Body mass index associated with respiration predicts motion in resting-state functional magnetic resonance imaging scans

Shishi Huang, Andrew D. Vigotsky, Apkar Vania Apkarian, Lejian Huang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Decreasing body mass index (BMI) reduces head motion in resting-state fMRI (rs-fMRI) data. Yet, the mechanism by which BMI affects head motion remains poorly understood. Understanding how BMI interacts with respiration to affect head motion can improve head motion reduction strategies. A total of 254 patients with back pain were included in this study, each of whom had two visits (interval time = 13.85 ± 7.81 weeks) during which two consecutive re-fMRI scans were obtained. We investigated the relationships between head motion and demographic and pain-related characteristics—head motion was reliable across scans and correlated with age, pain intensity, and BMI. Multiple linear regression models determined that BMI was the main determinant in predicting head motion. BMI was also associated with two features derived from respiration signal. Anterior–posterior and superior–inferior motion dominated both overall motion magnitude and the coupling between motion and respiration. BMI interacted with respiration to influence motion only in the pitch dimension. These findings indicate that BMI should be a critical parameter in both study designs and analyses of fMRI data.

Original languageEnglish (US)
Article numbere70015
JournalHuman Brain Mapping
Volume45
Issue number13
DOIs
StatePublished - Sep 2024

Funding

We thank NIH (grant 1P50DA044121\u201001A1) for funding data analysis. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE\u20101324585.

Keywords

  • BMI
  • back pain
  • fMRI
  • motion
  • respiration signal

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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