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BOLD Granger Causality Reflects Vascular Anatomy

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  • J Taylor Webb
  • Michael A Ferguson
  • Jared A Nielsen
  • Jeffrey S Anderson

Abstract

A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project) to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7–40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain’s functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group), as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.

Suggested Citation

  • J Taylor Webb & Michael A Ferguson & Jared A Nielsen & Jeffrey S Anderson, 2013. "BOLD Granger Causality Reflects Vascular Anatomy," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
  • Handle: RePEc:plo:pone00:0084279
    DOI: 10.1371/journal.pone.0084279
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    References listed on IDEAS

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    1. Xiaotong Wen & Govindan Rangarajan & Mingzhou Ding, 2013. "Is Granger Causality a Viable Technique for Analyzing fMRI Data?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-11, July.
    2. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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    1. Toshihiko Aso & Shinnichi Urayama & Hidenao Fukuyama & Toshiya Murai, 2019. "Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-25, September.

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