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Zhong T, Wang Y, Xu X, Wu X, Liang S, Ning Z, Wang L, Niu Y, Li G, Zhang Y. A brain subcortical segmentation tool based on anatomy attentional fusion network for developing macaques. Comput Med Imaging Graph 2024; 116:102404. [PMID: 38870599 DOI: 10.1016/j.compmedimag.2024.102404] [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: 01/31/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024]
Abstract
Magnetic Resonance Imaging (MRI) plays a pivotal role in the accurate measurement of brain subcortical structures in macaques, which is crucial for unraveling the complexities of brain structure and function, thereby enhancing our understanding of neurodegenerative diseases and brain development. However, due to significant differences in brain size, structure, and imaging characteristics between humans and macaques, computational tools developed for human neuroimaging studies often encounter obstacles when applied to macaques. In this context, we propose an Anatomy Attentional Fusion Network (AAF-Net), which integrates multimodal MRI data with anatomical constraints in a multi-scale framework to address the challenges posed by the dynamic development, regional heterogeneity, and age-related size variations of the juvenile macaque brain, thus achieving precise subcortical segmentation. Specifically, we generate a Signed Distance Map (SDM) based on the initial rough segmentation of the subcortical region by a network as an anatomical constraint, providing comprehensive information on positions, structures, and morphology. Then we construct AAF-Net to fully fuse the SDM anatomical constraints and multimodal images for refined segmentation. To thoroughly evaluate the performance of our proposed tool, over 700 macaque MRIs from 19 datasets were used in this study. Specifically, we employed two manually labeled longitudinal macaque datasets to develop the tool and complete four-fold cross-validations. Furthermore, we incorporated various external datasets to demonstrate the proposed tool's generalization capabilities and promise in brain development research. We have made this tool available as an open-source resource at https://github.com/TaoZhong11/Macaque_subcortical_segmentation for direct application.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Ya Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Xiaotong Xu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China.
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2
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Alldritt S, Ramirez JSB, de Wael RV, Bethlehem R, Seidlitz J, Wang Z, Nenning K, Esper NB, Smallwood J, Franco AR, Byeon K, Alexander-Bloch A, Amaral DG, Amiez C, Balezeau F, Baxter MG, Becker G, Bennett J, Berkner O, Blezer ELA, Brambrink AM, Brochier T, Butler B, Campos LJ, Canet-Soulas E, Chalet L, Chen A, Cléry J, Constantinidis C, Cook DJ, Dehaene S, Dorfschmidt L, Drzewiecki CM, Erdman JW, Everling S, Falchier A, Fleysher L, Fox A, Freiwald W, Froesel M, Froudist-Walsh S, Fudge J, Funck T, Gacoin M, Gale DJ, Gallivan J, Garin CM, Griffiths TD, Guedj C, Hadj-Bouziane F, Hamed SB, Harel N, Hartig R, Hiba B, Howell BR, Jarraya B, Jung B, Kalin N, Karpf J, Kastner S, Klink C, Kovacs-Balint ZA, Kroenke C, Kuchan MJ, Kwok SC, Lala KN, Leopold DA, Li G, Lindenfors P, Linn G, Mars RB, Masiello K, Menon RS, Messinger A, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Neudecker V, Neuringer M, Noonan MP, Ortiz-Rios M, Perez-Zoghbi JF, Petkov CI, Pinsk M, Poirier C, Procyk E, Rajimehr R, Reader SM, Rudko DA, Rushworth MFS, Russ BE, Sallet J, Sanchez MM, Schmid MC, Schwiedrzik CM, Scott JA, Sein J, Sharma KK, Shmuel A, Styner M, Sullivan EL, Thiele A, Todorov OS, Tsao D, Tusche A, Vlasova R, Wang Z, Wang L, Wang J, Weiss AR, Wilson CRE, Yacoub E, Zarco W, Zhou Y, Zhu J, Margulies D, Fair D, Schroeder C, Milham M, Xu T. Brain Charts for the Rhesus Macaque Lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.28.610193. [PMID: 39257737 PMCID: PMC11383706 DOI: 10.1101/2024.08.28.610193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2024]
Abstract
Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.
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Affiliation(s)
- S Alldritt
- Center for the Integrative Developmental Neuroscience, Child Mind Institute
| | | | | | - R Bethlehem
- University of Cambridge, Department of Psychology
| | | | | | | | | | | | - A R Franco
- Child Mind Institute
- Nathan Kline Institute
| | | | - A Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia
- Department of Psychiatry, University of Pennsylvania
| | - D G Amaral
- Department of Psychiatry and Behavioral Sciences and The MIND Institute
- University of California Davis
| | - C Amiez
- Stem Cell and Brain Research Institute
| | | | - M G Baxter
- Section on Comparative Medicine, Wake Forest University School of Medicine
| | - G Becker
- Universite Claude Bernard Lyon 1
| | - J Bennett
- University of California Davis, Dept of Psychology
| | - O Berkner
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | | | | | | | - B Butler
- Translational Neuroscience Division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | | | | | | | - A Chen
- East China Normal University
| | | | | | | | | | | | | | | | | | - A Falchier
- Translational Neuroscience Division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | | | - A Fox
- University of California Davis
| | | | - M Froesel
- Institute for Cognitive Science Marc Jeannerod
| | | | | | | | - M Gacoin
- Institute for Cognitive Science Marc Jeannerod
| | | | | | - C M Garin
- Institut des Sciences Cognitives Marc Jeannerod (ISC-MJ)
- Department of Biomedical Engineering, Vanderbilt University
| | | | - C Guedj
- Lyon Neuroscience Research Center, University of Geneva
| | | | - S B Hamed
- Institute for Cognitive Science Marc Jeannerod
| | | | - R Hartig
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | - B Hiba
- Institute for Cognitive Science Marc Jeannerod
| | - B R Howell
- Emory National Primate Research Center, Emory University
- Fralin Biomedical Research Institute, Virginia Tech
- Carilion Department of Human Development and Family Science, Virginia Tech
| | | | - B Jung
- University of Pennsylvania
| | - N Kalin
- University of Wisconsin Madison
| | - J Karpf
- Oregon National Primate Research Center
| | - S Kastner
- Princeton Neuroscience Institute & Department of Psychology, Princeton University
| | - C Klink
- Netherlands Institute for Neuroscience
| | | | - C Kroenke
- Oregon National Primate Research Center
| | | | | | - K N Lala
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews
| | | | - G Li
- University of North Carolina at Chapel Hill
| | - P Lindenfors
- Institute for Futures Studies, Stockholm, Sweden
- Centre for Cultural Evolution & Department of Zoology, Stockholm University, Sweden
| | - G Linn
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | | | - K Masiello
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | | | | | - M Meunier
- Lyon Neuroscience Research Center, ImpAct Team
| | | | - J H Morrison
- California National Primate Research Center, Davis
| | | | - J Nagy
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai
| | | | | | | | - M Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research
| | | | - C I Petkov
- Newcastle University, University of Iowa
| | - M Pinsk
- Princeton Neuroscience Institute, Princeton University
| | | | - E Procyk
- Stem Cell and Brain Research Institute
| | - R Rajimehr
- McGovern Institute for Brain Research, Massachusetts Institute of Technology
| | - S M Reader
- Department of Biology, Utrecht University
- Department of Biology, McGill University
| | | | | | - B E Russ
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
| | - J Sallet
- INSERM Stem Cell & Brain Research Institute
- University of Oxford
| | - M M Sanchez
- Department of Psychiatry & Behavioral Sciences, School of Medicine
- Emory National Primate Research Center; Emory University
| | | | - C M Schwiedrzik
- Ruhr University Bochum, Faculty of Biology and Biotechnology, Cognitive Neurobiology
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research
| | - J A Scott
- Department of Bioengineering, Santa Clara University
| | | | | | | | - M Styner
- University of North Carolina at Chapel Hill
| | | | | | - O S Todorov
- Department of Biology and Helmholtz Institute, Utrecht University
| | - D Tsao
- Department of Computation and Neural Systems, California Institute of Technology
| | | | - R Vlasova
- University of North Carolina at Chapel Hill
| | - Z Wang
- Institute of Neuroscience
| | - L Wang
- East China Normal University
| | - J Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
| | - A R Weiss
- Oregon National Primate Research Center
| | | | | | | | - Y Zhou
- Krieger Mind/Brain Institute, Department of Neurosurgery, Johns Hopkins University
| | - J Zhu
- Department of Biomedical Engineering, Vanderbilt University
| | - D Margulies
- French National Centre for Scientific Research
| | | | - C Schroeder
- Translational Neuroscience division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute
- Deptartment of Psychiatry, Neurology and Neurosurgery, Columbia University
| | - M Milham
- Child Mind Institute
- Nathan Kline Institute
| | - T Xu
- Center for the Integrative Developmental Neuroscience, Child Mind Institute
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3
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Zhong T, Wu X, Liang S, Ning Z, Wang L, Niu Y, Yang S, Kang Z, Feng Q, Li G, Zhang Y. nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species. Neuroimage 2024; 295:120652. [PMID: 38797384 DOI: 10.1016/j.neuroimage.2024.120652] [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: 02/07/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 05/29/2024] Open
Abstract
Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) serves an indispensable role in understanding brain evolution, development, aging, and diseases. Despite the accumulation of diverse NHP brain MRI datasets at various developmental stages and from various imaging sites/scanners, existing computational tools designed for human MRI typically perform poor on NHP data, due to huge differences in brain sizes, morphologies, and imaging appearances across species, sites, and ages, highlighting the imperative for NHP-specialized MRI processing tools. To address this issue, in this paper, we present a robust, generic, and fully automated computational pipeline, called non-human primates Brain Extraction and Segmentation Toolbox (nBEST), whose main functionality includes brain extraction, non-cerebrum removal, and tissue segmentation. Building on cutting-edge deep learning techniques by employing lifelong learning to flexibly integrate data from diverse NHP populations and innovatively constructing 3D U-NeXt architecture, nBEST can well handle structural NHP brain MR images from multi-species, multi-site, and multi-developmental-stage (from neonates to the elderly). We extensively validated nBEST based on, to our knowledge, the largest assemblage dataset in NHP brain studies, encompassing 1,469 scans with 11 species (e.g., rhesus macaques, cynomolgus macaques, chimpanzees, marmosets, squirrel monkeys, etc.) from 23 independent datasets. Compared to alternative tools, nBEST outperforms in precision, applicability, robustness, comprehensiveness, and generalizability, greatly benefiting downstream longitudinal, cross-sectional, and cross-species quantitative analyses. We have made nBEST an open-source toolbox (https://github.com/TaoZhong11/nBEST) and we are committed to its continual refinement through lifelong learning with incoming data to greatly contribute to the research field.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
| | - Shihua Yang
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Zhuang Kang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qianjin Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.
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4
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Skandalakis GP, Linn W, Yeh F, Kazim SF, Komaitis S, Neromyliotis E, Dimopoulos D, Drosos E, Hadjipanayis CG, Kongkham PN, Zadeh G, Stranjalis G, Koutsarnakis C, Kogan M, Evans LT, Kalyvas A. Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways. Hum Brain Mapp 2024; 45:e26771. [PMID: 38925589 PMCID: PMC11199201 DOI: 10.1002/hbm.26771] [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: 10/30/2023] [Revised: 04/17/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024] Open
Abstract
Neuroimaging studies have consistently demonstrated concurrent activation of the human precuneus and temporal pole (TP), both during resting-state conditions and various higher-order cognitive functions. However, the precise underlying structural connectivity between these brain regions remains uncertain despite significant advancements in neuroscience research. In this study, we investigated the connectivity of the precuneus and TP by employing parcellation-based fiber micro-dissections in human brains and fiber tractography techniques in a sample of 1065 human subjects and a sample of 41 rhesus macaques. Our results demonstrate the connectivity between the posterior precuneus area POS2 and the areas 35, 36, and TG of the TP via the fifth subcomponent of the cingulum (CB-V) also known as parahippocampal cingulum. This finding contributes to our understanding of the connections within the posteromedial cortices, facilitating a more comprehensive integration of anatomy and function in both normal and pathological brain processes. PRACTITIONER POINTS: Our investigation delves into the intricate architecture and connectivity patterns of subregions within the precuneus and temporal pole, filling a crucial gap in our knowledge. We revealed a direct axonal connection between the posterior precuneus (POS2) and specific areas (35, 35, and TG) of the temporal pole. The direct connections are part of the CB-V pathway and exhibit a significant association with the cingulum, SRF, forceps major, and ILF. Population-based human tractography and rhesus macaque fiber tractography showed consistent results that support micro-dissection outcomes.
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Affiliation(s)
- Georgios P. Skandalakis
- Section of NeurosurgeryDartmouth Hitchcock Medical CenterLebanonNew HampshireUSA
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Wen‐Jieh Linn
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Fang‐Cheng Yeh
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Syed Faraz Kazim
- Department of NeurosurgeryUniversity of New Mexico HospitalAlbuquerqueNew MexicoUSA
| | - Spyridon Komaitis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Eleftherios Neromyliotis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Dimitrios Dimopoulos
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Evangelos Drosos
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | | | - Paul N. Kongkham
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
| | - Gelareh Zadeh
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
| | - George Stranjalis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Christos Koutsarnakis
- Department of NeurosurgeryNational and Kapodistrian University of Athens School of MedicineAthensGreece
| | - Michael Kogan
- Department of NeurosurgeryUniversity of New Mexico HospitalAlbuquerqueNew MexicoUSA
| | - Linton T. Evans
- Section of NeurosurgeryDartmouth Hitchcock Medical CenterLebanonNew HampshireUSA
| | - Aristotelis Kalyvas
- Department of NeurosurgeryToronto Western Hospital, University Health NetworkTorontoOntarioCanada
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5
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Grandjean J, Lake EMR, Pagani M, Mandino F. What N Is N-ough for MRI-Based Animal Neuroimaging? eNeuro 2024; 11:ENEURO.0531-23.2024. [PMID: 38499355 PMCID: PMC10950324 DOI: 10.1523/eneuro.0531-23.2024] [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: 12/14/2023] [Revised: 02/08/2024] [Accepted: 02/13/2024] [Indexed: 03/20/2024] Open
Abstract
Fueled by the recent and controversial brain-wide association studies in humans, the animal neuroimaging community has also begun questioning whether using larger sample sizes is necessary for ethical and effective scientific progress. In this opinion piece, we illustrate two opposing views on sample size extremes in MRI-based animal neuroimaging.
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Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Cognition, and Behaviour, Nijmegen 6500HB, The Netherlands
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen 6500HB, The Netherlands
| | - Evelyn M R Lake
- Departments of Radiology and Biomedical Imaging, New Haven, Connecticut 06519
- Biomedical Engineering, Yale School of Medicine, New Haven, Connecticut 06519
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto 38068, Italy
- IMT School for Advanced Studies, Lucca 55100, Italy
| | - Francesca Mandino
- Departments of Radiology and Biomedical Imaging, New Haven, Connecticut 06519
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Auvity S, Vodovar D, Goutal S, Cisternino S, Chevillard L, Soyer A, Bottlaender M, Caillé F, Mégarbane B, Tournier N. Brain PET imaging using 11C-flumazenil and 11C-buprenorphine does not support the hypothesis of a mutual interaction between buprenorphine and benzodiazepines at the neuroreceptor level. J Cereb Blood Flow Metab 2024; 44:449-458. [PMID: 38097513 PMCID: PMC10870960 DOI: 10.1177/0271678x231221040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/20/2023] [Accepted: 11/20/2023] [Indexed: 02/16/2024]
Abstract
Among opioids, buprenorphine presents a favorable safety profile with a limited risk of respiratory depression. However, fatalities have been reported when buprenorphine is combined to a benzodiazepine. Potentiation of buprenorphine interaction with opioid receptors (ORs) with benzodiazepines, and/or vice versa, is hypothesized to explain this drug-drug interaction (DDI). The mutual DDI between buprenorphine and benzodiazepines was investigated at the neuroreceptor level in nonhuman primates (n = 4 individuals) using brain PET imaging and kinetic modelling. The binding potential (BPND) of benzodiazepine receptor (BzR) was assessed using 11C-flumazenil PET imaging before and after administration of buprenorphine (0.2 mg, i.v.). Moreover, the brain kinetics and receptor binding of buprenorphine were investigated in the same individuals using 11C-buprenorphine PET imaging before and after administration of diazepam (10 mg, i.v.). Outcome parameters were compared using a two-way ANOVA. Buprenorphine did not impact the plasma nor brain kinetics of 11C-flumazenil. 11C-flumazenil BPND was unchanged following buprenorphine exposure, in any brain region (p > 0.05). Similarly, diazepam did not impact the plasma or brain kinetics of 11C-buprenorphine. 11C-buprenorphine volume of distribution (VT) was unchanged following diazepam exposure, in any brain region (p > 0.05). To conclude, our PET imaging findings do not support a neuropharmacokinetic or neuroreceptor-related mechanism of the buprenorphine/benzodiazepine interaction.
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Affiliation(s)
- Sylvain Auvity
- Faculté de Pharmacie, Université Paris Cité, Inserm, UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
| | - Dominique Vodovar
- Faculté de Pharmacie, Université Paris Cité, Inserm, UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
- Réanimation Médicale et Toxicologique, Hôpital Lariboisière, Fédération de Toxicologie (APHP), 75010, Paris
| | - Sébastien Goutal
- Université Paris-Saclay, Inserm, CNRS, CEA, Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Orsay, France
| | - Salvatore Cisternino
- Faculté de Pharmacie, Université Paris Cité, Inserm, UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
| | - Lucie Chevillard
- Faculté de Pharmacie, Université Paris Cité, Inserm, UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
| | - Amélie Soyer
- Université Paris-Saclay, Inserm, CNRS, CEA, Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Orsay, France
| | - Michel Bottlaender
- Université Paris-Saclay, Inserm, CNRS, CEA, Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Orsay, France
| | - Fabien Caillé
- Université Paris-Saclay, Inserm, CNRS, CEA, Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Orsay, France
| | - Bruno Mégarbane
- Faculté de Pharmacie, Université Paris Cité, Inserm, UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
- Réanimation Médicale et Toxicologique, Hôpital Lariboisière, Fédération de Toxicologie (APHP), 75010, Paris
| | - Nicolas Tournier
- Université Paris-Saclay, Inserm, CNRS, CEA, Laboratoire d’Imagerie Biomédicale Multimodale (BioMaps), Orsay, France
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7
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Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, Yuste R. Automatic monitoring of neural activity with single-cell resolution in behaving Hydra. Sci Rep 2024; 14:5083. [PMID: 38429381 PMCID: PMC10907378 DOI: 10.1038/s41598-024-55608-2] [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: 09/25/2023] [Accepted: 02/26/2024] [Indexed: 03/03/2024] Open
Abstract
The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.
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Affiliation(s)
- Alison Hanson
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA.
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY, USA.
| | - Raphael Reme
- UMR3691, BioImage Analysis Unit, Institut Pasteur, Université Paris Cité, CNRS, Paris, France
| | - Noah Telerman
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
| | - Wataru Yamamoto
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
| | | | - Thibault Lagache
- UMR3691, BioImage Analysis Unit, Institut Pasteur, Université Paris Cité, CNRS, Paris, France
| | - Rafael Yuste
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
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8
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Assimopoulos S, Warrington S, Bryant KL, Pszczolkowski S, Jbabdi S, Mars RB, Sotiropoulos SN. Generalising XTRACT tractography protocols across common macaque brain templates. Brain Struct Funct 2024:10.1007/s00429-024-02760-0. [PMID: 38388696 DOI: 10.1007/s00429-024-02760-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/09/2024] [Indexed: 02/24/2024]
Abstract
Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human-macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates.
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Affiliation(s)
- Stephania Assimopoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Shaun Warrington
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Katherine L Bryant
- Laboratoire de Psychologie Cognitive, Aix-Marseille Université, Marseille, France
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stefan Pszczolkowski
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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9
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González-González MA, Conde SV, Latorre R, Thébault SC, Pratelli M, Spitzer NC, Verkhratsky A, Tremblay MÈ, Akcora CG, Hernández-Reynoso AG, Ecker M, Coates J, Vincent KL, Ma B. Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies. Front Integr Neurosci 2024; 18:1321872. [PMID: 38440417 PMCID: PMC10911101 DOI: 10.3389/fnint.2024.1321872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/10/2024] [Indexed: 03/06/2024] Open
Abstract
Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.
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Affiliation(s)
- María Alejandra González-González
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Department of Pediatric Neurology, Baylor College of Medicine, Houston, TX, United States
| | - Silvia V. Conde
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NOVA University, Lisbon, Portugal
| | - Ramon Latorre
- Centro Interdisciplinario de Neurociencia de Valparaíso, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Stéphanie C. Thébault
- Laboratorio de Investigación Traslacional en salud visual (D-13), Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM), Querétaro, Mexico
| | - Marta Pratelli
- Neurobiology Department, Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, United States
| | - Nicholas C. Spitzer
- Neurobiology Department, Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, United States
| | - Alexei Verkhratsky
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Achucarro Centre for Neuroscience, IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- International Collaborative Center on Big Science Plan for Purinergic Signaling, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of Stem Cell Biology, State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
| | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Molecular Medicine, Université Laval, Québec City, QC, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Cuneyt G. Akcora
- Department of Computer Science, University of Central Florida, Orlando, FL, United States
| | | | - Melanie Ecker
- Department of Biomedical Engineering, University of North Texas, Denton, TX, United States
| | | | - Kathleen L. Vincent
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX, United States
| | - Brandy Ma
- Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, TX, United States
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10
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Chalet L, Debatisse J, Wateau O, Boutelier T, Wiart M, Costes N, Mérida I, Redouté J, Langlois JB, Lancelot S, Léon C, Cho TH, Mechtouff L, Eker OF, Nighoghossian N, Canet-Soulas E, Becker G. The PREMISE database of 20 Macaca fascicularis PET/MRI brain images available for research. Lab Anim (NY) 2024; 53:13-17. [PMID: 37996697 PMCID: PMC10766538 DOI: 10.1038/s41684-023-01289-9] [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: 04/06/2023] [Accepted: 10/17/2023] [Indexed: 11/25/2023]
Abstract
Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [15O]H2O and [11C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository.
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Affiliation(s)
- Lucie Chalet
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
- Olea Medical, La Ciotat, France
| | - Justine Debatisse
- Institut des Sciences Cognitives Marc Jeannerod (ISCMJ), UMR 5229 CNRS, Bron Cedex, France
| | | | | | - Marlène Wiart
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
| | | | | | | | | | | | - Christelle Léon
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
| | - Tae-Hee Cho
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Laura Mechtouff
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Omer Faruk Eker
- Hospices Civils de Lyon, Lyon, France
- CREATIS, CNRS UMR 5220, INSERM U1206, Université Lyon 1, INSA Lyon, Bât. Blaise Pascal, Villeurbanne, France
| | - Norbert Nighoghossian
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Emmanuelle Canet-Soulas
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France.
| | - Guillaume Becker
- CarMeN Laboratory, Université Claude Bernard Lyon 1, INSERM U1060, INRA U1397, Lyon, France.
- Lyon Neuroscience Research Center, University Claude Bernard Lyon 1, INSERM U1028, CNRS UMR 5292, Lyon, France.
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11
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Merchant H, Mendoza G, Pérez O, Betancourt A, García-Saldivar P, Prado L. Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:117-140. [PMID: 38918349 DOI: 10.1007/978-3-031-60183-5_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.
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Affiliation(s)
- Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico.
| | - Germán Mendoza
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | - Oswaldo Pérez
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | | | | | - Luis Prado
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
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12
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Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, Yuste R. Automatic monitoring of whole-body neural activity in behaving Hydra. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.22.559063. [PMID: 37790332 PMCID: PMC10542483 DOI: 10.1101/2023.09.22.559063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.
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Affiliation(s)
- Alison Hanson
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY, USA
| | - Raphael Reme
- Institut Pasteur, Université Paris Cité, CNRS UMR3691, BioImage Analysis Unit, Paris, France
| | - Noah Telerman
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Wataru Yamamoto
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
| | | | - Thibault Lagache
- Institut Pasteur, Université Paris Cité, CNRS UMR3691, BioImage Analysis Unit, Paris, France
| | - Rafael Yuste
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
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13
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Demirci N, Hoffman ME, Holland MA. Systematic cortical thickness and curvature patterns in primates. Neuroimage 2023; 278:120283. [PMID: 37516374 PMCID: PMC10443624 DOI: 10.1016/j.neuroimage.2023.120283] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 07/31/2023] Open
Abstract
Humans are known to have significant and consistent differences in thickness throughout the cortex, with thick outer gyral folds and thin inner sulcal folds. Our previous work has suggested a mechanical basis for this thickness pattern, with the forces generated during cortical folding leading to thick gyri and thin sulci, and shown that cortical thickness varies along a gyral-sulcal spectrum in humans. While other primate species are expected to exhibit similar patterns of cortical thickness, it is currently unknown how these patterns scale across different sizes, forms, and foldedness. Among primates, brains vary enormously from roughly the size of a grape to the size of a grapefruit, and from nearly smooth to dramatically folded; of these, human brains are the largest and most folded. These variations in size and form make comparative neuroanatomy a rich resource for investigating common trends that transcend differences between species. In this study, we examine 12 primate species in order to cover a wide range of sizes and forms, and investigate the scaling of their cortical thickness relative to the surface geometry. The 12 species were selected due to the public availability of either reconstructed surfaces and/or population templates. After obtaining or reconstructing 3D surfaces from publicly available neuroimaging data, we used our surface-based computational pipeline (https://github.com/mholla/curveball) to analyze patterns of cortical thickness and folding with respect to size (total surface area), geometry (i.e. curvature, shape, and sulcal depth), and foldedness (gyrification). In all 12 species, we found consistent cortical thickness variations along a gyral-sulcal spectrum, with convex shapes thicker than concave shapes and saddle shapes in between. Furthermore, we saw an increasing thickness difference between gyri and sulci as brain size increases. Our results suggest a systematic folding mechanism relating local cortical thickness to geometry. Finally, all of our reconstructed surfaces and morphometry data are available for future research in comparative neuroanatomy.
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Affiliation(s)
- Nagehan Demirci
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Mia E Hoffman
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Maria A Holland
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
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14
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Eke D, Ogoh G, Knight W, Stahl B. Time to consider animal data governance: perspectives from neuroscience. Front Neuroinform 2023; 17:1233121. [PMID: 37711673 PMCID: PMC10497762 DOI: 10.3389/fninf.2023.1233121] [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: 06/01/2023] [Accepted: 08/09/2023] [Indexed: 09/16/2023] Open
Abstract
Introduction Scientific research relies mainly on multimodal, multidimensional big data generated from both animal and human organisms as well as technical data. However, unlike human data that is increasingly regulated at national, regional and international levels, regulatory frameworks that can govern the sharing and reuse of non-human animal data are yet to be established. Whereas the legal and ethical principles that shape animal data generation in many countries and regions differ, the generated data are shared beyond boundaries without any governance mechanism. This paper, through perspectives from neuroscience, shows conceptually and empirically that there is a need for animal data governance that is informed by ethical concerns. There is a plurality of ethical views on the use of animals in scientific research that data governance mechanisms need to consider. Methods Semi-structured interviews were used for data collection. Overall, 13 interviews with 12 participants (10 males and 2 females) were conducted. The interviews were transcribed and stored in NviVo 12 where they were thematically analyzed. Results The participants shared the view that it is time to consider animal data governance due to factors such as differences in regulations, differences in ethical principles, values and beliefs and data quality concerns. They also provided insights on possible approaches to governance. Discussion We therefore conclude that a procedural approach to data governance is needed: an approach that does not prescribe a particular ethical position but allows for a quick understanding of ethical concerns and debate about how different positions differ to facilitate cross-cultural and international collaboration.
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Affiliation(s)
- Damian Eke
- Centre for Computing and Social Responsibility, De Montfort University, Leicester, United Kingdom
| | - George Ogoh
- School of Computer Science, University of Nottingham, Nottingham, United Kingdom
| | - William Knight
- Centre for Computing and Social Responsibility, De Montfort University, Leicester, United Kingdom
| | - Bernd Stahl
- School of Computer Science, University of Nottingham, Nottingham, United Kingdom
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15
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Rapan L, Froudist-Walsh S, Niu M, Xu T, Zhao L, Funck T, Wang XJ, Amunts K, Palomero-Gallagher N. Cytoarchitectonic, receptor distribution and functional connectivity analyses of the macaque frontal lobe. eLife 2023; 12:e82850. [PMID: 37578332 PMCID: PMC10425179 DOI: 10.7554/elife.82850] [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: 08/19/2022] [Accepted: 06/14/2023] [Indexed: 08/15/2023] Open
Abstract
Based on quantitative cyto- and receptor architectonic analyses, we identified 35 prefrontal areas, including novel subdivisions of Walker's areas 10, 9, 8B, and 46. Statistical analysis of receptor densities revealed regional differences in lateral and ventrolateral prefrontal cortex. Indeed, structural and functional organization of subdivisions encompassing areas 46 and 12 demonstrated significant differences in the interareal levels of α2 receptors. Furthermore, multivariate analysis included receptor fingerprints of previously identified 16 motor areas in the same macaque brains and revealed 5 clusters encompassing frontal lobe areas. We used the MRI datasets from the non-human primate data sharing consortium PRIME-DE to perform functional connectivity analyses using the resulting frontal maps as seed regions. In general, rostrally located frontal areas were characterized by bigger fingerprints, that is, higher receptor densities, and stronger regional interconnections. Whereas more caudal areas had smaller fingerprints, but showed a widespread connectivity pattern with distant cortical regions. Taken together, this study provides a comprehensive insight into the molecular structure underlying the functional organization of the cortex and, thus, reconcile the discrepancies between the structural and functional hierarchical organization of the primate frontal lobe. Finally, our data are publicly available via the EBRAINS and BALSA repositories for the entire scientific community.
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Affiliation(s)
- Lucija Rapan
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Sean Froudist-Walsh
- Center for Neural Science, New York UniversityNew YorkUnited States
- Bristol Computational Neuroscience Unit, Faculty of Engineering, University of BristolBristolUnited Kingdom
| | - Meiqi Niu
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Ting Xu
- Center for the Developing Brain, Child Mind InstituteNew YorkUnited States
| | - Ling Zhao
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Thomas Funck
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Xiao-Jing Wang
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Katrin Amunts
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
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16
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de Sousa AA, Beaudet A, Calvey T, Bardo A, Benoit J, Charvet CJ, Dehay C, Gómez-Robles A, Gunz P, Heuer K, van den Heuvel MP, Hurst S, Lauters P, Reed D, Salagnon M, Sherwood CC, Ströckens F, Tawane M, Todorov OS, Toro R, Wei Y. From fossils to mind. Commun Biol 2023; 6:636. [PMID: 37311857 PMCID: PMC10262152 DOI: 10.1038/s42003-023-04803-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 04/04/2023] [Indexed: 06/15/2023] Open
Abstract
Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology's approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior.
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Affiliation(s)
| | - Amélie Beaudet
- Laboratoire de Paléontologie, Évolution, Paléoécosystèmes et Paléoprimatologie (PALEVOPRIM), UMR 7262 CNRS & Université de Poitiers, Poitiers, France.
- University of Cambridge, Cambridge, UK.
| | - Tanya Calvey
- Division of Clinical Anatomy and Biological Anthropology, University of Cape Town, Cape Town, South Africa.
| | - Ameline Bardo
- UMR 7194, CNRS-MNHN, Département Homme et Environnement, Musée de l'Homme, Paris, France
- Skeletal Biology Research Centre, School of Anthropology and Conservation, University of Kent, Canterbury, UK
| | - Julien Benoit
- Evolutionary Studies Institute, University of the Witwatersrand, Johannesburg, South Africa
| | - Christine J Charvet
- Department of Anatomy, Physiology and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Colette Dehay
- University of Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, F-69500, Bron, France
| | | | - Philipp Gunz
- Department of Human Origins, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103, Leipzig, Germany
| | - Katja Heuer
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | | | - Shawn Hurst
- University of Indianapolis, Indianapolis, IN, USA
| | - Pascaline Lauters
- Institut royal des Sciences naturelles, Direction Opérationnelle Terre et Histoire de la Vie, Brussels, Belgium
| | - Denné Reed
- Department of Anthropology, University of Texas at Austin, Austin, TX, USA
| | - Mathilde Salagnon
- CNRS, CEA, IMN, GIN, UMR 5293, Université Bordeaux, Bordeaux, France
- PACEA UMR 5199, CNRS, Université Bordeaux, Pessac, France
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - Felix Ströckens
- C. & O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Mirriam Tawane
- Ditsong National Museum of Natural History, Pretoria, South Africa
| | - Orlin S Todorov
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
| | - Roberto Toro
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Yongbin Wei
- Beijing University of Posts and Telecommunications, Beijing, China
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17
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Amiez C, Sallet J, Giacometti C, Verstraete C, Gandaux C, Morel-Latour V, Meguerditchian A, Hadj-Bouziane F, Ben Hamed S, Hopkins WD, Procyk E, Wilson CRE, Petrides M. A revised perspective on the evolution of the lateral frontal cortex in primates. SCIENCE ADVANCES 2023; 9:eadf9445. [PMID: 37205762 DOI: 10.1126/sciadv.adf9445] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 04/14/2023] [Indexed: 05/21/2023]
Abstract
Detailed neuroscientific data from macaque monkeys have been essential in advancing understanding of human frontal cortex function, particularly for regions of frontal cortex without homologs in other model species. However, precise transfer of this knowledge for direct use in human applications requires an understanding of monkey to hominid homologies, particularly whether and how sulci and cytoarchitectonic regions in the frontal cortex of macaques relate to those in hominids. We combine sulcal pattern analysis with resting-state functional magnetic resonance imaging and cytoarchitectonic analysis to show that old-world monkey brains have the same principles of organization as hominid brains, with the notable exception of sulci in the frontopolar cortex. This essential comparative framework provides insights into primate brain evolution and a key tool to drive translation from invasive research in monkeys to human applications.
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Affiliation(s)
- Céline Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Jérôme Sallet
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
- Wellcome Integrative Neuroimaging Centre, Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK
| | - Camille Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Charles Verstraete
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Clémence Gandaux
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Valentine Morel-Latour
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille, CNRS, 13331 Marseille, France
- Station de Primatologie CNRS, UPS846, 13790 Rousset, France
- Brain and Language Research Institute, Université Aix-Marseille, CNRS, 13604 Aix-en-Provence, France
| | - Fadila Hadj-Bouziane
- Integrative Multisensory Perception Action and Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France; University of Lyon 1, Lyon, France
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-Université Claude Bernard Lyon I, Bron, France
| | - William D Hopkins
- Department of Comparative Medicine, University of Texas MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Emmanuel Procyk
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Charles R E Wilson
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Michael Petrides
- Department of Neurology and Neurosurgery and Department of Psychology, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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18
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Gozzi A, Zerbi V. Modeling Brain Dysconnectivity in Rodents. Biol Psychiatry 2023; 93:419-429. [PMID: 36517282 DOI: 10.1016/j.biopsych.2022.09.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/19/2022] [Accepted: 09/10/2022] [Indexed: 02/04/2023]
Abstract
Altered or atypical functional connectivity as measured with functional magnetic resonance imaging (fMRI) is a hallmark feature of brain connectopathy in psychiatric, developmental, and neurological disorders. However, the biological underpinnings and etiopathological significance of this phenomenon remain unclear. The recent development of MRI-based techniques for mapping brain function in rodents provides a powerful platform to uncover the determinants of functional (dys)connectivity, whether they are genetic mutations, environmental risk factors, or specific cellular and circuit dysfunctions. Here, we summarize the recent contribution of rodent fMRI toward a deeper understanding of network dysconnectivity in developmental and psychiatric disorders. We highlight substantial correspondences in the spatiotemporal organization of rodent and human fMRI networks, supporting the translational relevance of this approach. We then show how this research platform might help us comprehend the importance of connectional heterogeneity in complex brain disorders and causally relate multiscale pathogenic contributors to functional dysconnectivity patterns. Finally, we explore how perturbational techniques can be used to dissect the fundamental aspects of fMRI coupling and reveal the causal contribution of neuromodulatory systems to macroscale network activity, as well as its altered dynamics in brain diseases. These examples outline how rodent functional imaging is poised to advance our understanding of the bases and determinants of human functional dysconnectivity.
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Affiliation(s)
- Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy.
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering, École polytechnique fédérale de Lausanne, Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Switzerland.
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19
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A framework and resource for global collaboration in non-human primate neuroscience. CURRENT RESEARCH IN NEUROBIOLOGY 2023. [DOI: 10.1016/j.crneur.2023.100079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023] Open
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20
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Tian X, Chen Y, Majka P, Szczupak D, Perl YS, Yen CCC, Tong C, Feng F, Jiang H, Glen D, Deco G, Rosa MGP, Silva AC, Liang Z, Liu C. An integrated resource for functional and structural connectivity of the marmoset brain. Nat Commun 2022; 13:7416. [PMID: 36456558 PMCID: PMC9715556 DOI: 10.1038/s41467-022-35197-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 11/21/2022] [Indexed: 12/02/2022] Open
Abstract
Comprehensive integration of structural and functional connectivity data is required to model brain functions accurately. While resources for studying the structural connectivity of non-human primate brains already exist, their integration with functional connectivity data has remained unavailable. Here we present a comprehensive resource that integrates the most extensive awake marmoset resting-state fMRI data available to date (39 marmoset monkeys, 710 runs, 12117 mins) with previously published cellular-level neuronal tracing data (52 marmoset monkeys, 143 injections) and multi-resolution diffusion MRI datasets. The combination of these data allowed us to (1) map the fine-detailed functional brain networks and cortical parcellations, (2) develop a deep-learning-based parcellation generator that preserves the topographical organization of functional connectivity and reflects individual variabilities, and (3) investigate the structural basis underlying functional connectivity by computational modeling. This resource will enable modeling structure-function relationships and facilitate future comparative and translational studies of primate brains.
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Affiliation(s)
- Xiaoguang Tian
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Yuyan Chen
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Piotr Majka
- grid.419305.a0000 0001 1943 2944Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland ,grid.1002.30000 0004 1936 7857Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800 Australia
| | - Diego Szczupak
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Yonatan Sanz Perl
- grid.5612.00000 0001 2172 2676Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018 Spain ,grid.441741.30000 0001 2325 2241Universidad de San Andrés, Vito Dumas 284 (B1644BID), Buenos Aires, Argentina
| | - Cecil Chern-Chyi Yen
- grid.94365.3d0000 0001 2297 5165Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD 20892 USA
| | - Chuanjun Tong
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Furui Feng
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
| | - Haiteng Jiang
- grid.13402.340000 0004 1759 700XDepartment of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Zhe Jiang Sheng, China ,grid.13402.340000 0004 1759 700XMOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Daniel Glen
- grid.94365.3d0000 0001 2297 5165Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH), Bethesda, MD 20892 USA
| | - Gustavo Deco
- grid.5612.00000 0001 2172 2676Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018 Spain ,grid.425902.80000 0000 9601 989XInstitució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010 Spain ,grid.419524.f0000 0001 0041 5028Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103 Germany ,grid.1002.30000 0004 1936 7857School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC 3800 Australia
| | - Marcello G. P. Rosa
- grid.1002.30000 0004 1936 7857Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800 Australia
| | - Afonso C. Silva
- grid.21925.3d0000 0004 1936 9000Department of Neurobiology, University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Zhifeng Liang
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China ,grid.511008.dShanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai, Shanghai, China
| | - Cirong Liu
- grid.9227.e0000000119573309Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China ,grid.511008.dShanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai, Shanghai, China ,Lingang Laboratory, Shanghai, 200031 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, China
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21
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Zablocki-Thomas PB, Rogers FD, Bales KL. Neuroimaging of human and non-human animal emotion and affect in the context of social relationships. Front Behav Neurosci 2022; 16:994504. [PMID: 36338883 PMCID: PMC9633678 DOI: 10.3389/fnbeh.2022.994504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/26/2022] [Indexed: 11/28/2022] Open
Abstract
Long-term relationships are essential for the psychological wellbeing of humans and many animals. Positive emotions and affective experiences (e.g., romantic or platonic love) seem to be closely related to the creation and maintenance of social bonds. When relationships are threatened or terminated, other emotions generally considered to be negative can arise (e.g., jealousy or loneliness). Because humans and animals share (to varying degrees) common evolutionary histories, researchers have attempted to explain the evolution of affect and emotion through the comparative approach. Now brain imaging techniques allow the comparison of the neurobiological substrates of affective states and emotion in human and animal brains using a common methodology. Here, we review brain imaging studies that feature emotions characterized by the context of social bonding. We compare imaging findings associated with affective and emotional states elicited by similar social situations between humans and animal models. We also highlight the role of key neurohormones (i.e., oxytocin, vasopressin, and dopamine) that jointly support the occurrence of socially contextualized emotions and affect across species. In doing so, we seek to explore and clarify if and how humans and animals might similarly experience social emotion and affect in the context of social relationships.
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Affiliation(s)
| | - Forrest D. Rogers
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
- Department of Psychology, University of California, Davis, Davis, CA, United States
- Psychology Graduate Group, University of California, Davis, Davis, CA, United States
| | - Karen L. Bales
- California National Primate Research Center, Davis, CA, United States
- Department of Psychology, University of California, Davis, Davis, CA, United States
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, Davis, CA, United States
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22
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Muta K, Hata J, Kawaguchi N, Haga Y, Yoshimaru D, Hagiya K, Kaneko T, Miyabe-Nishiwaki T, Komaki Y, Seki F, Okano HJ, Okano H. Effect of sedatives or anesthetics on the measurement of resting brain function in common marmosets. Cereb Cortex 2022; 33:5148-5162. [PMID: 36222604 PMCID: PMC10151911 DOI: 10.1093/cercor/bhac406] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 11/13/2022] Open
Abstract
Common marmosets are promising laboratory animals for the study of higher brain functions. Although there are many opportunities to use sedatives and anesthetics in resting brain function measurements in marmosets, their effects on the resting-state network remain unclear. In this study, the effects of sedatives or anesthetics such as midazolam, dexmedetomidine, co-administration of isoflurane and dexmedetomidine, propofol, alfaxalone, isoflurane, and sevoflurane on the resting brain function in common marmosets were evaluated using independent component analysis, dual regression analysis, and graph-theoretic analysis; and the sedatives or anesthetics suitable for the evaluation of resting brain function were investigated. The results show that network preservation tendency under light sedative with midazolam and dexmedetomidine is similar regardless of the type of target receptor. Moreover, alfaxalone, isoflurane, and sevoflurane have similar effects on resting state brain function, but only propofol exhibits different tendencies, as resting brain function is more preserved than it is following the administration of the other anesthetics. Co-administration of isoflurane and dexmedetomidine shows middle effect between sedatives and anesthetics.
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Affiliation(s)
- Kanako Muta
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo 116-8551, Japan.,Division of Regenerative Medicine, The Jikei University School of Medicine, Minato, Tokyo 105-8461, Japan
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo 116-8551, Japan.,Division of Regenerative Medicine, The Jikei University School of Medicine, Minato, Tokyo 105-8461, Japan.,Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.,Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Naoki Kawaguchi
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo 116-8551, Japan
| | - Yawara Haga
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa, Tokyo 116-8551, Japan.,Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.,Live Imaging Center, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Daisuke Yoshimaru
- Division of Regenerative Medicine, The Jikei University School of Medicine, Minato, Tokyo 105-8461, Japan.,Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.,Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.,Live Imaging Center, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Kei Hagiya
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan
| | - Takaaki Kaneko
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.,Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Takako Miyabe-Nishiwaki
- Center for Model Human Evolution Research, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Yuji Komaki
- Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.,Live Imaging Center, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Fumiko Seki
- Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.,Live Imaging Center, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Hirotaka James Okano
- Division of Regenerative Medicine, The Jikei University School of Medicine, Minato, Tokyo 105-8461, Japan
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.,Department of Physiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
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23
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Comparing human and chimpanzee temporal lobe neuroanatomy reveals modifications to human language hubs beyond the frontotemporal arcuate fasciculus. Proc Natl Acad Sci U S A 2022; 119:e2118295119. [PMID: 35787056 PMCID: PMC9282369 DOI: 10.1073/pnas.2118295119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The biological foundation for the language-ready brain in the human lineage remains a debated subject. In humans, the arcuate fasciculus (AF) white matter and the posterior portions of the middle temporal gyrus are crucial for language. Compared with other primates, the human AF has been shown to dramatically extend into the posterior temporal lobe, which forms the basis of a number of models of the structural connectivity basis of language. Recent advances in both language research and comparative neuroimaging invite a reassessment of the anatomical differences in language streams between humans and our closest relatives. Here, we show that posterior temporal connectivity via the AF in humans compared with chimpanzees is expanded in terms of its connectivity not just to the ventral frontal cortex but also to the parietal cortex. At the same time, posterior temporal regions connect more strongly to the ventral white matter in chimpanzees as opposed to humans. This pattern is present in both brain hemispheres. Additionally, we show that the anterior temporal lobe harbors a combination of connections present in both species through the inferior fronto-occipital fascicle and human-unique expansions through the uncinate and middle and inferior longitudinal fascicles. These findings elucidate structural changes that are unique to humans and may underlie the anatomical foundations for full-fledged language capacity.
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24
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Sirmpilatze N, Mylius J, Ortiz-Rios M, Baudewig J, Paasonen J, Golkowski D, Ranft A, Ilg R, Gröhn O, Boretius S. Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents. eLife 2022; 11:e74813. [PMID: 35607889 PMCID: PMC9129882 DOI: 10.7554/elife.74813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/01/2022] [Indexed: 01/19/2023] Open
Abstract
During deep anesthesia, the electroencephalographic (EEG) signal of the brain alternates between bursts of activity and periods of relative silence (suppressions). The origin of burst-suppression and its distribution across the brain remain matters of debate. In this work, we used functional magnetic resonance imaging (fMRI) to map the brain areas involved in anesthesia-induced burst-suppression across four mammalian species: humans, long-tailed macaques, common marmosets, and rats. At first, we determined the fMRI signatures of burst-suppression in human EEG-fMRI data. Applying this method to animal fMRI datasets, we found distinct burst-suppression signatures in all species. The burst-suppression maps revealed a marked inter-species difference: in rats, the entire neocortex engaged in burst-suppression, while in primates most sensory areas were excluded-predominantly the primary visual cortex. We anticipate that the identified species-specific fMRI signatures and whole-brain maps will guide future targeted studies investigating the cellular and molecular mechanisms of burst-suppression in unconscious states.
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Affiliation(s)
- Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
- Georg-August University of GöttingenGöttingenGermany
- International Max Planck Research School for NeurosciencesGöttingenGermany
| | - Judith Mylius
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Michael Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Jaakko Paasonen
- A.I.V. Institute for Molecular Sciences, University of Eastern FinlandKuopioFinland
| | - Daniel Golkowski
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
- Department of Neurology, Heidelberg University HospitalHeidelbergGermany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care Medicine, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
| | - Rüdiger Ilg
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
- Department of Neurology, Asklepios Stadtklinik Bad TölzBad TölzGermany
| | - Olli Gröhn
- A.I.V. Institute for Molecular Sciences, University of Eastern FinlandKuopioFinland
| | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
- Georg-August University of GöttingenGöttingenGermany
- International Max Planck Research School for NeurosciencesGöttingenGermany
- Leibniz Science Campus Primate CognitionGöttingenGermany
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25
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Bliss-Moreau E, Costa VD, Baxter MG. A pragmatic reevaluation of the efficacy of nonhuman primate optogenetics for psychiatry. OXFORD OPEN NEUROSCIENCE 2022; 1:kvac006. [PMID: 38596709 PMCID: PMC10939311 DOI: 10.1093/oons/kvac006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 03/03/2022] [Accepted: 03/08/2022] [Indexed: 04/11/2024]
Abstract
Translational neuroscience is committed to generating discoveries in the laboratory that ultimately can improve human lives. Optogenetics has received considerable attention because of its demonstrated promise in rodent brains to manipulate cells and circuits. In a recent report, Tremblay et al. [28] introduce an open resource detailing optogenetic studies of the nonhuman primate (NHP) brain and make robust claims about the translatability of the technology. We propose that their quantitative (e.g. a 91% success rate) and theoretical claims are questionable because the data were analyzed at a level relevant to the rodent but not NHP brain. Injections were clustered within a few monkeys in a few studies in a few brain regions, and their definitions of success were not clearly relevant to human neuropsychiatric disease. A reanalysis of the data with a modified definition of success that included a behavioral and biological effect revealed a 62.5% success rate that was lower when considering only strong outcomes (53.1%). This calls into question the current efficacy of optogenetic techniques in the NHP brain and suggests that we are a long way from being able to leverage them in 'the service of patients with neurological or psychiatric conditions' as the Tremblay report claims.
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Affiliation(s)
- Eliza Bliss-Moreau
- Department of Psychology, University of California Davis,
CA 95616, USA
- California National Primate Research Center, University of California Davis, CA 95616, USA
| | - Vincent D Costa
- Department of Behavioral Neuroscience, Oregon Health Sciences University, OR 97239, USA
- Oregon National Primate Research Center, Oregon Health Sciences University, OR 97239, USA
| | - Mark G Baxter
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, NY 10029-5674, USA
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26
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Structural Brain Asymmetries for Language: A Comparative Approach across Primates. Symmetry (Basel) 2022. [DOI: 10.3390/sym14050876] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Humans are the only species that can speak. Nonhuman primates, however, share some ‘domain-general’ cognitive properties that are essential to language processes. Whether these shared cognitive properties between humans and nonhuman primates are the results of a continuous evolution [homologies] or of a convergent evolution [analogies] remain difficult to demonstrate. However, comparing their respective underlying structure—the brain—to determinate their similarity or their divergence across species is critical to help increase the probability of either of the two hypotheses, respectively. Key areas associated with language processes are the Planum Temporale, Broca’s Area, the Arcuate Fasciculus, Cingulate Sulcus, The Insula, Superior Temporal Sulcus, the Inferior Parietal lobe, and the Central Sulcus. These structures share a fundamental feature: They are functionally and structurally specialised to one hemisphere. Interestingly, several nonhuman primate species, such as chimpanzees and baboons, show human-like structural brain asymmetries for areas homologous to key language regions. The question then arises: for what function did these asymmetries arise in non-linguistic primates, if not for language per se? In an attempt to provide some answers, we review the literature on the lateralisation of the gestural communication system, which may represent the missing behavioural link to brain asymmetries for language area’s homologues in our common ancestor.
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27
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Schaeffer DJ, Klassen LM, Hori Y, Tian X, Szczupak D, Yen CCC, Cléry JC, Gilbert KM, Gati JS, Menon RS, Liu C, Everling S, Silva AC. An open access resource for functional brain connectivity from fully awake marmosets. Neuroimage 2022; 252:119030. [PMID: 35217206 PMCID: PMC9048130 DOI: 10.1016/j.neuroimage.2022.119030] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/19/2022] [Accepted: 02/21/2022] [Indexed: 12/27/2022] Open
Abstract
The common marmoset (Callithrix jacchus) is quickly gaining traction as a premier neuroscientific model. However, considerable progress is still needed in understanding the functional and structural organization of the marmoset brain to rival that documented in longstanding preclinical model species, like mice, rats, and Old World primates. To accelerate such progress, we present the Marmoset Functional Brain Connectivity Resource (marmosetbrainconnectome.org), currently consisting of over 70 h of resting-state fMRI (RS-fMRI) data acquired at 500 µm isotropic resolution from 31 fully awake marmosets in a common stereotactic space. Three-dimensional functional connectivity (FC) maps for every cortical and subcortical gray matter voxel are stored online. Users can instantaneously view, manipulate, and download any whole-brain functional connectivity (FC) topology (at the subject- or group-level) along with the raw datasets and preprocessing code. Importantly, researchers can use this resource to test hypotheses about FC directly - with no additional analyses required - yielding whole-brain correlations for any gray matter voxel on demand. We demonstrate the resource's utility for presurgical planning and comparison with tracer-based neuronal connectivity as proof of concept. Complementing existing structural connectivity resources for the marmoset brain, the Marmoset Functional Brain Connectivity Resource affords users the distinct advantage of exploring the connectivity of any voxel in the marmoset brain, not limited to injection sites nor constrained by regional atlases. With the entire raw database (RS-fMRI and structural images) and preprocessing code openly available for download and use, we expect this resource to be broadly valuable to test novel hypotheses about the functional organization of the marmoset brain.
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Affiliation(s)
- David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - L Martyn Klassen
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Xiaoguang Tian
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, United States
| | - Diego Szczupak
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, United States
| | - Cecil Chern-Chyi Yen
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Justine C Cléry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Kyle M Gilbert
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
| | - CiRong Liu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada
| | - Afonso C Silva
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15261, United States
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Eke DO, Bernard A, Bjaalie JG, Chavarriaga R, Hanakawa T, Hannan AJ, Hill SL, Martone ME, McMahon A, Ruebel O, Crook S, Thiels E, Pestilli F. International data governance for neuroscience. Neuron 2022; 110:600-612. [PMID: 34914921 PMCID: PMC8857067 DOI: 10.1016/j.neuron.2021.11.017] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 06/16/2021] [Accepted: 11/15/2021] [Indexed: 12/19/2022]
Abstract
As neuroscience projects increase in scale and cross international borders, different ethical principles, national and international laws, regulations, and policies for data sharing must be considered. These concerns are part of what is collectively called data governance. Whereas neuroscience data transcend borders, data governance is typically constrained within geopolitical boundaries. An international data governance framework and accompanying infrastructure can assist investigators, institutions, data repositories, and funders with navigating disparate policies. Here, we propose principles and operational considerations for how data governance in neuroscience can be navigated at an international scale and highlight gaps, challenges, and opportunities in a global brain data ecosystem. We consider how to approach data governance in a way that balances data protection requirements and the need for open science, so as to promote international collaboration through federated constructs such as the International Brain Initiative (IBI).
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Affiliation(s)
- Damian O Eke
- Centre for Computing and Social Responsibility, De Montfort University, Leicester, UK; Human Brain Project
| | | | | | - Ricardo Chavarriaga
- Center for Artificial Intelligence, School of Engineering, Zurich University of Applied Sciences, Zurich, Switzerland
| | | | - Anthony J Hannan
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Sean L Hill
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | | | | | - Oliver Ruebel
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Sharon Crook
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA
| | - Edda Thiels
- National Science Foundation, Alexandria, VA, USA
| | - Franco Pestilli
- Department of Psychology, Center for Perceptual Systems, Center for Theoretical and Computational Neuroscience, and Institute for Neuroscience, University of Texas, Austin, TX, USA.
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Gutierrez-Barragan D, Singh NA, Alvino FG, Coletta L, Rocchi F, De Guzman E, Galbusera A, Uboldi M, Panzeri S, Gozzi A. Unique spatiotemporal fMRI dynamics in the awake mouse brain. Curr Biol 2022; 32:631-644.e6. [PMID: 34998465 PMCID: PMC8837277 DOI: 10.1016/j.cub.2021.12.015] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/15/2022]
Abstract
Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems and document that its dynamic structure recapitulates distinctive, evolutionarily relevant principles that are predictive of conscious states in higher mammalian species. fMRI networks in awake mice depart from underlying anatomical structure fMRI dynamics in wakeful mice is critically shaped by arousal-related nuclei Occurrence and topography of rsfMRI coactivation patterns define conscious states fMRI coactivation dynamics defines a signature of consciousness in the mouse brain
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Affiliation(s)
- Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Neha Atulkumar Singh
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Filomena Grazia Alvino
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy; Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Federico Rocchi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy; Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Elizabeth De Guzman
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | | | - Stefano Panzeri
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.
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30
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Consciousness: Mapping the awake mouse brain. Curr Biol 2022; 32:R138-R140. [DOI: 10.1016/j.cub.2021.11.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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31
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Shahdloo M, Schüffelgen U, Papp D, Miller KL, Chiew M. Model-based dynamic off-resonance correction for improved accelerated fMRI in awake behaving nonhuman primates. Magn Reson Med 2022; 87:2922-2932. [PMID: 35081259 PMCID: PMC9306555 DOI: 10.1002/mrm.29167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/26/2021] [Accepted: 01/03/2022] [Indexed: 11/18/2022]
Abstract
Purpose To estimate dynamic off‐resonance due to vigorous body motion in accelerated fMRI of awake behaving nonhuman primates (NHPs) using the echo‐planar imaging reference navigator, in order to attenuate the effects of time‐varying off‐resonance on the reconstruction. Methods In NHP fMRI, the animal’s head is usually head‐posted, and the dynamic off‐resonance is mainly caused by motion in body parts that are distant from the brain and have low spatial frequency. Hence, off‐resonance at each frame can be approximated as a spatially linear perturbation of the off‐resonance at a reference frame, and is manifested as a relative linear shift in k‐space. Using GRAPPA operators, we estimated these shifts by comparing the navigator at each time frame with that at the reference frame. Estimated shifts were then used to correct the data at each frame. The proposed method was evaluated in phantom scans, simulations, and in vivo data. Results The proposed method is shown to successfully estimate spatially low‐order dynamic off‐resonance perturbations, including induced linear off‐resonance perturbations in phantoms, and is able to correct retrospectively corrupted data in simulations. Finally, it is shown to reduce ghosting artifacts and geometric distortions by up to 20% in simultaneous multislice in vivo acquisitions in awake‐behaving NHPs. Conclusion A method is proposed that does not need sequence modification or extra acquisitions and makes accelerated awake behaving NHP imaging more robust and reliable, reducing the gap between what is possible with NHP protocols and state‐of‐the‐art human imaging.
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Affiliation(s)
- Mo Shahdloo
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Urs Schüffelgen
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Daniel Papp
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,NeuroPoly Lab, Electrical Engineering Department, Polytechnique Montréal, Montreal, Canada
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Mark Chiew
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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32
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Milham M, Petkov C, Belin P, Ben Hamed S, Evrard H, Fair D, Fox A, Froudist-Walsh S, Hayashi T, Kastner S, Klink C, Majka P, Mars R, Messinger A, Poirier C, Schroeder C, Shmuel A, Silva AC, Vanduffel W, Van Essen DC, Wang Z, Roe AW, Wilke M, Xu T, Aarabi MH, Adolphs R, Ahuja A, Alvand A, Amiez C, Autio J, Azadi R, Baeg E, Bai R, Bao P, Basso M, Behel AK, Bennett Y, Bernhardt B, Biswal B, Boopathy S, Boretius S, Borra E, Boshra R, Buffalo E, Cao L, Cavanaugh J, Celine A, Chavez G, Chen LM, Chen X, Cheng L, Chouinard-Decorte F, Clavagnier S, Cléry J, Colcombe SJ, Conway B, Cordeau M, Coulon O, Cui Y, Dadarwal R, Dahnke R, Desrochers T, Deying L, Dougherty K, Doyle H, Drzewiecki CM, Duyck M, Arachchi WE, Elorette C, Essamlali A, Evans A, Fajardo A, Figueroa H, Franco A, Freches G, Frey S, Friedrich P, Fujimoto A, Fukunaga M, Gacoin M, Gallardo G, Gao L, Gao Y, Garside D, Garza-Villarreal EA, Gaudet-Trafit M, Gerbella M, Giavasis S, Glen D, Ribeiro Gomes AR, Torrecilla SG, Gozzi A, Gulli R, Haber S, Hadj-Bouziane F, Fujimoto SH, Hawrylycz M, He Q, He Y, Heuer K, Hiba B, Hoffstaedter F, Hong SJ, Hori Y, Hou Y, Howard A, de la Iglesia-Vaya M, Ikeda T, Jankovic-Rapan L, Jaramillo J, Jedema HP, Jin H, Jiang M, Jung B, Kagan I, Kahn I, Kiar G, Kikuchi Y, Kilavik B, Kimura N, Klatzmann U, Kwok SC, Lai HY, Lamberton F, Lehman J, Li P, Li X, Li X, Liang Z, Liston C, Little R, Liu C, Liu N, Liu X, Liu X, Lu H, Loh KK, Madan C, Magrou L, Margulies D, Mathilda F, Mejia S, Meng Y, Menon R, Meunier D, Mitchell A, Mitchell A, Murphy A, Mvula T, Ortiz-Rios M, Ortuzar Martinez DE, Pagani M, Palomero-Gallagher N, Pareek V, Perkins P, Ponce F, Postans M, Pouget P, Qian M, Ramirez J“B, Raven E, Restrepo I, Rima S, Rockland K, Rodriguez NY, Roger E, Hortelano ER, Rosa M, Rossi A, Rudebeck P, Russ B, Sakai T, Saleem KS, Sallet J, Sawiak S, Schaeffer D, Schwiedrzik CM, Seidlitz J, Sein J, Sharma J, Shen K, Sheng WA, Shi NS, Shim WM, Simone L, Sirmpilatze N, Sivan V, Song X, Tanenbaum A, Tasserie J, Taylor P, Tian X, Toro R, Trambaiolli L, Upright N, Vezoli J, Vickery S, Villalon J, Wang X, Wang Y, Weiss AR, Wilson C, Wong TY, Woo CW, Wu B, Xiao D, Xu AG, Xu D, Xufeng Z, Yacoub E, Ye N, Ying Z, Yokoyama C, Yu X, Yue S, Yuheng L, Yumeng X, Zaldivar D, Zhang S, Zhao Y, Zuo Z. Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging. Neuron 2022; 110:16-20. [PMID: 34731649 DOI: 10.1016/j.neuron.2021.10.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/30/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
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Scan Once, Analyse Many: Using Large Open-Access Neuroimaging Datasets to Understand the Brain. Neuroinformatics 2022; 20:109-137. [PMID: 33974213 PMCID: PMC8111663 DOI: 10.1007/s12021-021-09519-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/07/2021] [Indexed: 02/06/2023]
Abstract
We are now in a time of readily available brain imaging data. Not only are researchers now sharing data more than ever before, but additionally large-scale data collecting initiatives are underway with the vision that many future researchers will use the data for secondary analyses. Here I provide an overview of available datasets and some example use cases. Example use cases include examining individual differences, more robust findings, reproducibility-both in public input data and availability as a replication sample, and methods development. I further discuss a variety of considerations associated with using existing data and the opportunities associated with large datasets. Suggestions for further readings on general neuroimaging and topic-specific discussions are also provided.
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34
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Petkov CI, Flecknell P, Murphy K, Basso MA, Mitchell AS, Hartig R, Thompson-Iritani S. Unified ethical principles and an animal research ‘Helsinki’ declaration as foundations for international collaboration. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 3:100060. [DOI: 10.1016/j.crneur.2022.100060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 10/09/2022] [Accepted: 10/17/2022] [Indexed: 11/09/2022] Open
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35
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Yokoyama C, Autio JA, Ikeda T, Sallet J, Mars RB, Van Essen DC, Glasser MF, Sadato N, Hayashi T. Comparative connectomics of the primate social brain. Neuroimage 2021; 245:118693. [PMID: 34732327 PMCID: PMC9159291 DOI: 10.1016/j.neuroimage.2021.118693] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/27/2021] [Accepted: 10/29/2021] [Indexed: 01/13/2023] Open
Abstract
Social interaction is thought to provide a selection pressure for human intelligence, yet little is known about its neurobiological basis and evolution throughout the primate lineage. Recent advances in neuroimaging have enabled whole brain investigation of brain structure, function, and connectivity in humans and non-human primates (NHPs), leading to a nascent field of comparative connectomics. However, linking social behavior to brain organization across the primates remains challenging. Here, we review the current understanding of the macroscale neural mechanisms of social behaviors from the viewpoint of system neuroscience. We first demonstrate an association between the number of cortical neurons and the size of social groups across primates, suggesting a link between neural information-processing capacity and social capabilities. Moreover, by capitalizing on recent advances in species-harmonized functional MRI, we demonstrate that portions of the mirror neuron system and default-mode networks, which are thought to be important for representation of the other's actions and sense of self, respectively, exhibit similarities in functional organization in macaque monkeys and humans, suggesting possible homologies. With respect to these two networks, we describe recent developments in the neurobiology of social perception, joint attention, personality and social complexity. Together, the Human Connectome Project (HCP)-style comparative neuroimaging, hyperscanning, behavioral, and other multi-modal investigations are expected to yield important insights into the evolutionary foundations of human social behavior.
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Affiliation(s)
- Chihiro Yokoyama
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan.
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Takuro Ikeda
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Jérôme Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, Oxford University, Oxford, United Kingdom; University of Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - David C Van Essen
- Departments of Neuroscience, Washington University Medical School, St Louis, MO, United States of America
| | - Matthew F Glasser
- Departments of Neuroscience, Washington University Medical School, St Louis, MO, United States of America; Department of Radiology, Washington University Medical School, St Louis, MO, United States of America
| | - Norihiro Sadato
- National Institute for Physiological Sciences, Okazaki, Japan; The Graduate University for Advanced Studies (SOKENDAI), Kanagawa, Japan
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan; School of Medicine, Kyoto University, Kyoto, Japan.
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Becker Y, Loh KK, Coulon O, Meguerditchian A. The Arcuate Fasciculus and language origins: Disentangling existing conceptions that influence evolutionary accounts. Neurosci Biobehav Rev 2021; 134:104490. [PMID: 34914937 DOI: 10.1016/j.neubiorev.2021.12.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 11/30/2021] [Accepted: 12/08/2021] [Indexed: 12/11/2022]
Abstract
The Arcuate Fasciculus (AF) is of considerable interdisciplinary interest, because of its major implication in language processing. Theories about language brain evolution are based on anatomical differences in the AF across primates. However, changing methodologies and nomenclatures have resulted in conflicting findings regarding interspecies AF differences: Historical knowledge about the AF originated from human blunt dissections and later from monkey tract-tracing studies. Contemporary tractography studies reinvestigate the fasciculus' morphology, but remain heavily bound to unclear anatomical priors and methodological limitations. First, we aim to disentangle the influences of these three epistemological steps on existing AF conceptions, and to propose a contemporary model to guide future work. Second, considering the influence of various AF conceptions, we discuss four key evolutionary changes that propagated current views about language evolution: 1) frontal terminations, 2) temporal terminations, 3) greater Dorsal- versus Ventral Pathway expansion, 4) lateralisation. We conclude that new data point towards a more shared AF anatomy across primates than previously described. Language evolution theories should incorporate this continuous AF evolution across primates.
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Affiliation(s)
- Yannick Becker
- Laboratoire de Psychologie Cognitive, Aix-Marseille Univ, CNRS UMR 7290, Marseille, France; Institut de Neurosciences de la Timone, Aix-Marseille Univ, CNRS UMR 7289, Marseille, France.
| | - Kep Kee Loh
- Laboratoire de Psychologie Cognitive, Aix-Marseille Univ, CNRS UMR 7290, Marseille, France; Institut de Neurosciences de la Timone, Aix-Marseille Univ, CNRS UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille Univ, Marseille, France
| | - Olivier Coulon
- Institut de Neurosciences de la Timone, Aix-Marseille Univ, CNRS UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille Univ, Marseille, France
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, Aix-Marseille Univ, CNRS UMR 7290, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille Univ, Marseille, France; Station de Primatologie CNRS, Rousset, France
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37
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Finn ES. Is it time to put rest to rest? Trends Cogn Sci 2021; 25:1021-1032. [PMID: 34625348 PMCID: PMC8585722 DOI: 10.1016/j.tics.2021.09.005] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/08/2021] [Accepted: 09/10/2021] [Indexed: 12/29/2022]
Abstract
The so-called resting state, in which participants lie quietly with no particular inputs or outputs, represented a paradigm shift from conventional task-based studies in human neuroimaging. Our foray into rest was fruitful from both a scientific and methodological perspective, but at this point, how much more can we learn from rest on its own? While rest still dominates in many subfields, data from tasks have empirically demonstrated benefits, as well as the potential to provide insights about the mind in addition to the brain. I argue that we can accelerate progress in human neuroscience by de-emphasizing rest in favor of more grounded experiments, including promising integrated designs that respect the prominence of self-generated activity while offering enhanced control and interpretability.
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Affiliation(s)
- Emily S Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA.
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38
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Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, Curtiss SW, Oostenveld R, Larson-Prior LJ, Schoffelen JM, Hodge MR, Cler EA, Marcus DM, Barch DM, Yacoub E, Smith SM, Ugurbil K, Van Essen DC. The Human Connectome Project: A retrospective. Neuroimage 2021; 244:118543. [PMID: 34508893 PMCID: PMC9387634 DOI: 10.1016/j.neuroimage.2021.118543] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/13/2021] [Accepted: 08/30/2021] [Indexed: 01/21/2023] Open
Abstract
The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.
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Affiliation(s)
| | | | - Michael P Harms
- Washington University School of Medicine, St. Louis, MO, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre & NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, School of Medicine, University of Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | | | | | | | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | | | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Michael R Hodge
- Washington University School of Medicine, St. Louis, MO, USA
| | - Eileen A Cler
- Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel M Marcus
- Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna M Barch
- Washington University School of Medicine, St. Louis, MO, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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Foster C, Sheng WA, Heed T, Ben Hamed S. The macaque ventral intraparietal area has expanded into three homologue human parietal areas. Prog Neurobiol 2021; 209:102185. [PMID: 34775040 DOI: 10.1016/j.pneurobio.2021.102185] [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: 06/21/2021] [Revised: 10/27/2021] [Accepted: 11/05/2021] [Indexed: 10/19/2022]
Abstract
The macaque ventral intraparietal area (VIP) in the fundus of the intraparietal sulcus has been implicated in a diverse range of sensorimotor and cognitive functions such as motion processing, multisensory integration, processing of head peripersonal space, defensive behavior, and numerosity coding. Here, we exhaustively review macaque VIP function, cytoarchitectonics, and anatomical connectivity and integrate it with human studies that have attempted to identify a potential human VIP homologue. We show that human VIP research has consistently identified three, rather than one, bilateral parietal areas that each appear to subsume some, but not all, of the macaque area's functionality. Available evidence suggests that this human "VIP complex" has evolved as an expansion of the macaque area, but that some precursory specialization within macaque VIP has been previously overlooked. The three human areas are dominated, roughly, by coding the head or self in the environment, visual heading direction, and the peripersonal environment around the head, respectively. A unifying functional principle may be best described as prediction in space and time, linking VIP to state estimation as a key parietal sensorimotor function. VIP's expansive differentiation of head and self-related processing may have been key in the emergence of human bodily self-consciousness.
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Affiliation(s)
- Celia Foster
- Biopsychology & Cognitive Neuroscience, Faculty of Psychology & Sports Science, Bielefeld University, Bielefeld, Germany; Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - Wei-An Sheng
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-University of Lyon 1, France
| | - Tobias Heed
- Biopsychology & Cognitive Neuroscience, Faculty of Psychology & Sports Science, Bielefeld University, Bielefeld, Germany; Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany; Department of Psychology, University of Salzburg, Salzburg, Austria; Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-University of Lyon 1, France.
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40
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Scott JT, Bourne JA. Modelling behaviors relevant to brain disorders in the nonhuman primate: Are we there yet? Prog Neurobiol 2021; 208:102183. [PMID: 34728308 DOI: 10.1016/j.pneurobio.2021.102183] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/27/2021] [Accepted: 10/27/2021] [Indexed: 12/30/2022]
Abstract
Recent years have seen a profound resurgence of activity with nonhuman primates (NHPs) to model human brain disorders. From marmosets to macaques, the study of NHP species offers a unique window into the function of primate-specific neural circuits that are impossible to examine in other models. Examining how these circuits manifest into the complex behaviors of primates, such as advanced cognitive and social functions, has provided enormous insights to date into the mechanisms underlying symptoms of numerous neurological and neuropsychiatric illnesses. With the recent optimization of modern techniques to manipulate and measure neural activity in vivo, such as optogenetics and calcium imaging, NHP research is more well-equipped than ever to probe the neural mechanisms underlying pathological behavior. However, methods for behavioral experimentation and analysis in NHPs have noticeably failed to keep pace with these advances. As behavior ultimately lies at the junction between preclinical findings and its translation to clinical outcomes for brain disorders, approaches to improve the integrity, reproducibility, and translatability of behavioral experiments in NHPs requires critical evaluation. In this review, we provide a unifying account of existing brain disorder models using NHPs, and provide insights into the present and emerging contributions of behavioral studies to the field.
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Affiliation(s)
- Jack T Scott
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia
| | - James A Bourne
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
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41
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Abstract
We are interested here in the central organ of our thoughts: the brain. Advances in neuroscience have made it possible to obtain increasing information on the anatomy of this organ, at ever-higher resolutions, with different imaging techniques, on ever-larger samples. At the same time, paleoanthropology has to deal with partial reflections on the shape of the brain, on fragmentary specimens and small samples in an attempt to approach the morphology of the brain of past human species. It undeniably emerges from the perspective we propose here that paleoanthropology has much to gain from interacting more with the field of neuroimaging. Improving our understanding of the morphology of the endocast necessarily involves studying the external surface of the brain and the link it maintains with the internal surface of the skull. The contribution of neuroimaging will allow us to better define the relationship between brain and endocast. Models of intra- and inter-species variability in brain morphology inferred from large neuroimaging databases will help make the most of the rare endocasts of extinct species. We also conclude that exchanges between these two disciplines will also be beneficial to our knowledge of the Homo sapiens brain. Documenting the anatomy among other human species and including the variation over time within our own species are approaches that offer us a new perspective through which to appreciate what really characterizes the brain of humanity today.
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42
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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: 21] [Impact Index Per Article: 7.0] [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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43
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Roumazeilles L, Lange FJ, Benn RA, Andersson JLR, Bertelsen MF, Manger PR, Flach E, Khrapitchev AA, Bryant KL, Sallet J, Mars RB. Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates: Evidence for a Simian Elaboration. Cereb Cortex 2021; 32:1608-1624. [PMID: 34518890 PMCID: PMC9016287 DOI: 10.1093/cercor/bhab285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 11/20/2022] Open
Abstract
Comparative neuroimaging has been used to identify changes in white matter architecture across primate species phylogenetically close to humans, but few have compared the phylogenetically distant species. Here, we acquired postmortem diffusion imaging data from ring-tailed lemurs (Lemur catta), black-capped squirrel monkeys (Saimiri boliviensis), and rhesus macaques (Macaca mulatta). We were able to establish templates and surfaces allowing us to investigate sulcal, cortical, and white matter anatomy. The results demonstrate an expansion of the frontal projections of the superior longitudinal fasciculus complex in squirrel monkeys and rhesus macaques compared to ring-tailed lemurs, which correlates with sulcal anatomy and the lemur’s smaller prefrontal granular cortex. The connectivity of the ventral pathway in the parietal region is also comparatively reduced in ring-tailed lemurs, with the posterior projections of the inferior longitudinal fasciculus not extending toward parietal cortical areas as in the other species. In the squirrel monkeys we note a very specific occipito-parietal anatomy that is apparent in their surface anatomy and the expansion of the posterior projections of the optical radiation. Our study supports the hypothesis that the connectivity of the prefrontal-parietal regions became relatively elaborated in the simian lineage after divergence from the prosimian lineage.
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Affiliation(s)
- Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX13TA, UK
| | - Frederik J Lange
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX39DU, UK
| | - R Austin Benn
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid 28029, Spain
| | - Jesper L R Andersson
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX39DU, UK
| | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen Zoo, Frederiksberg 2000, Denmark
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Edmund Flach
- Wildlife Health Services, Zoological Society of London, London NW14RY, UK (now retired)
| | - Alexandre A Khrapitchev
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford OX37DQ, UK
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX39DU, UK
| | - Jérôme Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX13TA, UK.,Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron 69500, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX39DU, UK.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen 6525 HR, The Netherlands
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Russ BE, Petkov CI, Kwok SC, Zhu Q, Belin P, Vanduffel W, Hamed SB. Common functional localizers to enhance NHP & cross-species neuroscience imaging research. Neuroimage 2021; 237:118203. [PMID: 34048898 PMCID: PMC8529529 DOI: 10.1016/j.neuroimage.2021.118203] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 05/15/2021] [Accepted: 05/24/2021] [Indexed: 11/25/2022] Open
Abstract
Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.
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Affiliation(s)
- Brian E Russ
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, NY, United States; Department of Psychiatry, New York University at Langone, New York City, NY, United States.
| | - Christopher I Petkov
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, United Kingdom
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, Key Laboratory of Brain Functional Genomics Ministry of Education, Shanghai Key Laboratory of Magnetic Resonance, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, Jiangsu, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China
| | - Qi Zhu
- Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France; Laboratory for Neuro-and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven, 3000, Belgium
| | - Pascal Belin
- Institut de Neurosciences de La Timone, Aix-Marseille Université et CNRS, Marseille, 13005, France
| | - Wim Vanduffel
- Laboratory for Neuro-and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven, 3000, Belgium; Leuven Brain Institute, KU Leuven, Leuven, 3000, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, United States; Department of Radiology, Harvard Medical School, Boston, MA 02144, United States.
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5229, Université de Lyon - CNRS, France.
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Song X, García-Saldivar P, Kindred N, Wang Y, Merchant H, Meguerditchian A, Yang Y, Stein EA, Bradberry CW, Ben Hamed S, Jedema HP, Poirier C. Strengths and challenges of longitudinal non-human primate neuroimaging. Neuroimage 2021; 236:118009. [PMID: 33794361 PMCID: PMC8270888 DOI: 10.1016/j.neuroimage.2021.118009] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 03/16/2021] [Accepted: 03/23/2021] [Indexed: 01/20/2023] Open
Abstract
Longitudinal non-human primate neuroimaging has the potential to greatly enhance our understanding of primate brain structure and function. Here we describe its specific strengths, compared to both cross-sectional non-human primate neuroimaging and longitudinal human neuroimaging, but also its associated challenges. We elaborate on factors guiding the use of different analytical tools, subject-specific versus age-specific templates for analyses, and issues related to statistical power.
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Affiliation(s)
- Xiaowei Song
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Pamela García-Saldivar
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230, México
| | - Nathan Kindred
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle University, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, United Kingdom
| | - Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla. Boulevard Juriquilla No. 3001 Querétaro, Qro. 76230, México
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille/CNRS, Institut Language, Communication and the Brain 13331 Marseille, France
| | - Yihong Yang
- Neuroimaging Research Branch, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Elliot A Stein
- Neuroimaging Research Branch, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Charles W Bradberry
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5229, Université de Lyon - CNRS, France
| | - Hank P Jedema
- Preclinical Pharmacology Section, Intramural Research Program, NIDA, NIH, Baltimore, MD 21224, USA.
| | - Colline Poirier
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle University, United Kingdom.
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Autio JA, Zhu Q, Li X, Glasser MF, Schwiedrzik CM, Fair DA, Zimmermann J, Yacoub E, Menon RS, Van Essen DC, Hayashi T, Russ B, Vanduffel W. Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection. Neuroimage 2021; 236:118082. [PMID: 33882349 PMCID: PMC8594288 DOI: 10.1016/j.neuroimage.2021.118082] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/16/2021] [Accepted: 04/07/2021] [Indexed: 02/07/2023] Open
Abstract
Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.
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Affiliation(s)
- Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Qi Zhu
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France
| | - Xiaolian Li
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium
| | - Matthew F Glasser
- Departments of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Caspar M Schwiedrzik
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077 Göttingen, Germany; Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Damien A Fair
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jan Zimmermann
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - David C Van Essen
- Departments of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Brian Russ
- Department of Psychiatry, New York University Langone, New York City, New York, USA; Center for the Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, New York, USA; Department of Neuroscience, Icahn School of Medicine, Mount Sinai, New York City, New York, USA
| | - Wim Vanduffel
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven 3000, Belgium; Leuven Brain Institute, KU Leuven, Leuven 3000, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
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Liu X, Eickhoff SB, Caspers S, Wu J, Genon S, Hoffstaedter F, Mars RB, Sommer IE, Eickhoff CR, Chen J, Jardri R, Reetz K, Dogan I, Aleman A, Kogler L, Gruber O, Caspers J, Mathys C, Patil KR. Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate. Neuroimage 2021; 235:118006. [PMID: 33819611 PMCID: PMC8214073 DOI: 10.1016/j.neuroimage.2021.118006] [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: 06/15/2020] [Revised: 02/10/2021] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.
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Affiliation(s)
- Xiaojin Liu
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jianxiao Wu
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Sarah Genon
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Iris E Sommer
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Ji Chen
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Renaud Jardri
- Division of Psychiatry, University of Lille, CNRS UMR9193, SCALab & CHU Lille, Fontan Hospital, CURE platform, Lille, France
| | - Kathrin Reetz
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, RWTH Aachen University, Aachen, Germany; Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Imis Dogan
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, RWTH Aachen University, Aachen, Germany; Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - André Aleman
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lydia Kogler
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany
| | - Julian Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Christian Mathys
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany; Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, University of Oldenburg, Oldenburg, Germany
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany.
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Klink PC, Aubry JF, Ferrera VP, Fox AS, Froudist-Walsh S, Jarraya B, Konofagou EE, Krauzlis RJ, Messinger A, Mitchell AS, Ortiz-Rios M, Oya H, Roberts AC, Roe AW, Rushworth MFS, Sallet J, Schmid MC, Schroeder CE, Tasserie J, Tsao DY, Uhrig L, Vanduffel W, Wilke M, Kagan I, Petkov CI. Combining brain perturbation and neuroimaging in non-human primates. Neuroimage 2021; 235:118017. [PMID: 33794355 PMCID: PMC11178240 DOI: 10.1016/j.neuroimage.2021.118017] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 03/07/2021] [Accepted: 03/22/2021] [Indexed: 12/11/2022] Open
Abstract
Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.
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Affiliation(s)
- P Christiaan Klink
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, the Netherlands.
| | - Jean-François Aubry
- Physics for Medicine Paris, Inserm U1273, CNRS UMR 8063, ESPCI Paris, PSL University, Paris, France
| | - Vincent P Ferrera
- Department of Neuroscience & Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Andrew S Fox
- Department of Psychology & California National Primate Research Center, University of California, Davis, CA, USA
| | | | - Béchir Jarraya
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France; Foch Hospital, UVSQ, Suresnes, France
| | - Elisa E Konofagou
- Ultrasound and Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Radiology, Columbia University, New York, NY, USA
| | - Richard J Krauzlis
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, USA
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Anna S Mitchell
- Department of Experimental Psychology, Oxford University, Oxford, United Kingdom
| | - Michael Ortiz-Rios
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom; German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Hiroyuki Oya
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Neurosurgery, University of Iowa, Iowa city, IA, USA
| | - Angela C Roberts
- Department of Physiology, Development and Neuroscience, Cambridge University, Cambridge, United Kingdom
| | - Anna Wang Roe
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou 310029, China
| | | | - Jérôme Sallet
- Department of Experimental Psychology, Oxford University, Oxford, United Kingdom; Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Michael Christoph Schmid
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom; Faculty of Science and Medicine, University of Fribourg, Chemin du Musée 5, CH-1700 Fribourg, Switzerland
| | - Charles E Schroeder
- Nathan Kline Institute, Orangeburg, NY, USA; Columbia University, New York, NY, USA
| | - Jordy Tasserie
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France
| | - Doris Y Tsao
- Division of Biology and Biological Engineering, Tianqiao and Chrissy Chen Institute for Neuroscience; Howard Hughes Medical Institute; Computation and Neural Systems, Caltech, Pasadena, CA, USA
| | - Lynn Uhrig
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France
| | - Wim Vanduffel
- Laboratory for Neuro- and Psychophysiology, Neurosciences Department, KU Leuven Medical School, Leuven, Belgium; Leuven Brain Institute, KU Leuven, Leuven Belgium; Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Melanie Wilke
- German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Department of Cognitive Neurology, University Medicine Göttingen, Göttingen, Germany
| | - Igor Kagan
- German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany.
| | - Christopher I Petkov
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom.
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Mitchell AS, Hartig R, Basso MA, Jarrett W, Kastner S, Poirier C. International primate neuroscience research regulation, public engagement and transparency opportunities. Neuroimage 2021; 229:117700. [PMID: 33418072 PMCID: PMC7994292 DOI: 10.1016/j.neuroimage.2020.117700] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/08/2020] [Accepted: 12/19/2020] [Indexed: 02/07/2023] Open
Abstract
Scientific excellence is a necessity for progress in biomedical research. As research becomes ever more international, establishing international collaborations will be key to advancing our scientific knowledge. Understanding the similarities in standards applied by different nations to animal research, and where the differences might lie, is crucial. Cultural differences and societal values will also contribute to these similarities and differences between countries and continents. Our overview is not comprehensive for all species, but rather focuses on non-human primate (NHP) research, involving New World marmosets and Old World macaques, conducted in countries where NHPs are involved in neuroimaging research. Here, an overview of the ethics and regulations is provided to help assess welfare standards amongst primate research institutions. A comparative examination of these standards was conducted to provide a basis for establishing a common set of standards for animal welfare. These criteria may serve to develop international guidelines, which can be managed by an International Animal Welfare and Use Committee (IAWUC). Internationally, scientists have a moral responsibility to ensure excellent care and welfare of their animals, which in turn, influences the quality of their research. When working with animal models, maintaining a high quality of care ("culture of care") and welfare is essential. The transparent promotion of this level of care and welfare, along with the results of the research and its impact, may reduce public concerns associated with animal experiments in neuroscience research.
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Affiliation(s)
- Anna S Mitchell
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
| | - Renée Hartig
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Michele A Basso
- Fuster Laboratory of Cognitive Neuroscience Department of Psychiatry and Biobehavioral Sciences UCLA Los Angeles 90095, CA United States
| | - Wendy Jarrett
- Understanding Animal Research, London, United Kingdom
| | - Sabine Kastner
- Princeton Neuroscience Institute & Department of Psychology, Princeton University, Princeton, United States
| | - Colline Poirier
- Biosciences Institute & Centre for Behaviour and Evolution, Faculty of Medical Sciences, Newcastle University, United Kingdom
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Hartig R, Glen D, Jung B, Logothetis NK, Paxinos G, Garza-Villarreal EA, Messinger A, Evrard HC. The Subcortical Atlas of the Rhesus Macaque (SARM) for neuroimaging. Neuroimage 2021; 235:117996. [PMID: 33794360 DOI: 10.1016/j.neuroimage.2021.117996] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 03/15/2021] [Accepted: 03/19/2021] [Indexed: 12/20/2022] Open
Abstract
Digitized neuroanatomical atlases that can be overlaid onto functional data are crucial for localizing brain structures and analyzing functional networks identified by neuroimaging techniques. To aid in functional and structural data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. This anatomical scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM) with 210 primary regions-of-interest (ROIs). The subcortical parcellation and nomenclature reflect those of the 4th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (Paxinos et al., in preparation), rather than proposing yet another novel atlas. The primary ROIs are organized across six spatial hierarchical scales from small, fine-grained ROIs to broader composites of multiple ROIs, making the SARM suitable for analysis at different resolutions and allowing broader labeling of functional signals when more accurate localization is not possible. As an example application of this atlas, we have included a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques using a visual flickering checkerboard stimulus, identifying and quantifying significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MRI data processing software, such as AFNI, where the atlas has been embedded into the software alongside cortical macaque atlases.
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Affiliation(s)
- Renée Hartig
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | - Benjamin Jung
- Department of Neuroscience, Brown University, Providence, RI, USA; Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA
| | - Nikos K Logothetis
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany; University of Manchester, Manchester, United Kingdom; International Center for Primate Brain Research, Songjiang, Shanghai, PR China
| | - George Paxinos
- Neuroscience Research Australia and The University of New South Wales, Sydney, NSW 2031, Australia
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico.
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA.
| | - Henry C Evrard
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Nathan S. Kline Institute for Psychiatric Research, Center for Biomedical Imaging and Neuromodulation, Orangeburg, NY, USA; International Center for Primate Brain Research, Songjiang, Shanghai, PR China.
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