Bistable perception is fundamentally a dynamic process: Our perceptual experience continuously alternates when an ambiguous or rivalrous stimulus is observed. Here we present a method to analyze instantaneous measures of dominance and transition between percepts. The analysis extracts three time-varying probabilities. First, the transient preference represents the probability of perceiving one interpretation at one instant. Second, the reversal probability is the probability that the current percept will change at the next evaluation. Finally, the survival probabilities are the probability that at one instant the current percept will not switch to the alternative interpretation. We derive the relationships between these probabilities and offer a test of independence between consecutive percepts. We also introduce a simple technique to sample the observer’s perception at regular intervals. The analyzing method is illustrated with the example of binocular rivalry. We demonstrate Levelt’s second proposition with the survival probability measure and show that the consecutive rivalrous percepts are not independent.

*λ*and

*r*; see Figure 2) are strongly correlated (Borsellino et al., 1972; De Marco et al., 1977) and often identical. While the reason for this correlation is still not clear, it does indicate that the gamma distribution has one degree of freedom too many.

*μ*= 9.15 s and 7.60 s for observers DM and KM, respectively). The distribution of these phase durations follows a sharp rise and a slow fall that is well summarized by a gamma distribution (Levelt, 1965). The best-fitted parameters for the gamma distribution fall between 2 and 3, and this is consistent with numerous previous studies (for references, see Blake & Logothetis, 2002). From this analysis of the phase durations, it seems therefore that our method of recording the dynamics of binocular rivalry did not substantially affect the pattern of responses.

*α*is the asymptotic value of the stationary regime. The second degree of freedom τ is the time constant to reach the stable regime. Finally, the third degree of freedom

*σ*is the slope of the function at its inflexion point. We define the time constant as the time at the intersection of the asymptotic line and the tangent at the inflexion point (see Figure 3 and ).

*α*= 0.709 and 0.708 for observers DM and KM, respectively). In spite of this similarity, the observers took different amounts of time to reach these stationary regimes (

*τ*= 21.5 s and 7.3 s, respectively). This fundamental difference in temporal dynamics between observers was not readily visible in the phase-duration analysis.

*v*represent the reversal probability and

*u*the alternation rate (in number of changes per second), then where

*σ*is the mean inter-beep interval (here 2 s). In other words, the higher the reversal probability, the faster the alternation rate. We should note that in this equation,

*v*≤ 1 because it is a probability. If the reversal probability is too close to 1 for comfort, the experimenter should attempt to reduce the inter-beep interval or avoid the use of the discrete sampling technique. As a conservative rule, we suggest that caution is exercised if

*v*τ; 0.5.

*α*= 0.373 and 0.366 for observers DM and KM, respectively). The second degree of freedom is the time constant to reach the stable regime and is defined as for the transient preference (i.e., the intersection of the asymptotic line and the tangent at the inflexion point). The third degree of freedom is the slope of the function at its inflexion point and is positive for both observers, indicating that the alternation rate progressively increases within a run of trials.

*τ*are very different between the two observers, observer DM being much slower to reach a stationary regime than KM (

*τ*= 19.5 s and 5.3 s, respectively). The start of the stationary regime can be defined as time (

*τ*+

*σ*) where the added

*δ*reflects the fact that reversal probability refers to the predicted percept at the next beep. These values (21.5 s and 7.3 s, respectively) match very well the time constants found for the transient preference. Note however that there is no particular relationship between the transient preference and the reversal probability (for details, see ). In particular, if the two percepts were matched in strength, we would expect a balanced transient preference from the start of the run (i.e., 0.5), and yet we may still observe a reversal probability resembling the one found here. It is for this reason that we define the duration of the nonstationary regime from the reversal probability and not simply from the transient preference.

*α*

_{H}= 0.740 and 0.744 for observers DM and KM, respectively, compared to the asymptotic values for the low-contrast percept

*α*

_{L}= 0.369 and 0.393, respectively.

*α*

_{H}= 0.62 and

*α*

_{L}= 0.42.

*SE*across observers: 0.029), indicating that consecutive percepts are not independent. This result is seemingly in contradiction with previous reports that have consistently argued for independence (Fox & Hermann, 1967; Blake, Fox, & McIntyre,1971; Walker, 1975; Lehky, 1995). However, it is important to remember that their independence test was on consecutive phase durations rather than consecutive percepts. Our dependence result might reflect the gradual build-up of adaptation to one percept while this percept is surviving, whereas the independence of phase durations suggests that the adaptation is reset whenever a transition occurs.

*α*) in the stationary regime, the time constant (

*τ*) to reach that stationary regime, and the slope (

*σ*) of the function at the inflection point. The time constant is defined as the intersection of the asymptotic line and the tangent of the function at the inflexion point (see Figure 3). The fitting function comes in two types, depending on whether the function is monotonically increasing (positive

*σ*) or decreasing (negative

*σ*).

*H*were adjusted to the data with a maximum likelihood procedure that took into account the variability of each data point to estimate the best fit.