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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 8 — Aug. 1, 2013
  • pp: 1366–1379

Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS

Jeffrey W. Barker, Ardalan Aarabi, and Theodore J. Huppert  »View Author Affiliations

Biomedical Optics Express, Vol. 4, Issue 8, pp. 1366-1379 (2013)

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Systemic physiology and motion-induced artifacts represent two major sources of confounding noise in functional near infrared spectroscopy (fNIRS) imaging that can reduce the performance of analyses and inflate false positive rates (i.e., type I errors) of detecting evoked hemodynamic responses. In this work, we demonstrated a general algorithm for solving the general linear model (GLM) for both deconvolution (finite impulse response) and canonical regression models based on designing optimal pre-whitening filters using autoregressive models and employing iteratively reweighted least squares. We evaluated the performance of the new method by performing receiver operating characteristic (ROC) analyses using synthetic data, in which serial correlations, motion artifacts, and evoked responses were controlled via simulations, as well as using experimental data from children (3–5 years old) as a source baseline physiological noise and motion artifacts. The new method outperformed ordinary least squares (OLS) with no motion correction, wavelet based motion correction, or spline interpolation based motion correction in the presence of physiological and motion related noise. In the experimental data, false positive rates were as high as 37% when the estimated p-value was 0.05 for the OLS methods. The false positive rate was reduced to 5–9% with the proposed method. Overall, the method improves control of type I errors and increases performance when motion artifacts are present.

© 2013 osa

OCIS Codes
(100.2960) Image processing : Image analysis
(170.5380) Medical optics and biotechnology : Physiology
(300.0300) Spectroscopy : Spectroscopy
(170.2655) Medical optics and biotechnology : Functional monitoring and imaging

ToC Category:
Image Processing

Original Manuscript: April 25, 2013
Revised Manuscript: June 7, 2013
Manuscript Accepted: June 8, 2013
Published: July 17, 2013

Jeffrey W. Barker, Ardalan Aarabi, and Theodore J. Huppert, "Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS," Biomed. Opt. Express 4, 1366-1379 (2013)

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