Forward Model

Definition: The forward model (y = Ax, where y is the simulated or measurement data, A is the sensitivity matrix, and x is the changes in optical properties) for fNIRS describes the relationship between the changes in optical density measured by source-detector pairs on the scalp and the changes in optical properties in the underlying brain tissue. Photon migration is simulated for any given source and detector pair using a segmented head model, typically with 5 tissue types. The result is the so-called sensitivity matrix (A) or Jacobian matrix. The rows of the sensitivity matrix (A) represent each source-detector pair’s sensitivity to the underlying absorption changes. This sensitivity matrix (A) can be used to solve the inverse problem in the Diffuse Optical Tomography image reconstruction process.

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References: https://doi.org/10.1016/j.neuroimage.2009.07.033

https://doi.org/10.34133/2022/9850248

Related terms: Forward Problem, Inverse Problem, Diffuse optical tomography, Sensitivity matrix,  

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