TY  - SER
AU  - Luccio, Riccardo 
TI  - Limits of the Application of Bayesian Modeling to Perception
PY  - 2019///
PB  - sage
KW  - Bayes’ rule
KW  -  imperfect discriminability,
KW  - assignment of probabilities,
KW  - SDT
N2  - The general lines of Bayesian modeling (BM) in the study of perception are outlined here. The main thesis argued here is that BM works well only in the so-called secondary processes of perception, and in particular in cases of imperfect discriminability between stimuli, or when a judgment is required, or in cases of multistability. In cases of “primary processes,” on the other hand, it is often arbitrary and anyway superfluous, as with the laws of Gestalt. However, it is pointed out that in these latter cases, simpler and more well-established methodologies already exist, such as signal detection theory and individual choice theory. The frequent recourse to arbitrary values of a priori probabilities is also open to question
UR  - https://doi.org/10.1177/0301006619868125
ER  -