Modular organization of intrinsic brain networks

A graph theoretical analysis of resting-state fMRI

Taira Uehara, Shozo Tobimatsu, Shigeyuki Kan, Satoru Miyauchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Recently, modular organization of intrinsic brain networks has been revealed by the graph theoretical analysis of resting-state functional MRI (rs-fMRI). In this paper, we introduce the concept of the graph theoretical analysis and modular organization. Then, we present the results of our analysis. In the graph theoretical analysis, intrinsic brain networks measured by rs-fMRI are modeled as the graphs (nodes linked by edges). Then, a module is defined as a group of highly inter-connected nodes which have relatively sparse connections to nodes in other modules. Recently, effective module detection methods have been proposed, and applied to rs-fMRI. In our study, rs-fMRI data were collected from 18 healthy young participants, and we detected the modules from a group level graph with fine spatial resolution. As a result, we found 6 dominant modules (default-mode, fronto-parietal, cingulo-opercular, sensorimotor, visual, and auditory). These modules were also detected when another module detection method was applied. Then, nodes were classified according to their roles based on their intra-module and inter-module connections. We found that majority of brain regions were classified as peripheral nodes which mostly connect with nodes within their modules. Interestingly, fronto-parietal module which consists of transmodal higher-order brain regions had more connector nodes (connecting with other modules) than unimodal visual and sensorimotor modules. This suggested that modular organization in intrinsic brain networks can reflect functional properties of brain systems.

Original languageEnglish
Title of host publication2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings
Pages722-727
Number of pages6
DOIs
Publication statusPublished - Oct 24 2012
Event6th International Conference on Complex Medical Engineering, CME 2012 - Kobe, Japan
Duration: Jul 1 2012Jul 4 2012

Other

Other6th International Conference on Complex Medical Engineering, CME 2012
CountryJapan
CityKobe
Period7/1/127/4/12

Fingerprint

Brain
Magnetic Resonance Imaging

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

Uehara, T., Tobimatsu, S., Kan, S., & Miyauchi, S. (2012). Modular organization of intrinsic brain networks: A graph theoretical analysis of resting-state fMRI. In 2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings (pp. 722-727). [6275597] https://doi.org/10.1109/ICCME.2012.6275597

Modular organization of intrinsic brain networks : A graph theoretical analysis of resting-state fMRI. / Uehara, Taira; Tobimatsu, Shozo; Kan, Shigeyuki; Miyauchi, Satoru.

2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings. 2012. p. 722-727 6275597.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Uehara, T, Tobimatsu, S, Kan, S & Miyauchi, S 2012, Modular organization of intrinsic brain networks: A graph theoretical analysis of resting-state fMRI. in 2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings., 6275597, pp. 722-727, 6th International Conference on Complex Medical Engineering, CME 2012, Kobe, Japan, 7/1/12. https://doi.org/10.1109/ICCME.2012.6275597
Uehara T, Tobimatsu S, Kan S, Miyauchi S. Modular organization of intrinsic brain networks: A graph theoretical analysis of resting-state fMRI. In 2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings. 2012. p. 722-727. 6275597 https://doi.org/10.1109/ICCME.2012.6275597
Uehara, Taira ; Tobimatsu, Shozo ; Kan, Shigeyuki ; Miyauchi, Satoru. / Modular organization of intrinsic brain networks : A graph theoretical analysis of resting-state fMRI. 2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings. 2012. pp. 722-727
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