51
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Jung B, Taylor PA, Seidlitz J, Sponheim C, Perkins P, Ungerleider LG, Glen D, Messinger A. A comprehensive macaque fMRI pipeline and hierarchical atlas. Neuroimage 2021; 235:117997. [PMID: 33789138 PMCID: PMC9272767 DOI: 10.1016/j.neuroimage.2021.117997] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 01/27/2021] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
Functional neuroimaging research in the non-human primate (NHP) has been advancing at a remarkable rate. The increase in available data establishes a need for robust analysis pipelines designed for NHP neuroimaging and accompanying template spaces to standardize the localization of neuroimaging results. Our group recently developed the NIMH Macaque Template (NMT), a high-resolution population average anatomical template and associated neuroimaging resources, providing researchers with a standard space for macaque neuroimaging . Here, we release NMT v2, which includes both symmetric and asymmetric templates in stereotaxic orientation, with improvements in spatial contrast, processing efficiency, and segmentation. We also introduce the Cortical Hierarchy Atlas of the Rhesus Macaque (CHARM), a hierarchical parcellation of the macaque cerebral cortex with varying degrees of detail. These tools have been integrated into the neuroimaging analysis software AFNI to provide a comprehensive and robust pipeline for fMRI processing, visualization and analysis of NHP data. AFNI's new @animal_warper program can be used to efficiently align anatomical scans to the NMT v2 space, and afni_proc.py integrates these results with full fMRI processing using macaque-specific parameters: from motion correction through regression modeling. Taken together, the NMT v2 and AFNI represent an all-in-one package for macaque functional neuroimaging analysis, as demonstrated with available demos for both task and resting state fMRI.
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Affiliation(s)
- Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA; Department of Neuroscience, Brown University, Providence, RI, USA
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Caleb Sponheim
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Pierce Perkins
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Leslie G Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA.
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA.
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52
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Rocchi F, Oya H, Balezeau F, Billig AJ, Kocsis Z, Jenison RL, Nourski KV, Kovach CK, Steinschneider M, Kikuchi Y, Rhone AE, Dlouhy BJ, Kawasaki H, Adolphs R, Greenlee JDW, Griffiths TD, Howard MA, Petkov CI. Common fronto-temporal effective connectivity in humans and monkeys. Neuron 2021; 109:852-868.e8. [PMID: 33482086 PMCID: PMC7927917 DOI: 10.1016/j.neuron.2020.12.026] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 10/02/2020] [Accepted: 12/30/2020] [Indexed: 01/24/2023]
Abstract
Human brain pathways supporting language and declarative memory are thought to have differentiated substantially during evolution. However, cross-species comparisons are missing on site-specific effective connectivity between regions important for cognition. We harnessed functional imaging to visualize the effects of direct electrical brain stimulation in macaque monkeys and human neurosurgery patients. We discovered comparable effective connectivity between caudal auditory cortex and both ventro-lateral prefrontal cortex (VLPFC, including area 44) and parahippocampal cortex in both species. Human-specific differences were clearest in the form of stronger hemispheric lateralization effects. In humans, electrical tractography revealed remarkably rapid evoked potentials in VLPFC following auditory cortex stimulation and speech sounds drove VLPFC, consistent with prior evidence in monkeys of direct auditory cortex projections to homologous vocalization-responsive regions. The results identify a common effective connectivity signature in human and nonhuman primates, which from auditory cortex appears equally direct to VLPFC and indirect to the hippocampus. VIDEO ABSTRACT.
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Affiliation(s)
- Francesca Rocchi
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK.
| | - Hiroyuki Oya
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA.
| | - Fabien Balezeau
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK
| | | | - Zsuzsanna Kocsis
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK; Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA
| | - Rick L Jenison
- Department of Neuroscience, University of Wisconsin - Madison, Madison, WI, USA
| | - Kirill V Nourski
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA
| | | | - Mitchell Steinschneider
- Departments of Neurology and Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yukiko Kikuchi
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK
| | - Ariane E Rhone
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA
| | - Brian J Dlouhy
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA
| | - Hiroto Kawasaki
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA
| | - Ralph Adolphs
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Jeremy D W Greenlee
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA
| | - Timothy D Griffiths
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK; Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Matthew A Howard
- Department of Neurosurgery, The University of Iowa, Iowa City, IA, USA; Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA; Pappajohn Biomedical Institute, The University of Iowa, Iowa City, IA, USA
| | - Christopher I Petkov
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, UK.
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53
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Poirier C, Hamed SB, Garcia-Saldivar P, Kwok SC, Meguerditchian A, Merchant H, Rogers J, Wells S, Fox AS. Beyond MRI: on the scientific value of combining non-human primate neuroimaging with metadata. Neuroimage 2021; 228:117679. [PMID: 33359343 PMCID: PMC7903159 DOI: 10.1016/j.neuroimage.2020.117679] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 12/07/2020] [Accepted: 12/16/2020] [Indexed: 01/01/2023] Open
Abstract
Sharing and pooling large amounts of non-human primate neuroimaging data offer new exciting opportunities to understand the primate brain. The potential of big data in non-human primate neuroimaging could however be tremendously enhanced by combining such neuroimaging data with other types of information. Here we describe metadata that have been identified as particularly valuable by the non-human primate neuroimaging community, including behavioural, genetic, physiological and phylogenetic data.
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Affiliation(s)
- Colline Poirier
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle 6, UK.
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5229, Université de Lyon - CNRS, France
| | - Pamela Garcia-Saldivar
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230 México
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, Key Laboratory of Brain Functional Genomics Ministry of Education, Shanghai Key Laboratory of Magnetic Resonance, Affiliated Mental Health Center (ECNU), Shanghai Changning Mental Health Center, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Division of Natural and Applied Sciences, Duke Kunshan University, Duke Institute for Brain Sciences, Kunshan, Jiangsu, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille/CNRS, Institut Language, Communication and the Brain 13331 Marseille, France
| | - Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230 México
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Dept. of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA 77030
| | - Sara Wells
- Centre for Macaques, MRC Harwell Institute, Porton Down, Salisbury, United Kingdom
| | - Andrew S Fox
- California National Primate Research Center, Department of Psychology, University of California, Davis, Davis, CA, 95616, USA
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Friedrich P, Forkel SJ, Amiez C, Balsters JH, Coulon O, Fan L, Goulas A, Hadj-Bouziane F, Hecht EE, Heuer K, Jiang T, Latzman RD, Liu X, Loh KK, Patil KR, Lopez-Persem A, Procyk E, Sallet J, Toro R, Vickery S, Weis S, Wilson CRE, Xu T, Zerbi V, Eickoff SB, Margulies DS, Mars RB, Thiebaut de Schotten M. Imaging evolution of the primate brain: the next frontier? Neuroimage 2021; 228:117685. [PMID: 33359344 PMCID: PMC7116589 DOI: 10.1016/j.neuroimage.2020.117685] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/14/2020] [Accepted: 12/16/2020] [Indexed: 11/22/2022] Open
Abstract
Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.
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Affiliation(s)
- Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France; Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Céline Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Joshua H Balsters
- Department of Psychology, Royal Holloway University of London, United Kingdom
| | - Olivier Coulon
- Institut de Neurosciences de la Timone, Aix Marseille Univ, CNRS, UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Hamburg, Germany
| | - Fadila Hadj-Bouziane
- Lyon Neuroscience Research Center, ImpAct Team, INSERM U1028, CNRS UMR5292, Université Lyon 1, Bron, France
| | - Erin E Hecht
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, United States
| | - Katja Heuer
- Center for Research and Interdisciplinarity (CRI), Université de Paris, Inserm, Paris 75004, France; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; The Queensland Brain Institute, University of Queensland, Brisbane QLD 4072, Australia
| | - Robert D Latzman
- Department of Psychology, Georgia State University, Atlanta, United States
| | - Xiaojin Liu
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Kep Kee Loh
- Institut de Neurosciences de la Timone, Aix Marseille Univ, CNRS, UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Alizée Lopez-Persem
- Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Emmanuel Procyk
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Jerome Sallet
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Roberto Toro
- Center for Research and Interdisciplinarity (CRI), Université de Paris, Inserm, Paris 75004, France; Neuroscience department, Institut Pasteur, UMR 3571, CNRS, Université de Paris, Paris 75015, France
| | - Sam Vickery
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Susanne Weis
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Charles R E Wilson
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Ting Xu
- Child Mind Institute, New York, United States
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Simon B Eickoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Daniel S Margulies
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Integrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique (CNRS) and Université de Paris, 75006, Paris, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France.
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55
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Schaeffer DJ, Liu C, Silva AC, Everling S. Magnetic Resonance Imaging of Marmoset Monkeys. ILAR J 2021; 61:274-285. [PMID: 33631015 PMCID: PMC8918195 DOI: 10.1093/ilar/ilaa029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 09/22/2020] [Accepted: 10/23/2020] [Indexed: 11/12/2022] Open
Abstract
The use of the common marmoset monkey (Callithrix jacchus) for neuroscientific research has grown markedly in the last decade. Magnetic resonance imaging (MRI) has played a significant role in establishing the extent of comparability of marmoset brain architecture with the human brain and brains of other preclinical species (eg, macaques and rodents). As a non-invasive technique, MRI allows for the flexible acquisition of the same sequences across different species in vivo, including imaging of whole-brain functional topologies not possible with more invasive techniques. Being one of the smallest New World primates, the marmoset may be an ideal nonhuman primate species to study with MRI. As primates, marmosets have an elaborated frontal cortex with features analogous to the human brain, while also having a small enough body size to fit into powerful small-bore MRI systems typically employed for rodent imaging; these systems offer superior signal strength and resolution. Further, marmosets have a rich behavioral repertoire uniquely paired with a lissencephalic cortex (like rodents). This smooth cortical surface lends itself well to MRI and also other invasive methodologies. With the advent of transgenic modification techniques, marmosets have gained significant traction as a powerful complement to canonical mammalian modelling species. Marmosets are poised to make major contributions to preclinical investigations of the pathophysiology of human brain disorders as well as more basic mechanistic explorations of the brain. The goal of this article is to provide an overview of the practical aspects of implementing MRI and fMRI in marmosets (both under anesthesia and fully awake) and discuss the development of resources recently made available for marmoset imaging.
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Affiliation(s)
- David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - CiRong Liu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Afonso C Silva
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Stefan Everling
- Department of Physiology and Pharmacology, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
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Abstract
Comparative neuroscience is entering the era of big data. New high-throughput methods and data-sharing initiatives have resulted in the availability of large, digital data sets containing many types of data from ever more species. Here, we present a framework for exploiting the new possibilities offered. The multimodality of the data allows vertical translations, which are comparisons of different aspects of brain organization within a single species and across scales. Horizontal translations compare particular aspects of brain organization across species, often by building abstract feature spaces. Combining vertical and horizontal translations allows for more sophisticated comparisons, including relating principles of brain organization across species by contrasting horizontal translations, and for making formal predictions of unobtainable data based on observed results in a model species.
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Affiliation(s)
- Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, United Kingdom; .,Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 HR Nijmegen, The Netherlands
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, United Kingdom;
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
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Rapan L, Froudist-Walsh S, Niu M, Xu T, Funck T, Zilles K, Palomero-Gallagher N. Multimodal 3D atlas of the macaque monkey motor and premotor cortex. Neuroimage 2021; 226:117574. [PMID: 33221453 PMCID: PMC8168280 DOI: 10.1016/j.neuroimage.2020.117574] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 10/19/2020] [Accepted: 11/10/2020] [Indexed: 01/16/2023] Open
Abstract
In the present study we reevaluated the parcellation scheme of the macaque frontal agranular cortex by implementing quantitative cytoarchitectonic and multireceptor analyses, with the purpose to integrate and reconcile the discrepancies between previously published maps of this region. We applied an observer-independent and statistically testable approach to determine the position of cytoarchitectonic borders. Analysis of the regional and laminar distribution patterns of 13 different transmitter receptors confirmed the position of cytoarchitectonically identified borders. Receptor densities were extracted from each area and visualized as its "receptor fingerprint". Hierarchical and principal components analyses were conducted to detect clusters of areas according to the degree of (dis)similarity of their fingerprints. Finally, functional connectivity pattern of each identified area was analyzed with areas of prefrontal, cingulate, somatosensory and lateral parietal cortex and the results were depicted as "connectivity fingerprints" and seed-to-vertex connectivity maps. We identified 16 cyto- and receptor architectonically distinct areas, including novel subdivisions of the primary motor area 4 (i.e. 4a, 4p, 4m) and of premotor areas F4 (i.e. F4s, F4d, F4v), F5 (i.e. F5s, F5d, F5v) and F7 (i.e. F7d, F7i, F7s). Multivariate analyses of receptor fingerprints revealed three clusters, which first segregated the subdivisions of area 4 with F4d and F4s from the remaining premotor areas, then separated ventrolateral from dorsolateral and medial premotor areas. The functional connectivity analysis revealed that medial and dorsolateral premotor and motor areas show stronger functional connectivity with areas involved in visual processing, whereas 4p and ventrolateral premotor areas presented a stronger functional connectivity with areas involved in somatomotor responses. For the first time, we provide a 3D atlas integrating cyto- and multi-receptor architectonic features of the macaque motor and premotor cortex. This atlas constitutes a valuable resource for the analysis of functional experiments carried out with non-human primates, for modeling approaches with realistic synaptic dynamics, as well as to provide insights into how brain functions have developed by changes in the underlying microstructure and encoding strategies during evolution.
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Affiliation(s)
- Lucija Rapan
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | | | - Meiqi Niu
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, New York
| | - Thomas Funck
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Karl Zilles
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Psychiatry, Psychotherapy, and Psychosomatics, Medical Faculty, RWTH Aachen, and JARA - Translational Brain Medicine, Aachen, Germany; C. & O. Vogt Institute for Brain Research, Heinrich-Heine-University, 40225 Düsseldorf, Germany.
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58
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Balezeau F, Nacef J, Kikuchi Y, Schneider F, Rocchi F, Muers RS, Fernandez-Palacios O'Connor R, Blau C, Wilson B, Saunders RC, Howard M, Thiele A, Griffiths TD, Petkov CI, Murphy K. MRI monitoring of macaque monkeys in neuroscience: Case studies, resource and normative data comparisons. Neuroimage 2021; 230:117778. [PMID: 33497775 PMCID: PMC8063182 DOI: 10.1016/j.neuroimage.2021.117778] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/17/2020] [Accepted: 01/13/2021] [Indexed: 12/14/2022] Open
Abstract
Information from Magnetic Resonance Imaging (MRI) is useful for diagnosis and treatment management of human neurological patients. MRI monitoring might also prove useful for non-human animals involved in neuroscience research provided that MRI is available and feasible and that there are no MRI contra-indications precluding scanning. However, MRI monitoring is not established in macaques and a resource is urgently needed that could grow with scientific community contributions. Here we show the utility and potential benefits of MRI-based monitoring in a few diverse cases with macaque monkeys. We also establish a PRIMatE MRI Monitoring (PRIME-MRM) resource within the PRIMatE Data Exchange (PRIME-DE) and quantitatively compare the cases to normative information drawn from MRI data from typical macaques in PRIME-DE. In the cases, the monkeys presented with no or mild/moderate clinical signs, were well otherwise and MRI scanning did not present a significant increase in welfare impact. Therefore, they were identified as suitable candidates for clinical investigation, MRI-based monitoring and treatment. For each case, we show MRI quantification of internal controls in relation to treatment steps and comparisons with normative data in typical monkeys drawn from PRIME-DE. We found that MRI assists in precise and early diagnosis of cerebral events and can be useful for visualising, treating and quantifying treatment response. The scientific community could now grow the PRIME-MRM resource with other cases and larger samples to further assess and increase the evidence base on the benefits of MRI monitoring of primates, complementing the animals’ clinical monitoring and treatment regime.
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Affiliation(s)
- Fabien Balezeau
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jennifer Nacef
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yukiko Kikuchi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Felix Schneider
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Francesca Rocchi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Ross S Muers
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | | | - Christoph Blau
- Comparative Biology Centre, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Benjamin Wilson
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Richard C Saunders
- Laboratory of Neuropsychology, National Institutes of Health (NIMH), Bethesda, MD, United States
| | - Matthew Howard
- Department of Neurosurgery, University of Iowa, Iowa City, IA, United States
| | - Alexander Thiele
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Timothy D Griffiths
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Christopher I Petkov
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.
| | - Kathy Murphy
- Comparative Biology Centre, Newcastle University, Newcastle upon Tyne, United Kingdom.
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59
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Garcia-Saldivar P, Garimella A, Garza-Villarreal EA, Mendez FA, Concha L, Merchant H. PREEMACS: Pipeline for preprocessing and extraction of the macaque brain surface. Neuroimage 2020; 227:117671. [PMID: 33359348 DOI: 10.1016/j.neuroimage.2020.117671] [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: 07/01/2020] [Revised: 12/04/2020] [Accepted: 12/16/2020] [Indexed: 01/18/2023] Open
Abstract
Accurate extraction of the cortical brain surface is critical for cortical thickness estimation and a key element to perform multimodal imaging analysis, where different metrics are integrated and compared in a common space. While brain surface extraction has become widespread practice in human studies, several challenges unique to neuroimaging of non-human primates (NHP) have hindered its adoption for the study of macaques. Although, some of these difficulties can be addressed at the acquisition stage, several common artifacts can be minimized through image preprocessing. Likewise, there are several image analysis pipelines for human MRIs, but very few automated methods for extraction of cortical surfaces have been reported for NHPs and none have been tested on data from diverse sources. We present PREEMACS, a pipeline that standardizes the preprocessing of structural MRI images (T1- and T2-weighted) and carries out an automatic surface extraction of the macaque brain. Building upon and extending pre-existing tools, the first module performs volume orientation, image cropping, intensity non-uniformity correction, and volume averaging, before skull-stripping through a convolutional neural network. The second module performs quality control using an adaptation of MRIqc method to extract objective quality metrics that are then used to determine the likelihood of accurate brain surface estimation. The third and final module estimates the white matter (wm) and pial surfaces from the T1-weighted volume (T1w) using an NHP customized version of FreeSurfer aided by the T2-weighted volumes (T2w). To evaluate the generalizability of PREEMACS, we tested the pipeline using 57 T1w/T2w NHP volumes acquired at 11 different sites from the PRIME-DE public dataset. Results showed an accurate and robust automatic brain surface extraction from images that passed the quality control segment of our pipeline. This work offers a robust, efficient and generalizable pipeline for the automatic standardization of MRI surface analysis on NHP.
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Affiliation(s)
- Pamela Garcia-Saldivar
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México
| | - Arun Garimella
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México; International Institute of Information Technology, Hyderabad, India
| | - Eduardo A Garza-Villarreal
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México
| | - Felipe A Mendez
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México.
| | - Hugo Merchant
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla. Blvd. Juriquilla, 3001 Querétaro, Querétaro, México.
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Yacoub E, Grier MD, Auerbach EJ, Lagore RL, Harel N, Adriany G, Zilverstand A, Hayden BY, Heilbronner SR, Uğurbil K, Zimmermann J. Ultra-high field (10.5 T) resting state fMRI in the macaque. Neuroimage 2020; 223:117349. [PMID: 32898683 PMCID: PMC7745777 DOI: 10.1016/j.neuroimage.2020.117349] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/20/2020] [Accepted: 08/31/2020] [Indexed: 01/02/2023] Open
Abstract
Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for contrast agents limiting translatability, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, imaging at magnetic fields above 7T has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed single-subject resting state analysis at high resolutions using a 10.5 Tesla scanner. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI 'macaque connectome' will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.
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Affiliation(s)
- Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Russell L Lagore
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States
| | - Gregor Adriany
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Anna Zilverstand
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55455, United States
| | - Benjamin Y Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States.
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Messinger A, Sirmpilatze N, Heuer K, Loh KK, Mars RB, Sein J, Xu T, Glen D, Jung B, Seidlitz J, Taylor P, Toro R, Garza-Villarreal EA, Sponheim C, Wang X, Benn RA, Cagna B, Dadarwal R, Evrard HC, Garcia-Saldivar P, Giavasis S, Hartig R, Lepage C, Liu C, Majka P, Merchant H, Milham MP, Rosa MGP, Tasserie J, Uhrig L, Margulies DS, Klink PC. A collaborative resource platform for non-human primate neuroimaging. Neuroimage 2020; 226:117519. [PMID: 33227425 PMCID: PMC9272762 DOI: 10.1016/j.neuroimage.2020.117519] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 10/15/2020] [Accepted: 10/24/2020] [Indexed: 01/12/2023] Open
Abstract
Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.
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Affiliation(s)
- Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA
| | - Nikoloz Sirmpilatze
- German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Georg-August-University Göttingen, 37073 Göttingen, Germany
| | - Katja Heuer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, Paris, France
| | - Kep Kee Loh
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands
| | - Julien Sein
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | - Ting Xu
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | - Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA; Department of Neuroscience, Brown University, Providence RI USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia PA USA; Department of Psychiatry, University of Pennsylvania, Philadelphia PA USA
| | - Paul Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | - Roberto Toro
- Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, Paris, France; Department of Neuroscience, Institut Pasteur, UMR 3571 CNRS, Université de Paris, Paris, France
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Caleb Sponheim
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago IL USA
| | - Xindi Wang
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute (MNI), Quebec, Canada
| | - R Austin Benn
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Bastien Cagna
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | - Rakshit Dadarwal
- German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Georg-August-University Göttingen, 37073 Göttingen, Germany
| | - Henry C Evrard
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA; International Center for Primate Brain Research, Chinese Academy of Science, Shanghai, PRC
| | - Pamela Garcia-Saldivar
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Steven Giavasis
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA
| | - Renée Hartig
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Focus Program Translational Neurosciences, University Medical Center, Mainz, Germany
| | - Claude Lepage
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute (MNI), Quebec, Canada
| | - Cirong Liu
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh PA, USA
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Hugo Merchant
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Michael P Milham
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Jordy Tasserie
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale U992, Gif-sur-Yvette, France; Université Paris-Saclay, France
| | - Lynn Uhrig
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale U992, Gif-sur-Yvette, France
| | - Daniel S Margulies
- Integrative Neuroscience and Cognition Center, Centre National de la Recherche Scientifique (CNRS) UMR 8002, Paris, France
| | - P Christiaan Klink
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
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Howells H, Simone L, Borra E, Fornia L, Cerri G, Luppino G. Reproducing macaque lateral grasping and oculomotor networks using resting state functional connectivity and diffusion tractography. Brain Struct Funct 2020; 225:2533-2551. [PMID: 32936342 PMCID: PMC7544728 DOI: 10.1007/s00429-020-02142-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 09/02/2020] [Indexed: 12/31/2022]
Abstract
Cortico-cortical networks involved in motor control have been well defined in the macaque using a range of invasive techniques. The advent of neuroimaging has enabled non-invasive study of these large-scale functionally specialized networks in the human brain; however, assessing its accuracy in reproducing genuine anatomy is more challenging. We set out to assess the similarities and differences between connections of macaque motor control networks defined using axonal tracing and those reproduced using structural and functional connectivity techniques. We processed a cohort of macaques scanned in vivo that were made available by the open access PRIME-DE resource, to evaluate connectivity using diffusion imaging tractography and resting state functional connectivity (rs-FC). Sectors of the lateral grasping and exploratory oculomotor networks were defined anatomically on structural images, and connections were reproduced using different structural and functional approaches (probabilistic and deterministic whole-brain and seed-based tractography; group template and native space functional connectivity analysis). The results showed that parieto-frontal connections were best reproduced using both structural and functional connectivity techniques. Tractography showed lower sensitivity but better specificity in reproducing connections identified by tracer data. Functional connectivity analysis performed in native space had higher sensitivity but lower specificity and was better at identifying connections between intrasulcal ROIs than group-level analysis. Connections of AIP were most consistently reproduced, although those connected with prefrontal sectors were not identified. We finally compared diffusion MR modelling with histology based on an injection in AIP and speculate on anatomical bases for the observed false negatives. Our results highlight the utility of precise ex vivo techniques to support the accuracy of neuroimaging in reproducing connections, which is relevant also for human studies.
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Affiliation(s)
- Henrietta Howells
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy.
| | - Luciano Simone
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy.
| | - Elena Borra
- Department of Medicine and Surgery, Neuroscience Unit, University of Parma, Parma, Italy
| | - Luca Fornia
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy
| | - Gabriella Cerri
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy
| | - Giuseppe Luppino
- Department of Medicine and Surgery, Neuroscience Unit, University of Parma, Parma, Italy
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Prescott MJ, Poirier C. The role of MRI in applying the 3Rs to non-human primate neuroscience. Neuroimage 2020; 225:117521. [PMID: 33137476 DOI: 10.1016/j.neuroimage.2020.117521] [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: 06/26/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 12/21/2022] Open
Abstract
Magnetic resonance imaging is playing a significant role in applying the 3Rs to neuroscience studies using non-human primates. MRI scans are contributing to refinement by enhancing the selection and assignment of animals, guiding the manufacture of custom-fitted recording and head fixation devices, and assisting with the diagnosis of health issues and their treatment. MRI is also being used to better understand the impact of neuroscience procedures on the welfare of NHPs. MRI has helped to optimise NHP use and make greater scientific progress than would otherwise be made using larger numbers of animals. Whilst human fMRI studies have replaced some NHP studies, their potential to directly replace NHP electrophysiology is limited at present. Given the considerable advantages of MRI for electrophysiology experiments, including improved welfare of NHPs, consideration should be given to focusing NHP electrophysiology laboratories around MRI facilities. Greater sharing of MRI data sets, and improvements in MRI contrast and resolution, are expected to further advance the 3Rs in the future.
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Affiliation(s)
- Mark J Prescott
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), Gibbs Building, 215 Euston Road, London NW1 2BE, UK.
| | - Colline Poirier
- Biosciences Institute & Centre for Behaviour and Evolution, Newcastle University, Medical School, Framlington Place, Newcastle upon Tyne NE2 4HH, UK.
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Fox AS, Holley D, Klink PC, Arbuckle SA, Barnes CA, Diedrichsen J, Kwok SC, Kyle C, Pruszynski JA, Seidlitz J, Zhou X, Poldrack RA, Gorgolewski KJ. Sharing voxelwise neuroimaging results from rhesus monkeys and other species with Neurovault. Neuroimage 2020; 225:117518. [PMID: 33137472 PMCID: PMC7846271 DOI: 10.1016/j.neuroimage.2020.117518] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 10/15/2020] [Accepted: 10/24/2020] [Indexed: 12/23/2022] Open
Abstract
Animal neuroimaging studies can provide unique insights into brain structure and function, and can be leveraged to bridge the gap between animal and human neuroscience. In part, this power comes from the ability to com bine mechanistic interventions with brain-wide neuroimaging. Due to their phylogenetic proximity to humans, nonhuman primate neuroimaging holds particular promise. Because nonhuman primate neuroimaging studies are often underpowered, there is a great need to share data amongst translational researchers. Data sharing efforts have been limited, however, by the lack of standardized tools and repositories through which nonhuman neuroimaging data can easily be archived and accessed. Here, we provide an extension of the Neurovault framework to enable sharing of statistical maps and related voxelwise neuroimaging data from other species and template-spaces. Neurovault, which was previously limited to human neuroimaging data, now allows researchers to easily upload and share nonhuman primate neuroimaging results. This promises to facilitate open, integrative cross-species science while affording researchers the increased statistical power provided by data aggregation. In addition, the Neurovault code-base now enables the addition of other species and template-spaces. Together, these advances promise to bring neuroimaging data sharing to research in other species, for supplemental data location-based atlases, and data that would otherwise be relegated to a “file-drawer”. As increasing numbers of researchers share their nonhuman neuroimaging data on Neurovault, this resource will enable novel, large-scale, cross-species comparisons that were previously impossible.
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Affiliation(s)
- Andrew S Fox
- University of California, Davis and the California National Primate Research Center, Davis, CA 95616, USA.
| | - Daniel Holley
- University of California, Davis and the California National Primate Research Center, Davis, CA 95616, USA
| | - Peter Christiaan Klink
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands
| | | | - Carol A Barnes
- University of Arizona, Evelyn F. McKnight Brain Institute and Division of Neural Systems, Memory and Aging, Tucson, AZ, USA
| | - Jörn Diedrichsen
- Brain and Mind Institute, Western University, London, Ontario, Canada
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, Key Laboratory of Brain Functional Genomics Ministry of Education, Shanghai Key Laboratory of Magnetic Resonance, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Division of Natural and Applied Sciences, Duke Kunshan University, Duke Institute for Brain Sciences, Kunshan, Jiangsu, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China; Shanghai Changning Mental Health Center, China
| | - Colin Kyle
- University of Arizona, Evelyn F. McKnight Brain Institute and Division of Neural Systems, Memory and Aging, Tucson, AZ, USA
| | | | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA
| | - XuFeng Zhou
- Shanghai Key Laboratory of Brain Functional Genomics, Key Laboratory of Brain Functional Genomics Ministry of Education, Shanghai Key Laboratory of Magnetic Resonance, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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Froesel M, Goudard Q, Hauser M, Gacoin M, Ben Hamed S. Automated video-based heart rate tracking for the anesthetized and behaving monkey. Sci Rep 2020; 10:17940. [PMID: 33087832 PMCID: PMC7578008 DOI: 10.1038/s41598-020-74954-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 10/08/2020] [Indexed: 02/06/2023] Open
Abstract
Heart rate (HR) is extremely valuable in the study of complex behaviours and their physiological correlates in non-human primates. However, collecting this information is often challenging, involving either invasive implants or tedious behavioural training. In the present study, we implement a Eulerian video magnification (EVM) heart tracking method in the macaque monkey combined with wavelet transform. This is based on a measure of image to image fluctuations in skin reflectance due to changes in blood influx. We show a strong temporal coherence and amplitude match between EVM-based heart tracking and ground truth ECG, from both color (RGB) and infrared (IR) videos, in anesthetized macaques, to a level comparable to what can be achieved in humans. We further show that this method allows to identify consistent HR changes following the presentation of conspecific emotional voices or faces. EVM is used to extract HR in humans but has never been applied to non-human primates. Video photoplethysmography allows to extract awake macaques HR from RGB videos. In contrast, our method allows to extract awake macaques HR from both RGB and IR videos and is particularly resilient to the head motion that can be observed in awake behaving monkeys. Overall, we believe that this method can be generalized as a tool to track HR of the awake behaving monkey, for ethological, behavioural, neuroscience or welfare purposes.
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Affiliation(s)
- Mathilda Froesel
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS, Université de Lyon, 67 Boulevard Pinel, 69675, Bron Cedex, France.
| | - Quentin Goudard
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS, Université de Lyon, 67 Boulevard Pinel, 69675, Bron Cedex, France.
| | - Marc Hauser
- Risk-Eraser, LLC, PO Box 376, West Falmouth, MA, 02574, USA
| | - Maëva Gacoin
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS, Université de Lyon, 67 Boulevard Pinel, 69675, Bron Cedex, France
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS, Université de Lyon, 67 Boulevard Pinel, 69675, Bron Cedex, France.
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Hori Y, Schaeffer DJ, Gilbert KM, Hayrynen LK, Cléry JC, Gati JS, Menon RS, Everling S. Altered Resting-State Functional Connectivity Between Awake and Isoflurane Anesthetized Marmosets. Cereb Cortex 2020; 30:5943-5959. [PMID: 32556184 PMCID: PMC7899065 DOI: 10.1093/cercor/bhaa168] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 05/28/2020] [Accepted: 05/28/2020] [Indexed: 01/02/2023] Open
Abstract
The common marmoset (Callithrix jacchus) is a New World primate that is becoming increasingly popular as a preclinical model. To assess functional connectivity (FC) across the marmoset brain, resting-state functional MRI (RS-fMRI) is often performed under isoflurane anesthesia to avoid the effects of motion, physiological stress, and training requirements. In marmosets, however, it remains unclear how isoflurane anesthesia affects patterns of FC. Here, we investigated the effects of isoflurane on FC when delivered with either medical air or 100% pure oxygen, two canonical methods of inhalant isoflurane anesthesia delivery. The results demonstrated that when delivered with either medical air or 100% oxygen, isoflurane globally decreased FC across resting-state networks that were identified in awake marmosets. Generally, although isoflurane globally decreased FC in resting-state networks, the spatial structure of the networks was preserved. Outside of the context of RS networks, we indexed pair-wise functional connectivity between regions across the brain and found that isoflurane substantially altered interhemispheric and thalamic FC. Taken together, these findings indicate that RS-fMRI under isoflurane anesthesia is useful to evaluate the global structure of functional networks, but may obfuscate important nodes of some network components when compared to data acquired in fully awake marmosets.
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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
| | - David J Schaeffer
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Kyle M Gilbert
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Lauren K Hayrynen
- 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
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - 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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Müller HP, Roselli F, Rasche V, Kassubek J. Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases. Front Neurosci 2020; 14:734. [PMID: 32982659 PMCID: PMC7487414 DOI: 10.3389/fnins.2020.00734] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/22/2020] [Indexed: 12/11/2022] Open
Abstract
The understanding of human and non-human microstructural brain alterations in the course of neurodegenerative diseases has substantially improved by the non-invasive magnetic resonance imaging (MRI) technique of diffusion tensor imaging (DTI). Animal models (including disease or knockout models) allow for a variety of experimental manipulations, which are not applicable to humans. Thus, the DTI approach provides a promising tool for cross-species cross-sectional and longitudinal investigations of the neurobiological targets and mechanisms of neurodegeneration. This overview with a systematic review focuses on the principles of DTI analysis as used in studies at the group level in living preclinical models of neurodegeneration. The translational aspect from in-vivo animal models toward (clinical) applications in humans is covered as well as the DTI-based research of the non-human brains' microstructure, the methodological aspects in data processing and analysis, and data interpretation at different abstraction levels. The aim of integrating DTI in multiparametric or multimodal imaging protocols will allow the interrogation of DTI data in terms of directional flow of information and may identify the microstructural underpinnings of neurodegeneration-related patterns.
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Affiliation(s)
| | - Francesco Roselli
- Department of Neurology, University of Ulm, Ulm, Germany.,German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Volker Rasche
- Core Facility Small Animal MRI, University of Ulm, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
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Ocklenburg S, Berretz G, Packheiser J, Friedrich P. Laterality 2020: entering the next decade. Laterality 2020; 26:265-297. [DOI: 10.1080/1357650x.2020.1804396] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Sebastian Ocklenburg
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Gesa Berretz
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Julian Packheiser
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
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Waymel A, Friedrich P, Bastian PA, Forkel SJ, Thiebaut de Schotten M. Anchoring the human olfactory system within a functional gradient. Neuroimage 2020; 216:116863. [PMID: 32325207 PMCID: PMC7116082 DOI: 10.1016/j.neuroimage.2020.116863] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/10/2020] [Accepted: 04/15/2020] [Indexed: 02/07/2023] Open
Abstract
Margulies et al. (2016) demonstrated the existence of at least five independent functional connectivity gradients in the human brain. However, it is unclear how these functional gradients might link to anatomy. The dual origin theory proposes that differences in cortical cytoarchitecture originate from two trends of progressive differentiation between the different layers of the cortex, referred to as the hippocampocentric and olfactocentric systems. When conceptualising the functional connectivity gradients within the evolutionary framework of the Dual Origin theory, the first gradient likely represents the hippocampocentric system anatomically. Here we expand on this concept and demonstrate that the fifth gradient likely links to the olfactocentric system. We describe the anatomy of the latter as well as the evidence to support this hypothesis. Together, the first and fifth gradients might help to model the Dual Origin theory of the human brain and inform brain models and pathologies.
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Affiliation(s)
- Alice Waymel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France; Hyperedge Instruments, France
| | - Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Pierre-Antoine Bastian
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Hyperedge Instruments, France
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France; King's College London, Institute of Psychiatry Psychology and Neurosciences, Department of Neuroimaging, London, UK
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France.
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Roe AW, Chen G, Xu AG, Hu J. A roadmap to a columnar visual cortical prosthetic. CURRENT OPINION IN PHYSIOLOGY 2020. [DOI: 10.1016/j.cophys.2020.06.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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