Skip to main content

Firing Pattern of Default Mode Brain Network with Spiking Neuron Model

  • Conference paper
Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2010)

Abstract

Recently, analyses of fMRI data have revealed functionally connected and interacting spontaneous active regions in the brain, which are referred as ”Default Mode Brain Network”. The fluctuations on BOLD signals of the default mode brain network have shown spatiotemporally correlated synchronization at a rate lower than 0.1 Hz in contrast to signals under concrete tasks like high frequency rhythms. Here we construct the default mode brain network by functionally connecting a neural network using functional correlation factors. For numerical simulations with Izhikevich’s spiking neuron model, the condition on the slow synchronization of this network model is fixed, and the network dynamics is analyzed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Greene, J.D., et al.: The Neural Bases of Cognitive Conflict and Control in Moral Judgment. Neuron 44, 389–400 (2004)

    Article  Google Scholar 

  2. Fox, M.D., et al.: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. PNAS 102, 9673–9678 (2005)

    Article  Google Scholar 

  3. Mason, M.F., et al.: Wondering Minds: The default Network and Stimulus-Independent Thought. Science 315, 393–395 (2007)

    Article  Google Scholar 

  4. Fox, M.D., Raichle, M.E.: Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews of Neuroscience 8, 700–711 (2007)

    Article  Google Scholar 

  5. Buckner, R.L., Andrews-Hanna, J.R., Schacter, D.L.: The Brain’s Default Network: Anatomy, Function, and Relevance to Disease. Ann. N. Y. Acad. Sci. 1124, 1–38 (2008)

    Article  Google Scholar 

  6. Gaab, N., Gabrieli, J.D.E., Glover, G.H.: Resting in peace or noise: Scanner background noise suppresses default–mode network. Human Brain Mapping, Special Issue: Endogenous Brain Oscillations and Networks in Functional MRI 29, 858–867 (2008)

    Article  Google Scholar 

  7. Beason-Held, L.L., Kraut, M.A., Resnick, S.M.: Stability of Default–mode network activity in the aging brain. Brain Imaging Behav. 3, 123–131 (2009)

    Article  Google Scholar 

  8. Izhikevich, E.M.: Simple Model of Spiking Neurons. IEEE Trans. Neural Networks 14, 1569–1572 (2003)

    Article  Google Scholar 

  9. Izhikevich, E.M.: Which Model to Use for Cortical Spiking Neurons? IEEE Trans. Neural Networks 15, 1063–1070 (2004)

    Article  Google Scholar 

  10. Deco, G., et al.: Key role of coupling, delay, and noise in resting brain fluctuations. PNAS 106, 10302–10307 (2009)

    Article  Google Scholar 

  11. Vincent, J.L., et al.: Coherent spontaneous activity identifies a hippocampal–parietal memory network. J. Neurophysiol. 96, 3517–3531 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Yamanishi, T., Liu, JQ., Nishimura, H. (2012). Firing Pattern of Default Mode Brain Network with Spiking Neuron Model. In: Suzuki, J., Nakano, T. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32615-8_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32615-8_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32614-1

  • Online ISBN: 978-3-642-32615-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics