Firing Pattern of Default Mode Brain Network with Spiking Neuron Model

Teruya Yamanishi; Jian-Qin Liu; Haruhiko Nishimura

Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers

Research Article

Firing Pattern of Default Mode Brain Network with Spiking Neuron Model

Download

474 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-32615-8_62,
    author={Teruya Yamanishi and Jian-Qin Liu and Haruhiko Nishimura},
    title={Firing Pattern of Default Mode Brain Network with Spiking Neuron Model},
    proceedings={Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers},
    proceedings_a={BIONETICS},
    year={2012},
    month={10},
    keywords={spiking neuron model default mode brain network spontaneous activity firing rate synchronization},
    doi={10.1007/978-3-642-32615-8_62}
}

Teruya Yamanishi
Jian-Qin Liu
Haruhiko Nishimura
Year: 2012
Firing Pattern of Default Mode Brain Network with Spiking Neuron Model
BIONETICS
Springer
DOI: 10.1007/978-3-642-32615-8_62

Teruya Yamanishi¹^,*, Jian-Qin Liu², Haruhiko Nishimura³

1: Fukui University of Technology
2: National Institute of Information and Communications Technology
3: University of Hyogo

*Contact email: yamanisi@fukui-ut.ac.jp

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.

Keywords: spiking neuron model default mode brain network spontaneous activity firing rate synchronization

Published: 2012-10-18

: http://dx.doi.org/10.1007/978-3-642-32615-8_62