ArticleNeurophotonics2022
MOCA: a systematic toolbox for designing and assessing modular functional near-infrared brain imaging probes.
Article in Neurophotonics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Functional near-infrared spectroscopy: Systematic mapping of abnormal brain function features in neurological disorders.Neural regeneration research · 2026Article
- NeuroCaptain v2 - Interactive Three-Dimensional fNIRS Optode and Probe Montage Design Platform Based on Blender.bioRxiv : the preprint server for biology · 2026Article
- Flexible circuit-based spatially aware modular optical brain imaging system for high-density measurements in natural settings.Neurophotonics · 2024Article
- Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings.medRxiv : the preprint server for health sciences · 2024Article
- Using preregistration as a tool for transparent fNIRS study design.Neurophotonics · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Significance: The expansion of functional near-infrared spectroscopy (fNIRS) systems toward broader utilities has led to the emergence of modular fNIRS systems composed of repeating optical source/detector modules. Compared to conventional fNIRS systems, modular fNIRS systems are more compact and flexible, making wearable and long-term monitoring possible. However, the large number of design parameters makes understanding their impact on a probe's performance a daunting task. Aim: We aim to create a systematic software platform to facilitate the design, characterization, and comparison of modular fNIRS probes. Approach: Our software-modular optode configuration analyzer (MOCA)-implements semi-automatic algorithms that assist in tessellating user-specified regions-of-interest, in interconnecting modules of various shapes, and in quantitatively comparing probe performance using metrics, such as spatial channel distributions and average brain sensitivity of the resulting probes. There is also support for limited parameter sweeping capabilities. Results: Through several examples, we show that users can use MOCA to design and optimize modular fNIRS probes, study trade-offs between several module shapes, improve brain sensitivity in probes via module re-orientation, and enhance probe performance via adjusting module spatial layouts. Conclusion: Despite its simplicity, our modular probe design platform offers a framework to describe and quantitatively assess probes made by modules, opening a new door for the growing fNIRS user community to approach the challenging problem of module- and probe-parameter selection and fine-tuning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.