NeuroDOT: a Matlab and Python toolbox for diffuse optical tomographic brain mapping

Processing pipelines for functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) data pose many challenges. Costly software licenses (e.g., Matlab) and a tendency to develop group-specific pipelines prevent the adoption of standardized practices for data processing, as are being leveraged in the fMRI community. Another challenge of fNIRS and DOT toolbox development is the need for compatibility with multiple data formats (e.g., SNIRF, BIDS, NIRS, NIfTI, GIFTI, 4dfp, etc.) and a wide variety of commercially available systems (e.g., GowerLabs, NIRx, etc.). NeuroDOT provides tools for pre-processing, data quality analysis, head modeling with either atlas or participant-specific MRI, image reconstruction, and post processing with statistical analyses, removing the need to combine multiple packages to perform these tasks. The NeuroDOT toolbox is being developed and maintained in both Matlab and Python in parallel. Additionally, NeuroDOT leverages the use of cloud-based computing to lessen the computational burden of processing, promote reproducibility of results, and simplify processing overall. NeuroDOT supplies the fNIRS community with a highly efficient, intuitive, and extensible toolbox with shared tools for fMRI-comparable high fidelity optical brain mapping. We aim to promote modernization of the growing components of NeuroDOT by continuing to refactor the toolbox to Python with enhanced development tools, data format standardization relevant to both optical and fMRI fields and enhanced the support for NeuroDOT users and developers with expanded documentation and tutorials. Open-source software is essential for standardization of processing for fNIRS data and accessibility of the NeuroDOT toolbox to new users.