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Chitsaz D, Rowley CD, Uccelli NA, Lefebvre S, Krahn AI, Reintsch WE, Durcan TM, Tardif CL, Kennedy TE. Multiplex Immunofluorescent Batch Labeling of Marmoset Brain Sections. Brain Behav 2025; 15:e70308. [PMID: 40181645 PMCID: PMC11968781 DOI: 10.1002/brb3.70308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 11/29/2024] [Accepted: 01/12/2025] [Indexed: 04/05/2025] Open
Abstract
PURPOSE The common marmoset is a small nonhuman primate that has emerged as a valuable animal model in neuroscience research. Accurate analysis of brain tissue is crucial to understand marmoset neurophysiology and to model neurodegenerative diseases. Many studies to date have complemented magnetic resonance imaging (MRI) with histochemical staining rather than immunofluorescent labeling, which can generate more informative and higher resolution images. There is a need for high-throughput immunolabeling and imaging methodologies to generate resources for the burgeoning marmoset field, particularly brain histology atlases to display the organization of different cell types and other structures. METHODS AND FINDINGS Here, we have characterized a set of marmoset-compatible fluorescent dyes and antibodies that label myelin, axons, dendrites, and the iron-storage protein ferritin, and developed a batch-style multiplex immunohistochemistry protocol to uniformly process large numbers of tissue slides for multiple cell-type specific markers. CONCLUSION We provide a practical guide for researchers interested in harnessing the potential of marmoset models to advance understanding of brain structure, function, and pathophysiology.
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Affiliation(s)
- Daryan Chitsaz
- Integrated Program in NeuroscienceMcGill UniversityMontréalQuebecCanada
- Department of Neurology & Neurosurgery, Montreal Neurological Institute‐HospitalMcGill UniversityMontréalQuebecCanada
| | | | - Nonthué A. Uccelli
- Department of Neurology & Neurosurgery, Montreal Neurological Institute‐HospitalMcGill UniversityMontréalQuebecCanada
| | - Sarah Lefebvre
- Cognitive Neuroscience Unit, Montreal Neurological Institute‐HospitalMcGill UniversityMontrealQuebecCanada
| | - Andrea I. Krahn
- The Neuro's Early Drug Discovery Unit (EDDU)McGill UniversityMontrealQuebecCanada
| | - Wolfgang E. Reintsch
- The Neuro's Early Drug Discovery Unit (EDDU)McGill UniversityMontrealQuebecCanada
| | - Thomas M. Durcan
- Integrated Program in NeuroscienceMcGill UniversityMontréalQuebecCanada
- Department of Neurology & Neurosurgery, Montreal Neurological Institute‐HospitalMcGill UniversityMontréalQuebecCanada
- The Neuro's Early Drug Discovery Unit (EDDU)McGill UniversityMontrealQuebecCanada
| | - Christine L. Tardif
- Integrated Program in NeuroscienceMcGill UniversityMontréalQuebecCanada
- Department of Neurology & Neurosurgery, Montreal Neurological Institute‐HospitalMcGill UniversityMontréalQuebecCanada
- Department of Biomedical Engineering, Faculty of Medicine and Health SciencesMcGill UniversityMontréalQuebecCanada
| | - Timothy E. Kennedy
- Integrated Program in NeuroscienceMcGill UniversityMontréalQuebecCanada
- Department of Neurology & Neurosurgery, Montreal Neurological Institute‐HospitalMcGill UniversityMontréalQuebecCanada
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2
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Teymornejad S, Majka P, Worthy KH, Atapour N, Rosa MGP. Bilateral connections from the amygdala to extrastriate visual cortex in the marmoset monkey. Cereb Cortex 2024; 34:bhae348. [PMID: 39227312 DOI: 10.1093/cercor/bhae348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/30/2024] [Accepted: 08/09/2024] [Indexed: 09/05/2024] Open
Abstract
It is known that the primate amygdala forms projections to many areas of the ipsilateral cortex, but the extent to which it forms connections with the contralateral visual cortex remains less understood. Based on retrograde tracer injections in marmoset monkeys, we report that the amygdala forms widespread projections to the ipsilateral extrastriate cortex, including V1 and areas in both the dorsal (MT, V4T, V3a, 19M, and PG/PFG) and the ventral (VLP and TEO) streams. In addition, contralateral projections were found to target each of the extrastriate areas, but not V1. In both hemispheres, the tracer-labeled neurons were exclusively located in the basolateral nuclear complex. The number of labeled neurons in the contralateral amygdala was small relative to the ipsilateral connection (1.2% to 5.8%). The percentage of contralateral connections increased progressively with hierarchical level. An injection in the corpus callosum demonstrated that at least some of the amygdalo-cortical connections cross through this fiber tract, in addition to the previously documented path through the anterior commissure. Our results expand knowledge of the amygdalofugal projections to the extrastriate cortex, while also revealing pathways through which visual stimuli conveying affective content can directly influence early stages of neural processing in the contralateral visual field.
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Affiliation(s)
- Sadaf Teymornejad
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC 3800, Australia
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 3 Pasteur Street, 02-093 Warsaw, Poland
| | - Katrina H Worthy
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC 3800, Australia
| | - Nafiseh Atapour
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC 3800, Australia
| | - Marcello G P Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC 3800, Australia
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3
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Atapour N, Rosa MGP, Bai S, Bednarek S, Kulesza A, Saworska G, Teymornejad S, Worthy KH, Majka P. Distribution of calbindin-positive neurons across areas and layers of the marmoset cerebral cortex. PLoS Comput Biol 2024; 20:e1012428. [PMID: 39312590 PMCID: PMC11495585 DOI: 10.1371/journal.pcbi.1012428] [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: 03/26/2024] [Revised: 10/22/2024] [Accepted: 08/16/2024] [Indexed: 09/25/2024] Open
Abstract
The diversity of the mammalian cerebral cortex demands technical approaches to map the spatial distribution of neurons with different biochemical identities. This issue is magnified in the case of the primate cortex, characterized by a large number of areas with distinctive cytoarchitectures. To date, no full map of the distribution of cells expressing a specific protein has been reported for the cortex of any primate. Here we have charted the 3-dimensional distribution of neurons expressing the calcium-binding protein calbindin (CB+ neurons) across the entire marmoset cortex, using a combination of immunohistochemistry, automated cell identification, computerized reconstruction, and cytoarchitecture-aware registration. CB+ neurons formed a heterogeneous population, which together corresponded to 10-20% of the cortical neurons. They occurred in higher proportions in areas corresponding to low hierarchical levels of processing, such as sensory cortices. Although CB+ neurons were concentrated in the supragranular and granular layers, there were clear global trends in their laminar distribution. For example, their relative density in infragranular layers increased with hierarchical level along sensorimotor processing streams, and their density in layer 4 was lower in areas involved in sensorimotor integration, action planning and motor control. These results reveal new quantitative aspects of the cytoarchitectural organization of the primate cortex, and demonstrate an approach to mapping the full distribution of neurochemically distinct cells throughout the brain which is readily applicable to most other mammalian species.
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Affiliation(s)
- Nafiseh Atapour
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia
| | - Marcello G. P. Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia
| | - Shi Bai
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia
| | - Sylwia Bednarek
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Agata Kulesza
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Gabriela Saworska
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Sadaf Teymornejad
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia
| | - Katrina H. Worthy
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
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Liu Z, Li A, Gong H, Yang X, Luo Q, Feng Z, Li X. The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex. Cereb Cortex 2024; 34:bhae229. [PMID: 38836835 DOI: 10.1093/cercor/bhae229] [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: 03/19/2024] [Revised: 05/13/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024] Open
Abstract
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.
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Affiliation(s)
- Zhixiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiaoquan Yang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
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5
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Kurz A, Müller H, Kather JN, Schneider L, Bucher TC, Brinker TJ. 3-Dimensional Reconstruction From Histopathological Sections: A Systematic Review. J Transl Med 2024; 104:102049. [PMID: 38513977 DOI: 10.1016/j.labinv.2024.102049] [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: 08/17/2023] [Revised: 02/18/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024] Open
Abstract
Although pathological tissue analysis is typically performed on single 2-dimensional (2D) histologic reference slides, 3-dimensional (3D) reconstruction from a sequence of histologic sections could provide novel opportunities for spatial analysis of the extracted tissue. In this review, we analyze recent works published after 2018 and report information on the extracted tissue types, the section thickness, and the number of sections used for reconstruction. By analyzing the technological requirements for 3D reconstruction, we observe that software tools exist, both free and commercial, which include the functionality to perform 3D reconstruction from a sequence of histologic images. Through the analysis of the most recent works, we provide an overview of the workflows and tools that are currently used for 3D reconstruction from histologic sections and address points for future work, such as a missing common file format or computer-aided analysis of the reconstructed model.
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Affiliation(s)
- Alexander Kurz
- Digital Biomarkers for Oncology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heimo Müller
- Diagnostics and Research Institute for Pathology, Medical University of Graz, Graz, Austria
| | - Jakob N Kather
- Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Lucas Schneider
- Digital Biomarkers for Oncology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tabea C Bucher
- Digital Biomarkers for Oncology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Titus J Brinker
- Digital Biomarkers for Oncology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Liu Z, Feng Z, Liu G, Li A, Gong H, Yang X, Li X. A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale. Front Neuroanat 2024; 18:1388084. [PMID: 38846539 PMCID: PMC11153794 DOI: 10.3389/fnana.2024.1388084] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/26/2024] [Indexed: 06/09/2024] Open
Abstract
Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.
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Affiliation(s)
- Zhixiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Guangcai Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Xiaoquan Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
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7
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Song X, Guo Y, Chen C, Lee JH, Wang X. Tonotopic organization of auditory cortex in awake marmosets revealed by multi-modal wide-field optical imaging. CURRENT RESEARCH IN NEUROBIOLOGY 2024; 6:100132. [PMID: 38799765 PMCID: PMC11127206 DOI: 10.1016/j.crneur.2024.100132] [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: 08/27/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024] Open
Abstract
Tonotopic organization of the auditory cortex has been extensively studied in many mammalian species using various methodologies and physiological preparations. Tonotopy mapping in primates, however, is more limited due to constraints such as cortical folding, use of anesthetized subjects, and mapping methodology. Here we applied a combination of through-skull and through-window intrinsic optical signal imaging, wide-field calcium imaging, and neural probe recording techniques in awake marmosets (Callithrix jacchus), a New World monkey with most of its auditory cortex located on a flat brain surface. Coarse tonotopic gradients, including a recently described rostral-temporal (RT) to parabelt gradient, were revealed by the through-skull imaging of intrinsic optical signals and were subsequently validated by single-unit recording. Furthermore, these tonotopic gradients were observed with more detail through chronically implanted cranial windows with additional verifications on the experimental design. Moreover, the tonotopy mapped by the intrinsic-signal imaging methods was verified by wide-field calcium imaging in an AAV-GCaMP labeled subject. After these validations and with further effort to expand the field of view more rostrally in both windowed and through-skull subjects, an additional putative tonotopic gradient was observed more rostrally to the area RT, which has not been previously described by the standard model of tonotopic organization of the primate auditory cortex. Together, these results provide the most comprehensive data of tonotopy mapping in an awake primate species with unprecedented coverage and details in the rostral proportion and support a caudal-rostrally arranged mesoscale organization of at least three repeats of functional gradients in the primate auditory cortex, similar to the ventral stream of primate visual cortex.
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Affiliation(s)
- Xindong Song
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Institute of Automation, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, China
| | - Yueqi Guo
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chenggang Chen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jong Hoon Lee
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Biological Sciences, KAIST, Daejeon, 34141, South Korea
| | - Xiaoqin Wang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
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Saleem KS, Avram AV, Glen D, Schram V, Basser PJ. The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology. Cereb Cortex 2024; 34:bhae120. [PMID: 38647221 PMCID: PMC11494440 DOI: 10.1093/cercor/bhae120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/07/2024] [Accepted: 03/07/2024] [Indexed: 04/25/2024] Open
Abstract
A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.
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Affiliation(s)
- Kadharbatcha S Saleem
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Health (NIH), 13, South Drive, Bethesda, MD 20892, United States
- Military Traumatic Brain Injury Initiative (MTBI2), Henry M. Jackson Foundation for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD 20817, United States
| | - Alexandru V Avram
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Health (NIH), 13, South Drive, Bethesda, MD 20892, United States
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health (NIMH), NIH, 10 Center Drive, Bethesda, MD 20817, United States
| | - Vincent Schram
- Microscopy and Imaging Core (MIC), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, 35 Convent Drive, Bethesda, MD 20892, United States
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Health (NIH), 13, South Drive, Bethesda, MD 20892, United States
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9
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Zhang Y, Shen SX, Bibic A, Wang X. Evolutionary continuity and divergence of auditory dorsal and ventral pathways in primates revealed by ultra-high field diffusion MRI. Proc Natl Acad Sci U S A 2024; 121:e2313831121. [PMID: 38377216 PMCID: PMC10907247 DOI: 10.1073/pnas.2313831121] [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: 08/10/2023] [Accepted: 01/22/2024] [Indexed: 02/22/2024] Open
Abstract
Auditory dorsal and ventral pathways in the human brain play important roles in supporting speech and language processing. However, the evolutionary root of the dual auditory pathways in the primate brain is unclear. By parcellating the auditory cortex of marmosets (a New World monkey species), macaques (an Old World monkey species), and humans using the same individual-based analysis method and tracking the pathways from the auditory cortex based on multi-shell diffusion-weighted MRI (dMRI), homologous auditory dorsal and ventral fiber tracks were identified in these primate species. The ventral pathway was found to be well conserved in all three primate species analyzed but extend to more anterior temporal regions in humans. In contrast, the dorsal pathway showed a divergence between monkey and human brains. First, frontal regions in the human brain have stronger connections to the higher-level auditory regions than to the lower-level auditory regions along the dorsal pathway, while frontal regions in the monkey brain show opposite connection patterns along the dorsal pathway. Second, the left lateralization of the dorsal pathway is only found in humans. Moreover, the connectivity strength of the dorsal pathway in marmosets is more similar to that of humans than macaques. These results demonstrate the continuity and divergence of the dual auditory pathways in the primate brains along the evolutionary path, suggesting that the putative neural networks supporting human speech and language processing might have emerged early in primate evolution.
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Affiliation(s)
- Yang Zhang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
| | - Sherry Xinyi Shen
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
| | - Adnan Bibic
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD21205
- Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, F. M. Kirby Center, Baltimore, MD21205
| | - Xiaoqin Wang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD21205
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10
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Saleem KS, Avram AV, Glen D, Schram V, Basser PJ. The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.06.574429. [PMID: 38260391 PMCID: PMC10802408 DOI: 10.1101/2024.01.06.574429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications for anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g., thalamic subregions, etc.) derived from the high-resolution MAP-MRI, T2W, and MTR images ex vivo. We then confirmed the location and borders of these segmented regions in MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within AFNI. Tracing and validating these important deep brain structures in 3D improves neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, fMRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.
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Affiliation(s)
- Kadharbatcha S Saleem
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892
- Military Traumatic Brain Injury Initiative (MTBI), Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817
| | - Alexandru V Avram
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health (NIMH)
| | - Vincent Schram
- Microscopy and Imaging Core (MIC), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892
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11
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Skibbe H, Rachmadi MF, Nakae K, Gutierrez CE, Hata J, Tsukada H, Poon C, Schlachter M, Doya K, Majka P, Rosa MGP, Okano H, Yamamori T, Ishii S, Reisert M, Watakabe A. The Brain/MINDS Marmoset Connectivity Resource: An open-access platform for cellular-level tracing and tractography in the primate brain. PLoS Biol 2023; 21:e3002158. [PMID: 37384809 DOI: 10.1371/journal.pbio.3002158] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/11/2023] [Indexed: 07/01/2023] Open
Abstract
The primate brain has unique anatomical characteristics, which translate into advanced cognitive, sensory, and motor abilities. Thus, it is important that we gain insight on its structure to provide a solid basis for models that will clarify function. Here, we report on the implementation and features of the Brain/MINDS Marmoset Connectivity Resource (BMCR), a new open-access platform that provides access to high-resolution anterograde neuronal tracer data in the marmoset brain, integrated to retrograde tracer and tractography data. Unlike other existing image explorers, the BMCR allows visualization of data from different individuals and modalities in a common reference space. This feature, allied to an unprecedented high resolution, enables analyses of features such as reciprocity, directionality, and spatial segregation of connections. The present release of the BMCR focuses on the prefrontal cortex (PFC), a uniquely developed region of the primate brain that is linked to advanced cognition, including the results of 52 anterograde and 164 retrograde tracer injections in the cortex of the marmoset. Moreover, the inclusion of tractography data from diffusion MRI allows systematic analyses of this noninvasive modality against gold-standard cellular connectivity data, enabling detection of false positives and negatives, which provide a basis for future development of tractography. This paper introduces the BMCR image preprocessing pipeline and resources, which include new tools for exploring and reviewing the data.
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Affiliation(s)
- Henrik Skibbe
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | | | - Ken Nakae
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Aichi, Japan
| | - Carlos Enrique Gutierrez
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Hiromichi Tsukada
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
- Center for Mathematical Science and Artificial Intelligence, Chubu University, Kasugai, Aichi, Japan
| | - Charissa Poon
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Matthias Schlachter
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Kenji Doya
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Tetsuo Yamamori
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Shin Ishii
- Department of Systems Science, Kyoto University, Kyoto, Japan
| | - Marco Reisert
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Stereotactic and Functional Neurosurgery, Medical Center of the University of Freiburg, Freiburg Im Breisgau, Germany
- Medical Faculty of the University of Freiburg, Freiburg Im Breisgau, Germany
- Department of Diagnostic and Interventional Radiology, Medical Physics, Medical Center-University of Freiburg, Freiburg Im Breisgau, Germany
| | - Akiya Watakabe
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
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12
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Ma G, Worthy KH, Liu C, Rosa MG, Atapour N. Parvalbumin as a neurochemical marker of the primate optic radiation. iScience 2023; 26:106608. [PMID: 37168578 PMCID: PMC10165026 DOI: 10.1016/j.isci.2023.106608] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/20/2023] [Accepted: 03/20/2023] [Indexed: 05/13/2023] Open
Abstract
Parvalbumin (PV) is a calcium-binding protein that labels neuronal cell bodies in the magno and parvocellular layers of the primate lateral geniculate nucleus (LGN). Here we demonstrate that PV immunohistochemistry can also be used to trace the optic radiation (OR) of the marmoset monkey (Callithrix jacchus) from its LGN origin to its destinations in the primary visual cortex (V1), thus providing a high-resolution method for identification of the OR with single axon resolution. The emergence of fibers from LGN, their entire course and even the entry points to V1 were clearly defined in coronal, parasagittal, and horizontal sections of marmoset brain. In all cases, the trajectory revealed by PV staining paralleled that defined by high-resolution diffusion tensor imaging (DTI). We found that V1 was the exclusive target for the PV-containing fibers, with abrupt transitions in staining observed in the white matter at the border with area V2, and no evidence of PV-labeled axons feeding into other visual areas. Changes in the pattern of PV staining in the OR were detected following V1 lesions, demonstrating that this method can be used to assess the progress of retrograde degeneration of geniculocortical projections. These results suggest a technically simple approach to advance our understanding of a major white matter structure, which provides a cellular resolution suitable for the detection of microstructural variations during development, health and disease. Understanding the relationship between PV staining and DTI in non-human primates may also offer clues for improving the specificity and sensitivity of OR tractography for clinical purposes.
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Affiliation(s)
- Gaoyuan Ma
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Katrina H. Worthy
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Cirong Liu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Marcello G.P. Rosa
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Nafiseh Atapour
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
- Corresponding author
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13
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Ngo GN, Hori Y, Everling S, Menon RS. Joint-embeddings reveal functional differences in default-mode network architecture between marmosets and humans. Neuroimage 2023; 272:120035. [PMID: 36948281 DOI: 10.1016/j.neuroimage.2023.120035] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/30/2022] [Accepted: 03/14/2023] [Indexed: 03/24/2023] Open
Abstract
The default-mode network (DMN) is a distributed functional brain system integral for social and higher-order cognition in humans with implications in a myriad of neuropsychological disorders. In this study, we compared the functional architecture of the DMN between humans and marmosets to assess their similarities and differences using joint gradients. This approach permits simultaneous large-scale mapping of functional systems across the cortex of humans and marmosets, revealing evidence of putative homologies between them. In doing so, we find that the DMN architecture of the marmoset exhibits differences along its anterolateral-posterior axis. Specifically, the anterolateral node of the DMN (dorsolateral prefrontal cortex) displayed weak connections and inconsistent connection topographies as compared to its posterior DMN-nodes (posterior cingulate and posterior parietal cortices). We also present evidence that the marmoset medial prefrontal cortex and temporal lobe areas correspond to other macroscopical distributed functional systems that are not part of the DMN. Given the importance of the marmoset as a pre-clinical primate model for higher-order cognitive functioning and the DMN's relevance to cognition, our results suggest that the marmoset may lack the capacity to integrate neural information to subserve cortical dynamics that is necessary for supporting diverse cognitive demands.
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Affiliation(s)
- Geoffrey N Ngo
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Functional Brain Imaging, National Institutes of Quantum and Radiological Science and Technology, Chiba 263-8555, Japan
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Ravi S Menon
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada.; Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada.
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14
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Tian X, Chen Y, Majka P, Szczupak D, Perl YS, Yen CCC, Tong C, Feng F, Jiang H, Glen D, Deco G, Rosa MGP, Silva AC, Liang Z, Liu C. An integrated resource for functional and structural connectivity of the marmoset brain. Nat Commun 2022; 13:7416. [PMID: 36456558 PMCID: PMC9715556 DOI: 10.1038/s41467-022-35197-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 11/21/2022] [Indexed: 12/02/2022] Open
Abstract
Comprehensive integration of structural and functional connectivity data is required to model brain functions accurately. While resources for studying the structural connectivity of non-human primate brains already exist, their integration with functional connectivity data has remained unavailable. Here we present a comprehensive resource that integrates the most extensive awake marmoset resting-state fMRI data available to date (39 marmoset monkeys, 710 runs, 12117 mins) with previously published cellular-level neuronal tracing data (52 marmoset monkeys, 143 injections) and multi-resolution diffusion MRI datasets. The combination of these data allowed us to (1) map the fine-detailed functional brain networks and cortical parcellations, (2) develop a deep-learning-based parcellation generator that preserves the topographical organization of functional connectivity and reflects individual variabilities, and (3) investigate the structural basis underlying functional connectivity by computational modeling. This resource will enable modeling structure-function relationships and facilitate future comparative and translational studies of primate brains.
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Affiliation(s)
- Xiaoguang Tian
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Yuyan Chen
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Piotr Majka
- grid.419305.a0000 0001 1943 2944Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland ,grid.1002.30000 0004 1936 7857Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800 Australia
| | - Diego Szczupak
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Yonatan Sanz Perl
- grid.5612.00000 0001 2172 2676Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018 Spain ,grid.441741.30000 0001 2325 2241Universidad de San Andrés, Vito Dumas 284 (B1644BID), Buenos Aires, Argentina
| | - Cecil Chern-Chyi Yen
- grid.94365.3d0000 0001 2297 5165Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD 20892 USA
| | - Chuanjun Tong
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Furui Feng
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Haiteng Jiang
- grid.13402.340000 0004 1759 700XDepartment of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Zhe Jiang Sheng, China ,grid.13402.340000 0004 1759 700XMOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Daniel Glen
- grid.94365.3d0000 0001 2297 5165Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH), Bethesda, MD 20892 USA
| | - Gustavo Deco
- grid.5612.00000 0001 2172 2676Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018 Spain ,grid.425902.80000 0000 9601 989XInstitució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010 Spain ,grid.419524.f0000 0001 0041 5028Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103 Germany ,grid.1002.30000 0004 1936 7857School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC 3800 Australia
| | - Marcello G. P. Rosa
- grid.1002.30000 0004 1936 7857Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800 Australia
| | - Afonso C. Silva
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Zhifeng Liang
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China ,grid.511008.dShanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai, Shanghai, China
| | - Cirong Liu
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China ,grid.511008.dShanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai, Shanghai, China ,Lingang Laboratory, Shanghai, 200031 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, China
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15
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Quah SKL, McIver L, Bullmore ET, Roberts AC, Sawiak SJ. Higher-order brain regions show shifts in structural covariance in adolescent marmosets. Cereb Cortex 2022; 32:4128-4140. [PMID: 35029670 PMCID: PMC9476623 DOI: 10.1093/cercor/bhab470] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/18/2021] [Accepted: 11/19/2021] [Indexed: 11/13/2022] Open
Abstract
Substantial progress has been made studying morphological changes in brain regions during adolescence, but less is known of network-level changes in their relationship. Here, we compare covariance networks constructed from the correlation of morphometric volumes across 135 brain regions of marmoset monkeys in early adolescence and adulthood. Substantial shifts are identified in the topology of structural covariance networks in the prefrontal cortex (PFC) and temporal lobe. PFC regions become more structurally differentiated and segregated within their own local network, hypothesized to reflect increased specialization after maturation. In contrast, temporal regions show increased inter-hemispheric covariances that may underlie the establishment of distributed networks. Regionally selective coupling of structural and maturational covariance is revealed, with relatively weak coupling in transmodal association areas. The latter may be a consequence of continued maturation within adulthood, but also environmental factors, for example, family size, affecting brain morphology. Advancing our understanding of how morphological relationships within higher-order brain areas mature in adolescence deepens our knowledge of the developing brain's organizing principles.
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Affiliation(s)
- Shaun K L Quah
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EB, UK
| | - Lauren McIver
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EB, UK
| | - Edward T Bullmore
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge CB21 5EF, UK
| | - Angela C Roberts
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EB, UK
| | - Stephen J Sawiak
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EB, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Translational Neuroimaging Laboratory, University of Cambridge, Cambridge, CB2 3EB, UK
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16
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Song X, Guo Y, Li H, Chen C, Lee JH, Zhang Y, Schmidt Z, Wang X. Mesoscopic landscape of cortical functions revealed by through-skull wide-field optical imaging in marmoset monkeys. Nat Commun 2022; 13:2238. [PMID: 35474064 PMCID: PMC9042927 DOI: 10.1038/s41467-022-29864-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 04/04/2022] [Indexed: 12/15/2022] Open
Abstract
The primate cerebral cortex is organized into specialized areas representing different modalities and functions along a continuous surface. The functional maps across the cortex, however, are often investigated a single modality at a time (e.g., audition or vision). To advance our understanding of the complex landscape of primate cortical functions, here we develop a polarization-gated wide-field optical imaging method for measuring cortical functions through the un-thinned intact skull in awake marmoset monkeys (Callithrix jacchus), a primate species featuring a smooth cortex. Using this method, adjacent auditory, visual, and somatosensory cortices are noninvasively parcellated in individual subjects with detailed tonotopy, retinotopy, and somatotopy. An additional pure-tone-responsive tonotopic gradient is discovered in auditory cortex and a face-patch sensitive to motion in the lower-center visual field is localized near an auditory region representing frequencies of conspecific vocalizations. This through-skull landscape-mapping approach provides new opportunities for understanding how the primate cortex is organized and coordinated to enable real-world behaviors.
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Affiliation(s)
- Xindong Song
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Yueqi Guo
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Hongbo Li
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Chenggang Chen
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Jong Hoon Lee
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Yang Zhang
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Zachary Schmidt
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Xiaoqin Wang
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
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17
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Ose T, Autio JA, Ohno M, Frey S, Uematsu A, Kawasaki A, Takeda C, Hori Y, Nishigori K, Nakako T, Yokoyama C, Nagata H, Yamamori T, Van Essen DC, Glasser MF, Watabe H, Hayashi T. Anatomical variability, multi-modal coordinate systems, and precision targeting in the marmoset brain. Neuroimage 2022; 250:118965. [PMID: 35122965 PMCID: PMC8948178 DOI: 10.1016/j.neuroimage.2022.118965] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 01/02/2023] Open
Abstract
Localising accurate brain regions needs careful evaluation in each experimental species due to their individual variability. However, the function and connectivity of brain areas is commonly studied using a single-subject cranial landmark-based stereotactic atlas in animal neuroscience. Here, we address this issue in a small primate, the common marmoset, which is increasingly widely used in systems neuroscience. We developed a non-invasive multi-modal neuroimaging-based targeting pipeline, which accounts for intersubject anatomical variability in cranial and cortical landmarks in marmosets. This methodology allowed creation of multi-modal templates (MarmosetRIKEN20) including head CT and brain MR images, embedded in coordinate systems of anterior and posterior commissures (AC-PC) and CIFTI grayordinates. We found that the horizontal plane of the stereotactic coordinate was significantly rotated in pitch relative to the AC-PC coordinate system (10 degrees, frontal downwards), and had a significant bias and uncertainty due to positioning procedures. We also found that many common cranial and brain landmarks (e.g., bregma, intraparietal sulcus) vary in location across subjects and are substantial relative to average marmoset cortical area dimensions. Combining the neuroimaging-based targeting pipeline with robot-guided surgery enabled proof-of-concept targeting of deep brain structures with an accuracy of 0.2 mm. Altogether, our findings demonstrate substantial intersubject variability in marmoset brain and cranial landmarks, implying that subject-specific neuroimaging-based localization is needed for precision targeting in marmosets. The population-based templates and atlases in grayordinates, created for the first time in marmoset monkeys, should help bridging between macroscale and microscale analyses.
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Affiliation(s)
- Takayuki Ose
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Masahiro Ohno
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | | | - Akiko Uematsu
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Akihiro Kawasaki
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Chiho Takeda
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Yuki Hori
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Department of Functional Brain Imaging, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.
| | - Kantaro Nishigori
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Sumitomo Dainippon Pharma Co., Ltd., Osaka, Japan.
| | - Tomokazu Nakako
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Sumitomo Dainippon Pharma Co., Ltd., Osaka, Japan.
| | - Chihiro Yokoyama
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Faculty of Human life and Environmental Science, Nara women's University, Nara, Japan.
| | | | - Tetsuo Yamamori
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Japan.
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA.
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Radiology, Washington University Medical School, St Louis, MO USA.
| | - Hiroshi Watabe
- Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Department of Brain Connectomics, Kyoto University Graduate School of Medicine, Kyoto, Japan.
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18
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Milham M, Petkov C, Belin P, Ben Hamed S, Evrard H, Fair D, Fox A, Froudist-Walsh S, Hayashi T, Kastner S, Klink C, Majka P, Mars R, Messinger A, Poirier C, Schroeder C, Shmuel A, Silva AC, Vanduffel W, Van Essen DC, Wang Z, Roe AW, Wilke M, Xu T, Aarabi MH, Adolphs R, Ahuja A, Alvand A, Amiez C, Autio J, Azadi R, Baeg E, Bai R, Bao P, Basso M, Behel AK, Bennett Y, Bernhardt B, Biswal B, Boopathy S, Boretius S, Borra E, Boshra R, Buffalo E, Cao L, Cavanaugh J, Celine A, Chavez G, Chen LM, Chen X, Cheng L, Chouinard-Decorte F, Clavagnier S, Cléry J, Colcombe SJ, Conway B, Cordeau M, Coulon O, Cui Y, Dadarwal R, Dahnke R, Desrochers T, Deying L, Dougherty K, Doyle H, Drzewiecki CM, Duyck M, Arachchi WE, Elorette C, Essamlali A, Evans A, Fajardo A, Figueroa H, Franco A, Freches G, Frey S, Friedrich P, Fujimoto A, Fukunaga M, Gacoin M, Gallardo G, Gao L, Gao Y, Garside D, Garza-Villarreal EA, Gaudet-Trafit M, Gerbella M, Giavasis S, Glen D, Ribeiro Gomes AR, Torrecilla SG, Gozzi A, Gulli R, Haber S, Hadj-Bouziane F, Fujimoto SH, Hawrylycz M, He Q, He Y, Heuer K, et alMilham M, Petkov C, Belin P, Ben Hamed S, Evrard H, Fair D, Fox A, Froudist-Walsh S, Hayashi T, Kastner S, Klink C, Majka P, Mars R, Messinger A, Poirier C, Schroeder C, Shmuel A, Silva AC, Vanduffel W, Van Essen DC, Wang Z, Roe AW, Wilke M, Xu T, Aarabi MH, Adolphs R, Ahuja A, Alvand A, Amiez C, Autio J, Azadi R, Baeg E, Bai R, Bao P, Basso M, Behel AK, Bennett Y, Bernhardt B, Biswal B, Boopathy S, Boretius S, Borra E, Boshra R, Buffalo E, Cao L, Cavanaugh J, Celine A, Chavez G, Chen LM, Chen X, Cheng L, Chouinard-Decorte F, Clavagnier S, Cléry J, Colcombe SJ, Conway B, Cordeau M, Coulon O, Cui Y, Dadarwal R, Dahnke R, Desrochers T, Deying L, Dougherty K, Doyle H, Drzewiecki CM, Duyck M, Arachchi WE, Elorette C, Essamlali A, Evans A, Fajardo A, Figueroa H, Franco A, Freches G, Frey S, Friedrich P, Fujimoto A, Fukunaga M, Gacoin M, Gallardo G, Gao L, Gao Y, Garside D, Garza-Villarreal EA, Gaudet-Trafit M, Gerbella M, Giavasis S, Glen D, Ribeiro Gomes AR, Torrecilla SG, Gozzi A, Gulli R, Haber S, Hadj-Bouziane F, Fujimoto SH, Hawrylycz M, He Q, He Y, Heuer K, Hiba B, Hoffstaedter F, Hong SJ, Hori Y, Hou Y, Howard A, de la Iglesia-Vaya M, Ikeda T, Jankovic-Rapan L, Jaramillo J, Jedema HP, Jin H, Jiang M, Jung B, Kagan I, Kahn I, Kiar G, Kikuchi Y, Kilavik B, Kimura N, Klatzmann U, Kwok SC, Lai HY, Lamberton F, Lehman J, Li P, Li X, Li X, Liang Z, Liston C, Little R, Liu C, Liu N, Liu X, Liu X, Lu H, Loh KK, Madan C, Magrou L, Margulies D, Mathilda F, Mejia S, Meng Y, Menon R, Meunier D, Mitchell A, Mitchell A, Murphy A, Mvula T, Ortiz-Rios M, Ortuzar Martinez DE, Pagani M, Palomero-Gallagher N, Pareek V, Perkins P, Ponce F, Postans M, Pouget P, Qian M, Ramirez J“B, Raven E, Restrepo I, Rima S, Rockland K, Rodriguez NY, Roger E, Hortelano ER, Rosa M, Rossi A, Rudebeck P, Russ B, Sakai T, Saleem KS, Sallet J, Sawiak S, Schaeffer D, Schwiedrzik CM, Seidlitz J, Sein J, Sharma J, Shen K, Sheng WA, Shi NS, Shim WM, Simone L, Sirmpilatze N, Sivan V, Song X, Tanenbaum A, Tasserie J, Taylor P, Tian X, Toro R, Trambaiolli L, Upright N, Vezoli J, Vickery S, Villalon J, Wang X, Wang Y, Weiss AR, Wilson C, Wong TY, Woo CW, Wu B, Xiao D, Xu AG, Xu D, Xufeng Z, Yacoub E, Ye N, Ying Z, Yokoyama C, Yu X, Yue S, Yuheng L, Yumeng X, Zaldivar D, Zhang S, Zhao Y, Zuo Z. Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging. Neuron 2022; 110:16-20. [PMID: 34731649 DOI: 10.1016/j.neuron.2021.10.015] [Show More Authors] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/30/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
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19
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Tyson AL, Margrie TW. Mesoscale microscopy and image analysis tools for understanding the brain. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 168:81-93. [PMID: 34216639 PMCID: PMC8786668 DOI: 10.1016/j.pbiomolbio.2021.06.013] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/09/2021] [Accepted: 06/29/2021] [Indexed: 12/12/2022]
Abstract
Over the last ten years, developments in whole-brain microscopy now allow for high-resolution imaging of intact brains of small animals such as mice. These complex images contain a wealth of information, but many neuroscience laboratories do not have all of the computational knowledge and tools needed to process these data. We review recent open source tools for registration of images to atlases, and the segmentation, visualisation and analysis of brain regions and labelled structures such as neurons. Since the field lacks fully integrated analysis pipelines for all types of whole-brain microscopy analysis, we propose a pathway for tool developers to work together to meet this challenge.
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Affiliation(s)
- Adam L Tyson
- Sainsbury Wellcome Centre, University College London, 25 Howland Street, London, W1T 4JG, United Kingdom
| | - Troy W Margrie
- Sainsbury Wellcome Centre, University College London, 25 Howland Street, London, W1T 4JG, United Kingdom.
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20
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Kwan C, Kang MS, Nuara SG, Gourdon JC, Bédard D, Tardif CL, Hopewell R, Ross K, Bdair H, Hamadjida A, Massarweh G, Soucy JP, Luo W, Del Cid Pellitero E, Shlaifer I, Durcan TM, Fon EA, Rosa-Neto P, Frey S, Huot P. Co-registration of Imaging Modalities (MRI, CT and PET) to Perform Frameless Stereotaxic Robotic Injections in the Common Marmoset. Neuroscience 2021; 480:143-154. [PMID: 34774970 DOI: 10.1016/j.neuroscience.2021.11.009] [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: 05/21/2021] [Revised: 11/02/2021] [Accepted: 11/03/2021] [Indexed: 11/17/2022]
Abstract
The common marmoset has emerged as a popular model in neuroscience research, in part due to its reproductive efficiency, genetic and neuroanatomical similarities to humans and the successful generation of transgenic lines. Stereotaxic procedures in marmosets are guided by 2D stereotaxic atlases, which are constructed with a limited number of animals and fail to account for inter-individual variability in skull and brain size. Here, we developed a frameless imaging-guided stereotaxic system that improves upon traditional approaches by using subject-specific registration of computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) data to identify a surgical target, namely the putamen, in two marmosets. The skull surface was laser-scanned to create a point cloud that was registered to the 3D reconstruction of the skull from CT. Reconstruction of the skull, as well as of the brain from MR images, was crucial for surgical planning. Localisation and injection into the putamen was done using a 6-axis robotic arm controlled by a surgical navigation software (Brainsight™). Integration of subject-specific registration and frameless stereotaxic navigation allowed target localisation specific to each animal. Injection of alpha-synuclein fibrils into the putamen triggered progressive neurodegeneration of the nigro-striatal system, a key feature of Parkinson's disease. Four months post-surgery, a PET scan found evidence of nigro-striatal denervation, supporting accurate targeting of the putamen during co-registration and subsequent surgery. Our results suggest that this approach, coupled with frameless stereotaxic neuronavigation, is accurate in localising surgical targets and can be used to assess endpoints for longitudinal studies.
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Affiliation(s)
- Cynthia Kwan
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Min Su Kang
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Stephen G Nuara
- Comparative Medicine & Animal Resource Centre, McGill University, Montreal, QC, Canada
| | - Jim C Gourdon
- Comparative Medicine & Animal Resource Centre, McGill University, Montreal, QC, Canada
| | - Dominique Bédard
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Christine L Tardif
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Department of Biomedical Engineering, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Robert Hopewell
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Karen Ross
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Hussein Bdair
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Adjia Hamadjida
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Gassan Massarweh
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Jean-Paul Soucy
- McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | - Wen Luo
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; The Neuro's Early Drug Discovery Unit, McGill University, Montreal, QC, Canada
| | - Esther Del Cid Pellitero
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Movement Disorder Clinic, Division of Neurology, Department of Neuroscience, McGill University Health Centre, Montreal, QC, Canada
| | - Irina Shlaifer
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; The Neuro's Early Drug Discovery Unit, McGill University, Montreal, QC, Canada
| | - Thomas M Durcan
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; The Neuro's Early Drug Discovery Unit, McGill University, Montreal, QC, Canada
| | - Edward A Fon
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Movement Disorder Clinic, Division of Neurology, Department of Neuroscience, McGill University Health Centre, Montreal, QC, Canada
| | - Pedro Rosa-Neto
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada
| | | | - Philippe Huot
- Neurodegenerative Disease Group, Montreal Neurological Institute-Hospital (The Neuro), Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Movement Disorder Clinic, Division of Neurology, Department of Neuroscience, McGill University Health Centre, Montreal, QC, Canada.
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21
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Interspecies activation correlations reveal functional correspondences between marmoset and human brain areas. Proc Natl Acad Sci U S A 2021; 118:2110980118. [PMID: 34493677 DOI: 10.1073/pnas.2110980118] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 08/09/2021] [Indexed: 12/12/2022] Open
Abstract
The common marmoset has enormous promise as a nonhuman primate model of human brain functions. While resting-state functional MRI (fMRI) has provided evidence for a similar organization of marmoset and human cortices, the technique cannot be used to map the functional correspondences of brain regions between species. This limitation can be overcome by movie-driven fMRI (md-fMRI), which has become a popular tool for noninvasively mapping the neural patterns generated by rich and naturalistic stimulation. Here, we used md-fMRI in marmosets and humans to identify whole-brain functional correspondences between the two primate species. In particular, we describe functional correlates for the well-known human face, body, and scene patches in marmosets. We find that these networks have a similar organization in both species, suggesting a largely conserved organization of higher-order visual areas between New World marmoset monkeys and humans. However, while face patches in humans and marmosets were activated by marmoset faces, only human face patches responded to the faces of other animals. Together, the results demonstrate that higher-order visual processing might be a conserved feature between humans and New World marmoset monkeys but that small, potentially important functional differences exist.
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22
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Hori Y, Cléry JC, Schaeffer DJ, Menon RS, Everling S. Functional Organization of Frontoparietal Cortex in the Marmoset Investigated with Awake Resting-State fMRI. Cereb Cortex 2021; 32:1965-1977. [PMID: 34515315 DOI: 10.1093/cercor/bhab328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/13/2021] [Accepted: 08/14/2021] [Indexed: 11/12/2022] Open
Abstract
Frontoparietal networks contribute to complex cognitive functions in humans and macaques, such as working memory, attention, task-switching, response suppression, grasping, reaching, and eye movement control. However, there has been no comprehensive examination of the functional organization of frontoparietal networks using functional magnetic resonance imaging in the New World common marmoset monkey (Callithrix jacchus), which is now widely recognized as a powerful nonhuman primate experimental animal. In this study, we employed hierarchical clustering of interareal blood oxygen level-dependent signals to investigate the hypothesis that the organization of the frontoparietal cortex in the marmoset follows the organizational principles of the macaque frontoparietal system. We found that the posterior part of the lateral frontal cortex (premotor regions) was functionally connected to the anterior parietal areas, while more anterior frontal regions (frontal eye field [FEF]) were connected to more posterior parietal areas (the region around the lateral intraparietal area [LIP]). These overarching patterns of interareal organization are consistent with a recent macaque study. These findings demonstrate parallel frontoparietal processing streams in marmosets and support the functional similarities of FEF-LIP and premotor-anterior parietal pathways between marmoset and macaque.
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Affiliation(s)
- Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada.,Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario N6A 5C1, Canada
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23
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Volume reduction without neuronal loss in the primate pulvinar complex following striate cortex lesions. Brain Struct Funct 2021; 226:2417-2430. [PMID: 34324075 DOI: 10.1007/s00429-021-02345-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 07/13/2021] [Indexed: 10/20/2022]
Abstract
Lesions in the primary visual cortex (V1) cause extensive retrograde degeneration in the lateral geniculate nucleus, but it remains unclear whether they also trigger any neuronal loss in other subcortical visual centers. The inferior (IPul) and lateral (LPul) pulvinar nuclei have been regarded as part of the pathways that convey visual information to both V1 and extrastriate cortex. Here, we apply stereological analysis techniques to NeuN-stained sections of marmoset brain, in order to investigate whether the volume of these nuclei, and the number of neurons they comprise, change following unilateral long-term V1 lesions. For comparison, the medial pulvinar nucleus (MPul), which has no connections with V1, was also studied. Compared to control animals, animals with lesions incurred either 6 weeks after birth or in adulthood showed significant LPul volume loss following long (> 11 months) survival times. However, no obvious areas of neuronal degeneration were observed. In addition, estimates of neuronal density in lesioned hemispheres were similar to those in the non-lesioned hemispheres of same animals. Our results support the view that, in marked contrast with the geniculocortical projection, the pulvinar pathway is largely spared from the most severe long-term effects of V1 lesions, whether incurred in early postnatal or adult life. This difference can be linked to the more divergent pattern of pulvinar connectivity to the visual cortex, including strong reciprocal connections with extrastriate areas. The results also caution against interpretation of volume loss in brain structures as a marker for neuronal degeneration.
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24
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Bakola S, Burman KJ, Bednarek S, Chan JM, Jermakow N, Worthy KH, Majka P, Rosa MGP. Afferent Connections of Cytoarchitectural Area 6M and Surrounding Cortex in the Marmoset: Putative Homologues of the Supplementary and Pre-supplementary Motor Areas. Cereb Cortex 2021; 32:41-62. [PMID: 34255833 DOI: 10.1093/cercor/bhab193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/07/2021] [Accepted: 06/07/2021] [Indexed: 01/02/2023] Open
Abstract
Cortical projections to the caudomedial frontal cortex were studied using retrograde tracers in marmosets. We tested the hypothesis that cytoarchitectural area 6M includes homologues of the supplementary and pre-supplementary motor areas (SMA and pre-SMA) of other primates. We found that, irrespective of the injection sites' location within 6M, over half of the labeled neurons were located in motor and premotor areas. Other connections originated in prefrontal area 8b, ventral anterior and posterior cingulate areas, somatosensory areas (3a and 1-2), and areas on the rostral aspect of the dorsal posterior parietal cortex. Although the origin of afferents was similar, injections in rostral 6M received higher percentages of prefrontal afferents, and fewer somatosensory afferents, compared to caudal injections, compatible with differentiation into SMA and pre-SMA. Injections rostral to 6M (area 8b) revealed a very different set of connections, with increased emphasis on prefrontal and posterior cingulate afferents, and fewer parietal afferents. The connections of 6M were also quantitatively different from those of the primary motor cortex, dorsal premotor areas, and cingulate motor area 24d. These results show that the cortical motor control circuit is conserved in simian primates, indicating that marmosets can be valuable models for studying movement planning and control.
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Affiliation(s)
- Sophia Bakola
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.,Monash University Node, ARC Centre of Excellence for Integrative Brain Function, Monash University, Clayton, VIC 3800, Australia
| | - Kathleen J Burman
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.,Monash University Node, ARC Centre of Excellence for Integrative Brain Function, Monash University, Clayton, VIC 3800, Australia
| | - Sylwia Bednarek
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
| | - Jonathan M Chan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.,Monash University Node, ARC Centre of Excellence for Integrative Brain Function, Monash University, Clayton, VIC 3800, Australia
| | - Natalia Jermakow
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
| | - Katrina H Worthy
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Piotr Majka
- Monash University Node, ARC Centre of Excellence for Integrative Brain Function, Monash University, Clayton, VIC 3800, Australia.,Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
| | - Marcello G P Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.,Monash University Node, ARC Centre of Excellence for Integrative Brain Function, Monash University, Clayton, VIC 3800, Australia
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25
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Atapour N, Worthy KH, Rosa MGP. Neurochemical changes in the primate lateral geniculate nucleus following lesions of striate cortex in infancy and adulthood: implications for residual vision and blindsight. Brain Struct Funct 2021; 226:2763-2775. [PMID: 33743077 DOI: 10.1007/s00429-021-02257-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/10/2021] [Indexed: 12/16/2022]
Abstract
Following lesions of the primary visual cortex (V1), the lateral geniculate nucleus (LGN) undergoes substantial cell loss due to retrograde degeneration. However, visually responsive neurons remain in the degenerated sector of LGN, and these have been implicated in mediation of residual visual capacities that remain within the affected sectors of the visual field. Using immunohistochemistry, we compared the neurochemical characteristics of LGN neurons in V1-lesioned marmoset monkeys (Callithrix jacchus) with those of non-lesioned control animals. We found that GABAergic neurons form approximately 6.5% of the neuronal population in the normal LGN, where most of these cells express the calcium-binding protein parvalbumin. Following long-term V1 lesions in adult monkeys, we observed a marked increase (~ sevenfold) in the proportion of GABA-expressing neurons in the degenerated sector of the LGN, indicating that GABAergic cells are less affected by retrograde degeneration in comparison with magno- and parvocellular projection neurons. In addition, following early postnatal V1 lesions and survival into adulthood, we found widespread expression of GABA in putative projection neurons, even outside the degenerated sectors (lesion projection zones). Our findings show that changes in the ratio of GABAergic neurons in LGN need to be taken into account in the interpretation of the mechanisms of visual abilities that survive V1 lesions in primates.
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Affiliation(s)
- Nafiseh Atapour
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, VIC, 3800, Australia. .,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Melbourne, VIC, Australia.
| | - Katrina H Worthy
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, VIC, 3800, Australia
| | - Marcello G P Rosa
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, VIC, 3800, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Melbourne, VIC, Australia
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26
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Feizpour A, Majka P, Chaplin TA, Rowley D, Yu HH, Zavitz E, Price NSC, Rosa MGP, Hagan MA. Visual responses in the dorsolateral frontal cortex of marmoset monkeys. J Neurophysiol 2020; 125:296-304. [PMID: 33326337 DOI: 10.1152/jn.00581.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
The marmoset monkey (Callithrix jacchus) has gained attention in neurophysiology research as a new primate model for visual processing and behavior. In particular, marmosets have a lissencephalic cortex, making multielectrode, optogenetic, and calcium-imaging techniques more accessible than other primate models. However, the degree of homology of brain circuits for visual behavior with those identified in macaques and humans is still being ascertained. For example, whereas the location of the frontal eye fields (FEF) within the dorsolateral frontal cortex has been proposed, it remains unclear whether neurons in the corresponding areas show visual responses-an important characteristic of FEF neurons in other species. Here, we provide the first description of receptive field properties and neural response latencies in the marmoset dorsolateral frontal cortex, based on recordings using Utah arrays in anesthetized animals. We find brisk visual responses in specific regions of the dorsolateral prefrontal cortex, particularly in areas 8aV, 8C, and 6DR. As in macaque FEF, the receptive fields were typically large (10°-30° in diameter) and the median responses latency was brisk (60 ms). These results constrain the possible interpretations about the location of the marmoset FEF and suggest that the marmoset model's significant advantages for the use of physiological techniques may be leveraged in the study of visuomotor cognition.NEW & NOTEWORTHY Behavior and cognition in humans and other primates rely on networks of brain areas guided by the frontal cortex. The marmoset offers exciting new opportunities to study links between brain physiology and behavior, but the functions of frontal cortex areas are still being identified in this species. Here, we provide the first evidence of visual receptive fields in the marmoset dorsolateral frontal cortex, an important step toward future studies of visual cognitive behavior.
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Affiliation(s)
- Azadeh Feizpour
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Piotr Majka
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Tristan A Chaplin
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Declan Rowley
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Hsin-Hao Yu
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Elizabeth Zavitz
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Nicholas S C Price
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Marcello G P Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Maureen A Hagan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
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