KEYWORDS: Near infrared spectroscopy, Data acquisition, Standards development, Software development, Neuroimaging, Neurophotonics, Design and modelling, MATLAB, Data storage, Compliance
SignificanceFunctional near-infrared spectroscopy (fNIRS) is a popular neuroimaging technique with proliferating hardware platforms, analysis approaches, and software tools. There has not been a standardized file format for storing fNIRS data, which has hindered the sharing of data as well as the adoption and development of software tools.AimWe endeavored to design a file format to facilitate the analysis and sharing of fNIRS data that is flexible enough to meet the community’s needs and sufficiently defined to be implemented consistently across various hardware and software platforms.ApproachThe shared NIRS format (SNIRF) specification was developed in consultation with the academic and commercial fNIRS community and the Society for functional Near Infrared Spectroscopy.ResultsThe SNIRF specification defines a format for fNIRS data acquired using continuous wave, frequency domain, time domain, and diffuse correlation spectroscopy devices.ConclusionsWe present the SNIRF along with validation software and example datasets. Support for reading and writing SNIRF data has been implemented by major hardware and software platforms, and the format has found widespread use in the fNIRS community.
Scanning microscopy’s resolution of highly localized dynamics in awake animals is limited by bulk motion. We present a modular optical flow sensor based on spectral domain OCT which measures the specimen’s 3D displacement in real-time. A rose-function scan pattern rapidly acquires B-lines used to estimate displacements via an adaptive cross-correlation approach. Axial displacements are estimated from phase fluctuations apparent in the cross-correlation of the complex SD-OCT signal. The technique’s 3-dimensional readout rate and sensitivity to physiologically-relevant motion frequencies and magnitudes is evaluated.
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