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.

Fig. 1

Flowchart of the steps (1–7) involved in creating and visualizing the optimal probe design for FNRIS studies. Each step in the flowchart has been numbered to follow the sections within the text

Fig. 2

(A–D) Steps for creating the left frontal probe geometry (chosen as an example). Note: all circles were drawn with radius = 29 mm. One of the final stages (before modification) of probe geometry for (E) left frontal and (F) left temporo-parietal connections. Red and blue circles show sources and detectors respectively. The white lines connecting the circles show the source-detector connections.

Fig. 3

Digitized points from an adult's probe geometry registered onto an adult atlas. Red and blue circles represent the sources and detectors and their connections are shown in yellow.

Fig. 4

Sensitivity distributions for one (top and bottom left) and across all channels (middle and right columns) generated from running Monte Carlo simulations using the digitized points from the adult probe geometry registered to an adult atlas (top panels) and a segmented head from the adult subject-specific MRI (bottom panels). The color scale depicts the sensitivity logarithmically from 0.001 to 0.1.

Fig. 5

Views from the left and right of 3D surface models of the skull, sensitivity distributions (gray = non-overlapping with any ROI; yellow = intersecting and/or overlying an ROI) and selected ROIs (blue) of the right hemisphere, generated from the adult probe geometry using an atlas approach (top) and adult subject-specific MRI approach (bottom). The ROIs presented are: 1. DLPFC, 2. IFG, 3. MFG, 4. FEF, 5. aIPS, 6. TPJ, 7. sIPS. 8. VOC, 9. OCC A planar view of the intersection between the right DLPFC ROI and channel C11 is shown in the inset in the top left corner with probabilities depicted by the colors (green = higher probability).

Fig. 6

Modification to probe geometry to capture intersection with right and left FEF (only left probe geometry and FEF shown) (A) Before modification, the right and left FEF did not intersect any of the channels of the probe geometry. (B) Lines were drawn from source S1 (F7) to T7 and S3 (F3) to C3. Using these lines as the reference, the entire frontal geometry was moved 1/5 of the distance between S1-T7 and S3-C3. New positions of the sources and detectors are shown in top plot The plot at the bottom right shows the intersection of left FEF with three channels after the geometry was modified.

Fig. 7

Views from the left and right of 3D surface models of the skull, sensitivity distributions (gray = non-overlapping with any ROI; yellow = intersecting and/or overlying an ROI) and selected ROIs (blue) of the right hemisphere, generated from the child probe geometry using an atlas approach (top) and child subject-specific MRI approach (bottom). The numbering of the ROIs follows the numbering from Fig. 5.

Fig. 8

Digitized points from an adult probe geometry registered onto an adult atlas (left). Red and blue circles represent the sources and detectors and their connections are shown in yellow. Sensitivity distributions of channels generated from running Monte Carlo simulations using the digitized points from the subject's probe geometry registered to an adult atlas (right). The color scale depicts the sensitivity logarithmically from 0.001 to 0.1.

Fig. 9

Views from the left and right of 3D surface models of the skull, sensitivity distributions (gray = non-overlapping with any ROI; yellow = intersecting and/or overlying an ROI) and selected ROIs (blue) of the right hemisphere, generated from the adult probe geometry using an atlas approach.