IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v447y2007i7140d10.1038_nature05758.html
   My bibliography  Save this article

Intrinsic functional architecture in the anaesthetized monkey brain

Author

Listed:
  • J. L. Vincent

    (Departments of Radiology,
    Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138, USA
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA)

  • G. H. Patel

    (Departments of Radiology,
    Neurology,
    Anatomy and Neurobiology, and,)

  • M. D. Fox

    (Departments of Radiology,)

  • A. Z. Snyder

    (Departments of Radiology,
    Neurology,)

  • J. T. Baker

    (Anatomy and Neurobiology, and,)

  • D. C. Van Essen

    (Anatomy and Neurobiology, and,)

  • J. M. Zempel

    (Neurology,)

  • L. H. Snyder

    (Anatomy and Neurobiology, and,)

  • M. Corbetta

    (Departments of Radiology,
    Neurology,
    Anatomy and Neurobiology, and,)

  • M. E. Raichle

    (Departments of Radiology,
    Neurology,
    Anatomy and Neurobiology, and,
    Biomedical Engineering, Washington University in St Louis, Missouri 63110, USA)

Abstract

The idling brain Studies of brain function tend to measure activity during specific tasks or in response to specific stimuli. Yet most of the brain's time and energy is not devoted to these activities. Functional magnetic resonance imaging now shows that the monkey brain is constantly cycling through elaborate, distributed patterns of activity of a type previously associated with sensory, motor or cognitive phenomena. The fluctuations are present even during anaesthesia-induced unconsciousness, and correspond to underlying patterns of anatomical connection. These neural circuits may represent the underlying structure that makes perception and thought possible. Intriguingly, the templates are similar (but not identical) in monkeys and humans, suggesting that this structure is conserved across primate species.

Suggested Citation

  • J. L. Vincent & G. H. Patel & M. D. Fox & A. Z. Snyder & J. T. Baker & D. C. Van Essen & J. M. Zempel & L. H. Snyder & M. Corbetta & M. E. Raichle, 2007. "Intrinsic functional architecture in the anaesthetized monkey brain," Nature, Nature, vol. 447(7140), pages 83-86, May.
  • Handle: RePEc:nat:nature:v:447:y:2007:i:7140:d:10.1038_nature05758
    DOI: 10.1038/nature05758
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature05758
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/nature05758?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Lavanga & O. De Wel & A. Caicedo & K. Jansen & A. Dereymaeker & G. Naulaers & S. Van Huffel, 2017. "Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation," Complexity, Hindawi, vol. 2017, pages 1-13, October.
    2. Protachevicz, Paulo Ricardo & Borges, Fernando da Silva & Batista, Antonio Marcos & Baptista, Murilo da Silva & Caldas, Iberê Luiz & Macau, Elbert Einstein Nehrer & Lameu, Ewandson Luiz, 2023. "Plastic neural network with transmission delays promotes equivalence between function and structure," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    3. Laura Biagi & Sofia Allegra Crespi & Michela Tosetti & Maria Concetta Morrone, 2015. "BOLD Response Selective to Flow-Motion in Very Young Infants," PLOS Biology, Public Library of Science, vol. 13(9), pages 1-22, September.
    4. Adrián Ponce-Alvarez & Biyu J He & Patric Hagmann & Gustavo Deco, 2015. "Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-26, August.
    5. Joseph A Lombardo & Matthew V Macellaio & Bing Liu & Stephanie E Palmer & Leslie C Osborne, 2018. "State dependence of stimulus-induced variability tuning in macaque MT," PLOS Computational Biology, Public Library of Science, vol. 14(10), pages 1-28, October.
    6. Huee Ru Chong & Yadollah Ranjbar-Slamloo & Malcolm Zheng Hao Ho & Xuan Ouyang & Tsukasa Kamigaki, 2023. "Functional alterations of the prefrontal circuit underlying cognitive aging in mice," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    7. Farnaz Zamani Esfahlani & Joshua Faskowitz & Jonah Slack & Bratislav Mišić & Richard F. Betzel, 2022. "Local structure-function relationships in human brain networks across the lifespan," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    8. Riccardo Storchi & Gabriele E M Biella & Diego Liberati & Giuseppe Baselli, 2009. "Extraction and Characterization of Essential Discharge Patterns from Multisite Recordings of Spiking Ongoing Activity," PLOS ONE, Public Library of Science, vol. 4(1), pages 1-13, January.
    9. Eric C Leuthardt & Gloria Guzman & S Kathleen Bandt & Carl Hacker & Ananth K Vellimana & David Limbrick & Mikhail Milchenko & Pamela Lamontagne & Benjamin Speidel & Jarod Roland & Michelle Miller-Thom, 2018. "Integration of resting state functional MRI into clinical practice - A large single institution experience," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
    10. Anandamohan Ghosh & Y Rho & A R McIntosh & R Kötter & V K Jirsa, 2008. "Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-12, October.
    11. Satohiro Tajima & Toru Yanagawa & Naotaka Fujii & Taro Toyoizumi, 2015. "Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-28, November.
    12. Lu, Hu & Wei, Hui, 2012. "Detection of community structure in networks based on community coefficients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6156-6164.
    13. Holger Finger & Marlene Bönstrup & Bastian Cheng & Arnaud Messé & Claus Hilgetag & Götz Thomalla & Christian Gerloff & Peter König, 2016. "Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modelin," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-28, August.
    14. Robert Leech & Gregory Scott & Robin Carhart-Harris & Federico Turkheimer & Simon D Taylor-Robinson & David J Sharp, 2014. "Spatial Dependencies between Large-Scale Brain Networks," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-10, June.
    15. Alessandra Griffa & Mathieu Mach & Julien Dedelley & Daniel Gutierrez-Barragan & Alessandro Gozzi & Gilles Allali & Joanes Grandjean & Dimitri Ville & Enrico Amico, 2023. "Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    16. Andrea I. Luppi & Lynn Uhrig & Jordy Tasserie & Camilo M. Signorelli & Emmanuel A. Stamatakis & Alain Destexhe & Bechir Jarraya & Rodrigo Cofre, 2024. "Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    17. Chaogan Yan & Dongqiang Liu & Yong He & Qihong Zou & Chaozhe Zhu & Xinian Zuo & Xiangyu Long & Yufeng Zang, 2009. "Spontaneous Brain Activity in the Default Mode Network Is Sensitive to Different Resting-State Conditions with Limited Cognitive Load," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-11, May.
    18. Biyu J He & John M Zempel, 2013. "Average Is Optimal: An Inverted-U Relationship between Trial-to-Trial Brain Activity and Behavioral Performance," PLOS Computational Biology, Public Library of Science, vol. 9(11), pages 1-14, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:447:y:2007:i:7140:d:10.1038_nature05758. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.