Effects of visual angle on perspective reversal for ambiguous patterns.

Reversal rates of an ambiguous figure (the Necker cube) were studied for different pattern sizes covering a range of visual angles theta from approximately 1 to 62 deg. A large number of reversals was obtained for each observer and each pattern in order to examine the statistical distributions of reversal times. A pronounced flattening of the statistical distributions (represented throughout by a gamma distribution) and a growth of the mean duration of each percept, with increasing pattern size was found. A plateau in the range of theta between 5 and 20-30 deg was observed. For larger values of theta two kinds of observers have been identified: for 'fast' observers the inversion rate is little affected by theta, whilst for 'slow' observers, the mean reversal time increases strongly with theta. A tentative model, based on three different contributions to the duration of the alternation process, is proposed: a constant term, independent of theta, and two terms dependent on theta--a retinal term, and a cortical one. The last term is interpreted as due to the spreading of excitation with the characteristic of a filling-in process.

A model of visual perception.

In this paper we propose a model of visual perception in which a positive feedback mechanism can reproduce the pattern stimulus on a neurons screen. The pattern stimulus reproduction is based on informations coming from the spatial derivatives of visual pattern. This information together with the response of the feature extractors provides to the reproduction of the visual pattern as neuron screen electric activity. We simulate several input patterns and prove that the model reproduces the percept.

Stochastic models and fluctuations in reversal time of ambiguous figures.

Five probability distributions for the description of temporal fluctuations in the perception of ambiguous figures were fitted to previously obtained experimental results and classified according to their efficiency in describing the data. The gamma, Wiener, and Capocelli-Riciardi distributions showed the highest efficiency, while the chi2 and Taylor-Aldridge distributions showed a very low effiency. Therefore the underlying process may be described either by a simple Poisson model or by a random-walk model. For the gamma distribution there was a strong correlation between the parameters, while for the Wiener distribution this correlation was lower.