Circular pearson correlation using cosine series expansion

Shih Gu Huang, Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung

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

Abstract

In resting-state fMRI, there is no external anchor that will lock brain activation across voxels. Thus, correlation of fMRI time series between voxels is often done by computing coherence in the frequency domain. However, such approach ignores the time lag of fMRI time series across voxels. To address the problem, we propose to use the concept of circular Pearson correlation in determining the time lag, which locks the time series, and the maximum correlation at locking. We further express the circular Pearson correlation analytically in terms of cosine series expansion. The proposed method is applied to 208 twin pairs to determine if the time lag and the maximum correlation are heritable genetic features.

Original languageEnglish (US)
Title of host publicationISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Pages1774-1777
Number of pages4
ISBN (Electronic)9781538636411
DOIs
StatePublished - Apr 2019
Event16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy
Duration: Apr 8 2019Apr 11 2019

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2019-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
CountryItaly
CityVenice
Period4/8/194/11/19

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Huang, S. G., Gritsenko, A., Lindquist, M. A., & Chung, M. K. (2019). Circular pearson correlation using cosine series expansion. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 1774-1777). [8759319] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759319