Fluorescence recovery after photobleaching (FRAP) is used to study actin-turnover in dendritic spines providing recovery_trajectories over time within a nested data structure (i.e. spine/neuron/culture). Statistical approaches to FRAP usually_consider one-phase association models to estimate recovery-curve-specific parameters and test statistical hypotheses on_curve parameters either at the spine or neuron level, ignoring the nested data structure. However, this approach leads to_pseudoreplication concerns. We propose a nonlinear mixed-effects model to integrate the one-phase association model_estimate with nested data structure of FRAP experiments; this allowed us to model heteroscedasticity with an exponential_variance function, accounting for the different effects of the experimental condition, and autocorrelation structure over time with_an autoregressive model. We used this approach to evaluate the effect of the downregulation of the actin-binding protein CAP2_on actin dynamics. Our model was able to capture the higher variance, thus increased instability, of actin cytoskeleton upon_CAP2 down-regulation. We developed an R-based Shiny application, termed FRApp, to fit the statistical models introduced_without requiring programming expertise._
