134 Toward transparency and trustworthy translation: An open and reproducible workflow for functional near-infrared spectroscopy

Maegan Calvert; Tatianna Wolfe; Tim Koscik; Stephen LaConte; G. Andrew James

doi:10.1017/cts.2026.10345

Back

134 Toward transparency and trustworthy translation: An open and reproducible workflow for functional near-infrared spectroscopy

Abstract

Open access

Peer reviewed

134 Toward transparency and trustworthy translation: An open and reproducible workflow for functional near-infrared spectroscopy

Maegan Calvert, Tatianna Wolfe, Tim Koscik, Stephen LaConte and G. Andrew James

Journal of clinical and translational science, Vol.10(s1), pp.41-42

04/01/2026

DOI: 10.1017/cts.2026.10345

Files and links (1)

url

https://doi.org/10.1017/cts.2026.10345View

Published (Version of record) Open Access

Abstract

Objectives/Goals: This project, at the intersection of psychological and neuroimaging science, aims to develop and validate an open, transparent, and reproducible workflow for measuring functional brain activity using functional near-infrared spectroscopy (fNIRS), advancing methodological rigor and translational potential in human neuroscience. Methods/Study Population: A Python-based workflow using MNE was designed to improve reproducibility in fNIRS data acquisition. The workflow includes the following: (1) electromagnetic digitizer accuracy testing and distortion correction; (2) integration of head shape and source-detector location data; (3) visualization tools for verifying optode placement accuracy before data collection; and (4) implementation entirely in an open-source software to promote accessibility and transparency. Results/Anticipated Results: Difference in data quality, spatial accuracy, and reproducibility between standard fNIRS practice and this open workflow will be systematically evaluated. Discussion/Significance of Impact: This project advances translation in neuroimaging by embedding rigor and transparency into all stages of the workflow. By openly sharing software tools and validation methods, the workflow enables independent replication, fosters methodological transparency, and reduces reliance on proprietary systems.

Data Acquisition

Medical Imaging

Neuroimaging

Translation

Accuracy

Data collection

Embedding

Infrared spectroscopy

Open source software

Population studies

Reproducibility

Spectrum analysis

Details

Title: Subtitle: 134 Toward transparency and trustworthy translation: An open and reproducible workflow for functional near-infrared spectroscopy
Creators: Maegan Calvert - University of Arkansas for Medical Sciences
Tatianna Wolfe - University of Arkansas for Medical Sciences
Tim Koscik - University of Arkansas for Medical Sciences
Stephen LaConte - Virginia Tech
G. Andrew James - University of Arkansas for Medical Sciences
Resource Type: Abstract
Publication Details: Journal of clinical and translational science, Vol.10(s1), pp.41-42
DOI: 10.1017/cts.2026.10345
ISSN: 2059-8661
eISSN: 2059-8661
Publisher: Cambridge University Press
Number of pages: 2
Language: English
Date published: 04/01/2026
Academic Unit: Psychiatry
Record Identifier: 9985161442802771

Metrics

1 Record Views