CortexLume: Rapid Geometry-Adaptive Cortical Feedback for Target-Informed fNIRS Design
Year: 2026
Type: preprint
Abstract: Target-informed functional near-infrared spectroscopy (fNIRS) probe design requires repeated evaluation of how candidate source-detector geometries sample the cortex, but full photon-transport modeling is too costly for interactive revision. We developed CortexLume, which couples an editable target-patch-placement representation with a geometry-adaptive cortical surrogate for rapid spatial assessment. The surrogate adapts its center, orientation, and anisotropic extent to fitted source-detector geometry and local scalp-cortex relationships, and is intended to approximate normalized cortical spatial allocation rather than absolute optical sensitivity. We benchmarked the method against MCX photon transport assembled through AtlasViewer on the ICBM152 anatomical model and then evaluated the frozen formulation on the independent Colin27 model without retuning. On ICBM152, mean channel-centroid discrepancy was 2.35 mm, 90%-mass Dice was 0.746 per channel and 0.826 per patch, and Jensen-Shannon distance was 0.330; the complete formulation improved Dice in 370 of 396 channels relative to a restricted reference. On Colin27, mean channel Dice was 0.748 and patch Dice was 0.812 across 88 retained channels. Patch-field construction required a median of only 75.81 ms. These results support CortexLume as a rapid cortical surrogate for iterative probe drafting and candidate shortlisting, with subject-specific photon modeling retained for final optical refinement.
Source: PsyArXiv (OSF Preprints)
Author: Ruiyi Huang
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7221127146