1
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function. J Neurophysiol 2024; 131:1014-1082. [PMID: 38489238 DOI: 10.1152/jn.00308.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development.NEW & NOTEWORTHY The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Aihuiping Xue
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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2
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Selvanayagam J, Johnston KD, Everling S. Laminar Dynamics of Target Selection in the Posterior Parietal Cortex of the Common Marmoset. J Neurosci 2024; 44:e1583232024. [PMID: 38627088 PMCID: PMC11112649 DOI: 10.1523/jneurosci.1583-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 04/02/2024] [Accepted: 04/06/2024] [Indexed: 05/24/2024] Open
Abstract
The lateral intraparietal area (LIP) plays a crucial role in target selection and attention in primates, but the laminar microcircuitry of this region is largely unknown. To address this, we used ultra-high density laminar electrophysiology with Neuropixels probes to record neural activity in the posterior parietal cortex (PPC) of two adult marmosets while they performed a simple visual target selection task. Our results reveal neural correlates of visual target selection in the marmoset, similar to those observed in macaques and humans, with distinct timing and profiles of activity across cell types and cortical layers. Notably, a greater proportion of neurons exhibited stimulus-related activity in superficial layers whereas a greater proportion of infragranular neurons exhibited significant postsaccadic activity. Stimulus-related activity was first observed in granular layer putative interneurons, whereas target discrimination activity emerged first in supragranular layers putative pyramidal neurons, supporting a canonical laminar circuit underlying visual target selection in marmoset PPC. These findings provide novel insights into the neural basis of visual attention and target selection in primates.
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Affiliation(s)
- Janahan Selvanayagam
- Graduate Program in Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Center for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
| | - Kevin D Johnston
- Center for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Center for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
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3
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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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4
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Coop SH, Yates JL, Mitchell JF. Pre-saccadic Neural Enhancements in Marmoset Area MT. J Neurosci 2024; 44:e2034222023. [PMID: 38050176 PMCID: PMC10860570 DOI: 10.1523/jneurosci.2034-22.2023] [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: 10/31/2022] [Revised: 09/15/2023] [Accepted: 11/20/2023] [Indexed: 12/06/2023] Open
Abstract
Each time we make an eye movement, attention moves before the eyes, resulting in a perceptual enhancement at the target. Recent psychophysical studies suggest that this pre-saccadic attention enhances the visual features at the saccade target, whereas covert attention causes only spatially selective enhancements. While previous nonhuman primate studies have found that pre-saccadic attention does enhance neural responses spatially, no studies have tested whether changes in neural tuning reflect an automatic feature enhancement. Here we examined pre-saccadic attention using a saccade foraging task developed for marmoset monkeys (one male and one female). We recorded from neurons in the middle temporal area with peripheral receptive fields that contained a motion stimulus, which would either be the target of a saccade or a distracter as a saccade was made to another location. We established that marmosets, like macaques, show enhanced pre-saccadic neural responses for saccades toward the receptive field, including increases in firing rate and motion information. We then examined if the specific changes in neural tuning might support feature enhancements for the target. Neurons exhibited diverse changes in tuning but predominantly showed additive and multiplicative increases that were uniformly applied across motion directions. These findings confirm that marmoset monkeys, like macaques, exhibit pre-saccadic neural enhancements during saccade foraging tasks with minimal training requirements. However, at the level of individual neurons, the lack of feature-tuned enhancements is similar to neural effects reported during covert spatial attention.
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Affiliation(s)
- Shanna H Coop
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
| | - Jacob L Yates
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
- Department of Biology, University of Maryland College Park, College Park, Maryland, 20742-5025
| | - Jude F Mitchell
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
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5
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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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6
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552437. [PMID: 37609246 PMCID: PMC10441314 DOI: 10.1101/2023.08.08.552437] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Aihuiping Xue
- Centre for Sleep & Cognition & Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition & Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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7
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Santana NNM, Silva EHA, dos Santos SF, Costa MSMO, Nascimento Junior ES, Engelberth RCJG, Cavalcante JS. Retinorecipient areas in the common marmoset ( Callithrix jacchus): An image-forming and non-image forming circuitry. Front Neural Circuits 2023; 17:1088686. [PMID: 36817647 PMCID: PMC9932520 DOI: 10.3389/fncir.2023.1088686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 01/10/2023] [Indexed: 02/05/2023] Open
Abstract
The mammalian retina captures a multitude of diverse features from the external environment and conveys them via the optic nerve to a myriad of retinorecipient nuclei. Understanding how retinal signals act in distinct brain functions is one of the most central and established goals of neuroscience. Using the common marmoset (Callithrix jacchus), a monkey from Northeastern Brazil, as an animal model for parsing how retinal innervation works in the brain, started decades ago due to their marmoset's small bodies, rapid reproduction rate, and brain features. In the course of that research, a large amount of new and sophisticated neuroanatomical techniques was developed and employed to explain retinal connectivity. As a consequence, image and non-image-forming regions, functions, and pathways, as well as retinal cell types were described. Image-forming circuits give rise directly to vision, while the non-image-forming territories support circadian physiological processes, although part of their functional significance is uncertain. Here, we reviewed the current state of knowledge concerning retinal circuitry in marmosets from neuroanatomical investigations. We have also highlighted the aspects of marmoset retinal circuitry that remain obscure, in addition, to identify what further research is needed to better understand the connections and functions of retinorecipient structures.
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Affiliation(s)
- Nelyane Nayara M. Santana
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Eryck H. A. Silva
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Sâmarah F. dos Santos
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Miriam S. M. O. Costa
- Laboratory of Neuroanatomy, Department of Morphology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Expedito S. Nascimento Junior
- Laboratory of Neuroanatomy, Department of Morphology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Rovena Clara J. G. Engelberth
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Jeferson S. Cavalcante
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil,*Correspondence: Jeferson S. Cavalcante,
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8
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Saghravanian SJ, Asadollahi A. Acclimatizing and training freely viewing marmosets for behavioral and electrophysiological experiments in oculomotor tasks. Physiol Rep 2023; 11:e15594. [PMID: 36754454 PMCID: PMC9908434 DOI: 10.14814/phy2.15594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 01/10/2023] [Accepted: 01/13/2023] [Indexed: 06/18/2023] Open
Abstract
The marmoset is a small-bodied primate with behavioral capacities and brain structures comparable to macaque monkeys and humans. Its amenability to modern biotechnological techniques like optogenetics, chemogenetics, and generation of transgenic primates have attracted neuroscientists' attention to use it as a model in neuroscience. In the past decade, several laboratories have been developing and refining tools and techniques for performing behavioral and electrophysiological experiments in this new model. In this regard, we developed a protocol to acclimate the marmoset to sit calmly in a primate chair; a method to calibrate the eye-tracking system while marmosets were freely viewing the screen; and a procedure to map motor field of neurons in the SC in freely viewing marmosets. Using a squeeze-walled transfer box, the animals were acclimatized, and chair trained in less than 4 weeks, much shorter than what other studies reported. Using salient stimuli allowed quick and accurate calibration of the eye-tracking system in untrained freely viewing marmosets. Applying reverse correlation to spiking activity and saccadic eye movements, we were able to map motor field of SC neurons in freely viewing marmosets. These refinements shortened the acclimation period, most likely reduced stress to the subjects, and allowed more efficient eye calibration and motor field mapping in freely viewing marmosets. With a penetration angle of 38 degrees, all 16 channels of the electrode array, that is, all recorded neurons across SC layers, had overlapping visual receptive and motor fields, indicating perpendicular penetration to the SC.
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Affiliation(s)
| | - Ali Asadollahi
- Visuo‐Motor Systems Laboratory, Department of BiologyFerdowsi University of MashhadMashhadIran
- Present address:
Washington National Primate Research Center, and Department of Biological StructuresUniversity of WashingtonSeattleWAUSA
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9
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Liu W, Zeng LL, Shen H, Zhou ZT, Hu D. Functional orderly topography of brain networks associated with gene expression heterogeneity. Commun Biol 2022; 5:1083. [PMID: 36220938 PMCID: PMC9554040 DOI: 10.1038/s42003-022-04039-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 09/27/2022] [Indexed: 11/09/2022] Open
Abstract
The human cerebral cortex is vastly expanded relative to nonhuman primates and rodents, leading to a functional orderly topography of brain networks. Here, we show that functional topography may be associated with gene expression heterogeneity. The neocortex exhibits greater heterogeneity in gene expression, with a lower expression of housekeeping genes, a longer mean path length, fewer clusters, and a lower degree of ordering in networks than archicortical and subcortical areas in human, rhesus macaque, and mouse brains. In particular, the cerebellar cortex displays greater heterogeneity in gene expression than cerebellar deep nuclei in the human brain, but not in the mouse brain, corresponding to the emergence of novel functions in the human cerebellar cortex. Moreover, the cortical areas with greater heterogeneity, primarily located in the multimodal association cortex, tend to express genes with higher evolutionary rates and exhibit a higher degree of functional connectivity measured by resting-state fMRI, implying that such a spatial distribution of gene expression may be shaped by evolution and is favourable for the specialization of higher cognitive functions. Together, the cross-species imaging and genetic findings may provide convergent evidence to support the association between the orderly topography of brain function networks and gene expression. Comparative analysis of human, macaque and mouse function and genetic heterogeneity in the brain reveals links between gene expression and orderly topography of functional networks.
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Affiliation(s)
- Wei Liu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China
| | - Zong-Tan Zhou
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China.
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10
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Zhang X, Maltbie EA, Keilholz SD. Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder. Neuroimage 2021; 244:118588. [PMID: 34607021 PMCID: PMC8637345 DOI: 10.1016/j.neuroimage.2021.118588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/15/2021] [Accepted: 09/16/2021] [Indexed: 11/23/2022] Open
Abstract
Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.
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Affiliation(s)
- Xiaodi Zhang
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building, 1760 Haygood Drive, SuiteW200, Atlanta, GA, 30322, USA.
| | - Eric A Maltbie
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building, 1760 Haygood Drive, SuiteW200, Atlanta, GA, 30322, USA.
| | - Shella D Keilholz
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building, 1760 Haygood Drive, SuiteW200, Atlanta, GA, 30322, USA.
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11
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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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12
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Du J, Buckner RL. Precision Estimates of Macroscale Network Organization in the Human and Their Relation to Anatomical Connectivity in the Marmoset Monkey. Curr Opin Behav Sci 2021; 40:144-152. [PMID: 34722833 DOI: 10.1016/j.cobeha.2021.04.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Precision estimates of network organization from functional connectivity MRI in the human and tract-tracing data in the marmoset monkey converge to reveal an orderly macroscale gradient of sequential networks across the cerebral cortex. Parallel networks begin with a sequence of multiple nested sensory-motor networks in both species progressing to more distributed association networks in rostral prefrontal and temporal association zones, which are expanded and differentiated in the human. From this perspective, the spatially-distributed motif encountered in association networks appears to be on a continuum with primary sensory-motor networks. Network motifs supporting sophisticated forms of human cognition may arise from specializations of distributed anatomical networks formed in an ancestor at least 45 million years ago.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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13
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D'Souza JF, Price NSC, Hagan MA. Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network. Brain Struct Funct 2021; 226:3007-3022. [PMID: 34518902 PMCID: PMC8541938 DOI: 10.1007/s00429-021-02367-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 08/23/2021] [Indexed: 01/02/2023]
Abstract
The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal–parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal–parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.
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Affiliation(s)
- Joanita F D'Souza
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia
| | - Nicholas S C Price
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia
| | - Maureen A Hagan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, 26 Innovation Walk, Clayton, VIC, 3800, Australia. .,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, 3800, Australia.
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14
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Interspecies activation correlations reveal functional correspondences between marmoset and human brain areas. Proc Natl Acad Sci U S A 2021; 118:2110980118. [PMID: 34493677 DOI: 10.1073/pnas.2110980118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 08/09/2021] [Indexed: 12/12/2022] Open
Abstract
The common marmoset has enormous promise as a nonhuman primate model of human brain functions. While resting-state functional MRI (fMRI) has provided evidence for a similar organization of marmoset and human cortices, the technique cannot be used to map the functional correspondences of brain regions between species. This limitation can be overcome by movie-driven fMRI (md-fMRI), which has become a popular tool for noninvasively mapping the neural patterns generated by rich and naturalistic stimulation. Here, we used md-fMRI in marmosets and humans to identify whole-brain functional correspondences between the two primate species. In particular, we describe functional correlates for the well-known human face, body, and scene patches in marmosets. We find that these networks have a similar organization in both species, suggesting a largely conserved organization of higher-order visual areas between New World marmoset monkeys and humans. However, while face patches in humans and marmosets were activated by marmoset faces, only human face patches responded to the faces of other animals. Together, the results demonstrate that higher-order visual processing might be a conserved feature between humans and New World marmoset monkeys but that small, potentially important functional differences exist.
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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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16
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DiNicola LM, Buckner RL. Precision Estimates of Parallel Distributed Association Networks: Evidence for Domain Specialization and Implications for Evolution and Development. Curr Opin Behav Sci 2021; 40:120-129. [PMID: 34263017 DOI: 10.1016/j.cobeha.2021.03.029] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Humans can reason about other minds, comprehend language and imagine. These abilities depend on association regions that exhibit evolutionary expansion and prolonged postnatal development. Precision maps within individuals reveal these expanded zones are populated by multiple specialized networks that each possess a spatially distributed motif but remain anatomically separated throughout the cortex for language, social and mnemonic / spatial functions. Rather than converge on multi-domain regions or hubs, these networks include distinct regions within rostral prefrontal and temporal association zones. To account for these observations, we propose the expansion-fractionation-specialization (EFS) hypothesis: evolutionary expansion of human association cortex may have allowed for an archetype distributed network to fractionate into multiple specialized networks. Human development may recapitulate fractionation and specialization when these abilities emerge.
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Affiliation(s)
- Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138 USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138 USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129 USA
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17
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Hayashi T, Hou Y, Glasser MF, Autio JA, Knoblauch K, Inoue-Murayama M, Coalson T, Yacoub E, Smith S, Kennedy H, Van Essen DC. The nonhuman primate neuroimaging and neuroanatomy project. Neuroimage 2021; 229:117726. [PMID: 33484849 PMCID: PMC8079967 DOI: 10.1016/j.neuroimage.2021.117726] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/13/2020] [Accepted: 01/02/2021] [Indexed: 11/29/2022] Open
Abstract
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
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Affiliation(s)
- Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan; Department of Neurobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yujie Hou
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Neuroscience and Radiology, Washington University Medical School, St Louis, MO USA
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Kenneth Knoblauch
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | | | - Tim Coalson
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA
| | - Stephen Smith
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henry Kennedy
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai, China
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
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18
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Cléry JC, Hori Y, Schaeffer DJ, Menon RS, Everling S. Neural network of social interaction observation in marmosets. eLife 2021; 10:e65012. [PMID: 33787492 PMCID: PMC8024015 DOI: 10.7554/elife.65012] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 03/29/2021] [Indexed: 11/13/2022] Open
Abstract
A crucial component of social cognition is to observe and understand the social interactions of other individuals. A promising nonhuman primate model for investigating the neural basis of social interaction observation is the common marmoset (Callithrix jacchus), a small New World primate that shares a rich social repertoire with humans. Here, we used functional magnetic resonance imaging acquired at 9.4 T to map the brain areas activated by social interaction observation in awake marmosets. We discovered a network of subcortical and cortical areas, predominately in the anterior lateral frontal and medial frontal cortex, that was specifically activated by social interaction observation. This network resembled that recently identified in Old World macaque monkeys. Our findings suggest that this network is largely conserved between New and Old World primates and support the use of marmosets for studying the neural basis of social cognition.
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Affiliation(s)
- Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western OntarioLondonCanada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western OntarioLondonCanada
| | - David J Schaeffer
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western OntarioLondonCanada
- University of Pittsburgh, Department of NeurobiologyPittsburghUnited States
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western OntarioLondonCanada
- Department of Physiology and Pharmacology, The University of Western OntarioLondonCanada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western OntarioLondonCanada
- Department of Physiology and Pharmacology, The University of Western OntarioLondonCanada
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19
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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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20
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Schaeffer DJ, Liu C, Silva AC, Everling S. Magnetic Resonance Imaging of Marmoset Monkeys. ILAR J 2021; 61:274-285. [PMID: 33631015 PMCID: PMC8918195 DOI: 10.1093/ilar/ilaa029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 09/22/2020] [Accepted: 10/23/2020] [Indexed: 11/12/2022] Open
Abstract
The use of the common marmoset monkey (Callithrix jacchus) for neuroscientific research has grown markedly in the last decade. Magnetic resonance imaging (MRI) has played a significant role in establishing the extent of comparability of marmoset brain architecture with the human brain and brains of other preclinical species (eg, macaques and rodents). As a non-invasive technique, MRI allows for the flexible acquisition of the same sequences across different species in vivo, including imaging of whole-brain functional topologies not possible with more invasive techniques. Being one of the smallest New World primates, the marmoset may be an ideal nonhuman primate species to study with MRI. As primates, marmosets have an elaborated frontal cortex with features analogous to the human brain, while also having a small enough body size to fit into powerful small-bore MRI systems typically employed for rodent imaging; these systems offer superior signal strength and resolution. Further, marmosets have a rich behavioral repertoire uniquely paired with a lissencephalic cortex (like rodents). This smooth cortical surface lends itself well to MRI and also other invasive methodologies. With the advent of transgenic modification techniques, marmosets have gained significant traction as a powerful complement to canonical mammalian modelling species. Marmosets are poised to make major contributions to preclinical investigations of the pathophysiology of human brain disorders as well as more basic mechanistic explorations of the brain. The goal of this article is to provide an overview of the practical aspects of implementing MRI and fMRI in marmosets (both under anesthesia and fully awake) and discuss the development of resources recently made available for marmoset imaging.
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Affiliation(s)
- David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - CiRong Liu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Afonso C Silva
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Stefan Everling
- Department of Physiology and Pharmacology, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
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21
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Feizpour A, Majka P, Chaplin TA, Rowley D, Yu HH, Zavitz E, Price NSC, Rosa MGP, Hagan MA. Visual responses in the dorsolateral frontal cortex of marmoset monkeys. J Neurophysiol 2020; 125:296-304. [PMID: 33326337 DOI: 10.1152/jn.00581.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
The marmoset monkey (Callithrix jacchus) has gained attention in neurophysiology research as a new primate model for visual processing and behavior. In particular, marmosets have a lissencephalic cortex, making multielectrode, optogenetic, and calcium-imaging techniques more accessible than other primate models. However, the degree of homology of brain circuits for visual behavior with those identified in macaques and humans is still being ascertained. For example, whereas the location of the frontal eye fields (FEF) within the dorsolateral frontal cortex has been proposed, it remains unclear whether neurons in the corresponding areas show visual responses-an important characteristic of FEF neurons in other species. Here, we provide the first description of receptive field properties and neural response latencies in the marmoset dorsolateral frontal cortex, based on recordings using Utah arrays in anesthetized animals. We find brisk visual responses in specific regions of the dorsolateral prefrontal cortex, particularly in areas 8aV, 8C, and 6DR. As in macaque FEF, the receptive fields were typically large (10°-30° in diameter) and the median responses latency was brisk (60 ms). These results constrain the possible interpretations about the location of the marmoset FEF and suggest that the marmoset model's significant advantages for the use of physiological techniques may be leveraged in the study of visuomotor cognition.NEW & NOTEWORTHY Behavior and cognition in humans and other primates rely on networks of brain areas guided by the frontal cortex. The marmoset offers exciting new opportunities to study links between brain physiology and behavior, but the functions of frontal cortex areas are still being identified in this species. Here, we provide the first evidence of visual receptive fields in the marmoset dorsolateral frontal cortex, an important step toward future studies of visual cognitive behavior.
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Affiliation(s)
- Azadeh Feizpour
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Piotr Majka
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Tristan A Chaplin
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Declan Rowley
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Hsin-Hao Yu
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Elizabeth Zavitz
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Nicholas S C Price
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Marcello G P Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Maureen A Hagan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
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22
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Hori Y, Schaeffer DJ, Yoshida A, Cléry JC, Hayrynen LK, Gati JS, Menon RS, Everling S. Cortico-Subcortical Functional Connectivity Profiles of Resting-State Networks in Marmosets and Humans. J Neurosci 2020; 40:9236-9249. [PMID: 33097633 PMCID: PMC7687060 DOI: 10.1523/jneurosci.1984-20.2020] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 10/01/2020] [Accepted: 10/15/2020] [Indexed: 11/21/2022] Open
Abstract
Understanding the similarity of cortico-subcortical networks topologies between humans and nonhuman primate species is critical to study the origin of network alternations underlying human neurologic and neuropsychiatric diseases. The New World common marmoset (Callithrix jacchus) has become popular as a nonhuman primate model for human brain function. Most marmoset connectomic research, however, has exclusively focused on cortical areas, with connectivity to subcortical networks less extensively explored. Here, we aimed to first isolate patterns of subcortical connectivity with cortical resting-state networks in awake marmosets using resting-state fMRI, then to compare these networks with those in humans using connectivity fingerprinting. In this study, we used 5 marmosets (4 males, 1 female). While we could match several marmoset and human resting-state networks based on their functional fingerprints, we also found a few striking differences, for example, strong functional connectivity of the default mode network with the superior colliculus in marmosets that was much weaker in humans. Together, these findings demonstrate that many of the core cortico-subcortical networks in humans are also present in marmosets, but that small, potentially functionally relevant differences exist.SIGNIFICANCE STATEMENT The common marmoset is becoming increasingly popular as an additional preclinical nonhuman primate model for human brain function. Here we compared the functional organization of cortico-subcortical networks in marmosets and humans using ultra-high field fMRI. We isolated the patterns of subcortical connectivity with cortical resting-state networks (RSNs) in awake marmosets using resting-state fMRI and then compared these networks with those in humans using connectivity fingerprinting. While we could match several marmoset and human RSNs based on their functional fingerprints, we also found several striking differences. Together, these findings demonstrate that many of the core cortico-subcortical RSNs in humans are also present in marmosets, but that small, potentially functionally relevant differences exist.
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Affiliation(s)
- Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - David J Schaeffer
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Atsushi Yoshida
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892
| | - Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Lauren K Hayrynen
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - 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
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23
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Greulich RS, Adam R, Everling S, Scherberger H. Shared functional connectivity between the dorso-medial and dorso-ventral streams in macaques. Sci Rep 2020; 10:18610. [PMID: 33122655 PMCID: PMC7596572 DOI: 10.1038/s41598-020-75219-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 10/07/2020] [Indexed: 12/04/2022] Open
Abstract
Manipulation of an object requires us to transport our hand towards the object (reach) and close our digits around that object (grasp). In current models, reach-related information is propagated in the dorso-medial stream from posterior parietal area V6A to medial intraparietal area, dorsal premotor cortex, and primary motor cortex. Grasp-related information is processed in the dorso-ventral stream from the anterior intraparietal area to ventral premotor cortex and the hand area of primary motor cortex. However, recent studies have cast doubt on the validity of this separation in separate processing streams. We investigated in 10 male rhesus macaques the whole-brain functional connectivity of these areas using resting state fMRI at 7-T. Although we found a clear separation between dorso-medial and dorso-ventral network connectivity in support of the two-stream hypothesis, we also found evidence of shared connectivity between these networks. The dorso-ventral network was distinctly correlated with high-order somatosensory areas and feeding related areas, whereas the dorso-medial network with visual areas and trunk/hindlimb motor areas. Shared connectivity was found in the superior frontal and precentral gyrus, central sulcus, intraparietal sulcus, precuneus, and insular cortex. These results suggest that while sensorimotor processing streams are functionally separated, they can access information through shared areas.
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Affiliation(s)
- R Stefan Greulich
- Deutsches Primatenzentrum GmbH, Kellnerweg 4, 37077, Göttingen, Germany. .,Faculty of Biology and Psychology, University of Goettingen, Göttingen, Germany.
| | - Ramina Adam
- Robarts Research Institute, University of Western Ontario, London, Canada.,Graduate Program in Neuroscience, University of Western Ontario, London, Canada
| | - Stefan Everling
- Robarts Research Institute, University of Western Ontario, London, Canada.,Department of Physiology and Pharmacology, University of Western Ontario, London, Canada
| | - Hansjörg Scherberger
- Deutsches Primatenzentrum GmbH, Kellnerweg 4, 37077, Göttingen, Germany. .,Faculty of Biology and Psychology, University of Goettingen, Göttingen, Germany.
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24
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Hori Y, Schaeffer DJ, Gilbert KM, Hayrynen LK, Cléry JC, Gati JS, Menon RS, Everling S. Altered Resting-State Functional Connectivity Between Awake and Isoflurane Anesthetized Marmosets. Cereb Cortex 2020; 30:5943-5959. [PMID: 32556184 PMCID: PMC7899065 DOI: 10.1093/cercor/bhaa168] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 05/28/2020] [Accepted: 05/28/2020] [Indexed: 01/02/2023] Open
Abstract
The common marmoset (Callithrix jacchus) is a New World primate that is becoming increasingly popular as a preclinical model. To assess functional connectivity (FC) across the marmoset brain, resting-state functional MRI (RS-fMRI) is often performed under isoflurane anesthesia to avoid the effects of motion, physiological stress, and training requirements. In marmosets, however, it remains unclear how isoflurane anesthesia affects patterns of FC. Here, we investigated the effects of isoflurane on FC when delivered with either medical air or 100% pure oxygen, two canonical methods of inhalant isoflurane anesthesia delivery. The results demonstrated that when delivered with either medical air or 100% oxygen, isoflurane globally decreased FC across resting-state networks that were identified in awake marmosets. Generally, although isoflurane globally decreased FC in resting-state networks, the spatial structure of the networks was preserved. Outside of the context of RS networks, we indexed pair-wise functional connectivity between regions across the brain and found that isoflurane substantially altered interhemispheric and thalamic FC. Taken together, these findings indicate that RS-fMRI under isoflurane anesthesia is useful to evaluate the global structure of functional networks, but may obfuscate important nodes of some network components when compared to data acquired in fully awake marmosets.
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Affiliation(s)
- Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - David J Schaeffer
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Kyle M Gilbert
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Lauren K Hayrynen
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario N6A 5B7, Canada
- Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario N6A 5C1, Canada
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25
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Braga RM, DiNicola LM, Becker HC, Buckner RL. Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks. J Neurophysiol 2020; 124:1415-1448. [PMID: 32965153 PMCID: PMC8356783 DOI: 10.1152/jn.00753.2019] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Using procedures optimized to explore network organization within the individual, the topography of a candidate language network was characterized and situated within the broader context of adjacent networks. The candidate network was first identified using functional connectivity and replicated across individuals, acquisition tasks, and analytical methods. In addition to classical language regions near the perisylvian cortex and temporal pole, regions were also observed in dorsal posterior cingulate, midcingulate, and anterior superior frontal and inferior temporal cortex. The candidate network was selectively activated when processing meaningful (as contrasted with nonword) sentences, whereas spatially adjacent networks showed minimal or even decreased activity. Results were replicated and triplicated across two prospectively acquired cohorts. Examined in relation to adjacent networks, the topography of the language network was found to parallel the motif of other association networks, including the transmodal association networks linked to theory of mind and episodic remembering (often collectively called the default network). The several networks contained juxtaposed regions in multiple association zones. Outside of these juxtaposed higher-order networks, we further noted a distinct frontotemporal network situated between language regions and a frontal orofacial motor region and a temporal auditory region. A possibility is that these functionally related sensorimotor regions might anchor specialization of neighboring association regions that develop into a language network. What is most striking is that the canonical language network appears to be just one of multiple similarly organized, differentially specialized distributed networks that populate the evolutionarily expanded zones of human association cortex. NEW & NOTEWORTHY This research shows that a language network can be identified within individuals using functional connectivity. Organizational details reveal that the language network shares a common spatial motif with other association networks, including default and frontoparietal control networks. The language network is activated by language task demands, whereas closely juxtaposed networks are not, suggesting that similarly organized but differentially specialized distributed networks populate association cortex.
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Affiliation(s)
- Rodrigo M Braga
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts.,Department of Neurology and Neurological Sciences, Stanford University, Stanford, California.,The Computational, Cognitive, and Clinical Neuroimaging Laboratory, Hammersmith Hospital Campus, Imperial College London, London, United Kingdom.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts
| | - Hannah C Becker
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts
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26
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Xu T, Nenning KH, Schwartz E, Hong SJ, Vogelstein JT, Goulas A, Fair DA, Schroeder CE, Margulies DS, Smallwood J, Milham MP, Langs G. Cross-species functional alignment reveals evolutionary hierarchy within the connectome. Neuroimage 2020; 223:117346. [PMID: 32916286 PMCID: PMC7871099 DOI: 10.1016/j.neuroimage.2020.117346] [Citation(s) in RCA: 96] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 08/04/2020] [Accepted: 08/31/2020] [Indexed: 11/22/2022] Open
Abstract
Evolution provides an important window into how cortical organization
shapes function and vice versa. The complex mosaic of changes in brain
morphology and functional organization that have shaped the mammalian cortex
during evolution, complicates attempts to chart cortical differences across
species. It limits our ability to fully appreciate how evolution has shaped our
brain, especially in systems associated with unique human cognitive capabilities
that lack anatomical homologues in other species. Here, we develop a
function-based method for cross-species alignment that enables the
quantification of homologous regions between humans and rhesus macaques, even
when their location is decoupled from anatomical landmarks. Critically, we find
cross-species similarity in functional organization reflects a gradient of
evolutionary change that decreases from unimodal systems and culminates with the
most pronounced changes in posterior regions of the default mode network
(angular gyrus, posterior cingulate and middle temporal cortices). Our findings
suggest that the establishment of the default mode network, as the apex of a
cognitive hierarchy, has changed in a complex manner during human evolution
– even within subnetworks.
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Affiliation(s)
- Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Seok-Jun Hong
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, Kavli Neuroscience Discovery Institute, Johns Hopkins University, MD, USA
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Hamburg, Germany
| | - Damien A Fair
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA; Departments of neurosurgery and Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) UMR 7225, Frontlab, Institut du Cerveau et de la Moelle Epinière, Paris, France
| | - Jonny Smallwood
- Department of Psychology, Queen's University, Kingston, Ontario, Canada; Psychology Department, University of York, York, UK
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
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27
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Ma L, Selvanayagam J, Ghahremani M, Hayrynen LK, Johnston KD, Everling S. Single-unit activity in marmoset posterior parietal cortex in a gap saccade task. J Neurophysiol 2020; 123:896-911. [DOI: 10.1152/jn.00614.2019] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Abnormal saccadic eye movements can serve as biomarkers for patients with several neuropsychiatric disorders. The common marmoset ( Callithrix jacchus) is becoming increasingly popular as a nonhuman primate model to investigate the cortical mechanisms of saccadic control. Recently, our group demonstrated that microstimulation in the posterior parietal cortex (PPC) of marmosets elicits contralateral saccades. Here we recorded single-unit activity in the PPC of the same two marmosets using chronic microelectrode arrays while the monkeys performed a saccadic task with gap trials (target onset lagged fixation point offset by 200 ms) interleaved with step trials (fixation point disappeared when the peripheral target appeared). Both marmosets showed a gap effect, shorter saccadic reaction times (SRTs) in gap vs. step trials. On average, stronger gap-period responses across the entire neuronal population preceded shorter SRTs on trials with contralateral targets although this correlation was stronger among the 15% “gap neurons,” which responded significantly during the gap. We also found 39% “target neurons” with significant saccadic target-related responses, which were stronger in gap trials and correlated with the SRTs better than the remaining neurons. Compared with saccades with relatively long SRTs, short-SRT saccades were preceded by both stronger gap-related and target-related responses in all PPC neurons, regardless of whether such response reached significance. Our findings suggest that the PPC in the marmoset contains an area that is involved in the modulation of saccadic preparation. NEW & NOTEWORTHY As a primate model in systems neuroscience, the marmoset is a great complement to the macaque monkey because of its unique advantages. To identify oculomotor networks in the marmoset, we recorded from the marmoset posterior parietal cortex during a saccadic task and found single-unit activities consistent with a role in saccadic modulation. This finding supports the marmoset as a valuable model for studying oculomotor control.
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Affiliation(s)
- Liya Ma
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Janahan Selvanayagam
- Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada
| | - Maryam Ghahremani
- Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada
| | - Lauren K. Hayrynen
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Kevin D. Johnston
- Departments of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
| | - Stefan Everling
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
- Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada
- Departments of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
- Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
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28
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Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey. Nat Commun 2020; 11:1133. [PMID: 32111833 PMCID: PMC7048793 DOI: 10.1038/s41467-020-14858-0] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 02/03/2020] [Indexed: 12/25/2022] Open
Abstract
Understanding the principles of neuronal connectivity requires tools for efficient quantification and visualization of large datasets. The primate cortex is particularly challenging due to its complex mosaic of areas, which in many cases lack clear boundaries. Here, we introduce a resource that allows exploration of results of 143 retrograde tracer injections in the marmoset neocortex. Data obtained in different animals are registered to a common stereotaxic space using an algorithm guided by expert delineation of histological borders, allowing accurate assignment of connections to areas despite interindividual variability. The resource incorporates tools for analyses relative to cytoarchitectural areas, including statistical properties such as the fraction of labeled neurons and the percentage of supragranular neurons. It also provides purely spatial (parcellation-free) data, based on the stereotaxic coordinates of 2 million labeled neurons. This resource helps bridge the gap between high-density cellular connectivity studies in rodents and imaging-based analyses of human brains. Understanding principles of neuronal connectivity requires tools for quantification and visualization of large datasets. Here, the authors introduce an online resource encompassing the coordinates of two million neurons labelled by tracer injections in the marmoset cortex, and analysis tools.
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29
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Functional Localization of the Frontal Eye Fields in the Common Marmoset Using Microstimulation. J Neurosci 2019; 39:9197-9206. [PMID: 31582528 DOI: 10.1523/jneurosci.1786-19.2019] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/23/2019] [Accepted: 09/26/2019] [Indexed: 12/12/2022] Open
Abstract
The frontal eye field (FEF) is a critical region for the deployment of overt and covert spatial attention. Although investigations in the macaque continue to provide insight into the neural underpinnings of the FEF, due to its location within a sulcus, the macaque FEF is virtually inaccessible to electrophysiological techniques such as high-density and laminar recordings. With a largely lissencephalic cortex, the common marmoset (Callithrix jacchus) is a promising alternative primate model for studying FEF microcircuitry. Putative homologies have been established with the macaque FEF on the basis of cytoarchitecture and connectivity; however, physiological investigation in awake, behaving marmosets is necessary to physiologically locate this area. Here, we addressed this gap using intracortical microstimulation in a broad range of frontal cortical areas in three adult marmosets (two males, one female). We implanted marmosets with 96-channel Utah arrays and applied microstimulation trains while they freely viewed video clips. We evoked short-latency fixed vector saccades at low currents (<50 μA) in areas 45, 8aV, 8C, and 6DR. We observed a topography of saccade direction and amplitude consistent with findings in macaques and humans: small saccades in ventrolateral FEF and large saccades combined with contralateral neck and shoulder movements encoded in dorsomedial FEF. Our data provide compelling evidence supporting homology between marmoset and macaque FEF and suggest that the marmoset is a useful primate model for investigating FEF microcircuitry and its contributions to oculomotor and cognitive functions.SIGNIFICANCE STATEMENT The frontal eye field (FEF) is a critical cortical region for overt and covert spatial attention. The microcircuitry of this area remains poorly understood because in the macaque, the most commonly used model, it is embedded within a sulcus and is inaccessible to modern electrophysiological and imaging techniques. The common marmoset is a promising alternative primate model due to its lissencephalic cortex and potential for genetic manipulation. However, evidence for homologous cortical areas in this model remains limited and unclear. Here, we applied microstimulation in frontal cortical areas in marmosets to physiologically identify FEF. Our results provide compelling evidence for an FEF in the marmoset and suggest that the marmoset is a useful model for investigating FEF microcircuitry.
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30
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Ghahremani M, Johnston KD, Ma L, Hayrynen LK, Everling S. Electrical microstimulation evokes saccades in posterior parietal cortex of common marmosets. J Neurophysiol 2019; 122:1765-1776. [DOI: 10.1152/jn.00417.2019] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The common marmoset ( Callithrix jacchus) is a small-bodied New World primate increasing in prominence as a model animal for neuroscience research. The lissencephalic cortex of this primate species provides substantial advantages for the application of electrophysiological techniques such as high-density and laminar recordings, which have the capacity to advance our understanding of local and laminar cortical circuits and their roles in cognitive and motor functions. This is particularly the case with respect to the oculomotor system, as critical cortical areas of this network such as the frontal eye fields (FEF) and lateral intraparietal area (LIP) lie deep within sulci in macaques. Studies of cytoarchitecture and connectivity have established putative homologies between cortical oculomotor fields in marmoset and macaque, but physiological investigations of these areas, particularly in awake marmosets, have yet to be carried out. Here we addressed this gap by probing the function of posterior parietal cortex of the common marmoset with electrical microstimulation. We implanted two animals with 32-channel Utah arrays at the location of the putative area LIP and applied microstimulation while they viewed a video display and made untrained eye movements. Similar to previous studies in macaques, stimulation evoked fixed-vector and goal-directed saccades, staircase saccades, and eyeblinks. These data demonstrate that area LIP of the marmoset plays a role in the regulation of eye movements, provide additional evidence that this area is homologous with that of the macaque, and further establish the marmoset as a valuable model for neurophysiological investigations of oculomotor and cognitive control. NEW & NOTEWORTHY The macaque monkey has been the preeminent model for investigations of oculomotor control, but studies of cortical areas are limited, as many of these areas are buried within sulci in this species. Here we applied electrical microstimulation to the putative area LIP of the lissencephalic cortex of awake marmosets. Similar to the macaque, microstimulation evoked contralateral saccades from this area, supporting the marmoset as a valuable model for studies of oculomotor control.
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Affiliation(s)
- Maryam Ghahremani
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Kevin D. Johnston
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada
- Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada
- Brain and Mind Institute, The University of Western Ontario, London, Ontario, Canada
| | - Liya Ma
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Lauren K. Hayrynen
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada
- Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada
- Brain and Mind Institute, The University of Western Ontario, London, Ontario, Canada
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
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31
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Shen K, Bezgin G, Schirner M, Ritter P, Everling S, McIntosh AR. A macaque connectome for large-scale network simulations in TheVirtualBrain. Sci Data 2019; 6:123. [PMID: 31316116 PMCID: PMC6637142 DOI: 10.1038/s41597-019-0129-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 06/18/2019] [Indexed: 12/15/2022] Open
Abstract
Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.
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Affiliation(s)
- Kelly Shen
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.
| | - Gleb Bezgin
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Michael Schirner
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Petra Ritter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Stefan Everling
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
| | - Anthony R McIntosh
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
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32
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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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33
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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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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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Folloni D, Verhagen L, Mars RB, Fouragnan E, Constans C, Aubry JF, Rushworth MFS, Sallet J. Manipulation of Subcortical and Deep Cortical Activity in the Primate Brain Using Transcranial Focused Ultrasound Stimulation. Neuron 2019. [PMID: 30765166 DOI: 10.1101/342303] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their application, particularly in deep areas of the primate brain. Here, we demonstrate that a focused transcranial ultrasound stimulation (TUS) protocol impacts activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, the anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions, but such relationships are reduced after sonication, specifically for the targeted areas. Dissociable and focal effects on neural activity could not be explained by auditory confounds.
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Affiliation(s)
- Davide Folloni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 HR Nijmegen, the Netherlands
| | - Elsa Fouragnan
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK; School of Psychology, University of Plymouth, Plymouth PL4 8AA, UK
| | - Charlotte Constans
- Physics for Medicine Paris, Inserm, ESPCI Paris, CNRS, PSL Research University, Univ Paris Diderot, Sorbonne Paris Cité, Paris 75012, France
| | - Jean-François Aubry
- Physics for Medicine Paris, Inserm, ESPCI Paris, CNRS, PSL Research University, Paris 75012, France
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Jérôme Sallet
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
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Verhagen L, Gallea C, Folloni D, Constans C, Jensen DE, Ahnine H, Roumazeilles L, Santin M, Ahmed B, Lehericy S, Klein-Flügge MC, Krug K, Mars RB, Rushworth MF, Pouget P, Aubry JF, Sallet J. Offline impact of transcranial focused ultrasound on cortical activation in primates. eLife 2019; 8:40541. [PMID: 30747105 DOI: 10.7554/elife.40541.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Accepted: 01/26/2019] [Indexed: 05/23/2023] Open
Abstract
To understand brain circuits it is necessary both to record and manipulate their activity. Transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation technique. To date, investigations report short-lived neuromodulatory effects, but to deliver on its full potential for research and therapy, ultrasound protocols are required that induce longer-lasting 'offline' changes. Here, we present a TUS protocol that modulates brain activation in macaques for more than one hour after 40 s of stimulation, while circumventing auditory confounds. Normally activity in brain areas reflects activity in interconnected regions but TUS caused stimulated areas to interact more selectively with the rest of the brain. In a within-subject design, we observe regionally specific TUS effects for two medial frontal brain regions - supplementary motor area and frontal polar cortex. Independently of these site-specific effects, TUS also induced signal changes in the meningeal compartment. TUS effects were temporary and not associated with microstructural changes.
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Affiliation(s)
- Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Cécile Gallea
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Davide Folloni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Charlotte Constans
- Physics for Medicine Paris, Inserm, ESPCI Paris, CNRS, PSL Research University, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Daria Ea Jensen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Harry Ahnine
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Léa Roumazeilles
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Mathieu Santin
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Bashir Ahmed
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Stéphane Lehericy
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Kristine Krug
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Matthew Fs Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Pierre Pouget
- Institute du Cerveau et de la Moelle épinière (ICM), UMRS 975 INSERM, CNRS 7225, UMPC, Paris, France
| | - Jean-François Aubry
- Physics for Medicine Paris, Inserm, ESPCI Paris, CNRS, PSL Research University, Paris, France
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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Verhagen L, Gallea C, Folloni D, Constans C, Jensen DEA, Ahnine H, Roumazeilles L, Santin M, Ahmed B, Lehericy S, Klein-Flügge MC, Krug K, Mars RB, Rushworth MFS, Pouget P, Aubry JF, Sallet J. Offline impact of transcranial focused ultrasound on cortical activation in primates. eLife 2019; 8:e40541. [PMID: 30747105 PMCID: PMC6372282 DOI: 10.7554/elife.40541] [Citation(s) in RCA: 167] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Accepted: 01/26/2019] [Indexed: 12/17/2022] Open
Abstract
To understand brain circuits it is necessary both to record and manipulate their activity. Transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation technique. To date, investigations report short-lived neuromodulatory effects, but to deliver on its full potential for research and therapy, ultrasound protocols are required that induce longer-lasting 'offline' changes. Here, we present a TUS protocol that modulates brain activation in macaques for more than one hour after 40 s of stimulation, while circumventing auditory confounds. Normally activity in brain areas reflects activity in interconnected regions but TUS caused stimulated areas to interact more selectively with the rest of the brain. In a within-subject design, we observe regionally specific TUS effects for two medial frontal brain regions - supplementary motor area and frontal polar cortex. Independently of these site-specific effects, TUS also induced signal changes in the meningeal compartment. TUS effects were temporary and not associated with microstructural changes.
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Affiliation(s)
- Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Cécile Gallea
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR)Inserm U 1127, CNRS UMR 7225, Sorbonne UniversitéParisFrance
| | - Davide Folloni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Charlotte Constans
- Physics for Medicine ParisInserm, ESPCI Paris, CNRS, PSL Research University, Université Paris Diderot, Sorbonne Paris CitéParisFrance
| | - Daria EA Jensen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Harry Ahnine
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR)Inserm U 1127, CNRS UMR 7225, Sorbonne UniversitéParisFrance
| | - Léa Roumazeilles
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Mathieu Santin
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR)Inserm U 1127, CNRS UMR 7225, Sorbonne UniversitéParisFrance
| | - Bashir Ahmed
- Department of Physiology, Anatomy and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Stéphane Lehericy
- Institute du Cerveau et de la Moelle épinière (ICM), Centre for NeuroImaging Research (CENIR)Inserm U 1127, CNRS UMR 7225, Sorbonne UniversitéParisFrance
| | - Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Kristine Krug
- Department of Physiology, Anatomy and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and BehaviourRadboud University NijmegenNijmegenThe Netherlands
| | - Matthew FS Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
| | - Pierre Pouget
- Institute du Cerveau et de la Moelle épinière (ICM)UMRS 975 INSERM, CNRS 7225, UMPCParisFrance
| | - Jean-François Aubry
- Physics for Medicine ParisInserm, ESPCI Paris, CNRS, PSL Research UniversityParisFrance
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
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Alpha Oscillations Modulate Preparatory Activity in Marmoset Area 8Ad. J Neurosci 2019; 39:1855-1866. [PMID: 30651331 DOI: 10.1523/jneurosci.2703-18.2019] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 01/03/2019] [Accepted: 01/04/2019] [Indexed: 11/21/2022] Open
Abstract
Cognitive control often requires suppression of prepotent stimulus-driven responses in favor of less potent alternatives. Suppression of prepotent saccades has been shown to require proactive inhibition in the frontoparietal saccade network. Electrophysiological evidence in macaque monkeys has revealed neural correlates of such inhibition in this network; however, the interlaminar instantiation of inhibitory processes remains poorly understood because these areas lie deep within sulci in macaques, rendering them inaccessible to laminar recordings. Here, we addressed this gap by exploiting the mostly lissencephalic cortex of the common marmoset (Callithrix jacchus). We inserted linear electrode arrays into areas 8Ad-the putative marmoset frontal eye field-and the lateral intraparietal area of two male marmosets and recorded neural activity during performance of a task comprised of alternating blocks of trials requiring a saccade either toward a large, high-luminance stimulus or the inhibition of this prepotent response in favor of a saccade toward a small, low-luminance stimulus. We observed prominent task-dependent activity in both alpha/gamma bands of the LFP and discharge rates of single neurons in area 8Ad during a prestimulus task epoch in which the animals had been instructed which of these two tasks to perform but before peripheral stimulus onset. These data are consistent with a model in which rhythmic alpha-band activity in deeper layers inhibits spiking in upper layers to support proactive inhibitory saccade control.SIGNIFICANCE STATEMENT Failures to inhibit automatic saccadic responses are a hallmark of many neuropsychiatric disorders, but how this process is implemented across the cortical layers in the frontoparietal saccade network remains unknown because many of the areas are inaccessible to laminar recordings in macaques. Here, we investigated laminar neural activity in marmoset monkeys, which have a smooth cortex. Monkeys were required either to generate or inhibit a prepotent saccade response. In area 8Ad, the putative frontal eye field in marmosets, rhythmic alpha-band activity (9-14 Hz) was higher in deeper layers and spiking activity was lower in upper layers when the animals were instructed to suppress a saccade toward a peripheral stimulus. Reduced alpha power during task preparation may be the underlying common neural basis of a saccade suppression deficit.
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Intrinsic Functional Boundaries of Lateral Frontal Cortex in the Common Marmoset Monkey. J Neurosci 2018; 39:1020-1029. [PMID: 30530862 DOI: 10.1523/jneurosci.2595-18.2018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2018] [Revised: 11/29/2018] [Accepted: 12/01/2018] [Indexed: 12/28/2022] Open
Abstract
The common marmoset (Callithrix jacchus) is a small New World primate species that has been recently targeted as a potentially powerful preclinical model of human prefrontal cortex dysfunction. Although the structural boundaries of frontal cortex were described in marmosets at the start of the 20th century (Brodmann, 1909) and refined more recently (Paxinos et al., 2012), the broad functional boundaries of marmoset frontal cortex have yet to be established. In this study, we sought to functionally derive boundaries of the marmoset lateral frontal cortex (LFC) using ultra-high field (9.4 T) resting-state functional magnetic resonance imaging (RS-fMRI). We collected RS-fMRI data in seven (four females, three males) lightly anesthetized marmosets and used a data-driven hierarchical clustering approach to derive subdivisions of the LFC based on intrinsic functional connectivity. We then conducted seed-based analyses to assess the functional connectivity between these clusters and the rest of the brain. The results demonstrated seven distinct functional clusters within the LFC. The functional connectivity patterns of these clusters with the rest of the brain were also found to be distinct and organized along a rostrocaudal gradient, consonant with those found in humans and macaques. Overall, these results support the view that marmosets are a promising preclinical modeling species for studying LFC dysfunction related to neuropsychiatric or neurodegenerative human brain diseases.SIGNIFICANCE STATEMENT The common marmoset is a New World primate that has garnered recent attention as a powerful complement to canonical Old World primate (e.g., macaques) and rodent models (e.g., rats, mice) for preclinical modeling of the human brain in healthy and diseased states. A critical step in the development of marmosets for such models is to characterize functional network topologies of frontal cortex in healthy, normally functioning marmosets, that is, how these circuitries are functionally divided and how those topologies compare to human circuitry. To our knowledge, this is the first study to demonstrate functional boundaries of the lateral frontal cortex and the corresponding network topologies in marmoset monkeys.
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Vijayakumar S, Sallet J, Verhagen L, Folloni D, Medendorp WP, Mars RB. Mapping multiple principles of parietal-frontal cortical organization using functional connectivity. Brain Struct Funct 2018; 224:681-697. [PMID: 30470895 PMCID: PMC6420483 DOI: 10.1007/s00429-018-1791-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 11/08/2018] [Indexed: 12/02/2022]
Abstract
Resting state functional connectivity has been promoted as a promising tool for creating cortical maps that show remarkable similarity to those established by invasive histological methods. While this tool has been largely used to identify and map cortical areas, its true potential in the context of studying connectional architecture and in conducting comparative neuroscience has remained unexplored. Here, we employ widely used resting state connectivity and data-driven clustering methods to extend this approach for the study of the organizational principles of the macaque parietal–frontal system. We show multiple, overlapping principles of organization, including a dissociation between dorsomedial and dorsolateral pathways and separate parietal–premotor and parietal–frontal pathways. These results demonstrate the suitability of this approach for understanding the complex organizational principles of the brain and for large-scale comparative neuroscience.
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Affiliation(s)
- Suhas Vijayakumar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525HR, Nijmegen, The Netherlands.
| | - Jerome Sallet
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, 9 South Parks Road, Oxford, OX1 3UD, United Kingdom
| | - Lennart Verhagen
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, 9 South Parks Road, Oxford, OX1 3UD, United Kingdom
| | - Davide Folloni
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, 9 South Parks Road, Oxford, OX1 3UD, United Kingdom
| | - W Pieter Medendorp
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525HR, Nijmegen, The Netherlands
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525HR, Nijmegen, The Netherlands.,Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX3 9DU, United Kingdom
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41
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Milham MP, Ai L, Koo B, Xu T, Amiez C, Balezeau F, Baxter MG, Blezer ELA, Brochier T, Chen A, Croxson PL, Damatac CG, Dehaene S, Everling S, Fair DA, Fleysher L, Freiwald W, Froudist-Walsh S, Griffiths TD, Guedj C, Hadj-Bouziane F, Ben Hamed S, Harel N, Hiba B, Jarraya B, Jung B, Kastner S, Klink PC, Kwok SC, Laland KN, Leopold DA, Lindenfors P, Mars RB, Menon RS, Messinger A, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Rios MO, Petkov CI, Pinsk M, Poirier C, Procyk E, Rajimehr R, Reader SM, Roelfsema PR, Rudko DA, Rushworth MFS, Russ BE, Sallet J, Schmid MC, Schwiedrzik CM, Seidlitz J, Sein J, Shmuel A, Sullivan EL, Ungerleider L, Thiele A, Todorov OS, Tsao D, Wang Z, Wilson CRE, Yacoub E, Ye FQ, Zarco W, Zhou YD, Margulies DS, Schroeder CE. An Open Resource for Non-human Primate Imaging. Neuron 2018; 100:61-74.e2. [PMID: 30269990 PMCID: PMC6231397 DOI: 10.1016/j.neuron.2018.08.039] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/02/2018] [Accepted: 08/30/2018] [Indexed: 01/11/2023]
Abstract
Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
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Affiliation(s)
- Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
| | - Lei Ai
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Bonhwang Koo
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Céline Amiez
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Fabien Balezeau
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark G Baxter
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thomas Brochier
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Aihua Chen
- Key Laboratory of Brain Functional Genomics (Ministry of Education & Science and Technology Commission of Shanghai Municipality), School of Life Sciences, East China Normal University, Shanghai 200062, China
| | - Paula L Croxson
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Christienne G Damatac
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands
| | - Stanislas Dehaene
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Damian A Fair
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, USA
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Winrich Freiwald
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | | | - Timothy D Griffiths
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Carole Guedj
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | | | - Suliann Ben Hamed
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Bassem Hiba
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Bechir Jarraya
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Sabine Kastner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - P Christiaan Klink
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai 200062, China; Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai 200062, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, UK
| | - David A Leopold
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA; Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Patrik Lindenfors
- Institute for Future Studies, Stockholm, Sweden; Centre for Cultural Evolution & Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Martine Meunier
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | - Kelvin Mok
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - John H Morrison
- California National Primate Research Center, Davis, CA 95616, USA; Department of Neurology, School of Medicine, University of California, Davis, CA 95616, USA
| | - Jennifer Nacef
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Jamie Nagy
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Ortiz Rios
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Christopher I Petkov
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark Pinsk
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - Colline Poirier
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Emmanuel Procyk
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Reza Rajimehr
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Simon M Reader
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands; Department of Biology, McGill University, Montreal, QC H3A 1BA, Canada
| | - Pieter R Roelfsema
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands; Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | - Brian E Russ
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | | | | | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Julien Sein
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Amir Shmuel
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Elinor L Sullivan
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Human Physiology, University of Oregon, Eugene, OR, USA
| | - Leslie Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Alexander Thiele
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Orlin S Todorov
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands
| | - Doris Tsao
- Department of Computation and Neural Systems, California Institute of Technology, Pasadena, CA 91125, USA
| | - Zheng Wang
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Charles R E Wilson
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Wilbert Zarco
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | - Yong-di Zhou
- Krieger Mind/Brain Institute, Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Daniel S Margulies
- Max Planck Research Group for Neuroanatomy and Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; Centre national de la recherche scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, 75013 Paris, France
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; Department of Neurological Surgery, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
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42
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Xu T, Falchier A, Sullivan EL, Linn G, Ramirez JSB, Ross D, Feczko E, Opitz A, Bagley J, Sturgeon D, Earl E, Miranda-Domínguez O, Perrone A, Craddock RC, Schroeder CE, Colcombe S, Fair DA, Milham MP. Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo. Cell Rep 2018; 23:429-441. [PMID: 29642002 PMCID: PMC6157013 DOI: 10.1016/j.celrep.2018.03.049] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Revised: 02/15/2018] [Accepted: 03/08/2018] [Indexed: 12/22/2022] Open
Abstract
Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols.
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Affiliation(s)
- Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
| | - Arnaud Falchier
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Elinor L Sullivan
- Divisions of Neuroscience and Cardio-metabolic Health, Oregon National Primate Research Center, Beaverton, OR 97006, USA
| | - Gary Linn
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Julian S B Ramirez
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Deborah Ross
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Eric Feczko
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Alexander Opitz
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Jennifer Bagley
- Divisions of Neuroscience and Cardio-metabolic Health, Oregon National Primate Research Center, Beaverton, OR 97006, USA
| | - Darrick Sturgeon
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Eric Earl
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Oscar Miranda-Domínguez
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Anders Perrone
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - R Cameron Craddock
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; Department of Neurological Surgery, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
| | - Stan Colcombe
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Damien A Fair
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
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43
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Neuronal Encoding of Self and Others' Head Rotation in the Macaque Dorsal Prefrontal Cortex. Sci Rep 2017; 7:8571. [PMID: 28819117 PMCID: PMC5561028 DOI: 10.1038/s41598-017-08936-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 07/17/2017] [Indexed: 12/25/2022] Open
Abstract
Following gaze is a crucial skill, in primates, for understanding where and at what others are looking, and often requires head rotation. The neural basis underlying head rotation are deemed to overlap with the parieto-frontal attention/gaze-shift network. Here, we show that a set of neurons in monkey’s Brodmann area 9/46dr (BA 9/46dr), which is involved in orienting processes and joint attention, becomes active during self head rotation and that the activity of these neurons cannot be accounted for by saccade-related activity (head-rotation neurons). Another set of BA 9/46dr neurons encodes head rotation performed by an observed agent facing the monkey (visually triggered neurons). Among these latter neurons, almost half exhibit the intriguing property of encoding both execution and observation of head rotation (mirror-like neurons). Finally, by means of neuronal tracing techniques, we showed that BA 9/46dr takes part into two distinct networks: a dorso/mesial network, playing a role in spatial head/gaze orientation, and a ventrolateral network, likely involved in processing social stimuli and mirroring others’ head. The overall results of this study provide a new, comprehensive picture of the role of BA 9/46dr in encoding self and others’ head rotation, likely playing a role in head-following behaviors.
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44
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Gilbert KM, Gati JS, Klassen LM, Zeman P, Schaeffer DJ, Everling S, Menon RS. A geometrically adjustable receive array for imaging marmoset cohorts. Neuroimage 2017; 156:78-86. [DOI: 10.1016/j.neuroimage.2017.05.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 05/03/2017] [Accepted: 05/08/2017] [Indexed: 12/19/2022] Open
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45
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Schaeffer DJ, Adam R, Gilbert KM, Gati JS, Li AX, Menon RS, Everling S. Diffusion-weighted tractography in the common marmoset monkey at 9.4T. J Neurophysiol 2017; 118:1344-1354. [PMID: 28615334 DOI: 10.1152/jn.00259.2017] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Revised: 05/08/2017] [Accepted: 06/08/2017] [Indexed: 11/22/2022] Open
Abstract
The common marmoset (Callithrix jacchus) is a small New World primate that is becoming increasingly popular in the neurosciences as an animal model of preclinical human disease. With several major disorders characterized by alterations in neural white matter (e.g., multiple sclerosis, Alzheimer's disease, schizophrenia), proposed to be transgenically modeled using marmosets, the ability to isolate and characterize reliably major white matter fiber tracts with MRI will be of use for evaluating structural brain changes related to disease processes and symptomatology. Here, we propose protocols for isolating major white matter fiber tracts in the common marmoset using in vivo ultrahigh-field MRI (9.4T) diffusion-weighted imaging (DWI) data. With the use of a high angular-resolution DWI (256 diffusion-encoding directions) sequence, collected on four anesthetized marmosets, we provide guidelines for manually drawing fiber-tracking regions of interest, based on easily identified anatomical landmarks in DWI native space. These fiber-tract isolation protocols are expected to be experimentally useful for visualization and quantification of individual white matter fiber tracts in both control and experimental groups of marmosets (e.g., transgenic models). As disease models in the marmoset advance, the determination of how macroscopic white matter anatomy is altered as a function of disease state will be relevant in bridging the existing translational gap between preclinical rodent models and human patients.NEW & NOTEWORTHY Although significant progress has been made in mapping white matter connections in the marmoset brain using ex vivo tracing techniques, the application of in vivo virtual dissection of major white matter fiber tracts has been established by few studies in the marmoset literature. Here, we demonstrate the feasibility of whole-brain diffusion-weighted tractography in anesthetized marmosets at ultrahigh-field MRI (9.4T) and propose protocols for isolating nine major white matter fiber tracts in the marmoset brain.
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Affiliation(s)
- David J Schaeffer
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
| | - Ramina Adam
- Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada
| | - Kyle M Gilbert
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
| | - Joseph S Gati
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
| | - Alex X Li
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
| | - Ravi S Menon
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
| | - Stefan Everling
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; and
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46
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Keilholz SD, Pan WJ, Billings J, Nezafati M, Shakil S. Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies. Neuroimage 2016; 154:267-281. [PMID: 28017922 DOI: 10.1016/j.neuroimage.2016.12.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Revised: 10/21/2016] [Accepted: 12/08/2016] [Indexed: 01/08/2023] Open
Abstract
The BOLD signal reflects hemodynamic events within the brain, which in turn are driven by metabolic changes and neural activity. However, the link between BOLD changes and neural activity is indirect and can be influenced by a number of non-neuronal processes. Motion and physiological cycles have long been known to affect the BOLD signal and are present in both humans and animal models. Differences in physiological baseline can also contribute to intra- and inter-subject variability. The use of anesthesia, common in animal studies, alters neural activity, vascular tone, and neurovascular coupling. Most intriguing, perhaps, are the contributions from other processes that do not appear to be neural in origin but which may provide information about other aspects of neurophysiology. This review discusses different types of noise and non-neuronal contributors to the BOLD signal, sources of variability for animal studies, and insights to be gained from animal models.
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Affiliation(s)
- Shella D Keilholz
- Wallace H. Coulter Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, United States; Neuroscience Program, Emory University, Atlanta, GA, United States.
| | - Wen-Ju Pan
- Wallace H. Coulter Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, United States
| | - Jacob Billings
- Neuroscience Program, Emory University, Atlanta, GA, United States
| | - Maysam Nezafati
- Wallace H. Coulter Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, United States
| | - Sadia Shakil
- Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
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