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Surface-based Image Reconstruction Optimization For High-density Functional Near-infrared Spectroscopy.

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Surface-based Image Reconstruction Optimization For High-density Functional Near-infrared Spectroscopy.

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Surface-based image reconstruction optimization for high-density functional near-infrared spectroscopy.

Laura B Carlton¹, Miray Altınkaynak¹, Shannon M Kelley¹

¹Boston University, Neurophotonics Center, Department of Biomedical Engineering, Boston, Massachusetts, United States.

|March 18, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

High-density hexagonal arrays improve diffuse optical tomography (DOT) surface reconstructions for brain and scalp imaging. Optimized DOT with synthetic data effectively identifies localized brain activation, enhancing functional near-infrared spectroscopy analysis.

Keywords:

diffuse optical tomography functional near-infrared spectroscopy human brain function inverse problem

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Conducting Hyperscanning Experiments with Functional Near-Infrared Spectroscopy

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Published on: January 19, 2019

Area of Science:

Neuroimaging
Biomedical Optics
Functional Near-Infrared Spectroscopy (fNIRS)

Background:

Diffuse optical tomography (DOT) reconstructs functional near-infrared spectroscopy (fNIRS) data into spatial images of hemoglobin oxygenation.
Accurate DOT reconstruction depends on probe geometry and optimization strategies.
Previous research primarily focused on volumetric reconstructions using grid arrays, necessitating new approaches for surface-based imaging.

Purpose of the Study:

To evaluate high-density hexagonal arrays for surface-based DOT reconstructions of the brain and scalp.
To compare single-wavelength (indirect) and dual-wavelength (direct) reconstruction approaches.
To optimize measurement, spatial regularization, and basis functions for improved localization and reduced crosstalk.

Main Methods:

Simulations using a white-noise model guided parameter optimization with image quality metrics.
Augmentation of resting-state fNIRS data with synthetic hemodynamic response functions (HRFs) to model real measurement variance.
Validation using a ball-squeezing motor task to assess real-world performance.

Main Results:

Gaussian spatial bases reduced brain-scalp crosstalk but decreased contrast-to-noise ratio and increased localization error.
Indirect hemoglobin reconstruction effectively reduced oxy-deoxy crosstalk.
Validation data demonstrated strong, lateralized motor cortex activation contralateral to the stimulated hand.

Conclusions:

Optimized high-density hexagonal arrays enable accurate surface DOT reconstructions.
Augmenting resting-state data with synthetic HRFs is an effective strategy for parameter selection in DOT.
The optimized approach yields localized brain activation with high contrast-to-noise ratios.