Automated Processing of fNIRS Data-A Visual Guide to the Pitfalls and Consequences

Algorithms. 2018 May;11(5):67. doi: 10.3390/a11050067. Epub 2018 May 8.

Abstract

With the rapid increase in new fNIRS users employing commercial software, there is a concern that many studies are biased by suboptimal processing methods. The purpose of this study is to provide a visual reference showing the effects of different processing methods, to help inform researchers in setting up and evaluating a processing pipeline. We show the significant impact of pre- and post-processing choices and stress again how important it is to combine data from both hemoglobin species in order to make accurate inferences about the activation site.

Keywords: GLM; LF de-noising; channel exclusion; functional Near-Infrared Spectroscopy; motion correction; post-processing; pre-processing; single subject.