HRfunc

HRfunc is a tool built for the neuroimaging community to model hemodynamic variability and estimate neural activity from functional near infrared spectroscopy (fNIRS) data. Neuroimaging data like fNIRS and fMRI is often analyzed in its hemoglobin state modeled alongside a canonical hemodynamic response function (HRF) to infer neural activity. This can be problematic as canonical HRFs are variable and a one-size-fits-all HRF does not exist. HRfunc aims to fix this by enabling scientists to easily model HRFs within their own data and estimate neural activity through deconvolution.

HRF estimates, contributed by the neuroimaging community, are stored within a database called the HRtree that long term we hope will be a community resource for investigating hemodynamic variability. Each HRF estimate stores a rich amount of details about the derived HRFs origin aside from their location like task being complete, age range of subject pool, stimuli intensity, etc. Along with this, submitted estimates are only accepted from datasources with a paper published (pre-print accepted as well) detailing data collection to ensure the database is as comprehensive as possible.