Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging

Stephanie Sutoko, Yee Ling Chan, Akiko Obata, Hiroki Sato, Atsushi Maki, Takashi Numata, Tsukasa Funane, Hirokazu Atsumori, Masashi Kiguchi, Tong Boon Tang, Yingwei Li, Blaise Deb Frederick, Yunjie Tong

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2 Citations (Scopus)

Abstract

Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., O2Hb) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task.

Original languageEnglish
Article number015001
JournalNeurophotonics
Volume6
Issue number1
DOIs
Publication statusPublished - 2019 Jan 1

Keywords

  • brain
  • denoising
  • low-frequency oscillation
  • near-infrared spectroscopy
  • peripheral
  • systemic noise
  • working memory.

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Sutoko, S., Chan, Y. L., Obata, A., Sato, H., Maki, A., Numata, T., Funane, T., Atsumori, H., Kiguchi, M., Tang, T. B., Li, Y., Frederick, B. D., & Tong, Y. (2019). Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging. Neurophotonics, 6(1), [015001]. https://doi.org/10.1117/1.NPh.6.1.015001