Sensor space group analysis for fNIRS data

J Neurosci Methods. 2016 May 1;264:103-112. doi: 10.1016/j.jneumeth.2016.03.003. Epub 2016 Mar 4.

Abstract

Background: Functional near-infrared spectroscopy (fNIRS) is a method for monitoring hemoglobin responses using optical probes placed on the scalp. fNIRS spatial resolution is limited by the distance between channels defined as a pair of source and detector, and channel positions are often inconsistent across subjects. These challenges can lead to less accurate estimate of group level effects from channel-specific measurements.

New method: This paper addresses this shortcoming by applying random-effects analysis using summary statistics to interpolated fNIRS topographic images. Specifically, we generate individual contrast images containing the experimental effects of interest in a canonical scalp surface. Random-effects analysis then allows for making inference about the regionally specific effects induced by (potentially) multiple experimental factors in a population.

Results: We illustrate the approach using experimental data acquired during a colour-word matching Stroop task, and show that left frontopolar regions are significantly activated in a population during Stroop effects. This result agrees with previous neuroimaging findings.

Compared with existing methods: The proposed methods (i) address potential misalignment of sensor locations between subjects using spatial interpolation; (ii) produce experimental effects of interest either on a 2D regular grid or on a 3D triangular mesh, both representations of a canonical scalp surface; and (iii) enables one to infer population effects from fNIRS data using a computationally efficient summary statistic approach (random-effects analysis). Significance of regional effects is assessed using random field theory.

Conclusions: In this paper, we have shown how fNIRS data from multiple subjects can be analysed in sensor space using random-effects analysis.

Keywords: Canonical scalp surface; Functional near-infrared spectroscopy; Random field theory; Random-effects analysis; Sensor space group analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain Mapping / methods*
  • Executive Function / physiology
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Prefrontal Cortex / physiology
  • Spectroscopy, Near-Infrared / methods*
  • Stroop Test