Parameter inference using continuous change in degenerate biophysical diffusion models

Biophysical modelling of diffusion MRI (dMRI) may elucidate key microstructural features. However, most models include many input parameters, making simultaneous estimations of all parameters ill-posed. To overcome this, the recently published Bayesian framework EstimatioN for CHange (BENCH) characterises changes (variation) in parameters across multiple measurements/samples, rather than inferring the actual parameters from a single measurement/sample. BENCH has been previously applied to understand group-wise changes (e.g., patients vs. controls) in biophysical parameters. Here, we adapted BENCH to interpret situations of continuous change and validate its behaviour using synthetic dMRI data from numerical simulations.