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Sukoff Rizzo SJ, Homanics G, Schaeffer DJ, Schaeffer L, Park JE, Oluoch J, Zhang T, Haber A, Seyfried NT, Paten B, Greenwood A, Murai T, Choi SH, Huhe H, Kofler J, Strick PL, Carter GW, Silva AC. Bridging the rodent to human translational gap: Marmosets as model systems for the study of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2023; 9:e12417. [PMID: 37614242 PMCID: PMC10442521 DOI: 10.1002/trc2.12417] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/21/2023] [Accepted: 07/31/2023] [Indexed: 08/25/2023]
Abstract
Introduction Our limited understanding of the mechanisms that trigger the emergence of Alzheimer's disease (AD) has contributed to the lack of interventions that stop, prevent, or fully treat this disease. We believe that the development of a non-human primate model of AD will be an essential step toward overcoming limitations of other model systems and is crucial for investigating primate-specific mechanisms underlying the cellular and molecular root causes of the pathogenesis and progression of AD. Methods A new consortium has been established with funding support from the National Institute on Aging aimed at the generation, characterization, and validation of Marmosets As Research Models of AD (MARMO-AD). This consortium will study gene-edited marmoset models carrying genetic risk for AD and wild-type genetically diverse aging marmosets from birth throughout their lifespan, using non-invasive longitudinal assessments. These include characterizing the genetic, molecular, functional, behavioral, cognitive, and pathological features of aging and AD. Results The consortium successfully generated viable founders carrying PSEN1 mutations in C410Y and A426P using CRISPR/Cas9 approaches, with germline transmission demonstrated in the C410Y line. Longitudinal characterization of these models, their germline offspring, and normal aging outbred marmosets is ongoing. All data and resources from this consortium will be shared with the greater AD research community. Discussion By establishing marmoset models of AD, we will be able to investigate primate-specific cellular and molecular root causes that underlie the pathogenesis and progression of AD, overcome limitations of other model organisms, and support future translational studies to accelerate the pace of bringing therapies to patients.
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Affiliation(s)
| | - Gregg Homanics
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | | | - Lauren Schaeffer
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Jung Eun Park
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Julia Oluoch
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Tingting Zhang
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | | | | | - Benedict Paten
- University of California Santa Cruz Genomics InstituteUniversity of California Santa CruzSanta CruzCaliforniaUSA
| | | | - Takeshi Murai
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Sang Ho Choi
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Hasi Huhe
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Julia Kofler
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Peter L. Strick
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | | | - Afonso C. Silva
- University of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
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2
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McAlpine D, de Hoz L. Listening loops and the adapting auditory brain. Front Neurosci 2023; 17:1081295. [PMID: 37008228 PMCID: PMC10060829 DOI: 10.3389/fnins.2023.1081295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 02/17/2023] [Indexed: 03/18/2023] Open
Abstract
Analysing complex auditory scenes depends in part on learning the long-term statistical structure of sounds comprising those scenes. One way in which the listening brain achieves this is by analysing the statistical structure of acoustic environments over multiple time courses and separating background from foreground sounds. A critical component of this statistical learning in the auditory brain is the interplay between feedforward and feedback pathways—“listening loops”—connecting the inner ear to higher cortical regions and back. These loops are likely important in setting and adjusting the different cadences over which learned listening occurs through adaptive processes that tailor neural responses to sound environments that unfold over seconds, days, development, and the life-course. Here, we posit that exploring listening loops at different scales of investigation—from in vivo recording to human assessment—their role in detecting different timescales of regularity, and the consequences this has for background detection, will reveal the fundamental processes that transform hearing into the essential task of listening.
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Affiliation(s)
- David McAlpine
- Department of Linguistics, Macquarie University, Sydney, NSW, Australia
- *Correspondence: David McAlpine,
| | - Livia de Hoz
- Neuroscience Research Center, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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3
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Zhang X. Effects of Anesthesia on Cerebral Blood Flow and Functional Connectivity of Nonhuman Primates. Vet Sci 2022; 9:516. [PMID: 36288129 PMCID: PMC9609818 DOI: 10.3390/vetsci9100516] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/14/2022] [Accepted: 09/19/2022] [Indexed: 02/07/2023] Open
Abstract
Nonhuman primates (NHPs) are the closest living relatives of humans and play a critical and unique role in neuroscience research and pharmaceutical development. General anesthesia is usually required in neuroimaging studies of NHPs to keep the animal from stress and motion. However, the adverse effects of anesthesia on cerebral physiology and neural activity are pronounced and can compromise the data collection and interpretation. Functional connectivity is frequently examined using resting-state functional MRI (rsfMRI) to assess the functional abnormality in the animal brain under anesthesia. The fMRI signal can be dramatically suppressed by most anesthetics in a dose-dependent manner. In addition, rsfMRI studies may be further compromised by inter-subject variations when the sample size is small (as seen in most neuroscience studies of NHPs). Therefore, proper use of anesthesia is strongly demanded to ensure steady and consistent physiology maintained during rsfMRI data collection of each subject. The aim of this review is to summarize typical anesthesia used in rsfMRI scans of NHPs and the effects of anesthetics on cerebral physiology and functional connectivity. Moreover, the protocols with optimal rsfMRI data acquisition and anesthesia procedures for functional connectivity study of macaque monkeys are introduced.
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Affiliation(s)
- Xiaodong Zhang
- EPC Imaging Center and Division of Neuropharmacology and Neurologic Diseases, Emory National Primate Research Center, Emory University, 954 Gatewood RD, Atlanta, GA 30329, USA
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4
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Ferris CF. Applications in Awake Animal Magnetic Resonance Imaging. Front Neurosci 2022; 16:854377. [PMID: 35450017 PMCID: PMC9017993 DOI: 10.3389/fnins.2022.854377] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 03/09/2022] [Indexed: 12/16/2022] Open
Abstract
There are numerous publications on methods and applications for awake functional MRI across different species, e.g., voles, rabbits, cats, dogs, and rhesus macaques. Each of these species, most obviously rhesus monkey, have general or unique attributes that provide a better understanding of the human condition. However, much of the work today is done on rodents. The growing number of small bore (≤30 cm) high field systems 7T- 11.7T favor the use of small animals. To that point, this review is primarily focused on rodents and their many applications in awake function MRI. Applications include, pharmacological MRI, drugs of abuse, sensory evoked stimuli, brain disorders, pain, social behavior, and fear.
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5
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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: 3] [Impact Index Per Article: 1.0] [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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6
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Autio JA, Zhu Q, Li X, Glasser MF, Schwiedrzik CM, Fair DA, Zimmermann J, Yacoub E, Menon RS, Van Essen DC, Hayashi T, Russ B, Vanduffel W. Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection. Neuroimage 2021; 236:118082. [PMID: 33882349 PMCID: PMC8594288 DOI: 10.1016/j.neuroimage.2021.118082] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/16/2021] [Accepted: 04/07/2021] [Indexed: 02/07/2023] Open
Abstract
Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.
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Affiliation(s)
- Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Qi Zhu
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France
| | - Xiaolian Li
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium
| | - Matthew F Glasser
- Departments of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Caspar M Schwiedrzik
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077 Göttingen, Germany; Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Damien A Fair
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jan Zimmermann
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - David C Van Essen
- Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Brian Russ
- Department of Psychiatry, New York University Langone, New York City, New York, USA; Center for the Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, New York, USA; Department of Neuroscience, Icahn School of Medicine, Mount Sinai, New York City, New York, USA
| | - Wim Vanduffel
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Leuven Brain Institute, KU Leuven, Leuven 3000, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
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7
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Basso MA, Frey S, Guerriero KA, Jarraya B, Kastner S, Koyano KW, Leopold DA, Murphy K, Poirier C, Pope W, Silva AC, Tansey G, Uhrig L. Using non-invasive neuroimaging to enhance the care, well-being and experimental outcomes of laboratory non-human primates (monkeys). Neuroimage 2021; 228:117667. [PMID: 33359353 PMCID: PMC8005297 DOI: 10.1016/j.neuroimage.2020.117667] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 02/09/2023] Open
Abstract
Over the past 10-20 years, neuroscience witnessed an explosion in the use of non-invasive imaging methods, particularly magnetic resonance imaging (MRI), to study brain structure and function. Simultaneously, with access to MRI in many research institutions, MRI has become an indispensable tool for researchers and veterinarians to guide improvements in surgical procedures and implants and thus, experimental as well as clinical outcomes, given that access to MRI also allows for improved diagnosis and monitoring for brain disease. As part of the PRIMEatE Data Exchange, we gathered expert scientists, veterinarians, and clinicians who treat humans, to provide an overview of the use of non-invasive imaging tools, primarily MRI, to enhance experimental and welfare outcomes for laboratory non-human primates engaged in neuroscientific experiments. We aimed to provide guidance for other researchers, scientists and veterinarians in the use of this powerful imaging technology as well as to foster a larger conversation and community of scientists and veterinarians with a shared goal of improving the well-being and experimental outcomes for laboratory animals.
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Affiliation(s)
- M A Basso
- Fuster Laboratory of Cognitive Neuroscience, Department of Psychiatry and Biobehavioral Sciences UCLA Los Angeles CA 90095 USA
| | - S Frey
- Rogue Research, Inc. Montreal, QC, Canada
| | - K A Guerriero
- Washington National Primate Research Center University of Washington Seattle, WA USA
| | - B Jarraya
- Cognitive Neuroimaging Unit, INSERM, CEA, NeuroSpin center, 91191 Gif/Yvette, France; Université Paris-Saclay, UVSQ, Foch hospital, Paris, France
| | - S Kastner
- Princeton Neuroscience Institute & Department of Psychology Princeton University Princeton, NJ USA
| | - K W Koyano
- National Institute of Mental Health NIH Bethesda MD 20892 USA
| | - D A Leopold
- National Institute of Mental Health NIH Bethesda MD 20892 USA
| | - K Murphy
- Biosciences Institute and Centre for Behaviour and Evolution, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne NE2 4HH United Kingdom UK
| | - C Poirier
- Biosciences Institute and Centre for Behaviour and Evolution, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne NE2 4HH United Kingdom UK
| | - W Pope
- Department of Radiology UCLA Los Angeles, CA 90095 USA
| | - A C Silva
- Department of Neurobiology University of Pittsburgh, Pittsburgh PA 15261 USA
| | - G Tansey
- National Eye Institute NIH Bethesda MD 20892 USA
| | - L Uhrig
- Cognitive Neuroimaging Unit, INSERM, CEA, NeuroSpin center, 91191 Gif/Yvette, France
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8
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Colman RJ, Capuano S, Bakker J, Keeley J, Nakamura K, Ross C. Marmosets: Welfare, Ethical Use, and IACUC/Regulatory Considerations. ILAR J 2020; 61:167-178. [PMID: 33620069 PMCID: PMC9214643 DOI: 10.1093/ilar/ilab003] [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: 05/15/2020] [Revised: 11/13/2020] [Accepted: 12/20/2020] [Indexed: 11/12/2022] Open
Abstract
Use of marmosets in biomedical research has increased dramatically in recent years due, in large part, to their suitability for transgenic applications and utility as models for neuroscience investigations. This increased use includes the establishment of new colonies and involvement of people new to marmoset research. To facilitate the use of the marmoset as a research model, we provide an overview of issues surrounding the ethics and regulations associated with captive marmoset research, including discussion of the history of marmosets in research, current uses of marmosets, ethical considerations related to marmoset use, issues related to importation of animals, and recommendations for regulatory oversight of gene-edited marmosets. To understand the main concerns that oversight bodies have regarding captive biomedical research with marmosets, we developed a brief, 15-question survey that was then sent electronically to academic and biomedical research institutions worldwide that were believed to house colonies of marmosets intended for biomedical research. The survey included general questions regarding the individual respondent's colony, status of research use of the colony and institutional oversight of both the colony itself and the research use of the colony. We received completed surveys from a total of 18 institutions from North America, Europe, and Asia. Overall, there appeared to be no clear difference in regulatory oversight body concerns between countries/regions. One difference that we were able to appreciate was that while biomedical research with marmosets was noted to be either stable or decreasing in Europe, use was clearly increasing elsewhere.
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Affiliation(s)
- Ricki J Colman
- Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Saverio Capuano
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jaco Bakker
- Biomedical Primate Research Centre, Rijswijk, the Netherlands
| | - Jo Keeley
- University of Cambridge, Cambridge, United Kingdom
| | | | - Corinna Ross
- Department of Life Sciences, Texas A&M University, San Antonio, Texas, USA; and Population Health, Texas Biomedical Research Institute, San Antonio, Texas, USA
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9
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Szczupak D, Yen CC, Liu C, Tian X, Lent R, Tovar-Moll F, Silva AC. Dynamic Interhemispheric Desynchronization in Marmosets and Humans With Disorders of the Corpus Callosum. Front Neural Circuits 2020; 14:612595. [PMID: 33408615 PMCID: PMC7779638 DOI: 10.3389/fncir.2020.612595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/24/2020] [Indexed: 11/13/2022] Open
Abstract
The corpus callosum, the principal structural avenue for interhemispheric neuronal communication, controls the brain's lateralization. Developmental malformations of the corpus callosum (CCD) can lead to learning and intellectual disabilities. Currently, there is no clear explanation for these symptoms. Here, we used resting-state functional MRI (rsfMRI) to evaluate the dynamic resting-state functional connectivity (rsFC) in both the cingulate cortex (CG) and the sensory areas (S1, S2, A1) in three marmosets (Callithrix jacchus) with spontaneous CCD. We also performed rsfMRI in 10 CCD human subjects (six hypoplasic and four agenesic). We observed no differences in the strength of rsFC between homotopic CG and sensory areas in both species when comparing them to healthy controls. However, in CCD marmosets, we found lower strength of quasi-periodic patterns (QPP) correlation in the posterior interhemispheric sensory areas. We also found a significant lag of interhemispheric communication in the medial CG, suggesting asynchrony between the two hemispheres. Correspondingly, in human subjects, we found that the CG of acallosal subjects had a higher QPP correlation than controls. In comparison, hypoplasic subjects had a lower QPP correlation and a delay of 1.6 s in the sensory regions. These results show that CCD affects the interhemispheric synchrony of both CG and sensory areas and that, in both species, its impact on cortical communication varies along the CC development gradient. Our study shines a light on how CCD misconnects homotopic regions and opens a line of research to explain the causes of the symptoms exhibited by CCD patients and how to mitigate them.
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Affiliation(s)
- Diego Szczupak
- Department of Neurobiology, University Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA, United States.,Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Cecil C Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Cirong Liu
- Department of Neurobiology, University Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA, United States.,Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.,Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoguang Tian
- Department of Neurobiology, University Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA, United States.,Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Roberto Lent
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.,Instituto D'Or de Pesquisa e Ensino, Rio de Janeiro, Brazil
| | - Fernanda Tovar-Moll
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.,Instituto D'Or de Pesquisa e Ensino, Rio de Janeiro, Brazil
| | - Afonso C Silva
- Department of Neurobiology, University Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA, United States.,Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
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10
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Liu C, Yen CCC, Szczupak D, Tian X, Glen D, Silva AC. Marmoset Brain Mapping V3: Population multi-modal standard volumetric and surface-based templates. Neuroimage 2020; 226:117620. [PMID: 33307224 PMCID: PMC7908070 DOI: 10.1016/j.neuroimage.2020.117620] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 10/27/2020] [Accepted: 11/28/2020] [Indexed: 12/14/2022] Open
Abstract
The standard anatomical brain template provides a common space and coordinate system for visualizing and analyzing neuroimaging data from large cohorts of subjects. Previous templates and atlases for the common marmoset brain were either based on data from a single individual or lacked essential functionalities for neuroimaging analysis. Here, we present new population-based in-vivo standard templates and tools derived from multi-modal data of 27 marmosets, including multiple types of T1w and T2w contrast images, DTI contrasts, and large field-of-view MRI and CT images. We performed multi-atlas labeling of anatomical structures on the new templates and constructed highly accurate tissue-type segmentation maps to facilitate volumetric studies. We built fully featured brain surfaces and cortical flat maps to facilitate 3D visualization and surface-based analyses, which are compatible with most surface analyzing tools, including FreeSurfer, AFNI/SUMA, and the Connectome Workbench. Analysis of the MRI and CT datasets revealed significant variations in brain shapes, sizes, and regional volumes of brain structures, highlighting substantial individual variabilities in the marmoset population. Thus, our population-based template and associated tools provide a versatile analysis platform and standard coordinate system for a wide range of MRI and connectome studies of common marmosets. These new template tools comprise version 3 of our Marmoset Brain Mapping Project and are publicly available via marmosetbrainmapping.org/v3.html.
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Affiliation(s)
- Cirong Liu
- Department of Neurobiology, University of Pittsburgh Brain Institute, 3501 Fifth Avenue, 6065 Biomedical Science Tower 3, Pittsburgh PA, USA; Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Cecil Chern-Chyi Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Diego Szczupak
- Department of Neurobiology, University of Pittsburgh Brain Institute, 3501 Fifth Avenue, 6065 Biomedical Science Tower 3, Pittsburgh PA, USA; Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Xiaoguang Tian
- Department of Neurobiology, University of Pittsburgh Brain Institute, 3501 Fifth Avenue, 6065 Biomedical Science Tower 3, Pittsburgh PA, USA; Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH), Bethesda, MD, USA
| | - Afonso C Silva
- Department of Neurobiology, University of Pittsburgh Brain Institute, 3501 Fifth Avenue, 6065 Biomedical Science Tower 3, Pittsburgh PA, USA; Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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11
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Cléry JC, Hori Y, Schaeffer DJ, Gati JS, Pruszynski JA, Everling S. Whole brain mapping of somatosensory responses in awake marmosets investigated with ultra-high-field fMRI. J Neurophysiol 2020; 124:1900-1913. [PMID: 33112698 DOI: 10.1152/jn.00480.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
The common marmoset (Callithrix jacchus) is a small-bodied New World primate that is becoming an important model to study brain functions. Despite several studies exploring the somatosensory system of marmosets, all results have come from anesthetized animals using invasive techniques and postmortem analyses. Here, we demonstrate the feasibility for getting high-quality and reproducible somatosensory mapping in awake marmosets with functional magnetic resonance imaging (fMRI). We acquired fMRI sequences in four animals, while they received tactile stimulation (via air-puffs), delivered to the face, arm, or leg. We found a topographic body representation with the leg representation in the most medial part, the face representation in the most lateral part, and the arm representation between leg and face representation within areas 3a, 3b, and 1/2. A similar sequence from leg to face from caudal to rostral sites was identified in areas S2 and PV. By generating functional connectivity maps of seeds defined in the primary and second somatosensory regions, we identified two clusters of tactile representation within the posterior and midcingulate cortex. However, unlike humans and macaques, no clear somatotopic maps were observed. At the subcortical level, we found a somatotopic body representation in the thalamus and, for the first time in marmosets, in the putamen. These maps have similar organizations, as those previously found in Old World macaque monkeys and humans, suggesting that these subcortical somatotopic organizations were already established before Old and New World primates diverged. Our results show the first whole brain mapping of somatosensory responses acquired in a noninvasive way in awake marmosets.NEW & NOTEWORTHY We used somatosensory stimulation combined with functional MRI (fMRI) in awake marmosets to reveal the topographic body representation in areas S1, S2, thalamus, and putamen. We showed the existence of a body representation organization within the thalamus and the cingulate cortex by computing functional connectivity maps from seeds defined in S1/S2, using resting-state fMRI data. This noninvasive approach will be essential for chronic studies by guiding invasive recording and manipulation techniques.
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Affiliation(s)
- Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - David J Schaeffer
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada.,Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - J Andrew Pruszynski
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada.,Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada.,Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada
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12
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Bollmann S, Barth M. New acquisition techniques and their prospects for the achievable resolution of fMRI. Prog Neurobiol 2020; 207:101936. [PMID: 33130229 DOI: 10.1016/j.pneurobio.2020.101936] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/10/2020] [Accepted: 10/18/2020] [Indexed: 01/17/2023]
Abstract
This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.
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Affiliation(s)
- Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD, Australia.
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13
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Liu C, Ye FQ, Newman JD, Szczupak D, Tian X, Yen CCC, Majka P, Glen D, Rosa MGP, Leopold DA, Silva AC. A resource for the detailed 3D mapping of white matter pathways in the marmoset brain. Nat Neurosci 2020; 23:271-280. [PMID: 31932765 PMCID: PMC7007400 DOI: 10.1038/s41593-019-0575-0] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 12/10/2019] [Indexed: 12/19/2022]
Abstract
While the fundamental importance of the white matter in supporting neuronal communication is well known, existing publications of primate brains do not feature a detailed description of its complex anatomy. The main barrier to achieving this is that existing primate neuroimaging data have insufficient spatial resolution to resolve white matter pathways fully. Here we present a resource that allows detailed descriptions of white matter structures and trajectories of fiber pathways in the marmoset brain. The resource includes: (1) the highest-resolution diffusion-weighted MRI data available to date, which reveal white matter features not previously described; (2) a comprehensive three-dimensional white matter atlas depicting fiber pathways that were either omitted or misidentified in previous atlases; and (3) comprehensive fiber pathway maps of cortical connections combining diffusion-weighted MRI tractography and neuronal tracing data. The resource, which can be downloaded from marmosetbrainmapping.org, will facilitate studies of brain connectivity and the development of tractography algorithms in the primate brain.
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Affiliation(s)
- Cirong Liu
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA.
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - John D Newman
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Section on Quantitative Imaging and Tissue Sciences, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Diego Szczupak
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
| | - Xiaoguang Tian
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
| | - Cecil Chern-Chyi Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- ARC Centre of Excellence for Integrative Brain Function, Clayton, Melbourne, Victoria, Australia
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH), Bethesda, MD, USA
| | - Marcello G P Rosa
- ARC Centre of Excellence for Integrative Brain Function, Clayton, Melbourne, Victoria, Australia
- Neuroscience Program, Monash Biomedicine Discovery Institute, Clayton, Melbourne, Victoria, Australia
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, USA
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Afonso C Silva
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA.
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14
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Bodin C, Belin P. Exploring the cerebral substrate of voice perception in primate brains. Philos Trans R Soc Lond B Biol Sci 2019; 375:20180386. [PMID: 31735143 PMCID: PMC6895549 DOI: 10.1098/rstb.2018.0386] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
One can consider human language to be the Swiss army knife of the vast domain of animal communication. There is now growing evidence suggesting that this technology may have emerged from already operational material instead of being a sudden innovation. Sharing ideas and thoughts with conspecifics via language constitutes an amazing ability, but what value would it hold if our conspecifics were not first detected and recognized? Conspecific voice (CV) perception is fundamental to communication and widely shared across the animal kingdom. Two questions that arise then are: is this apparently shared ability reflected in common cerebral substrate? And, how has this substrate evolved? The paper addresses these questions by examining studies on the cerebral basis of CV perception in humans' closest relatives, non-human primates. Neuroimaging studies, in particular, suggest the existence of a ‘voice patch system’, a network of interconnected cortical areas that can provide a common template for the cerebral processing of CV in primates. This article is part of the theme issue ‘What can animal communication teach us about human language?’
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Affiliation(s)
- Clémentine Bodin
- Institut de Neurosciences de la Timone, UMR 7289 Centre National de la Recherche Scientifique and Aix-Marseille Université, Marseille, France
| | - Pascal Belin
- Institut de Neurosciences de la Timone, UMR 7289 Centre National de la Recherche Scientifique and Aix-Marseille Université, Marseille, France.,Département de Psychologie, Université de Montréal, Montréal, Canada
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15
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Hata J. [16. Brain Mapping of Common Marmoset Using Ultra-high Magnetic Field MRI-from Structure to Function]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2019; 75:555-561. [PMID: 31217406 DOI: 10.6009/jjrt.2019_jsrt_75.6.555] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Junichi Hata
- Division of Regenerative Medicine, Jikei University School of Medicine.,RIKEN Center of Brain Science
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16
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Liu C, Yen CCC, Szczupak D, Ye FQ, Leopold DA, Silva AC. Anatomical and functional investigation of the marmoset default mode network. Nat Commun 2019; 10:1975. [PMID: 31036814 PMCID: PMC6488610 DOI: 10.1038/s41467-019-09813-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 03/27/2019] [Indexed: 11/09/2022] Open
Abstract
The default mode network (DMN) is associated with a wide range of brain functions. In humans, the DMN is marked by strong functional connectivity among three core regions: medial prefrontal cortex (mPFC), posterior parietal cortex (PPC), and the medial parietal and posterior cingulate cortex (PCC). Neuroimaging studies have shown that the DMN also exists in non-human primates, suggesting that it may be a conserved feature of the primate brain. Here, we found that, in common marmosets, the dorsolateral prefrontal cortex (dlPFC; peak at A8aD) has robust fMRI functional connectivity and reciprocal anatomical connections with the posterior DMN core regions (PPC and PCC), while the mPFC has weak connections with the posterior DMN core regions. This strong dlPFC but weak mPFC connectivity in marmoset differs markedly from the stereotypical DMN in humans. The mPFC may be involved in brain functions that are further developed in humans than in other primates.
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Affiliation(s)
- Cirong Liu
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Cecil Chern-Chyi Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Diego Szczupak
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Afonso C Silva
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
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17
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Buckner RL, Margulies DS. Macroscale cortical organization and a default-like apex transmodal network in the marmoset monkey. Nat Commun 2019; 10:1976. [PMID: 31036823 PMCID: PMC6488644 DOI: 10.1038/s41467-019-09812-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 03/28/2019] [Indexed: 12/13/2022] Open
Abstract
Networks of widely distributed regions populate human association cortex. One network, often called the default network, is positioned at the apex of a gradient of sequential networks that radiate outward from primary cortex. Here, extensive anatomical data made available through the Marmoset Brain Architecture Project are explored to show a homologue exists in marmoset. Results reveal that a gradient of networks extend outward from primary cortex to progressively higher-order transmodal association cortex in both frontal and temporal cortex. The apex transmodal network comprises frontopolar and rostral temporal association cortex, parahippocampal areas TH / TF, the ventral posterior midline, and lateral parietal association cortex. The positioning of this network in the gradient and its composition of areas make it a candidate homologue to the human default network. That the marmoset, a physiologically- and genetically-accessible primate, might possess a default-network-like candidate creates opportunities for study of higher cognitive and social functions.
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Affiliation(s)
- Randy L Buckner
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, 02138, USA.
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, Paris, 75013, France
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18
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Risser L, Sadoun A, Mescam M, Strelnikov K, Lebreton S, Boucher S, Girard P, Vayssière N, Rosa MGP, Fonta C. In vivo localization of cortical areas using a 3D computerized atlas of the marmoset brain. Brain Struct Funct 2019; 224:1957-1969. [DOI: 10.1007/s00429-019-01869-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 03/25/2019] [Indexed: 01/03/2023]
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19
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Park JE, Silva AC. Generation of genetically engineered non-human primate models of brain function and neurological disorders. Am J Primatol 2018; 81:e22931. [PMID: 30585654 DOI: 10.1002/ajp.22931] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 09/18/2018] [Accepted: 09/23/2018] [Indexed: 12/26/2022]
Abstract
Research with non-human primates (NHP) has been essential and effective in increasing our ability to find cures for a large number of diseases that cause human suffering and death. Extending the availability and use of genetic engineering techniques to NHP will allow the creation and study of NHP models of human disease, as well as broaden our understanding of neural circuits in the primate brain. With the recent development of efficient genetic engineering techniques that can be used for NHP, there's increased hope that NHP will significantly accelerate our understanding of the etiology of human neurological and neuropsychiatric disorders. In this article, we review the present state of genetic engineering tools used in NHP, from the early efforts to induce exogeneous gene expression in macaques and marmosets, to the latest results in producing germline transmission of different transgenes and the establishment of knockout lines of specific genes. We conclude with future perspectives on the further development and employment of these tools to generate genetically engineered NHP.
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Affiliation(s)
- Jung Eun Park
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Afonso C Silva
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
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20
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Arle JE, Iftimia N, Shils JL, Mei L, Carlson KW. Dynamic Computational Model of the Human Spinal Cord Connectome. Neural Comput 2018; 31:388-416. [PMID: 30576619 DOI: 10.1162/neco_a_01159] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Connectomes abound, but few for the human spinal cord. Using anatomical data in the literature, we constructed a draft connectivity map of the human spinal cord connectome, providing a template for the many calibrations of specialized behavior to be overlaid on it and the basis for an initial computational model. A thorough literature review gleaned cell types, connectivity, and connection strength indications. Where human data were not available, we selected species that have been studied. Cadaveric spinal cord measurements, cross-sectional histology images, and cytoarchitectural data regarding cell size and density served as the starting point for estimating numbers of neurons. Simulations were run using neural circuitry simulation software. The model contains the neural circuitry in all ten Rexed laminae with intralaminar, interlaminar, and intersegmental connections, as well as ascending and descending brain connections and estimated neuron counts for various cell types in every lamina of all 31 segments. We noted the presence of highly interconnected complex networks exhibiting several orders of recurrence. The model was used to perform a detailed study of spinal cord stimulation for analgesia. This model is a starting point for workers to develop and test hypotheses across an array of biomedical applications focused on the spinal cord. Each such model requires additional calibrations to constrain its output to verifiable predictions. Future work will include simulating additional segments and expanding the research uses of the model.
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Affiliation(s)
- Jeffrey E Arle
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA 02215; Department of Neurosurgery, Harvard Medical School, Boston, MA 02115; and Department of Neurosurgery, Mt. Auburn Hospital, Cambridge, MA 02138, U.S.A.
| | - Nicolae Iftimia
- Molecular Pathology Department, Massachusetts General Hospital, Charlestown, MA 02114, U.S.A.
| | - Jay L Shils
- Department of Anesthesiology, Rush Medical Center, Chicago, IL 60612, U.S.A.
| | - Longzhi Mei
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA 02215, U.S.A.
| | - Kristen W Carlson
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA 02215, U.S.A.
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21
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Atapour N, Majka P, Wolkowicz IH, Malamanova D, Worthy KH, Rosa MGP. Neuronal Distribution Across the Cerebral Cortex of the Marmoset Monkey (Callithrix jacchus). Cereb Cortex 2018; 29:3836-3863. [DOI: 10.1093/cercor/bhy263] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Revised: 09/13/2018] [Accepted: 09/19/2018] [Indexed: 01/18/2023] Open
Abstract
Abstract
Using stereological analysis of NeuN-stained sections, we investigated neuronal density and number of neurons per column throughout the marmoset cortex. Estimates of mean neuronal density encompassed a greater than 3-fold range, from >150 000 neurons/mm3 in the primary visual cortex to ~50 000 neurons/mm3 in the piriform complex. There was a trend for density to decrease from posterior to anterior cortex, but also local gradients, which resulted in a complex pattern; for example, in frontal, auditory, and somatosensory cortex neuronal density tended to increase towards anterior areas. Anterior cingulate, motor, premotor, insular, and ventral temporal areas were characterized by relatively low neuronal densities. Analysis across the depth of the cortex revealed greater laminar variation of neuronal density in occipital, parietal, and inferior temporal areas, in comparison with other regions. Moreover, differences between areas were more pronounced in the supragranular layers than in infragranular layers. Calculations of the number of neurons per unit column revealed a pattern that was distinct from that of neuronal density, including local peaks in the posterior parietal, superior temporal, precuneate, frontopolar, and temporopolar regions. These results suggest that neuronal distribution in adult cortex result from a complex interaction of developmental/ evolutionary determinants and functional requirements.
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Affiliation(s)
- Nafiseh Atapour
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, 770 Blackburn Road, Clayton, Melbourne, VIC, Australia
| | - Piotr Majka
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, 770 Blackburn Road, Clayton, Melbourne, VIC, Australia
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, Warsaw, Poland
| | - Ianina H Wolkowicz
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
| | - Daria Malamanova
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
| | - Katrina H Worthy
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
| | - Marcello G P Rosa
- Neuroscience Program, Monash Biomedicine Discovery Institute, 19 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Department of Physiology, Monash University, 26 Innovation Walk, Clayton, Melbourne, VIC, Australia
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, 770 Blackburn Road, Clayton, Melbourne, VIC, Australia
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22
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Majka P, Rosa MGP, Bai S, Chan JM, Huo BX, Jermakow N, Lin MK, Takahashi YS, Wolkowicz IH, Worthy KH, Rajan R, Reser DH, Wójcik DK, Okano H, Mitra PP. Unidirectional monosynaptic connections from auditory areas to the primary visual cortex in the marmoset monkey. Brain Struct Funct 2018; 224:111-131. [PMID: 30288557 PMCID: PMC6373361 DOI: 10.1007/s00429-018-1764-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 09/27/2018] [Indexed: 11/26/2022]
Abstract
Until the late twentieth century, it was believed that different sensory modalities were processed by largely independent pathways in the primate cortex, with cross-modal integration only occurring in specialized polysensory areas. This model was challenged by the finding that the peripheral representation of the primary visual cortex (V1) receives monosynaptic connections from areas of the auditory cortex in the macaque. However, auditory projections to V1 have not been reported in other primates. We investigated the existence of direct interconnections between V1 and auditory areas in the marmoset, a New World monkey. Labelled neurons in auditory cortex were observed following 4 out of 10 retrograde tracer injections involving V1. These projections to V1 originated in the caudal subdivisions of auditory cortex (primary auditory cortex, caudal belt and parabelt areas), and targeted parts of V1 that represent parafoveal and peripheral vision. Injections near the representation of the vertical meridian of the visual field labelled few or no cells in auditory cortex. We also placed 8 retrograde tracer injections involving core, belt and parabelt auditory areas, none of which revealed direct projections from V1. These results confirm the existence of a direct, nonreciprocal projection from auditory areas to V1 in a different primate species, which has evolved separately from the macaque for over 30 million years. The essential similarity of these observations between marmoset and macaque indicate that early-stage audiovisual integration is a shared characteristic of primate sensory processing.
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Affiliation(s)
- Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093, Warsaw, Poland
- Monash University Node, Australian Research Council, Centre of Excellence for Integrative Brain Function, Clayton, VIC, 3800, Australia
| | - Marcello G P Rosa
- Monash University Node, Australian Research Council, Centre of Excellence for Integrative Brain Function, Clayton, VIC, 3800, Australia.
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia.
| | - Shi Bai
- Monash University Node, Australian Research Council, Centre of Excellence for Integrative Brain Function, Clayton, VIC, 3800, Australia
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia
| | - Jonathan M Chan
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia
| | - Bing-Xing Huo
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, 351-0106, Japan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Natalia Jermakow
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093, Warsaw, Poland
| | - Meng K Lin
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, 351-0106, Japan
| | - Yeonsook S Takahashi
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, 351-0106, Japan
| | - Ianina H Wolkowicz
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia
| | - Katrina H Worthy
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia
| | - Ramesh Rajan
- Monash University Node, Australian Research Council, Centre of Excellence for Integrative Brain Function, Clayton, VIC, 3800, Australia
- Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC, 3800, Australia
| | - David H Reser
- School of Rural Health, Monash University, Churchill, VIC, 3842, Australia
| | - Daniel K Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 02-093, Warsaw, Poland
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, 351-0106, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Partha P Mitra
- Monash University Node, Australian Research Council, Centre of Excellence for Integrative Brain Function, Clayton, VIC, 3800, Australia.
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, 351-0106, Japan.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA.
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23
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Workman KP, Healey B, Carlotto A, Lacreuse A. One-year change in cognitive flexibility and fine motor function in middle-aged male and female marmosets (Callithrix jacchus). Am J Primatol 2018; 81:e22924. [PMID: 30281810 DOI: 10.1002/ajp.22924] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 09/07/2018] [Accepted: 09/08/2018] [Indexed: 11/07/2022]
Abstract
The common marmoset (Callithrix jacchus) is uniquely suited for longitudinal studies of cognitive aging, due to a relatively short lifespan, sophisticated cognitive abilities, and patterns of brain aging that resemble those of humans. We examined cognitive function and fine motor skills in male and female marmosets (mean age ∼5 at study entry) followed longitudinally for 2 years. Each year, monkeys were tested on a reversal learning task with three pairs of stimuli (n = 18, 9 females) and a fine motor task requiring them to grasp small rewards from two staircases (Hill and Valley test, n = 12, 6 females). There was little evidence for a decline in cognitive flexibility between the two time points, in part because of practice effects. However, independent of year of testing, females took longer than males to reach criterion in the reversals, indicating impaired cognitive flexibility. Motivation was unlikely to contribute to this effect, as males refused a greater percentage of trials than females in the reversals. With regards to motor function, females were significantly faster than males in the Hill and Valley task. From Year 1 to Year 2, a slight slowing of motor function was observed in both sexes, but accuracy decreased significantly in males only. This study (1) demonstrates that marmosets exhibit sex differences in cognitive flexibility and fine motor function that resemble those described in humans; (2) that changes in fine motor function can already be detected at middle-age; and (3) that males may experience greater age-related changes in fine motor skills than females. Additional data points will determine whether these sex and age differences persist over time.
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Affiliation(s)
- Kathryn P Workman
- Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, Massachusetts
| | - Brianna Healey
- Neuroscience and Behavior Graduate Program, University of Massachusetts, Amherst, Massachusetts
| | - Alyssa Carlotto
- Neuroscience and Behavior Graduate Program, University of Massachusetts, Amherst, Massachusetts
| | - Agnès Lacreuse
- Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, Massachusetts.,Neuroscience and Behavior Graduate Program, University of Massachusetts, Amherst, Massachusetts.,Center for Neuroendocrine Studies, University of Massachusetts, Amherst, Massachusetts
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24
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Miller CT. Why marmosets? Dev Neurobiol 2018; 77:237-243. [PMID: 28170158 DOI: 10.1002/dneu.22483] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Revised: 01/05/2017] [Accepted: 01/05/2017] [Indexed: 12/17/2022]
Affiliation(s)
- Cory T Miller
- Cortical Systems and Behavior Laboratory, Neurosciences Graduate Program, University of California, San Diego, California
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25
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A "voice patch" system in the primate brain for processing vocal information? Hear Res 2018; 366:65-74. [PMID: 29776691 DOI: 10.1016/j.heares.2018.04.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 04/14/2018] [Accepted: 04/25/2018] [Indexed: 12/13/2022]
Abstract
We review behavioural and neural evidence for the processing of information contained in conspecific vocalizations (CVs) in three primate species: humans, macaques and marmosets. We focus on abilities that are present and ecologically relevant in all three species: the detection and sensitivity to CVs; and the processing of identity cues in CVs. Current evidence, although fragmentary, supports the notion of a "voice patch system" in the primate brain analogous to the face patch system of visual cortex: a series of discrete, interconnected cortical areas supporting increasingly abstract representations of the vocal input. A central question concerns the degree to which the voice patch system is conserved in evolution. We outline challenges that arise and suggesting potential avenues for comparing the organization of the voice patch system across primate brains.
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26
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Liu C, Ye FQ, Yen CCC, Newman JD, Glen D, Leopold DA, Silva AC. A digital 3D atlas of the marmoset brain based on multi-modal MRI. Neuroimage 2018; 169:106-116. [PMID: 29208569 PMCID: PMC5856608 DOI: 10.1016/j.neuroimage.2017.12.004] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 11/28/2017] [Accepted: 12/01/2017] [Indexed: 11/26/2022] Open
Abstract
The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets.
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Affiliation(s)
- Cirong Liu
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Cecil Chern-Chyi Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - John D Newman
- Laboratory of Comparative Ethology, Eunice Kennedy Shriver, National Institute of Child Health and Human Development, National Institutes of Health, Poolesville, MD 20837, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH), Bethesda, MD 20892, USA
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA; Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, Bethesda, MD 20892-4400, USA
| | - Afonso C Silva
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
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27
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Le Gal R, Bernaudin M, Toutain J, Touzani O. Assessment of behavioural deficits following ischaemic stroke in the marmoset. Behav Brain Res 2017; 352:151-160. [PMID: 28760698 DOI: 10.1016/j.bbr.2017.07.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 07/11/2017] [Accepted: 07/27/2017] [Indexed: 11/29/2022]
Abstract
Stroke is a common and devastating disease worldwide. Over the last two decades, many therapeutic approaches to ameliorate ischaemic stroke have been promising in animal studies but failed when transferred to the clinical situation. One of the possible explanations for these failures is the widespread use of animal models of cerebral ischemia that do not mimic the pathology encountered in the clinic. Accordingly, many expert committees recommended the integration of higher order species such as non-human primates in pre-clinical stroke studies. The common marmoset (Callithrix jacchus), a small New World monkey, start to stand out in the neuroscience field as a good compromise between larger primates and rodents. In this review, we discuss the relevance of the use of the marmoset in stroke studies. We will focus on behavioural tests developed in this species to assess sensorimotor deficits and their recovery during acute and chronic stages of brain ischaemia. The aim of this appraisal is to provide a comprehensive overview of the existing approaches to induce stroke in the marmoset as well as the paradigms for behavioural testing in this species. The data summarized in this review should contribute to the improvement of future stoke studies in the marmoset and accordingly improve the translation of the results from bench to bed.
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Affiliation(s)
- Rozenn Le Gal
- Normandie-Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, Caen, France
| | - Myriam Bernaudin
- Normandie-Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, Caen, France
| | - Jérôme Toutain
- Normandie-Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, Caen, France
| | - Omar Touzani
- Normandie-Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, Caen, France.
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