Validation of a novel hemodynamic model for coherent hemodynamics spectroscopy (CHS) and functional brain studies with fNIRS and fMRI
We report an experimental validation and applications of the new hemodynamic model presented in the companion article (Fantini, 2014–this issue) both in the frequency domain and in the time domain. In the frequency domain, we have performed diffuse optical measurements for coherent hemodynamics spec...
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Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2014-01, Vol.85 (1), p.222-233 |
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Sprache: | eng |
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Zusammenfassung: | We report an experimental validation and applications of the new hemodynamic model presented in the companion article (Fantini, 2014–this issue) both in the frequency domain and in the time domain. In the frequency domain, we have performed diffuse optical measurements for coherent hemodynamics spectroscopy (CHS) on the brain and calf muscle of human subjects, showing that the hemodynamic model predictions (both in terms of spectral shapes and absolute spectral values) are confirmed experimentally. We show how the quantitative analysis based on the new model allows for autoregulation measurements from brain data, and provides an analytical description of near-infrared spiroximetry from muscle data. In the time domain, we have used data from the literature to perform a comparison between brain activation signals measured with functional near-infrared spectroscopy (fNIRS) or with blood oxygenation level dependent (BOLD) fMRI, and the corresponding signals predicted by the new model. This comparison shows an excellent agreement between the model predictions and the reported fNIRS and BOLD fMRI signals. This new hemodynamic model provides a valuable tool for brain studies with hemodynamic-based techniques.
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•We have validated a novel hemodynamic model in the frequency and time domains.•Frequency domain: coherent hemodynamics spectroscopy (CHS) on brain and muscle•Shape and absolute values of CHS spectra are accurately described by the model.•CHS spectra yield measures of autoregulation and other physiological parameters.•In the time domain, the model accurately predicts fNIRS and BOLD fMRI signals. |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2013.03.037 |