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100			_aLuccio, Riccardo _949652
245			_aLimits of the Application of Bayesian Modeling to Perception/
260			_bsage _c2019
300			_aVol 48, Issue 10, 2019: ( 901-917 p.).
520			_aThe 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.
650			_aBayes’ rule, _949653
650			_a imperfect discriminability, _949654
650			_aassignment of probabilities, _949655
650			_aSDT _949656
773	0		_012374 _916462 _dSage, _tPerception _x1468-4233
856			_uhttps://doi.org/10.1177/0301006619868125
942			_2ddc _cART
999			_c12491 _d12491