Multiple correlation and multi-seed for robust inference of functional connectivity in FMRI

Yongmei Michelle Wang, Jing Xia, John Marden

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

Abstract

A novel statistical method for estimating brain networks from functional MRI data is presented. Instead of examining the correlations with each individual seed, we detect functional connectivity from fMRI data by simultaneously examining the multi-seed correlations via the multiple correlation coefficients. In addition, we propose to take into account the spatially structured noise in fMRI during the identification of the networks of functional interconnections by comparing the temporal multiple correlations against a model of the spatial multiple correlations in the noise. Evaluation for accuracy and robustness of the approach was performed using both simulated data and real fMRI data.

Original languageEnglish (US)
Title of host publication2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages408-411
Number of pages4
DOIs
StatePublished - Nov 27 2007
Event2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States
Duration: Apr 12 2007Apr 15 2007

Publication series

Name2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
CountryUnited States
CityArlington, VA
Period4/12/074/15/07

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Medicine(all)

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    Wang, Y. M., Xia, J., & Marden, J. (2007). Multiple correlation and multi-seed for robust inference of functional connectivity in FMRI. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings (pp. 408-411). [4193309] (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings). https://doi.org/10.1109/ISBI.2007.356875