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

@article{Barker2013AutoregressiveMB,
  title={Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS.},
  author={Jeffrey William Barker and Ardalan Aarabi and Theodore J. Huppert},
  journal={Biomedical optics express},
  year={2013},
  volume={4 8},
  pages={1366-79}
}
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… CONTINUE READING
28 Citations
0 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 28 extracted citations

Similar Papers

Loading similar papers…