Deep learning based decomposition of brain networks

Pilsub Lee, Myungwon Choi, Daegyeom Kim, Suji Lee, Hyun Ghang Jeong, Cheol E. Han

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

2 Citations (Scopus)

Abstract

A brain network is the essence of the intelligence where it consists of nodes that are anatomically defined brain regions, and edges that connect a pair of brain regions. The diffusion-weighted magnetic resonance (MR) images and the advances in computer-Aided tractography algorithms let us know strong association between human brain networks and cognitive functions. Brain regions dedicated to a certain specific cognitive function were spatially clustered and efficiently connected each other; it is called local functional segregation. However, it is not well known that such a local segregation is associated with a certain sub-network which may act as a building block of the brain network. In this work, using a graph auto-encoder, we extracted building blocks of brain networks and investigate whether they are affected by a neurological disease, Alzheimer's disease. We found that the brain network of each person is linear summation of the learned building blocks. Also, the activation levels of these building blocks vary in the normal controls and patients with Alzheimer's disease, showing that network deterioration in the disease group.

Original languageEnglish
Title of host publication1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages349-354
Number of pages6
ISBN (Electronic)9781538678220
DOIs
Publication statusPublished - 2019 Mar 18
Event1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019 - Okinawa, Japan
Duration: 2019 Feb 112019 Feb 13

Publication series

Name1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019

Conference

Conference1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019
CountryJapan
CityOkinawa
Period19/2/1119/2/13

Keywords

  • Alzheimer's disease
  • brain networks
  • graph auto-encoder
  • graph convolutional neural network

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Artificial Intelligence

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  • Cite this

    Lee, P., Choi, M., Kim, D., Lee, S., Jeong, H. G., & Han, C. E. (2019). Deep learning based decomposition of brain networks. In 1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019 (pp. 349-354). [8669055] (1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIIC.2019.8669055