Validating a new methodology for optical probe design and image registration in fNIRS studies

Abstract

Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing.

Validating an image-based fNIRS approach with fMRI and a working memory task

“…These tissue volumes were identified and assigned unique values. These 273 volumes were then converted to 3D mesh surfaces and merged together to 274 create a subject-specific head atlas using scripts in the HOMER2 repository 275 (Wijeakumar et al, 2015). We chose to use subject-specific structural scans 276 instead of a generic adult atlas following findings from Cooper and colleagues 277 (Cooper et al, 2012).…”

“…These subject-specific masks were thresholded to include voxels with an optical 301 density of greater than 0.0001, a robust threshold value that is derived from our 302 previous work (Wijeakumar et al, 2015). 303…”

Modulating perceptual complexity and load reveals degradation of the visual working memory network in ageing

“…fNIRS is also cheaper than fMRI, making intensive study of age-related decline more feasible, and older adults do not have to remain completely still in a supine position for lengthy periods of time. Moreover, recent innovations in fNIRS analyses allow us to obtain voxel-wise measures of functional activation that can be directly compared to fMRI data (Wijeakumar et al, 2017(Wijeakumar et al, , 2015. …”

“…In total, there were 40 channels covering the frontal and parietal cortices. In our previous work, we optimized this probe geometry such that it covered ROIs from the fMRI VWM literature and was anchored to the 10-20 system of electrode placement so that the geometry could be scaled to different head sizes (Wijeakumar et al, 2015). …”

“…The sensitivity profiles and head volumes were converted to NIFTI format. The sensitivity profiles for each participant were summed together and thresholded to include voxels with an optical density of greater than 0.0001 (see Wijeakumar et al, 2015). Each subject-specific mask was transformed to MNI space using 3dAllineate.…”