Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering.

Xian Zhang,Joy Hirsch,Jack Adam Noah

doi:10.1117/1.nph.3.1.015004

Abstract

Global systemic effects not specific to a task can be prominent in functional near-infrared spectroscopy (fNIRS) signals and the separation of task-specific fNIRS signals and global nonspecific effects is challenging due to waveform correlations. We describe a principal component spatial filter algorithm for separation of the global and local effects. The effectiveness of the approach is demonstrated using fNIRS signals acquired during a right finger-thumb tapping task where the response patterns are well established. Both the temporal waveforms and the spatial pattern consistencies between oxyhemoglobin and deoxyhemoglobin signals are significantly improved, consistent with the basic physiological basis of fNIRS signals and the expected pattern of activity associated with the task.

Highlights

Functional near-infrared spectroscopy measures relative changes by radiating near-infrared lights of two or more wavelengths and records the reflected lights
Since the relative concentrations of oxyhemoglobin and deoxyhemoglobin change in opposite directions, their signals would be expected to have similar waveforms with opposite polarity, and the amplitudes of oxyhemoglobin and deoxyhemoglobin would have similar spatial patterns provided that the Functional near-infrared spectroscopy (fNIRS) signal originates only from brain regions associated with the task
The global component may be more pronounced in fNIRS than in functional magnetic resonance imaging acquisitions because the near-infrared lights pass through superficial layers of blood vessels in skin and yield significant signal changes primarily due to systemic components

Summary

Introduction

Functional near-infrared spectroscopy (fNIRS) measures relative changes by radiating near-infrared lights of two or more wavelengths and records the reflected lights. FNIRS data are often not consistent with this expectation and raise concerns for interpretation. Systemic effects, such as blood pressure, respiratory and blood flow variation, alter relative blood oxyhemoglobin and deoxyhemoglobin concentrations. It is well established that fNIRS signals contain both global (systemic) and cortical BOLD effects.[2,3,4,5] In this paper, we use the term global components to denote the combined systemic components not associated with task-specific activity in fNIRS data. The global component may be more pronounced in fNIRS than in functional magnetic resonance imaging (fMRI) acquisitions because the near-infrared lights pass through superficial layers of blood vessels in skin and yield significant signal changes primarily due to systemic components.

Methods

Results

Conclusion