Perceptual tri-stability, measured and fitted as emergent from a model for bistable alternations

Abstract

The human auditory system in attempting to decipher ambiguous sounds appears to resort to perceptual exploration as evidenced by multi-stable perceptual alternations. This phenomenon has been widely investigated via the auditory streaming paradigm, employing ABA_ triplet sequences with much research focused on perceptual bi-stability with the alternate percepts as either a single integrated stream or as two simultaneous distinct streams. We extend this inquiry with experiments and modeling to include tri-stable perception. Here, the segregated percepts may involve a foreground/background distinction. We collected empirical data from participants engaged in a tri-stable auditory task, utilizing this dataset to refine a neural mechanistic model that had successfully reproduced multiple features of auditory bi-stability. Remarkably, the model successfully emulated basic statistical characteristics of tri-stability without substantial modification. This model also allows us to demonstrate a parsimonious approach to account for individual variability by adjusting the parameter of either the noise level or the neural adaptation strength.