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Zhang F, Chen Y, Ning L, Rushmore J, Liu Q, Du M, Hassanzadeh‐Behbahani S, Legarreta J, Yeterian E, Makris N, Rathi Y, O'Donnell L. Assessment of the Depiction of Superficial White Matter Using Ultra-High-Resolution Diffusion MRI. Hum Brain Mapp 2024; 45:e70041. [PMID: 39392220 PMCID: PMC11467805 DOI: 10.1002/hbm.70041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 09/22/2024] [Indexed: 10/12/2024] Open
Abstract
The superficial white matter (SWM) consists of numerous short-range association fibers connecting adjacent and nearby gyri and plays an important role in brain function, development, aging, and various neurological disorders. Diffusion MRI (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the SWM. However, detailed imaging of the small, highly-curved fibers of the SWM is a challenge for current clinical and research dMRI acquisitions. This work investigates the efficacy of mapping the SWM using in vivo ultra-high-resolution dMRI data. We compare the SWM mapping performance from two dMRI acquisitions: a high-resolution 0.76-mm isotropic acquisition using the generalized slice-dithered enhanced resolution (gSlider) protocol and a lower resolution 1.25-mm isotropic acquisition obtained from the Human Connectome Project Young Adult (HCP-YA) database. Our results demonstrate significant differences in the cortico-cortical anatomical connectivity that is depicted by these two acquisitions. We perform a detailed assessment of the anatomical plausibility of these results with respect to the nonhuman primate (macaque) tract-tracing literature. We find that the high-resolution gSlider dataset is more successful at depicting a large number of true positive anatomical connections in the SWM. An additional cortical coverage analysis demonstrates significantly higher cortical coverage in the gSlider dataset for SWM streamlines under 40 mm in length. Overall, we conclude that the spatial resolution of the dMRI data is one important factor that can significantly affect the mapping of SWM. Considering the relatively long acquisition time, the application of dMRI tractography for SWM mapping in future work should consider the balance of data acquisition efforts and the efficacy of SWM depiction.
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Affiliation(s)
- Fan Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yuqian Chen
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lipeng Ning
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Jarrett Rushmore
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Qiang Liu
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Mubai Du
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
| | | | - Jon Haitz Legarreta
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Edward Yeterian
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
- Department of PsychologyColby CollegeWatervilleMaineUSA
| | - Nikos Makris
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lauren J. O'Donnell
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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Mavrovounis G, Skouroliakou A, Kalatzis I, Stranjalis G, Kalamatianos T. Over 30 Years of DiI Use for Human Neuroanatomical Tract Tracing: A Scoping Review. Biomolecules 2024; 14:536. [PMID: 38785943 PMCID: PMC11117484 DOI: 10.3390/biom14050536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/25/2024] Open
Abstract
In the present study, we conducted a scoping review to provide an overview of the existing literature on the carbocyanine dye DiI, in human neuroanatomical tract tracing. The PubMed, Scopus, and Web of Science databases were systematically searched. We identified 61 studies published during the last three decades. While studies incorporated specimens across human life from the embryonic stage onwards, the majority of studies focused on adult human tissue. Studies that utilized peripheral nervous system (PNS) tissue were a minority, with the majority of studies focusing on the central nervous system (CNS). The most common topic of interest in previous tract tracing investigations was the connectivity of the visual pathway. DiI crystals were more commonly applied. Nevertheless, several studies utilized DiI in a paste or dissolved form. The maximum tracing distance and tracing speed achieved was, respectively, 70 mm and 1 mm/h. We identified studies that focused on optimizing tracing efficacy by varying parameters such as fixation, incubation temperature, dye re-application, or the application of electric fields. Additional studies aimed at broadening the scope of DiI use by assessing the utility of archival tissue and compatibility of tissue clearing in DiI applications. A combination of DiI tracing and immunohistochemistry in double-labeling studies have been shown to provide the means for assessing connectivity of phenotypically defined human CNS and PNS neuronal populations.
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Affiliation(s)
- Georgios Mavrovounis
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
| | - Aikaterini Skouroliakou
- Department of Biomedical Engineering, The University of West Attica, 12243 Athens, Greece; (A.S.); (I.K.)
| | - Ioannis Kalatzis
- Department of Biomedical Engineering, The University of West Attica, 12243 Athens, Greece; (A.S.); (I.K.)
| | - George Stranjalis
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
- Hellenic Centre for Neurosurgery Research “Professor Petros S. Kokkalis”, 10675 Athens, Greece
| | - Theodosis Kalamatianos
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
- Hellenic Centre for Neurosurgery Research “Professor Petros S. Kokkalis”, 10675 Athens, Greece
- Clinical and Experimental Neuroscience Research Group, Department of Neurosurgery, National and Kapodistrian University of Athens, 10675 Athens, Greece
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Xia J, Liu C, Li J, Meng Y, Yang S, Chen H, Liao W. Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets. Nat Commun 2024; 15:2289. [PMID: 38480767 PMCID: PMC10937940 DOI: 10.1038/s41467-024-46651-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 03/06/2024] [Indexed: 03/17/2024] Open
Abstract
Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain's anatomical-functional relationship.
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Affiliation(s)
- Jie Xia
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Cirong Liu
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, P.R. China
| | - Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Siqi Yang
- School of Cybersecurity, Chengdu University of Information Technology, Chengdu, 610225, P.R. China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
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Makris N, Rushmore R, Yeterian E. A proposed structural connectivity matrices approach for the superior fronto-occipital fascicle in the Harvard-Oxford Atlas comparative framework following the Pandya comparative extrapolation principle. J Comp Neurol 2023; 531:2172-2184. [PMID: 38010231 PMCID: PMC11019921 DOI: 10.1002/cne.25562] [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: 04/10/2023] [Revised: 09/19/2023] [Accepted: 10/13/2023] [Indexed: 11/29/2023]
Abstract
A key set of connections necessary for the most complex brain functions are the long association cortico-cortical fiber tracts. These pathways have been described by the Dejerines and others using post mortem histological or brain dissection techniques. Given methodological limitations, these fiber connections have not been delineated completely in humans. Although the stem portions of fiber tracts have been identified in humans, their precise origins and terminations remain to be determined. By contrast, the origins and terminations as well as the stems of long cortico-cortical association fiber pathways in monkeys have been detailed in the macaque monkey brain using experimental tract tracing methods. Deepak Pandya made major contributions to the delineation of fiber tracts in the monkey brain. In the early 1990s, he compared his observations in monkeys with the original descriptions in humans by the Dejerines. With the advent of diffusion-weighted imaging, Dr. Pandya extended this line of investigation to the human brain with Dr. Nikos Makris. In this translational analysis of long association cortico-cortical fiber tracts, they applied a principle of extrapolation from monkey to human. In the present study, we addressed the reasoning and the complex methodology in translating brain structural connectivity from monkey to human in one cortico-cortical fiber tract, namely the superior fronto-occipital fascicle, which was delineated in both species by Dr. Pandya and colleagues. Furthermore, we represented this information in the form of connectional matrices in the context of the HOA2.0-ComPaRe framework, a homological monkey-to-human translational system used in neuroimaging.
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Affiliation(s)
- Nikos Makris
- Center for Morphometric Analysis, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Richard Rushmore
- Center for Morphometric Analysis, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Edward Yeterian
- Center for Morphometric Analysis, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychology, Colby College, Waterville, ME, USA
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Zheng J, Yang Q, Makris N, Huang K, Liang J, Ye C, Yu X, Tian M, Ma T, Mou T, Guo W, Kikinis R, Gao Y. Three-Dimensional Digital Reconstruction of the Cerebellar Cortex: Lobule Thickness, Surface Area Measurements, and Layer Architecture. CEREBELLUM (LONDON, ENGLAND) 2023; 22:249-260. [PMID: 35286708 PMCID: PMC9470778 DOI: 10.1007/s12311-022-01390-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 02/28/2022] [Indexed: 11/28/2022]
Abstract
The cerebellum is ontogenetically one of the first structures to develop in the central nervous system; nevertheless, it has been only recently reconsidered for its significant neurobiological, functional, and clinical relevance in humans. Thus, it has been a relatively under-studied compared to the cerebrum. Currently, non-invasive imaging modalities can barely reach the necessary resolution to unfold its entire, convoluted surface, while only histological analyses can reveal local information at the micrometer scale. Herein, we used the BigBrain dataset to generate area and point-wise thickness measurements for all layers of the cerebellar cortex and for each lobule in particular. We found that the overall surface area of the cerebellar granular layer (including Purkinje cells) was 1,732 cm2 and the molecular layer was 1,945 cm2. The average thickness of the granular layer is 0.88 mm (± 0.83) and that of the molecular layer is 0.32 mm (± 0.08). The cerebellum (both granular and molecular layers) is thicker at the depth of the sulci and thinner at the crowns of the gyri. Globally, the granular layer is thicker in the lateral-posterior-inferior region than the medial-superior regions. The characterization of individual layers in the cerebellum achieved herein represents a stepping-stone for investigations interrelating structural and functional connectivity with cerebellar architectonics using neuroimaging, which is a matter of considerable relevance in basic and clinical neuroscience. Furthermore, these data provide templates for the construction of cerebellar topographic maps and the precise localization of structural and functional alterations in diseases affecting the cerebellum.
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Affiliation(s)
- Junxiao Zheng
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Qinzhu Yang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Nikos Makris
- Center for Morphometric Analysis, Departments of Psychiatry, Neurology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Department of Anatomy and Neurobiology, Boston University Medical School, Boston, USA
| | - Kaibin Huang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Jianwen Liang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Chenfei Ye
- Pengcheng Lab, Shenzhen, Guangdong, China
| | - Xiaxia Yu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Mu Tian
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Ting Ma
- Pengcheng Lab, Shenzhen, Guangdong, China
- Department of Electronic and Information Engineering, Harbin Institute of Technology Campus, Shenzhen, Guangdong, China
| | - Tian Mou
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Wenlong Guo
- Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Ron Kikinis
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Yi Gao
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China.
- Pengcheng Lab, Shenzhen, Guangdong, China.
- Marshall Laboratory of Biomedical Engineering, Shenzhen, Guangdong, China.
- Shenzhen Key Laboratory of Precision Medicine for Hematological Malignancies, Shenzhen, Guangdong, China.
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Makris N, Rushmore R, Kaiser J, Albaugh M, Kubicki M, Rathi Y, Zhang F, O’Donnell LJ, Yeterian E, Caviness VS, Kennedy DN. A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology. Dev Neurosci 2023; 45:161-180. [PMID: 36977393 PMCID: PMC10526721 DOI: 10.1159/000530358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 03/02/2023] [Indexed: 03/30/2023] Open
Abstract
A complete structural definition of the human nervous system must include delineation of its wiring diagram (e.g., Swanson LW. Brain architecture: understanding the basic plan, 2012). The complete formulation of the human brain circuit diagram (BCD [Front Neuroanat. 2020;14:18]) has been hampered by an inability to determine connections in their entirety (i.e., not only pathway stems but also origins and terminations). From a structural point of view, a neuroanatomic formulation of the BCD should include the origins and terminations of each fiber tract as well as the topographic course of the fiber tract in three dimensions. Classic neuroanatomical studies have provided trajectory information for pathway stems and their speculative origins and terminations [Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux, 1901; Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux: Méthodes générales d'étude-embryologie-histogénèse et histologie. Anatomie du cerveau, 1895; Ludwig E and Klingler J. Atlas cerebri humani, 1956; Makris N. Delineation of human association fiber pathways using histologic and magnetic resonance methodologies; 1999; Neuroimage. 1999 Jan;9(1):18-45]. We have summarized these studies previously [Neuroimage. 1999 Jan;9(1):18-45] and present them here in a macroscale-level human cerebral structural connectivity matrix. A matrix in the present context is an organizational construct that embodies anatomical knowledge about cortical areas and their connections. This is represented in relation to parcellation units according to the Harvard-Oxford Atlas neuroanatomical framework established by the Center for Morphometric Analysis at Massachusetts General Hospital in the early 2000s, which is based on the MRI volumetrics paradigm of Dr. Verne Caviness and colleagues [Brain Dev. 1999 Jul;21(5):289-95]. This is a classic connectional matrix based mainly on data predating the advent of DTI tractography, which we refer to as the "pre-DTI era" human structural connectivity matrix. In addition, we present representative examples that incorporate validated structural connectivity information from nonhuman primates and more recent information on human structural connectivity emerging from DTI tractography studies. We refer to this as the "DTI era" human structural connectivity matrix. This newer matrix represents a work in progress and is necessarily incomplete due to the lack of validated human connectivity findings on origins and terminations as well as pathway stems. Importantly, we use a neuroanatomical typology to characterize different types of connections in the human brain, which is critical for organizing the matrices and the prospective database. Although substantial in detail, the present matrices may be assumed to be only partially complete because the sources of data relating to human fiber system organization are limited largely to inferences from gross dissections of anatomic specimens or extrapolations of pathway tracing information from nonhuman primate experiments [Front Neuroanat. 2020;14:18, Front Neuroanat. 2022;16:1035420, and Brain Imaging Behav. 2021;15(3):1589-1621]. These matrices, which embody a systematic description of cerebral connectivity, can be used in cognitive and clinical studies in neuroscience and, importantly, to guide research efforts for further elucidating, validating, and completing the human BCD [Front Neuroanat. 2020;14:18].
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Affiliation(s)
- Nikos Makris
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Richard Rushmore
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Jonathan Kaiser
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Matthew Albaugh
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Marek Kubicki
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA
| | - Yogesh Rathi
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Lauren J. O’Donnell
- Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Edward Yeterian
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychology, Colby College, Waterville, ME, USA
| | - Verne S. Caviness
- Center for Morphometric Analysis, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - David N. Kennedy
- Department of Psychiatry, University of Massachusetts Chan Medical School, Worcester, MA, USA
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Rushmore RJ, Bouix S, Kubicki M, Rathi Y, Yeterian E, Makris N. HOA2.0-ComPaRe: A next generation Harvard-Oxford Atlas comparative parcellation reasoning method for human and macaque individual brain parcellation and atlases of the cerebral cortex. Front Neuroanat 2022; 16:1035420. [PMID: 36439195 PMCID: PMC9684647 DOI: 10.3389/fnana.2022.1035420] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/06/2022] [Indexed: 11/29/2023] Open
Abstract
Comparative structural neuroanatomy is a cornerstone for understanding human brain structure and function. A parcellation framework that relates systematically to fundamental principles of histological organization is an essential step in generating structural comparisons between species. In the present investigation, we developed a comparative parcellation reasoning system (ComPaRe), which is a formal ontological system in human and non-human primate brains based on the cortical cytoarchitectonic mapping used for both species as detailed by Brodmann. ComPaRe provides a theoretical foundation for mapping neural systems in humans and other species using neuroimaging. Based on this approach, we revised the methodology of the original Harvard-Oxford Atlas (HOA) system of brain parcellation to produce a comparative framework for the human (hHOA) and the rhesus monkey (mHOA) brains, which we refer to as HOA2.0-ComPaRe. In addition, we used dedicated segmentation software in the publicly available 3D Slicer platform to parcellate an individual human and rhesus monkey brain. This method produces quantitative morphometric parcellations in the individual brains. Based on these parcellations we created a representative template and 3D brain atlas for the two species, each based on a single subject. Thus, HOA2.0-ComPaRe provides a theoretical foundation for mapping neural systems in humans and other species using neuroimaging, while also representing a significant revision of the original human and macaque monkey HOA parcellation schemas. The methodology and atlases presented here can be used in basic and clinical neuroimaging for morphometric (volumetric) analysis, further generation of atlases, as well as localization of function and structural lesions.
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Affiliation(s)
- Richard Jarrett Rushmore
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Software Engineering and Information Technology, École de Technologie Supérieure, Montreal, QC, Canada
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
| | - Edward Yeterian
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
- Department of Psychology, Colby College, Waterville, ME, United States
| | - Nikos Makris
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
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Rushmore RJ, Sunderland K, Carrington H, Chen J, Halle M, Lasso A, Papadimitriou G, Prunier N, Rizzoni E, Vessey B, Wilson-Braun P, Rathi Y, Kubicki M, Bouix S, Yeterian E, Makris N. Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach. Front Neuroanat 2022; 16:894606. [PMID: 36249866 PMCID: PMC9562126 DOI: 10.3389/fnana.2022.894606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 07/15/2022] [Indexed: 11/27/2022] Open
Abstract
Magnetic resonance imaging (MRI)-based brain segmentation has recently been revolutionized by deep learning methods. These methods use large numbers of annotated segmentations to train algorithms that have the potential to perform brain segmentations reliably and quickly. However, training data for these algorithms are frequently obtained from automated brain segmentation systems, which may contain inaccurate neuroanatomy. Thus, the neuroimaging community would benefit from an open source database of high quality, neuroanatomically curated and manually edited MRI brain images, as well as the publicly available tools and detailed procedures for generating these curated data. Manual segmentation approaches are regarded as the gold standard for brain segmentation and parcellation. These approaches underpin the construction of neuroanatomically accurate human brain atlases. In addition, neuroanatomically precise definitions of MRI-based regions of interest (ROIs) derived from manual brain segmentation are essential for accuracy in structural connectivity studies and in surgical planning for procedures such as deep brain stimulation. However, manual segmentation procedures are time and labor intensive, and not practical in studies utilizing very large datasets, large cohorts, or multimodal imaging. Automated segmentation methods were developed to overcome these issues, and provide high data throughput, increased reliability, and multimodal imaging capability. These methods utilize manually labeled brain atlases to automatically parcellate the brain into different ROIs, but do not have the anatomical accuracy of skilled manual segmentation approaches. In the present study, we developed a custom software module for manual editing of brain structures in the freely available 3D Slicer software platform that employs principles and tools based on pioneering work from the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. We used these novel 3D Slicer segmentation tools and techniques in conjunction with well-established neuroanatomical definitions of subcortical brain structures to manually segment 50 high resolution T1w MRI brains from the Human Connectome Project (HCP) Young Adult database. The structural definitions used herein are associated with specific neuroanatomical ontologies to systematically interrelate histological and MRI-based morphometric definitions. The resulting brain datasets are publicly available and will provide the basis for a larger database of anatomically curated brains as an open science resource.
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Affiliation(s)
- R. Jarrett Rushmore
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Kyle Sunderland
- School of Computing, Queen’s University, Kingston, ON, Canada
| | - Holly Carrington
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Justine Chen
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Michael Halle
- Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Andras Lasso
- School of Computing, Queen’s University, Kingston, ON, Canada
| | - G. Papadimitriou
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - N. Prunier
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Elizabeth Rizzoni
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Brynn Vessey
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Peter Wilson-Braun
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Yogesh Rathi
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Marek Kubicki
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Edward Yeterian
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Department of Psychology, Colby College, Waterville, ME, United States
| | - Nikos Makris
- Department of Psychiatry, Department of Neurology, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
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9
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Pujol S, Cabeen RP, Yelnik J, François C, Fernandez Vidal S, Karachi C, Bardinet E, Cosgrove GR, Kikinis R. Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain. Front Neurol 2022; 13:791092. [PMID: 35547388 PMCID: PMC9081715 DOI: 10.3389/fneur.2022.791092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 03/04/2022] [Indexed: 11/25/2022] Open
Abstract
Background The subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients. Objective This study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1). Methods We used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles. Results We successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta. Conclusion Multi-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.
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Affiliation(s)
- Sonia Pujol
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of the USC, University of Southern California, Los Angeles, CA, United States
| | - Jérôme Yelnik
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Chantal François
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Sara Fernandez Vidal
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Carine Karachi
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France.,Department of Neurosurgery, APHP, Hôpitaux Universitaires Pitié-Salpêtriére/Charles Foix, Paris, France
| | - Eric Bardinet
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Ron Kikinis
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
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10
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11
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Rushmore RJ, Bouix S, Kubicki M, Rathi Y, Rosene DL, Yeterian EH, Makris N. MRI-based Parcellation and Morphometry of the Individual Rhesus Monkey Brain: the macaque Harvard-Oxford Atlas (mHOA), a translational system referencing a standardized ontology. Brain Imaging Behav 2021; 15:1589-1621. [PMID: 32960419 PMCID: PMC8608281 DOI: 10.1007/s11682-020-00357-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Investigations of the rhesus monkey (Macaca mulatta) brain have shed light on the function and organization of the primate brain at a scale and resolution not yet possible in humans. A cornerstone of the linkage between non-human primate and human studies of the brain is magnetic resonance imaging, which allows for an association to be made between the detailed structural and physiological analysis of the non-human primate and that of the human brain. To further this end, we present a novel parcellation method and system for the rhesus monkey brain, referred to as the macaque Harvard-Oxford Atlas (mHOA), which is based on the human Harvard-Oxford Atlas (HOA) and grounded in an ontological and taxonomic framework. Consistent anatomical features were used to delimit and parcellate brain regions in the macaque, which were then categorized according to functional systems. This system of parcellation will be expanded with advances in technology and, like the HOA, will provide a framework upon which the results from other experimental studies (e.g., functional magnetic resonance imaging (fMRI), physiology, connectivity, graph theory) can be interpreted.
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Affiliation(s)
- R Jarrett Rushmore
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Douglas L Rosene
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Edward H Yeterian
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
- Department of Psychology, Colby College, Waterville, ME, USA
| | - Nikos Makris
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA.
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Pre-Brodmann pioneers of cortical cytoarchitectonics II: Carl Hammarberg, Alfred Walter Campbell and Grafton Elliot Smith. Brain Struct Funct 2020; 225:2591-2614. [PMID: 33141293 DOI: 10.1007/s00429-020-02166-8] [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: 07/25/2020] [Accepted: 10/17/2020] [Indexed: 10/23/2022]
Abstract
The present study and the preceding paper revisit landmark discoveries that paved the way to the definition of the renowned Brodmann areas in the human cerebral cortex, in an attempt to rectify certain undeserved historical neglects. A 'second period of discoveries', from 1893 to 1908, is marked by the work of Carl Hammarberg (1865-1893) in Uppsala, Alfred Walter Campbell (1868-1937) in Liverpool and Grafton Elliot Smith (1871-1937) in Cairo. Their classical findings are placed in a modern perspective.
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13
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Takemura H, Thiebaut de Schotten M. Perspectives given by structural connectivity bridge the gap between structure and function. Brain Struct Funct 2020; 225:1189-1192. [PMID: 32415413 PMCID: PMC7270985 DOI: 10.1007/s00429-020-02080-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita-shi, Japan. .,Graduate School of Frontier Biosciences, Osaka University, Suita-shi, Japan.
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.,Groupe D'Imagerie Neurofonctionnelle, Institut Des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
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14
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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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