuroscientific and clinical investigations of this pathway.
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Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan; Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan; Graduate Institute for Advanced Studies, SOKENDAI, Hayama, Japan.
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | | | - Toshikazu Miyata
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan; Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
| | - Ikuhiro Kida
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
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15
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Morita T, Takemura H, Naito E. Functional and Structural Properties of Interhemispheric Interaction between Bilateral Precentral Hand Motor Regions in a Top Wheelchair Racing Paralympian. Brain Sci 2023; 13:brainsci13050715. [PMID: 37239187 DOI: 10.3390/brainsci13050715] [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: 03/15/2023] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 05/28/2023] Open
Abstract
Long-term motor training can cause functional and structural changes in the human brain. Assessing how the training of specific movements affects specific parts of the neural circuitry is essential to understand better the underlying mechanisms of motor training-induced plasticity in the human brain. We report a single-case neuroimaging study that investigated functional and structural properties in a professional athlete of wheelchair racing. As wheelchair racing requires bilateral synchronization of upper limb movements, we hypothesized that functional and structural properties of interhemispheric interactions in the central motor system might differ between the professional athlete and controls. Functional and diffusion magnetic resonance imaging (fMRI and dMRI) data were obtained from a top Paralympian (P1) in wheelchair racing. With 23 years of wheelchair racing training starting at age eight, she holds an exceptional competitive record. Furthermore, fMRI and dMRI data were collected from three other paraplegic participants (P2-P4) with long-term wheelchair sports training other than wheelchair racing and 37 able-bodied control volunteers. Based on the fMRI data analyses, P1 showed activation in the bilateral precentral hand sections and greater functional connectivity between these sections during a right-hand unimanual task. In contrast, other paraplegic participants and controls showed activation in the contralateral hemisphere and deactivation in the ipsilateral hemisphere. Moreover, dMRI data analysis revealed that P1 exhibited significantly lower mean diffusivity along the transcallosal pathway connecting the bilateral precentral motor regions than control participants, which was not observed in the other paraplegic participants. These results suggest that long-term training with bilaterally synchronized upper-limb movements may promote bilateral recruitment of the precentral hand sections. Such recruitment may affect the structural circuitry involved in the interhemispheric interaction between the bilateral precentral regions. This study provides valuable evidence of the extreme adaptability of the human brain.
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Affiliation(s)
- Tomoyo Morita
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita 565-0871, Osaka, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki 444-8585, Aichi, Japan
- The Graduate Institute for Advanced Studies, SOKENDAI, Shonan Village, Hayama 240-0193, Kanagawa, Japan
| | - Eiichi Naito
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita 565-0871, Osaka, Japan
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16
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Orset T, Royo J, Santin MD, Pouget P, Thiebaut de Schotten M. A new open, high-resolution, multishell, diffusion-weighted imaging dataset of the living squirrel monkey. Sci Data 2023; 10:224. [PMID: 37081025 PMCID: PMC10119165 DOI: 10.1038/s41597-023-02126-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/31/2023] [Indexed: 04/22/2023] Open
Abstract
Although very well adapted to brain study, Magnetic Resonance Imaging (MRI) remains limited by the facilities and capabilities required to acquire data, especially for non-human primates. Addressing the data gaps resulting from these limitations requires making data more accessible and open. In contempt of the regular use of Saimiri sciureus in neuroscience research, in vivo diffusion has yet to be openly available for this species. Here we built and made openly available a unique new resource consisting of a high-resolution, multishell diffusion-weighted dataset in the anesthetized Saimiri sciureus. The data were acquired on 11 individuals with an 11.7 T MRI scanner (isotropic resolution of 400 µm3). This paper presents an overview of our dataset and illustrates some of its possible use through example analyses. To assess the quality of our data, we analyzed long-range connections (whole-brain tractography), microstructure (Neurite Orientation Dispersion and Density Imaging), and axon diameter in the corpus callosum (ActiveAx). Constituting an essential new resource for primate evolution studies, all data are openly available.
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Affiliation(s)
- Thomas Orset
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France.
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France.
| | - Julie Royo
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France
| | | | - Pierre Pouget
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
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17
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Dauvermann MR, Costello L, Tronchin G, Holleran L, Mothersill D, Rokita KI, Kane R, Hallahan B, Corvin A, Morris D, McKernan DP, Kelly J, McDonald C, Donohoe G, Cannon DM. Childhood trauma is associated with altered white matter microstructural organization in schizophrenia. Psychiatry Res Neuroimaging 2023; 330:111616. [PMID: 36827958 DOI: 10.1016/j.pscychresns.2023.111616] [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: 12/09/2022] [Revised: 02/02/2023] [Accepted: 02/15/2023] [Indexed: 02/24/2023]
Abstract
It has been reported that childhood trauma (CT) is associated with reductions in fractional anisotropy (FA) in individuals with schizophrenia (SZ). Here, we hypothesized that SZ with high levels of CT will show the greatest reductions in FA in frontolimbic and frontoparietal regions compared to healthy controls (HC) with high trauma levels and participants with no/low levels of CT. Thirty-seven SZ and 129 HC with CT experience were dichotomized into groups of 'none/low' or 'high' levels. Participants underwent diffusion-weighted MRI, and Tract-based spatial statistics were employed to assess the main effect of diagnosis, main effect of CT severity irrespective of diagnosis, and interaction between diagnosis and CT severity. SZ showed FA reductions in the corpus callosum and corona radiata compared to HC. Irrespective of a diagnosis, high CT levels (n = 48) were related to FA reductions in frontolimbic and frontoparietal regions compared to those with none/low levels of CT (n = 118). However, no significant interaction between diagnosis and high levels of CT was found (n = 13). Across all participants, we observed effects of CT on late developing frontolimbic and frontoparietal regions, suggesting that the effects of CT severity on white matter organization may be independent of schizophrenia.
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Affiliation(s)
- Maria R Dauvermann
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland; Institute for Mental Health, School of Psychology, University of Birmingham, B15 2TT, United Kingdom.
| | - Laura Costello
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Giulia Tronchin
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Laurena Holleran
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - David Mothersill
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland; Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland; Department of Psychiatry, Trinity College Dublin, St. James's Hospital, Dublin, Ireland
| | - Karolina I Rokita
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Ruán Kane
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Brian Hallahan
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Aiden Corvin
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
| | - Derek Morris
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Declan P McKernan
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - John Kelly
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Colm McDonald
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Gary Donohoe
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
| | - Dara M Cannon
- Center for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, University of Galway, Ireland, Galway, H91TK33, Ireland
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18
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Carhart-Harris RL, Chandaria S, Erritzoe DE, Gazzaley A, Girn M, Kettner H, Mediano PAM, Nutt DJ, Rosas FE, Roseman L, Timmermann C, Weiss B, Zeifman RJ, Friston KJ. Canalization and plasticity in psychopathology. Neuropharmacology 2023; 226:109398. [PMID: 36584883 DOI: 10.1016/j.neuropharm.2022.109398] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/01/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022]
Abstract
This theoretical article revives a classical bridging construct, canalization, to describe a new model of a general factor of psychopathology. To achieve this, we have distinguished between two types of plasticity, an early one that we call 'TEMP' for 'Temperature or Entropy Mediated Plasticity', and another, we call 'canalization', which is close to Hebbian plasticity. These two forms of plasticity can be most easily distinguished by their relationship to 'precision' or inverse variance; TEMP relates to increased model variance or decreased precision, whereas the opposite is true for canalization. TEMP also subsumes increased learning rate, (Ising) temperature and entropy. Dictionary definitions of 'plasticity' describe it as the property of being easily shaped or molded; TEMP is the better match for this. Importantly, we propose that 'pathological' phenotypes develop via mechanisms of canalization or increased model precision, as a defensive response to adversity and associated distress or dysphoria. Our model states that canalization entrenches in psychopathology, narrowing the phenotypic state-space as the agent develops expertise in their pathology. We suggest that TEMP - combined with gently guiding psychological support - can counter canalization. We address questions of whether and when canalization is adaptive versus maladaptive, furnish our model with references to basic and human neuroscience, and offer concrete experiments and measures to test its main hypotheses and implications. This article is part of the Special Issue on "National Institutes of Health Psilocybin Research Speaker Series".
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Affiliation(s)
- R L Carhart-Harris
- Psychedelics Division - Neuroscape, Department of Neurology, University of California, San Francisco, USA; Centre for Psychedelic Research, Imperial College London, UK.
| | - S Chandaria
- Centre for Psychedelic Research, Imperial College London, UK; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, UK; Institute of Philosophy, School of Advanced Study, University of London, UK
| | - D E Erritzoe
- Centre for Psychedelic Research, Imperial College London, UK; CNWL-Imperial Psychopharmacology and Psychedelic Research Clinic (CIPPRS), UK
| | - A Gazzaley
- Psychedelics Division - Neuroscape, Department of Neurology, University of California, San Francisco, USA
| | - M Girn
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - H Kettner
- Psychedelics Division - Neuroscape, Department of Neurology, University of California, San Francisco, USA; Centre for Psychedelic Research, Imperial College London, UK
| | - P A M Mediano
- Department of Computing, Imperial College London, London, UK; Department of Psychology, University of Cambridge, UK
| | - D J Nutt
- Centre for Psychedelic Research, Imperial College London, UK
| | - F E Rosas
- Centre for Psychedelic Research, Imperial College London, UK; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, UK; Department of Informatics, University of Sussex, UK; Centre for Complexity Science, Imperial College London, UK
| | - L Roseman
- Centre for Psychedelic Research, Imperial College London, UK; CNWL-Imperial Psychopharmacology and Psychedelic Research Clinic (CIPPRS), UK
| | - C Timmermann
- Centre for Psychedelic Research, Imperial College London, UK; CNWL-Imperial Psychopharmacology and Psychedelic Research Clinic (CIPPRS), UK
| | - B Weiss
- Centre for Psychedelic Research, Imperial College London, UK; CNWL-Imperial Psychopharmacology and Psychedelic Research Clinic (CIPPRS), UK
| | - R J Zeifman
- Centre for Psychedelic Research, Imperial College London, UK; NYU Langone Center for Psychedelic Medicine, NYU Grossman School of Medicine, USA
| | - K J Friston
- Wellcome Centre for Human Neuroimaging, University College London, UK
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19
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Li G, Ma X, Li S, Ye X, Börnert P, Zhou XJ, Guo H. Comparison of uniform-density, variable-density, and dual-density spiral samplings for multi-shot DWI. Magn Reson Med 2023; 90:133-149. [PMID: 36883748 DOI: 10.1002/mrm.29633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 02/17/2023] [Accepted: 02/21/2023] [Indexed: 03/09/2023]
Abstract
PURPOSE To compare the performances of uniform-density spiral (UDS), variable-density spiral (VDS), and dual-density spiral (DDS) samplings in multi-shot diffusion imaging, and determine a sampling strategy that balances reliability of shot navigator and overall DWI image quality. THEORY AND METHODS UDS, VDS, and DDS trajectories were implemented to achieve four-shot diffusion-weighted spiral imaging. First, the static B0 off-resonance effects in UDS, VDS, and DDS acquisitions were analyzed based on a signal model. Then, in vivo experiments were performed to verify the theoretical analyses, and fractional anisotropy (FA) fitting residuals were used to quantitatively assess the quality of spiral diffusion data for tensor estimation. Finally, the SNR performances and g-factor behavior of the three spiral samplings were evaluated using a Monte Carlo-based pseudo multiple replica method. RESULTS Among the three spiral trajectories with the same readout duration, UDS sampling exhibited the least off-resonance artifacts. This was most evident when the static B0 off-resonance effect was severe. The UDS diffusion images had higher anatomical fidelity and lower FA fitting residuals than the other two counterparts. Furthermore, the four-shot UDS acquisition achieved the best SNR performance in diffusion imaging with 12.11% and 40.85% improvements over the VDS and DDS acquisitions with the same readout duration, respectively. CONCLUSION UDS sampling is an efficient spiral acquisition scheme for high-resolution diffusion imaging with reliable navigator information. It provides superior off-resonance performance and SNR efficiency over the VDS and DDS samplings for the tested scenarios.
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Affiliation(s)
- Guangqi Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Xiaodong Ma
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Sisi Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Xinyu Ye
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Peter Börnert
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands.,Philips Research, Hamburg, Germany
| | - Xiaohong Joe Zhou
- Center for MR Research and Departments of Radiology, Neurosurgery, and Biomedical Engineering, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
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20
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Lv J, Zeng R, Ho MP, D'Souza A, Calamante F. Building a tissue-unbiased brain template of fiber orientation distribution and tractography with multimodal registration. Magn Reson Med 2023; 89:1207-1220. [PMID: 36299169 PMCID: PMC10952616 DOI: 10.1002/mrm.29496] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/07/2022] [Accepted: 09/30/2022] [Indexed: 02/02/2023]
Abstract
PURPOSE Brain templates provide an essential standard space for statistical analysis of brain structure and function. Despite recent advances, diffusion MRI still lacks a template of fiber orientation distribution (FOD) and tractography that is unbiased for both white and gray matter. Therefore, we aim to build up a set of such templates for better white-matter analysis and joint structural and functional analysis. METHODS We have developed a multimodal registration method to leverage the complementary information captured by T1 -weighted, T2 -weighted, and diffusion MRI, so that a coherent transformation is generated to register FODs into a common space and average them into a template. Consequently, the anatomically constrained fiber-tracking method was applied to the FOD template to generate a tractography template. Fiber-centered functional connectivity analysis was then performed as an example of the benefits of such an unbiased template. RESULTS Our FOD template preserves fine structural details in white matter and also, importantly, clear folding patterns in the cortex and good contrast in the subcortex. Quantitatively, our templates show better individual-template agreement at the whole-brain scale and segmentation scale. The tractography template aligns well with the gray matter, which led to fiber-centered functional connectivity showing high cross-group consistency. CONCLUSION We have proposed a novel methodology for building a tissue-unbiased FOD and anatomically constrained tractography template based on multimodal registration. Our templates provide a standard space and statistical platform for not only white-matter analysis but also joint structural and functional analysis, therefore filling an important gap in multimodal neuroimage analysis.
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Affiliation(s)
- Jinglei Lv
- School of Biomedical EngineeringThe University of Sydney
SydneyNew South WalesAustralia
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
| | - Rui Zeng
- School of Biomedical EngineeringThe University of Sydney
SydneyNew South WalesAustralia
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
| | - Mai Phuong Ho
- School of Biomedical EngineeringThe University of Sydney
SydneyNew South WalesAustralia
| | - Arkiev D'Souza
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
- Translational Research Collective, Faculty of Medicine and HealthThe University of SydneySydneyNew South WalesAustralia
| | - Fernando Calamante
- School of Biomedical EngineeringThe University of Sydney
SydneyNew South WalesAustralia
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
- Sydney ImagingThe University of SydneySydneyNew South WalesAustralia
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21
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Sánchez SM, Schmidt H, Gallardo G, Anwander A, Brauer J, Friederici AD, Knösche TR. White matter brain structure predicts language performance and learning success. Hum Brain Mapp 2023; 44:1445-1455. [PMID: 36399515 PMCID: PMC9921223 DOI: 10.1002/hbm.26132] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 09/01/2022] [Accepted: 10/11/2022] [Indexed: 11/19/2022] Open
Abstract
Individual differences in the ability to process language have long been discussed. Much of the neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multiday training. We identified specific network motifs by singular value decomposition that indeed related white matter structural connectivity to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance, suggesting an anatomical predisposition for the individual ability to process syntactically complex sentences. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.
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Affiliation(s)
- Stella M Sánchez
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.,Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Helmut Schmidt
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
| | - Guillermo Gallardo
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alfred Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jens Brauer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Friedrich Schiller University, Office of the Vice-President for Young Researchers, Jena, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thomas R Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Institute of Biomedical Engineering and Informatics, TU Ilmenau, Ilmenau, Germany
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22
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Lissaman R, Lancaster TM, Parker GD, Graham KS, Lawrence AD, Hodgetts CJ. Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study. NEUROIMAGE. REPORTS 2022; 2:None. [PMID: 36507069 PMCID: PMC9726682 DOI: 10.1016/j.ynirp.2022.100126] [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: 04/07/2022] [Revised: 08/05/2022] [Accepted: 08/18/2022] [Indexed: 12/15/2022]
Abstract
The parahippocampal cingulum bundle (PHCB) interconnects regions known to be vulnerable to early Alzheimer's disease (AD) pathology, including posteromedial cortex and medial temporal lobe. While AD-related pathology has been robustly associated with alterations in PHCB microstructure, specifically lower fractional anisotropy (FA) and higher mean diffusivity (MD), emerging evidence indicates that the reverse pattern is evident in younger adults at increased risk of AD. In one such study, Hodgetts et al. (2019) reported that healthy young adult carriers of the apolipoprotein-E (APOE) ε4 allele - the strongest common genetic risk factor for AD - showed higher FA and lower MD in the PHCB but not the inferior longitudinal fasciculus (ILF). These results are consistent with proposals claiming that heightened neural activity and intrinsic connectivity play a significant role in increasing posteromedial cortex vulnerability to amyloid-β and tau spread beyond the medial temporal lobe. Given the implications for understanding AD risk, here we sought to replicate Hodgetts et al.'s finding in a larger sample (N = 128; 40 APOE ε4 carriers, 88 APOE ε4 non-carriers) of young adults (age range = 19-33). Extending this work, we also conducted an exploratory analysis using a more advanced measure of white matter microstructure: hindrance modulated orientational anisotropy (HMOA). Contrary to the original study, we did not observe higher FA or lower MD in the PHCB of APOE ε4 carriers relative to non-carriers. Bayes factors (BFs) further revealed moderate-to-strong evidence in support of these null findings. In addition, we observed no APOE ε4-related differences in PHCB HMOA. Our findings indicate that young adult APOE ε4 carriers and non-carriers do not differ in PHCB microstructure, casting some doubt on the notion that early-life variation in PHCB tract microstructure might enhance vulnerability to amyloid-β accumulation and/or tau spread.
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Affiliation(s)
- Rikki Lissaman
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Douglas Research Centre, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Thomas M. Lancaster
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- School of Psychology, University of Bath, Bath, England, United Kingdom
| | - Greg D. Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
| | - Kim S. Graham
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Andrew D. Lawrence
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
| | - Carl J. Hodgetts
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Department of Psychology, Royal Holloway, University of London, Egham, England, United Kingdom
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23
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Thiebaut de Schotten M, Forkel SJ. The emergent properties of the connected brain. Science 2022; 378:505-510. [DOI: 10.1126/science.abq2591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
There is more to brain connections than the mere transfer of signals between brain regions. Behavior and cognition emerge through cortical area interaction. This requires integration between local and distant areas orchestrated by densely connected networks. Brain connections determine the brain’s functional organization. The imaging of connections in the living brain has provided an opportunity to identify the driving factors behind the neurobiology of cognition. Connectivity differences between species and among humans have furthered the understanding of brain evolution and of diverging cognitive profiles. Brain pathologies amplify this variability through disconnections and, consequently, the disintegration of cognitive functions. The prediction of long-term symptoms is now preferentially based on brain disconnections. This paradigm shift will reshape our brain maps and challenge current brain models.
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Affiliation(s)
- Michel Thiebaut de Schotten
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
| | - Stephanie J. Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Donders Centre for Brain Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
- Department of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
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24
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Ruiz-Rizzo AL, Viviano RP, Daugherty AM, Finke K, Müller HJ, Damoiseaux JS. Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor: Cingulo-opercular network in SCD. Neuroimage 2022; 263:119662. [PMID: 36198354 DOI: 10.1016/j.neuroimage.2022.119662] [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: 07/18/2022] [Revised: 09/19/2022] [Accepted: 10/01/2022] [Indexed: 11/18/2022] Open
Abstract
Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 ± 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.
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Affiliation(s)
- Adriana L Ruiz-Rizzo
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany; Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena 07747, Germany.
| | - Raymond P Viviano
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Ana M Daugherty
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Kathrin Finke
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany; Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena 07747, Germany
| | - Hermann J Müller
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany
| | - Jessica S Damoiseaux
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
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25
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Rocha RP, Koçillari L, Suweis S, De Filippo De Grazia M, de Schotten MT, Zorzi M, Corbetta M. Recovery of neural dynamics criticality in personalized whole-brain models of stroke. Nat Commun 2022; 13:3683. [PMID: 35760787 PMCID: PMC9237050 DOI: 10.1038/s41467-022-30892-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/16/2022] [Indexed: 01/13/2023] Open
Abstract
The critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single participants using directly measured individual structural connectomes and whole-brain models. Lesions engender a sub-critical state that recovers over time in parallel with behavior. The improvement of criticality is associated with the re-modeling of specific white-matter connections. We show that personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single participants. The authors investigate the influence of brain injury (strokes) on the criticality of neural dynamics using directly measured connectomes and whole-brain models. They show that lesions engender a sub-critical state that recovers over time in parallel with behavior.
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Affiliation(s)
- Rodrigo P Rocha
- Departamento de Física, Centro de Ciências Físicas e Matemáticas, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, SC, Brazil. .,Department of Physics, School of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil. .,Padova Neuroscience Center, Università di Padova, Padova, Italy.
| | - Loren Koçillari
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Laboratory of Neural Computation, Istituto Italiano di Tecnologia, 38068, Rovereto, Italy.,Dipartimento di Fisica e Astronomia, Università di Padova and INFN, via Marzolo 8, I-35131, Padova, Italy
| | - Samir Suweis
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Dipartimento di Fisica e Astronomia, Università di Padova and INFN, via Marzolo 8, I-35131, Padova, Italy
| | | | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, BCBlab, Sorbonne Universities, Paris, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Marco Zorzi
- IRCCS San Camillo Hospital, Venice, Italy.,Dipartimento di Psicologia Generale, Università di Padova, Padova, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Dipartimento di Neuroscienze, Università di Padova, Padova, Italy.,Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padova, Italy
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26
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Shamir I, Tomer O, Krupnik R, Assaf Y. Modelling the laminar connectome of the human brain. Brain Struct Funct 2022; 227:2153-2165. [DOI: 10.1007/s00429-022-02513-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/22/2022] [Indexed: 12/20/2022]
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27
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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28
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Rosen BQ, Halgren E. An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected. PLoS Biol 2022; 20:e3001575. [PMID: 35286306 PMCID: PMC8947121 DOI: 10.1371/journal.pbio.3001575] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 03/24/2022] [Accepted: 02/17/2022] [Indexed: 12/17/2022] Open
Abstract
The tracts between cortical areas are conceived as playing a central role in cortical information processing, but their actual numbers have never been determined in humans. Here, we estimate the absolute number of axons linking cortical areas from a whole-cortex diffusion MRI (dMRI) connectome, calibrated using the histologically measured callosal fiber density. Median connectivity is estimated as approximately 6,200 axons between cortical areas within hemisphere and approximately 1,300 axons interhemispherically, with axons connecting functionally related areas surprisingly sparse. For example, we estimate that <5% of the axons in the trunk of the arcuate and superior longitudinal fasciculi connect Wernicke's and Broca's areas. These results suggest that detailed information is transmitted between cortical areas either via linkage of the dense local connections or via rare, extraordinarily privileged long-range connections.
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Affiliation(s)
- Burke Q Rosen
- Neurosciences Graduate Program, University of California San Diego, La Jolla, California, United States of America
| | - Eric Halgren
- Neurosciences Graduate Program, University of California San Diego, La Jolla, California, United States of America
- Departments of Neurosciences & Radiology, University of California San Diego, La Jolla, California, United States of America
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29
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Rui L, Jing L, Zhenchang W. Diffusion Tensor Imaging Technology to Quantitatively Assess Abnormal Changes in Patients With Thyroid-Associated Ophthalmopathy. Front Hum Neurosci 2022; 15:805945. [PMID: 35185495 PMCID: PMC8855114 DOI: 10.3389/fnhum.2021.805945] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 12/28/2021] [Indexed: 11/13/2022] Open
Abstract
Objective We aim to investigate the feasibility of using diffusion tensor imaging (DTI) to evaluate changes in extraocular muscles (EOMs) and lacrimal gland (LG) in patients with thyroid-associated ophthalmopathy (TAO) and to evaluate disease severity. Materials and Methods A total of 74 participants, including 17 healthy controls (HCs), 22 patients with mild TAO, and 35 patients with moderate-severe TAO, underwent 3-Tesla DTI to measure fractional anisotropy (FA) and mean diffusivity (MD) of the EOMs and LG. Ophthalmological examinations, including visual acuity, exophthalmos, intraocular pressure, and fundoscopy, were performed. FA and MD values were compared among patients with different disease severity. Multiple linear regression was adopted to predict the impact of clinical variables on DTI parameters of orbital soft tissue. Results TAO patients’ EOMs and LG showed significantly lower FA values and higher MD compared to HCs’ (P < 0.05). Moderate-severe TAO patients’ EOMs and LG had dramatically lower FA and higher MD compared with HCs (P < 0.05). In addition, only the DTI parameters of the medial rectus were considerably different between mild and moderate-severe TAO patients (P = 0.017, P = 0.021). Multiple linear regression showed that disease severity had a significant impact on the DTI parameters of orbital soft tissue. Conclusion DTI is a useful tool for detecting microstructural changes in TAO patients’ orbital soft tissue. DTI findings, especially medial rectus DTI parameters, can help to indicate the disease severity in TAO patients.
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30
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Ogawa S, Takemura H, Horiguchi H, Miyazaki A, Matsumoto K, Masuda Y, Yoshikawa K, Nakano T. Multi-Contrast Magnetic Resonance Imaging of Visual White Matter Pathways in Patients With Glaucoma. Invest Ophthalmol Vis Sci 2022; 63:29. [PMID: 35201263 PMCID: PMC8883150 DOI: 10.1167/iovs.63.2.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose Glaucoma is a disorder that involves visual field loss caused by retinal ganglion cell damage. Previous diffusion magnetic resonance imaging (dMRI) studies have demonstrated that retinal ganglion cell damage affects tissues in the optic tract (OT) and optic radiation (OR). However, because previous studies have used a simple diffusion tensor model to analyze dMRI data, the microstructural interpretation of white matter tissue changes remains uncertain. In this study, we used a multi-contrast MRI approach to further clarify the type of microstructural damage that occurs in patients with glaucoma. Methods We collected dMRI data from 17 patients with glaucoma and 30 controls using 3-tesla (3T) MRI. Using the dMRI data, we estimated three types of tissue property metrics: intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (IsoV). Quantitative T1 (qT1) data, which may be relatively specific to myelin, were collected from all subjects. Results In the OT, all four metrics showed significant differences between the glaucoma and control groups. In the OR, only the ICVF showed significant between-group differences. ICVF was significantly correlated with qT1 in the OR of the glaucoma group, although qT1 did not show any abnormality at the group level. Conclusions Our results suggest that, at the group level, tissue changes in OR caused by glaucoma might be explained by axonal damage, which is reflected in the intracellular diffusion signals, rather than myelin damage. The significant correlation between ICVF and qT1 suggests that myelin damage might also occur in a smaller number of severe cases.
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Affiliation(s)
- Shumpei Ogawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan.,Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.,Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan.,Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Hiroshi Horiguchi
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | | | - Kenji Matsumoto
- Brain Science Institute, Tamagawa University, Machida, Japan
| | - Yoichiro Masuda
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Keiji Yoshikawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan.,Yoshikawa Eye Clinic, Machida, Japan
| | - Tadashi Nakano
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
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31
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Figley CR, Uddin MN, Wong K, Kornelsen J, Puig J, Figley TD. Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure. Front Neurosci 2022; 15:799576. [PMID: 35095400 PMCID: PMC8795606 DOI: 10.3389/fnins.2021.799576] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/17/2021] [Indexed: 01/31/2023] Open
Abstract
Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.
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Affiliation(s)
- Chase R. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Chase R. Figley,
| | - Md Nasir Uddin
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Kaihim Wong
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| | - Josep Puig
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr. Josep Trueta, Girona, Spain
| | - Teresa D. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
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Blazquez Freches G, Haak KV, Beckmann CF, Mars RB. Connectivity gradients on tractography data: Pipeline and example applications. Hum Brain Mapp 2021; 42:5827-5845. [PMID: 34559432 PMCID: PMC8596970 DOI: 10.1002/hbm.25623] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 07/03/2021] [Accepted: 07/30/2021] [Indexed: 11/08/2022] Open
Abstract
Gray matter connectivity can be described in terms of its topographical organization, but the differential role of white matter connections underlying that organization is often unknown. In this study, we propose a method for unveiling principles of organization of both gray and white matter based on white matter connectivity as assessed using diffusion magnetic ressonance imaging (MRI) tractography with spectral embedding gradient mapping. A key feature of the proposed approach is its capacity to project the individual connectivity gradients it reveals back onto its input data in the form of projection images, allowing one to assess the contributions of specific white matter tracts to the observed gradients. We demonstrate the ability of our proposed pipeline to identify connectivity gradients in prefrontal and occipital gray matter. Finally, leveraging the use of tractography, we demonstrate that it is possible to observe gradients within the white matter bundles themselves. Together, the proposed framework presents a generalized way to assess both the topographical organization of structural brain connectivity and the anatomical features driving it.
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Affiliation(s)
- Guilherme Blazquez Freches
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
| | - Koen V. Haak
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Christian F. Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nufeld Department of Clinical NeurosciencesJohn Radclife Hospital, University of OxfordOxfordUK
| | - Rogier B. Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
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Yoo J, Kerkelä L, Hales PW, Seunarine KK, Clark CA. High-resolution microscopic diffusion anisotropy imaging in the human hippocampus at 3T. Magn Reson Med 2021; 87:1903-1913. [PMID: 34841566 DOI: 10.1002/mrm.29104] [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: 05/26/2021] [Revised: 11/10/2021] [Accepted: 11/10/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE Several neurological conditions are associated with microstructural changes in the hippocampus that can be observed using DWI. Imaging studies often use protocols with whole-brain coverage, imposing limits on image resolution and worsening partial-volume effects. Also, conventional single-diffusion-encoding methods confound microscopic diffusion anisotropy with size variance of microscopic diffusion environments. This study addresses these issues by implementing a multidimensional diffusion-encoding protocol for microstructural imaging of the hippocampus at high resolution. METHODS The hippocampus of 8 healthy volunteers was imaged at 1.5-mm isotropic resolution with a multidimensional diffusion-encoding sequence developed in house. Microscopic fractional anisotropy (µFA) and normalized size variance (CMD ) were estimated using q-space trajectory imaging, and their values were compared with DTI metrics. The overall scan time was 1 hour. The reproducibility of the protocol was confirmed with scan-rescan experiments, and a shorter protocol (14 minutes) was defined for situations with time constraints. RESULTS Mean µFA (0.47) was greater than mean FA (0.20), indicating orientation dispersion in hippocampal tissue microstructure. Mean CMD was 0.17. The reproducibility of q-space trajectory imaging metrics was comparable to DTI, and microstructural metrics in the healthy hippocampus are reported. CONCLUSION This work shows the feasibility of high-resolution microscopic anisotropy imaging in the human hippocampus at 3 T and provides reference values for microstructural metrics in a healthy hippocampus.
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Affiliation(s)
- Jiyoon Yoo
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Leevi Kerkelä
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Patrick W Hales
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Kiran K Seunarine
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Christopher A Clark
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
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White matter variability, cognition, and disorders: a systematic review. Brain Struct Funct 2021; 227:529-544. [PMID: 34731328 PMCID: PMC8844174 DOI: 10.1007/s00429-021-02382-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 09/03/2021] [Indexed: 11/23/2022]
Abstract
Inter-individual differences can inform treatment procedures and—if accounted for—have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional, and connectional anatomy. Brain connections are essential to facilitate functional organization and, when severed, cause impairments or complete loss of function. Hence, the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate cognitive functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not correlated with one, but multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract–function correlations might still be a promising tool in identifying biomarkers for precision medicine. They can characterize variations in brain anatomy, differences in functional organization, and predicts resilience and recovery in patients.
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Spencer APC, Brooks JCW, Masuda N, Byrne H, Lee-Kelland R, Jary S, Thoresen M, Goodfellow M, Cowan FM, Chakkarapani E. Motor function and white matter connectivity in children cooled for neonatal encephalopathy. Neuroimage Clin 2021; 32:102872. [PMID: 34749285 PMCID: PMC8578038 DOI: 10.1016/j.nicl.2021.102872] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/13/2021] [Accepted: 10/30/2021] [Indexed: 11/24/2022]
Abstract
Therapeutic hypothermia reduces the incidence of severe motor disability, such as cerebral palsy, following neonatal hypoxic-ischaemic encephalopathy. However, cooled children without cerebral palsy at school-age demonstrate motor deficits and altered white matter connectivity. In this study, we used diffusion-weighted imaging to investigate the relationship between white matter connectivity and motor performance, measured using the Movement Assessment Battery for Children-2, in children aged 6-8 years treated with therapeutic hypothermia for neonatal hypoxic-ischaemic encephalopathy at birth, who did not develop cerebral palsy (cases), and matched typically developing controls. Correlations between total motor scores and diffusion properties in major white matter tracts were assessed in 33 cases and 36 controls. In cases, significant correlations (FDR-corrected P < 0.05) were found in the anterior thalamic radiation bilaterally (left: r = 0.513; right: r = 0.488), the cingulate gyrus part of the left cingulum (r = 0.588), the hippocampal part of the left cingulum (r = 0.541), and the inferior fronto-occipital fasciculus bilaterally (left: r = 0.445; right: r = 0.494). No significant correlations were found in controls. We then constructed structural connectivity networks, for 22 cases and 32 controls, in which nodes represent brain regions and edges were determined by probabilistic tractography and weighted by fractional anisotropy. Analysis of whole-brain network metrics revealed correlations (FDR-corrected P < 0.05), in cases, between total motor scores and average node strength (r = 0.571), local efficiency (r = 0.664), global efficiency (r = 0.677), clustering coefficient (r = 0.608), and characteristic path length (r = -0.652). No significant correlations were found in controls. We then investigated edge-level association with motor function using the network-based statistic. This revealed subnetworks which exhibited group differences in the association between motor outcome and edge weights, for total motor scores (P = 0.0109) as well as for balance (P = 0.0245) and manual dexterity (P = 0.0233) domain scores. All three of these subnetworks comprised numerous frontal lobe regions known to be associated with motor function, including the superior frontal gyrus and middle frontal gyrus. The subnetwork associated with total motor scores was highly left-lateralised. These findings demonstrate an association between impaired motor function and brain organisation in school-age children treated with therapeutic hypothermia for neonatal hypoxic-ischaemic encephalopathy.
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Affiliation(s)
- Arthur P C Spencer
- Clinical Research and Imaging Centre, University of Bristol, Bristol, UK; Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jonathan C W Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol, UK; School of Psychology, University of East Anglia, Norwich, UK
| | - Naoki Masuda
- Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, USA; Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY, USA
| | - Hollie Byrne
- Clinical Research and Imaging Centre, University of Bristol, Bristol, UK; Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Richard Lee-Kelland
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sally Jary
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marianne Thoresen
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Marc Goodfellow
- Living Systems Institute, University of Exeter, Exeter, UK; Wellcome Trust Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, UK; EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, UK; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Frances M Cowan
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Department of Paediatrics, Imperial College London, London, UK
| | - Ela Chakkarapani
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Neonatal Intensive Care Unit, St Michael's Hospital, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
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Minosse S, Picchi E, Giuliano FD, di Cio F, Pistolese CA, Sarmati L, Teti E, Andreoni M, Floris R, Guerrisi M, Garaci F, Toschi N. Compartmental models for diffusion weighted MRI reveal widespread brain changes in HIV-infected patients. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:3834-3837. [PMID: 34892070 DOI: 10.1109/embc46164.2021.9629510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Diffusion tensor imaging (DTI) has been used to explore changes in the brain of subjects with human immunodeficiency virus (HIV) infection. However, DTI notoriously suffers from low specificity. Neurite orientation dispersion and density imaging (NODDI) is a compartmental model able to provide specific microstructural information with additional sensitivity/specificity. In this study we use both the NODDI and the DTI models to evaluate microstructural differences between 35 HIV-positive patients and 20 healthy controls. Diffusion-weighted imaging was acquired using three b-values (0, 1000 and 2500 s/mm2). Both DTI and NODDI models were fitted to the data, obtaining estimates for fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), neurite density index (NDI) and orientation dispersion index (ODI), after which we performed group comparisons using Tract-based spatial statistics (TBSS). While significant group effects were found in in FA, MD, RD, AD and NDI, NDI analysis uncovered a much wider involvement of brain tissue in HIV infection as compared to DTI. In region-of interest (ROI)-based analysis, NDI estimates from the right corticospinal tract produced excellent performance in discriminating the two groups (AUC = 0.974, sensitivity = 90%; specificity =97%).
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Spencer APC, Byrne H, Lee-Kelland R, Jary S, Thoresen M, Cowan FM, Chakkarapani E, Brooks JCW. An Age-Specific Atlas for Delineation of White Matter Pathways in Children Aged 6-8 Years. Brain Connect 2021; 12:402-416. [PMID: 34210166 PMCID: PMC7612846 DOI: 10.1089/brain.2021.0058] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction Diffusion MRI allows non-invasive assessment of white matter connectivity in typical development and of changes due to brain injury or pathology. Probabilistic white matter atlases allow diffusion metrics to be measured in specific white matter pathways, and are a critical component in spatial normalisation for group analysis. However, given the known developmental changes in white matter it may be sub-optimal to use an adult template when assessing data acquired from children. Methods By averaging subject-specific fibre bundles from 28 children aged from 6 to 8 years, we created an age-specific probabilistic white matter atlas for 12 major white matter tracts. Using both the newly developed and Johns Hopkins adult atlases, we compared the atlas to subject-specific fibre bundles in two independent validation cohorts, assessing accuracy in terms of volumetric overlap and measured diffusion metrics. Results Our age-specific atlas gave better overall performance than the adult atlas, achieving higher volumetric overlap with subject-specific fibre tracking and higher correlation of FA measurements with those measured from subject-specific fibre bundles. Specifically, estimates of FA values for cortico-spinal tract, uncinate fasciculus, forceps minor, cingulate gyrus part of the cingulum and anterior thalamic radiation were all significantly more accurate when estimated with an age-specific atlas. Discussion The age-specific atlas allows delineation of white matter tracts in children aged 6-8 years, without the need for tractography, more accurately than when normalising to an adult atlas. To our knowledge, this is the first publicly available probabilistic atlas of white matter tracts for this age group.
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Affiliation(s)
- Arthur P C Spencer
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom.,Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Hollie Byrne
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom
| | - Richard Lee-Kelland
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sally Jary
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Marianne Thoresen
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Frances M Cowan
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,Department of Paediatrics, Imperial College London, London, United Kingdom
| | - Ela Chakkarapani
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jonathan C W Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom.,School of Psychology, University of East Anglia, Norwich, United Kingdom
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Kerkelä L, Nery F, Callaghan R, Zhou F, Gyori NG, Szczepankiewicz F, Palombo M, Parker GJM, Zhang H, Hall MG, Clark CA. Comparative analysis of signal models for microscopic fractional anisotropy estimation using q-space trajectory encoding. Neuroimage 2021; 242:118445. [PMID: 34375753 DOI: 10.1016/j.neuroimage.2021.118445] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 07/06/2021] [Accepted: 08/02/2021] [Indexed: 12/12/2022] Open
Abstract
Microscopic diffusion anisotropy imaging using diffusion-weighted MRI and multidimensional diffusion encoding is a promising method for quantifying clinically and scientifically relevant microstructural properties of neural tissue. Several methods for estimating microscopic fractional anisotropy (µFA), a normalized measure of microscopic diffusion anisotropy, have been introduced but the differences between the methods have received little attention thus far. In this study, the accuracy and precision of µFA estimation using q-space trajectory encoding and different signal models were assessed using imaging experiments and simulations. Three healthy volunteers and a microfibre phantom were imaged with five non-zero b-values and gradient waveforms encoding linear and spherical b-tensors. Since the ground-truth µFA was unknown in the imaging experiments, Monte Carlo random walk simulations were performed using axon-mimicking fibres for which the ground truth was known. Furthermore, parameter bias due to time-dependent diffusion was quantified by repeating the simulations with tuned waveforms, which have similar power spectra, and with triple diffusion encoding, which, unlike q-space trajectory encoding, is not based on the assumption of time-independent diffusion. The truncated cumulant expansion of the powder-averaged signal, gamma-distributed diffusivities assumption, and q-space trajectory imaging, a generalization of the truncated cumulant expansion to individual signals, were used to estimate µFA. The gamma-distributed diffusivities assumption consistently resulted in greater µFA values than the second order cumulant expansion, 0.1 greater when averaged over the whole brain. In the simulations, the generalized cumulant expansion provided the most accurate estimates. Importantly, although time-dependent diffusion caused significant overestimation of µFA using all the studied methods, the simulations suggest that the resulting bias in µFA is less than 0.1 in human white matter.
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Affiliation(s)
- Leevi Kerkelä
- UCL Great Ormond Street Institute of Child Health, University College London, London, UK.
| | - Fabio Nery
- UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Ross Callaghan
- UCL Centre for Medical Image Computing, University College London, London, UK
| | - Fenglei Zhou
- UCL Centre for Medical Image Computing, University College London, London, UK; UCL School of Pharmacy, University College London, London, UK
| | - Noemi G Gyori
- UCL Centre for Medical Image Computing, University College London, London, UK; UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Filip Szczepankiewicz
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, US; Harvard Medical School, Boston, Massachusetts, US; Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Marco Palombo
- UCL Centre for Medical Image Computing, University College London, London, UK
| | - Geoff J M Parker
- UCL Centre for Medical Image Computing, University College London, London, UK; Bioxydyn Limited, Manchester, UK; UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Hui Zhang
- UCL Centre for Medical Image Computing, University College London, London, UK
| | - Matt G Hall
- UCL Great Ormond Street Institute of Child Health, University College London, London, UK; National Physical Laboratory, Teddington, UK
| | - Chris A Clark
- UCL Great Ormond Street Institute of Child Health, University College London, London, UK
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Clark IA, Callaghan MF, Weiskopf N, Maguire EA, Mohammadi S. Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data. Front Neurosci 2021; 15:706473. [PMID: 34421526 PMCID: PMC8376472 DOI: 10.3389/fnins.2021.706473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022] Open
Abstract
Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.
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Affiliation(s)
- Ian A. Clark
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Eleanor A. Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Institute of Systems Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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40
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Bigler ED. Charting Brain Development in Graphs, Diagrams, and Figures from Childhood, Adolescence, to Early Adulthood: Neuroimaging Implications for Neuropsychology. JOURNAL OF PEDIATRIC NEUROPSYCHOLOGY 2021. [DOI: 10.1007/s40817-021-00099-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Hasan KM, Yamada K. Overview of Diffusion Tensor, Diffusion Kurtosis, and Q-space Imaging and Software Tools. Magn Reson Imaging Clin N Am 2021; 29:263-268. [PMID: 33902908 DOI: 10.1016/j.mric.2021.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
This work offers a short up-to-date review of diffusion-weighted MR imaging (dMRI) and software tools that are used widely to process and analyze clinical dMRI. A consolidated dMRI protocol for clinical applications that enables the mapping of tissue microstructural attributes is presented.
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Affiliation(s)
- Khader M Hasan
- Department of Diagnostic and Interventional Radiology, The University of Texas Health Science Center, McGovern Medical School, Houston, Texas, USA.
| | - Kei Yamada
- Department of Radiology, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo-ku, Kyoto 6028566, Japan
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Amemiya K, Naito E, Takemura H. Age dependency and lateralization in the three branches of the human superior longitudinal fasciculus. Cortex 2021; 139:116-133. [PMID: 33852990 DOI: 10.1016/j.cortex.2021.02.027] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 01/28/2021] [Accepted: 02/23/2021] [Indexed: 01/02/2023]
Abstract
The superior longitudinal fascicle/fasciculus (SLF) is a major white matter tract connecting the frontal and parietal cortices in humans. Although the SLF has often been analyzed as a single entity, several studies have reported that the SLF is segregated into three distinct branches (SLF I, II, and III). They have also reported the right lateralization of the SLF III volume and discussed its relationship with lateralized cortical functions in the fronto-parietal network. However, to date, the homogeneity or heterogeneity of the age dependency and lateralization properties of SLF branches have not been fully clarified. Through this study, we aimed to clarify the age dependency and lateralization of SLF I-III by analyzing diffusion-weighted MRI (dMRI) and quantitative R1 (qR1) map datasets collected from a wide range of age groups, mostly comprising right-handed children, adolescents, adults, and seniors (6 to 81 years old). The age dependency in dMRI measurement (fractional anisotropy, FA) was heterogeneous among the three SLF branches, suggesting that these branches are regulated by distinct developmental and aging processes. Lateralization analysis on SLF branches revealed that the right SLF III was larger than the left SLF III in adults, replicating previous reports. FA measurement also suggested that, in addition to SLF III, SLF II was lateralized to the right hemisphere in adolescents and adults. We further found a left lateralization of SLF I in qR1 data, a microstructural measurement sensitive to myelin levels, in adults. These findings suggest that the SLF sub-bundles are distinct entities in terms of age dependency and lateralization.
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Affiliation(s)
- Kaoru Amemiya
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka University, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
| | - Eiichi Naito
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka University, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka University, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.
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Spencer APC, Brooks JCW, Masuda N, Byrne H, Lee-Kelland R, Jary S, Thoresen M, Tonks J, Goodfellow M, Cowan FM, Chakkarapani E. Disrupted brain connectivity in children treated with therapeutic hypothermia for neonatal encephalopathy. NEUROIMAGE-CLINICAL 2021; 30:102582. [PMID: 33636541 PMCID: PMC7906894 DOI: 10.1016/j.nicl.2021.102582] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 01/18/2021] [Accepted: 01/28/2021] [Indexed: 11/27/2022]
Abstract
We studied brain structure in case children cooled for neonatal encephalopathy. Cases did not have cerebral palsy and were matched with controls. Cases had reduced fractional anisotropy in several white matter tracts. Several whole-brain structural connectivity network metrics correlated with IQ. We identified subnetworks associated with case status, IQ and processing speed.
Therapeutic hypothermia following neonatal encephalopathy due to birth asphyxia reduces death and cerebral palsy. However, school-age children without cerebral palsy treated with therapeutic hypothermia for neonatal encephalopathy still have reduced performance on cognitive and motor tests, attention difficulties, slower reaction times and reduced visuo-spatial processing abilities compared to typically developing controls. We acquired diffusion-weighted imaging data from school-age children without cerebral palsy treated with therapeutic hypothermia for neonatal encephalopathy at birth, and a matched control group. Voxelwise analysis (33 cases, 36 controls) confirmed reduced fractional anisotropy in widespread areas of white matter in cases, particularly in the fornix, corpus callosum, anterior and posterior limbs of the internal capsule bilaterally and cingulum bilaterally. In structural brain networks constructed using probabilistic tractography (22 cases, 32 controls), graph-theoretic measures of strength, local and global efficiency, clustering coefficient and characteristic path length were found to correlate with IQ in cases but not controls. Network-based statistic analysis implicated brain regions involved in visuo-spatial processing and attention, aligning with previous behavioural findings. These included the precuneus, thalamus, left superior parietal gyrus and left inferior temporal gyrus. Our findings demonstrate that, despite the manifest successes of therapeutic hypothermia, brain development is impaired in these children.
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Affiliation(s)
- Arthur P C Spencer
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom
| | - Jonathan C W Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom; School of Psychological Science, University of Bristol, Bristol, United Kingdom
| | - Naoki Masuda
- Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, United States; Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY, United States
| | - Hollie Byrne
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom
| | - Richard Lee-Kelland
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sally Jary
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Marianne Thoresen
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - James Tonks
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; University of Exeter Medical School, Exeter, United Kingdom
| | - Marc Goodfellow
- Living Systems Institute, University of Exeter, Exeter, United Kingdom; Wellcome Trust Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom; EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Frances M Cowan
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Department of Paediatrics, Imperial College London, London, United Kingdom
| | - Ela Chakkarapani
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Neonatal Intensive Care Unit, St Michael's Hospital, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom.
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44
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Szczepankiewicz F, Westin CF, Nilsson M. Gradient waveform design for tensor-valued encoding in diffusion MRI. J Neurosci Methods 2021; 348:109007. [PMID: 33242529 PMCID: PMC8443151 DOI: 10.1016/j.jneumeth.2020.109007] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/17/2020] [Accepted: 11/19/2020] [Indexed: 12/13/2022]
Abstract
Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.
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Affiliation(s)
- Filip Szczepankiewicz
- Radiology, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Clinical Sciences, Lund University, Lund, Sweden.
| | - Carl-Fredrik Westin
- Radiology, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States
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Basso MA, Frey S, Guerriero KA, Jarraya B, Kastner S, Koyano KW, Leopold DA, Murphy K, Poirier C, Pope W, Silva AC, Tansey G, Uhrig L. Using non-invasive neuroimaging to enhance the care, well-being and experimental outcomes of laboratory non-human primates (monkeys). Neuroimage 2020; 228:117667. [PMID: 33359353 PMCID: PMC8005297 DOI: 10.1016/j.neuroimage.2020.117667] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 02/09/2023] Open
Abstract
Over the past 10-20 years, neuroscience witnessed an explosion in the use of non-invasive imaging methods, particularly magnetic resonance imaging (MRI), to study brain structure and function. Simultaneously, with access to MRI in many research institutions, MRI has become an indispensable tool for researchers and veterinarians to guide improvements in surgical procedures and implants and thus, experimental as well as clinical outcomes, given that access to MRI also allows for improved diagnosis and monitoring for brain disease. As part of the PRIMEatE Data Exchange, we gathered expert scientists, veterinarians, and clinicians who treat humans, to provide an overview of the use of non-invasive imaging tools, primarily MRI, to enhance experimental and welfare outcomes for laboratory non-human primates engaged in neuroscientific experiments. We aimed to provide guidance for other researchers, scientists and veterinarians in the use of this powerful imaging technology as well as to foster a larger conversation and community of scientists and veterinarians with a shared goal of improving the well-being and experimental outcomes for laboratory animals.
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Affiliation(s)
- M A Basso
- Fuster Laboratory of Cognitive Neuroscience, Department of Psychiatry and Biobehavioral Sciences UCLA Los Angeles CA 90095 USA
| | - S Frey
- Rogue Research, Inc. Montreal, QC, Canada
| | - K A Guerriero
- Washington National Primate Research Center University of Washington Seattle, WA USA
| | - B Jarraya
- Cognitive Neuroimaging Unit, INSERM, CEA, NeuroSpin center, 91191 Gif/Yvette, France; Université Paris-Saclay, UVSQ, Foch hospital, Paris, France
| | - S Kastner
- Princeton Neuroscience Institute & Department of Psychology Princeton University Princeton, NJ USA
| | - K W Koyano
- National Institute of Mental Health NIH Bethesda MD 20892 USA
| | - D A Leopold
- National Institute of Mental Health NIH Bethesda MD 20892 USA
| | - K Murphy
- Biosciences Institute and Centre for Behaviour and Evolution, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne NE2 4HH United Kingdom UK
| | - C Poirier
- Biosciences Institute and Centre for Behaviour and Evolution, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne NE2 4HH United Kingdom UK
| | - W Pope
- Department of Radiology UCLA Los Angeles, CA 90095 USA
| | - A C Silva
- Department of Neurobiology University of Pittsburgh, Pittsburgh PA 15261 USA
| | - G Tansey
- National Eye Institute NIH Bethesda MD 20892 USA
| | - L Uhrig
- Cognitive Neuroimaging Unit, INSERM, CEA, NeuroSpin center, 91191 Gif/Yvette, France
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46
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Lee Y, Wilm BJ, Brunner DO, Gross S, Schmid T, Nagy Z, Pruessmann KP. On the signal-to-noise ratio benefit of spiral acquisition in diffusion MRI. Magn Reson Med 2020; 85:1924-1937. [PMID: 33280160 DOI: 10.1002/mrm.28554] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 09/15/2020] [Accepted: 09/22/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE Spiral readouts combine several favorable properties that promise superior net sensitivity for diffusion imaging. The purpose of this study is to verify the signal-to-noise ratio (SNR) benefit of spiral acquisition in comparison with current echo-planar imaging (EPI) schemes. METHODS Diffusion-weighted in vivo brain data from three subjects were acquired with a single-shot spiral sequence and several variants of single-shot EPI, including full-Fourier and partial-Fourier readouts as well as different diffusion-encoding schemes. Image reconstruction was based on an expanded signal model including field dynamics obtained by concurrent field monitoring. The effective resolution of each sequence was matched to that of full-Fourier EPI with 1 mm nominal resolution. SNR maps were generated by determining the noise statistics of the raw data and analyzing the propagation of equivalent synthetic noise through image reconstruction. Using the same approach, maps of noise amplification due to parallel imaging (g-factor) were calculated for different acceleration factors. RESULTS Relative to full-Fourier EPI at b = 0 s/mm2 , spiral acquisition yielded SNR gains of 42-88% and 40-89% in white and gray matter, respectively, depending on the diffusion-encoding scheme. Relative to partial-Fourier EPI, the gains were 36-44% and 34-42%. Spiral g-factor maps exhibited less spatial variation and lower maxima than their EPI counterparts. CONCLUSION Spiral readouts achieve significant SNR gains in the order of 40-80% over EPI in diffusion imaging at 3T. Combining systematic effects of shorter echo time, readout efficiency, and favorable g-factor behavior, similar benefits are expected across clinical and neurosciences uses of diffusion imaging.
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Affiliation(s)
- Yoojin Lee
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.,Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland
| | - Bertram J Wilm
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - David O Brunner
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Thomas Schmid
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Pron A, Deruelle C, Coulon O. U-shape short-range extrinsic connectivity organisation around the human central sulcus. Brain Struct Funct 2020; 226:179-193. [PMID: 33245395 DOI: 10.1007/s00429-020-02177-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 11/09/2020] [Indexed: 12/20/2022]
Abstract
The central sulcus is probably one of the most studied folds in the human brain, owing to its clear relationship with primary sensory-motor functional areas. However, due to the difficulty of estimating the trajectories of the U-shape fibres from diffusion MRI, the short structural connectivity of this sulcus remains relatively unknown. In this context, we studied the spatial organization of these U-shape fibres along the central sulcus. Based on high quality diffusion MRI data of 100 right-handed subjects and state-of-the-art pre-processing pipeline, we first define a connectivity space that provides a comprehensive and continuous description of the short-range anatomical connectivity around the central sulcus at both the individual and group levels. We then infer the presence of five major U-shape fibre bundles at the group level in both hemispheres by applying unsupervised clustering in the connectivity space. We propose a quantitative investigation of their position and number of streamlines as a function of hemisphere, sex and functional scores such as handedness and manual dexterity. Main findings of this study are twofold: a description of U-shape short-range connectivity along the central sulcus at group level and the evidence of a significant relationship between the position of three hand related U-shape fibre bundles and the handedness score of subjects.
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Affiliation(s)
- Alexandre Pron
- Institut de Neurosciences de La Timone, Aix-Marseille Université, CNRS, UMR 7289, Marseille, France
| | - Christine Deruelle
- Institut de Neurosciences de La Timone, Aix-Marseille Université, CNRS, UMR 7289, Marseille, France
| | - Olivier Coulon
- Institut de Neurosciences de La Timone, Aix-Marseille Université, CNRS, UMR 7289, Marseille, France.
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48
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He B, Cao L, Xia X, Zhang B, Zhang D, You B, Fan L, Jiang T. Fine-Grained Topography and Modularity of the Macaque Frontal Pole Cortex Revealed by Anatomical Connectivity Profiles. Neurosci Bull 2020; 36:1454-1473. [PMID: 33108588 PMCID: PMC7719154 DOI: 10.1007/s12264-020-00589-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 07/30/2020] [Indexed: 11/25/2022] Open
Abstract
The frontal pole cortex (FPC) plays key roles in various higher-order functions and is highly developed in non-human primates. An essential missing piece of information is the detailed anatomical connections for finer parcellation of the macaque FPC than provided by the previous tracer results. This is important for understanding the functional architecture of the cerebral cortex. Here, combining cross-validation and principal component analysis, we formed a tractography-based parcellation scheme that applied a machine learning algorithm to divide the macaque FPC (2 males and 6 females) into eight subareas using high-resolution diffusion magnetic resonance imaging with the 9.4T Bruker system, and then revealed their subregional connections. Furthermore, we applied improved hierarchical clustering to the obtained parcels to probe the modular structure of the subregions, and found that the dorsolateral FPC, which contains an extension to the medial FPC, was mainly connected to regions of the default-mode network. The ventral FPC was mainly involved in the social-interaction network and the dorsal FPC in the metacognitive network. These results enhance our understanding of the anatomy and circuitry of the macaque brain, and contribute to FPC-related clinical research.
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Affiliation(s)
- Bin He
- School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China
| | - Long Cao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Xiaoluan Xia
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China
| | - Dan Zhang
- Core Facility, Center of Biomedical Analysis, Tsinghua University, Beijing, 100084, China
| | - Bo You
- School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China. .,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, CAS, Beijing, 100190, China. .,University of CAS, Beijing, 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China. .,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, CAS, Beijing, 100190, China. .,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China. .,The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia. .,University of CAS, Beijing, 100049, China. .,Chinese Institute for Brain Research, Beijing, 102206, China.
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49
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Takemura H, Palomero-Gallagher N, Axer M, Gräßel D, Jorgensen MJ, Woods R, Zilles K. Anatomy of nerve fiber bundles at micrometer-resolution in the vervet monkey visual system. eLife 2020; 9:e55444. [PMID: 32844747 PMCID: PMC7532002 DOI: 10.7554/elife.55444] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 08/22/2020] [Indexed: 12/11/2022] Open
Abstract
Although the primate visual system has been extensively studied, detailed spatial organization of white matter fiber tracts carrying visual information between areas has not been fully established. This is mainly due to the large gap between tracer studies and diffusion-weighted MRI studies, which focus on specific axonal connections and macroscale organization of fiber tracts, respectively. Here we used 3D polarization light imaging (3D-PLI), which enables direct visualization of fiber tracts at micrometer resolution, to identify and visualize fiber tracts of the visual system, such as stratum sagittale, inferior longitudinal fascicle, vertical occipital fascicle, tapetum and dorsal occipital bundle in vervet monkey brains. Moreover, 3D-PLI data provide detailed information on cortical projections of these tracts, distinction between neighboring tracts, and novel short-range pathways. This work provides essential information for interpretation of functional and diffusion-weighted MRI data, as well as revision of wiring diagrams based upon observations in the vervet visual system.
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Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka UniversityOsakaJapan
- Graduate School of Frontier Biosciences, Osaka UniversityOsakaJapan
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH AachenAachenGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
| | - Markus Axer
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - David Gräßel
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Matthew J Jorgensen
- Department of Pathology, Section on Comparative Medicine, Wake Forest School of MedicineWinston-SalemUnited States
| | - Roger Woods
- Ahmanson-Lovelace Brain Mapping Center, Departments of Neurology and of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLALos AngelesUnited States
| | - Karl Zilles
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- JARA - Translational Brain MedicineAachenGermany
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50
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Benear SL, Ngo CT, Olson IR. Dissecting the Fornix in Basic Memory Processes and Neuropsychiatric Disease: A Review. Brain Connect 2020; 10:331-354. [PMID: 32567331 DOI: 10.1089/brain.2020.0749] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: The fornix is the primary axonal tract of the hippocampus, connecting it to modulatory subcortical structures. This review reveals that fornix damage causes cognitive deficits that closely mirror those resulting from hippocampal lesions. Methods: We reviewed the literature on the fornix, spanning non-human animal lesion research, clinical case studies of human patients with fornix damage, as well as diffusion-weighted imaging (DWI) work that evaluates fornix microstructure in vivo. Results: The fornix is essential for memory formation because it serves as the conduit for theta rhythms and acetylcholine, as well as providing mnemonic representations to deep brain structures that guide motivated behavior, such as when and where to eat. In rodents and non-human primates, fornix lesions lead to deficits in conditioning, reversal learning, and navigation. In humans, damage to the fornix manifests as anterograde amnesia. DWI research reveals that the fornix plays a key role in mild cognitive impairment and Alzheimer's Disease, and can potentially predict conversion from the former to the latter. Emerging DWI findings link perturbations in this structure to schizophrenia, mood disorders, and eating disorders. Cutting-edge research has investigated how deep brain stimulation of the fornix can potentially attenuate memory loss, control epileptic seizures, and even improve mood. Conclusions: The fornix is essential to a fully functioning memory system and is implicated in nearly all neurological functions that rely on the hippocampus. Future research needs to use optimized DWI methods to study the fornix in vivo, which we discuss, given the difficult nature of fornix reconstruction. Impact Statement The fornix is a white matter tract that connects the hippocampus to several subcortical brain regions and is pivotal for episodic memory functioning. Functionally, the fornix transmits essential neurotransmitters, as well as theta rhythms, to the hippocampus. In addition, it is the conduit by which memories guide decisions. The fornix is biomedically important because lesions to this tract result in irreversible anterograde amnesia. Research using in vivo imaging methods has linked fornix pathology to cognitive aging, mild cognitive impairment, psychosis, epilepsy, and, importantly, Alzheimer's Disease.
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Affiliation(s)
- Susan L Benear
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
| | - Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ingrid R Olson
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
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