1
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Muta K, Haga Y, Hata J, Kaneko T, Hagiya K, Komaki Y, Seki F, Yoshimaru D, Nakae K, Woodward A, Gong R, Kishi N, Okano H. Commonality and variance of resting-state networks in common marmoset brains. Sci Rep 2024; 14:8316. [PMID: 38594386 PMCID: PMC11004137 DOI: 10.1038/s41598-024-58799-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 04/03/2024] [Indexed: 04/11/2024] Open
Abstract
Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrix jacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases.
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Affiliation(s)
- Kanako Muta
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
| | - Yawara Haga
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
- Live Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
- Live Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
- Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, Japan
| | - Takaaki Kaneko
- Division of Behavioral Development, Department of System Neuroscience, National Institute for Physiological Science, Aichi, Japan
| | - Kei Hagiya
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
| | - Yuji Komaki
- Live Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Fumiko Seki
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
- Live Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Daisuke Yoshimaru
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
- Live Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
- Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, Japan
| | - Ken Nakae
- Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Aichi, Japan
| | - Alexander Woodward
- Connectome Analysis Unit, Center for Brain Science, RIKEN, Saitama, Japan
| | - Rui Gong
- Connectome Analysis Unit, Center for Brain Science, RIKEN, Saitama, Japan
| | - Noriyuki Kishi
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Saitama, Japan.
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan.
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2
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Okuno T, Ichinohe N, Woodward A. A reappraisal of the default mode and frontoparietal networks in the common marmoset brain. FRONTIERS IN NEUROIMAGING 2024; 2:1345643. [PMID: 38264540 PMCID: PMC10803424 DOI: 10.3389/fnimg.2023.1345643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 12/20/2023] [Indexed: 01/25/2024]
Abstract
In recent years the common marmoset homolog of the human default mode network (DMN) has been a hot topic of discussion in the marmoset research field. Previously, the posterior cingulate cortex regions (PGM, A19M) and posterior parietal cortex regions (LIP, MIP) were defined as the DMN, but some studies claim that these form the frontoparietal network (FPN). We restarted from a neuroanatomical point of view and identified two DMN candidates: Comp-A (which has been called both the DMN and FPN) and Comp-B. We performed GLM analysis on auditory task-fMRI and found Comp-B to be more appropriate as the DMN, and Comp-A as the FPN. Additionally, through fingerprint analysis, a DMN and FPN in the tasking human was closer to the resting common marmoset. The human DMN appears to have an advanced function that may be underdeveloped in the common marmoset brain.
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Affiliation(s)
- Takuto Okuno
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Noritaka Ichinohe
- Laboratory for Ultrastructure Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Alexander Woodward
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
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3
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Sengupta A, Wang F, Mishra A, Reed JL, Chen LM, Gore JC. Detection and characterization of resting state functional networks in squirrel monkey brain. Cereb Cortex Commun 2023; 4:tgad018. [PMID: 37753115 PMCID: PMC10518810 DOI: 10.1093/texcom/tgad018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 09/28/2023] Open
Abstract
Resting-state fMRI based on analyzing BOLD signals is widely used to derive functional networks in the brain and how they alter during disease or injury conditions. Resting-state networks can also be used to study brain functional connectomes across species, which provides insights into brain evolution. The squirrel monkey (SM) is a non-human primate (NHP) that is widely used as a preclinical model for experimental manipulations to understand the organization and functioning of the brain. We derived resting-state networks from the whole brain of anesthetized SMs using Independent Component Analysis of BOLD acquisitions. We detected 15 anatomically constrained resting-state networks localized in the cortical and subcortical regions as well as in the white-matter. Networks encompassing visual, somatosensory, executive control, sensorimotor, salience and default mode regions, and subcortical networks including the Hippocampus-Amygdala, thalamus, basal-ganglia and brainstem region correspond well with previously detected networks in humans and NHPs. The connectivity pattern between the networks also agrees well with previously reported seed-based resting-state connectivity of SM brain. This study demonstrates that SMs share remarkable homologous network organization with humans and other NHPs, thereby providing strong support for their suitability as a translational animal model for research and additional insight into brain evolution across species.
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Affiliation(s)
- Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Jamie L Reed
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Department of Psychology, Vanderbilt University, Nashville, TN, United States of America
| | - Li Min Chen
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Biomedical Engineering, Vanderbilt University, Nashville, TN, United States of America
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Nashville, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
- Biomedical Engineering, Vanderbilt University, Nashville, TN, United States of America
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States of America
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4
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Giacometti C, Amiez C, Hadj-Bouziane F. Multiple routes of communication within the amygdala-mPFC network: A comparative approach in humans and macaques. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100103. [PMID: 37601951 PMCID: PMC10432920 DOI: 10.1016/j.crneur.2023.100103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 06/14/2023] [Accepted: 07/15/2023] [Indexed: 08/22/2023] Open
Abstract
The network formed by the amygdala (AMG) and the medial Prefrontal Cortex (mPFC), at the interface between our internal and external environment, has been shown to support some important aspects of behavioral adaptation. Whether and how the anatomo-functional organization of this network evolved across primates remains unclear. Here, we compared AMG nuclei morphological characteristics and their functional connectivity with the mPFC in humans and macaques to identify potential homologies and differences between these species. Based on selected studies, we highlight two subsystems within the AMG-mPFC circuits, likely involved in distinct temporal dynamics of integration during behavioral adaptation. We also show that whereas the mPFC displays a large expansion but a preserved intrinsic anatomo-functional organization, the AMG displays a volume reduction and morphological changes related to specific nuclei. We discuss potential commonalities and differences in the dialogue between AMG nuclei and mPFC in humans and macaques based on available data.
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Affiliation(s)
- C. Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - C. Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - F. Hadj-Bouziane
- Integrative Multisensory Perception Action & Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), University of Lyon 1, Lyon, France
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5
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Jafari A, Dureux A, Zanini A, Menon RS, Gilbert KM, Everling S. A vocalization-processing network in marmosets. Cell Rep 2023; 42:112526. [PMID: 37195863 DOI: 10.1016/j.celrep.2023.112526] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/31/2023] [Accepted: 05/02/2023] [Indexed: 05/19/2023] Open
Abstract
Vocalizations play an important role in the daily life of primates and likely form the basis of human language. Functional imaging studies have demonstrated that listening to voices activates a fronto-temporal voice perception network in human participants. Here, we acquired whole-brain ultrahigh-field (9.4 T) fMRI in awake marmosets (Callithrix jacchus) and demonstrate that these small, highly vocal New World primates possess a similar fronto-temporal network, including subcortical regions, that is activated by the presentation of conspecific vocalizations. The findings suggest that the human voice perception network has evolved from an ancestral vocalization-processing network that predates the separation of New and Old World primates.
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Affiliation(s)
- Azadeh Jafari
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Audrey Dureux
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Alessandro Zanini
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Kyle M Gilbert
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada.
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6
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Ngo GN, Hori Y, Everling S, Menon RS. Joint-embeddings reveal functional differences in default-mode network architecture between marmosets and humans. Neuroimage 2023; 272:120035. [PMID: 36948281 DOI: 10.1016/j.neuroimage.2023.120035] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/30/2022] [Accepted: 03/14/2023] [Indexed: 03/24/2023] Open
Abstract
The default-mode network (DMN) is a distributed functional brain system integral for social and higher-order cognition in humans with implications in a myriad of neuropsychological disorders. In this study, we compared the functional architecture of the DMN between humans and marmosets to assess their similarities and differences using joint gradients. This approach permits simultaneous large-scale mapping of functional systems across the cortex of humans and marmosets, revealing evidence of putative homologies between them. In doing so, we find that the DMN architecture of the marmoset exhibits differences along its anterolateral-posterior axis. Specifically, the anterolateral node of the DMN (dorsolateral prefrontal cortex) displayed weak connections and inconsistent connection topographies as compared to its posterior DMN-nodes (posterior cingulate and posterior parietal cortices). We also present evidence that the marmoset medial prefrontal cortex and temporal lobe areas correspond to other macroscopical distributed functional systems that are not part of the DMN. Given the importance of the marmoset as a pre-clinical primate model for higher-order cognitive functioning and the DMN's relevance to cognition, our results suggest that the marmoset may lack the capacity to integrate neural information to subserve cortical dynamics that is necessary for supporting diverse cognitive demands.
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Affiliation(s)
- Geoffrey N Ngo
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Functional Brain Imaging, National Institutes of Quantum and Radiological Science and Technology, Chiba 263-8555, Japan
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Ravi S Menon
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada.; Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada.
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7
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Representations and decodability of diverse cognitive functions are preserved across the human cortex, cerebellum, and subcortex. Commun Biol 2022; 5:1245. [PMCID: PMC9663596 DOI: 10.1038/s42003-022-04221-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 11/03/2022] [Indexed: 11/16/2022] Open
Abstract
AbstractWhich part of the brain contributes to our complex cognitive processes? Studies have revealed contributions of the cerebellum and subcortex to higher-order cognitive functions; however, it has been unclear whether such functional representations are preserved across the cortex, cerebellum, and subcortex. In this study, we use functional magnetic resonance imaging data with 103 cognitive tasks and construct three voxel-wise encoding and decoding models independently using cortical, cerebellar, and subcortical voxels. Representational similarity analysis reveals that the structure of task representations is preserved across the three brain parts. Principal component analysis visualizes distinct organizations of abstract cognitive functions in each part of the cerebellum and subcortex. More than 90% of the cognitive tasks are decodable from the cerebellum and subcortical activities, even for the novel tasks not included in model training. Furthermore, we show that the cerebellum and subcortex have sufficient information to reconstruct activity in the cerebral cortex.
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8
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Zhang X. Effects of Anesthesia on Cerebral Blood Flow and Functional Connectivity of Nonhuman Primates. Vet Sci 2022; 9:vetsci9100516. [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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9
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Samandra R, Haque ZZ, Rosa MGP, Mansouri FA. The marmoset as a model for investigating the neural basis of social cognition in health and disease. Neurosci Biobehav Rev 2022; 138:104692. [PMID: 35569579 DOI: 10.1016/j.neubiorev.2022.104692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/05/2022] [Accepted: 05/09/2022] [Indexed: 01/23/2023]
Abstract
Social-cognitive processes facilitate the use of environmental cues to understand others, and to be understood by others. Animal models provide vital insights into the neural underpinning of social behaviours. To understand social cognition at even deeper behavioural, cognitive, neural, and molecular levels, we need to develop more representative study models, which allow testing of novel hypotheses using human-relevant cognitive tasks. Due to their cooperative breeding system and relatively small size, common marmosets (Callithrix jacchus) offer a promising translational model for such endeavours. In addition to having social behavioural patterns and group dynamics analogous to those of humans, marmosets have cortical brain areas relevant for the mechanistic analysis of human social cognition, albeit in simplified form. Thus, they are likely suitable animal models for deciphering the physiological processes, connectivity and molecular mechanisms supporting advanced cognitive functions. Here, we review findings emerging from marmoset social and behavioural studies, which have already provided significant insights into executive, motivational, social, and emotional dysfunction associated with neurological and psychiatric disorders.
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Affiliation(s)
- Ranshikha Samandra
- Cognitive Neuroscience Laboratory, Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Zakia Z Haque
- Cognitive Neuroscience Laboratory, Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Marcello G P Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia; ARC Centre for Integrative Brain Function, Monash University, Australia.
| | - Farshad Alizadeh Mansouri
- Cognitive Neuroscience Laboratory, Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia; ARC Centre for Integrative Brain Function, Monash University, Australia.
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10
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Guilbert J, Légaré A, De Koninck P, Desrosiers P, Desjardins M. Toward an integrative neurovascular framework for studying brain networks. NEUROPHOTONICS 2022; 9:032211. [PMID: 35434179 PMCID: PMC8989057 DOI: 10.1117/1.nph.9.3.032211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 03/11/2022] [Indexed: 05/28/2023]
Abstract
Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.
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Affiliation(s)
- Jérémie Guilbert
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
| | - Antoine Légaré
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Paul De Koninck
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Patrick Desrosiers
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
| | - Michèle Desjardins
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
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11
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Dvořáková L, Stenroos P, Paasonen E, Salo RA, Paasonen J, Gröhn O. Light sedation with short habituation time for large-scale functional magnetic resonance imaging studies in rats. NMR IN BIOMEDICINE 2022; 35:e4679. [PMID: 34961988 PMCID: PMC9285600 DOI: 10.1002/nbm.4679] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 12/14/2021] [Accepted: 12/15/2021] [Indexed: 06/14/2023]
Abstract
Traditionally, preclinical resting state functional magnetic resonance imaging (fMRI) studies have been performed in anesthetized animals. Nevertheless, as anesthesia affects the functional connectivity (FC) in the brain, there has been a growing interest in imaging in the awake state. Obviously, awake imaging requires resource- and time-consuming habituation prior to data acquisition to reduce the stress and motion of the animals. Light sedation has been a less widely exploited alternative for awake imaging, requiring shorter habituation times, while still reducing the effect of anesthesia. Here, we imaged 102 rats under light sedation and 10 awake animals to conduct an FC analysis. We established an automated data-processing pipeline suitable for both groups. Additionally, the same pipeline was used on data obtained from an openly available awake rat database (289 measurements in 90 rats). The FC pattern in the light sedation measurements closely resembled the corresponding patterns in both onsite and offsite awake datasets. However, fewer datasets had to be excluded due to movement in rats with light sedation. The temporal analysis of FC in the lightly sedated group indicated a lingering effect of anesthesia that stabilized after the first 5 min. In summary, our results indicate that the light sedation protocol is a valid alternative for large-scale studies where awake protocols may become prohibitively resource-demanding, as it provides similar results to awake imaging, preserves more scans, and requires shorter habituation times. The large amount of fMRI data obtained in this work are openly available for further analyses.
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Affiliation(s)
- Lenka Dvořáková
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
| | - Petteri Stenroos
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
- Grenoble Institut des NeurosciencesUniversité Grenoble AlpesGrenobleFrance
| | - Ekaterina Paasonen
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
| | - Raimo A. Salo
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
| | - Jaakko Paasonen
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
| | - Olli Gröhn
- A. I. V. Institute for Molecular SciencesUniversity of Eastern FinlandKuopioFinland
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12
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Cortico-subcortical interactions in overlapping communities of edge functional connectivity. Neuroimage 2022; 250:118971. [PMID: 35131435 PMCID: PMC9903436 DOI: 10.1016/j.neuroimage.2022.118971] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 01/25/2022] [Accepted: 02/03/2022] [Indexed: 02/01/2023] Open
Abstract
Both cortical and subcortical regions can be functionally organized into networks. Regions of the basal ganglia are extensively interconnected with the cortex via reciprocal connections that relay and modulate cortical function. Here we employ an edge-centric approach, which computes co-fluctuations among region pairs in a network to investigate the role and interaction of subcortical regions with cortical systems. By clustering edges into communities, we show that cortical systems and subcortical regions couple via multiple edge communities, with hippocampus and amygdala having a distinct pattern from striatum and thalamus. We show that the edge community structure of cortical networks is highly similar to one obtained from cortical nodes when the subcortex is present in the network. Additionally, we show that the edge community profile of both cortical and subcortical nodes can be estimates solely from cortico-subcortical interactions. Finally, we used a motif analysis focusing on edge community triads where a subcortical region coupled to two cortical regions and found that two community triads where one community couples the subcortex to the cortex were overrepresented. In summary, our results show organized coupling of the subcortex to the cortex that may play a role in cortical organization of primary sensorimotor/attention and heteromodal systems and puts forth the motif analysis of edge community triads as a promising method for investigation of communication patterns in networks.
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13
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Abstract
Social cognition is a dynamic process that requires the perception and integration of a complex set of idiosyncratic features between interacting conspecifics. Here we present a method for simultaneously measuring the whole-brain activation of two socially interacting marmoset monkeys using functional magnetic resonance imaging. MRI hardware (a radiofrequency coil and peripheral devices) and image-processing pipelines were developed to assess brain responses to socialization, both on an intra-brain and inter-brain level. Notably, the brain activation of a marmoset when viewing a second marmoset in-person versus when viewing a pre-recorded video of the same marmoset-i.e., when either capable or incapable of socially interacting with a visible conspecific-demonstrates increased activation in the face-patch network. This method enables a wide range of possibilities for potentially studying social function and dysfunction in a non-human primate model.
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14
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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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15
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Hori Y, Cléry JC, Schaeffer DJ, Menon RS, Everling S. Functional Organization of Frontoparietal Cortex in the Marmoset Investigated with Awake Resting-State fMRI. Cereb Cortex 2021; 32:1965-1977. [PMID: 34515315 DOI: 10.1093/cercor/bhab328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/13/2021] [Accepted: 08/14/2021] [Indexed: 11/12/2022] Open
Abstract
Frontoparietal networks contribute to complex cognitive functions in humans and macaques, such as working memory, attention, task-switching, response suppression, grasping, reaching, and eye movement control. However, there has been no comprehensive examination of the functional organization of frontoparietal networks using functional magnetic resonance imaging in the New World common marmoset monkey (Callithrix jacchus), which is now widely recognized as a powerful nonhuman primate experimental animal. In this study, we employed hierarchical clustering of interareal blood oxygen level-dependent signals to investigate the hypothesis that the organization of the frontoparietal cortex in the marmoset follows the organizational principles of the macaque frontoparietal system. We found that the posterior part of the lateral frontal cortex (premotor regions) was functionally connected to the anterior parietal areas, while more anterior frontal regions (frontal eye field [FEF]) were connected to more posterior parietal areas (the region around the lateral intraparietal area [LIP]). These overarching patterns of interareal organization are consistent with a recent macaque study. These findings demonstrate parallel frontoparietal processing streams in marmosets and support the functional similarities of FEF-LIP and premotor-anterior parietal pathways between marmoset and macaque.
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Affiliation(s)
- Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada.,Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario N6A 5C1, Canada
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