Poster session: Switching dynamics of border ownership: a stochastic model for multi-stable perception
Naoki Kogo · Lirias · 2009
The stochastic nature of perception is modelled using "face or vase“ stimuli. The border-ownership (BOWN) is computed and its 2-D integration determines the figure-ground relationships. Random numbers are multiplied to the BOWN signals and feedback connections skew the probability density function in favour of the figure. This enhances the figure-ground segregation. Adaptation results in a decay of the response which leads to alternation. This triggers recovery of the adaptation. The alternation rate decreases in response to the increased levels of disambiguation. With intermittent presentation, due to the recovery not only during the blank periods but also during the periods when the model is giving the opposite figure-ground relationship to the current response, the model shows the prolongation of the alternation as shown in other cases of bi-stable perception. In this framework, the adaptation and the recovery processes need to be perception dependent (not physical input dependent) to reproduce human perception.