Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception
Fig 5
Posteriors over model parameters.
Each panel shows the marginal posterior distributions over a single parameter for each subject and task. Each line is an individual subject’s posterior (thick line: interquartile range; light line: 95% credible interval); different colors correspond to different tasks. For each subject and task, posteriors are marginalized over models according to their posterior probability (see Methods). For each parameter we report the across-tasks compatibility probability Cp, that is the (posterior) probability that subjects were best described by the assumption that parameter values were the same across separate tasks, above and beyond chance. The first two rows of parameters compute compatibility across all three tasks, whereas in the last row compatibility only includes the bisensory tasks (bisensory inertial discrimination and unity judgment), as these parameters are irrelevant for the unisensory task.