Biophysically interpretable recurrent neural network for functional magnetic resonance imaging analysis and sparsity based causal architecture discovery

Yuan Wang, Yao Wang, Yvonne W. Lui

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

Abstract

Recent efforts use state-of-the-art Recurrent Neural Networks (RNN) to gain insight into neuroscience. A limitation of these works is that the used generic RNNs lack biophysical meaning, making the interpretation of the results in a neuroscience context difficult. In this paper, we propose a biophysically interpretable RNN built on the Dynamic Causal Modelling (DCM). DCM is an advanced nonlinear generative model typically used to test hypotheses of brain causal architectures and associated effective connectivities. We show that DCM can be cast faithfully as a special form of a new generalized RNN. In the resulting DCM-RNN, the hidden states are neural activity, blood flow, blood volume, and deoxyhemoglobin content and the parameters are biological quantities such as effective connectivity, oxygen extraction fraction and vessel wall elasticity. DCM-RNN is a versatile tool for neuroscience with great potential especially when combined with deep learning networks. In this study, we explore sparsity- based causal architecture discovery with DCM-RNN. In the experiments, we demonstrate that DCM-RNN equipped with l-{1} connectivity regulation is more robust to noise and more powerful at discovering sparse architectures than classic DCM with l-{2} connectivity regulation.

Original languageEnglish (US)
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages275-278
Number of pages4
ISBN (Electronic)9781538636466
DOIs
StatePublished - Oct 26 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: Jul 18 2018Jul 21 2018

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Other

Other40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/TerritoryUnited States
CityHonolulu
Period7/18/187/21/18

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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