A behavioral stochastic self-oscillator model with perception-attention coupling and re-entrant cognitive processing is used for simulating interrupted ambiguous stimulus induced percept reversals. The results provide further support for a dynamical systems foundation of cognitive and psychological problems as discussed in detail within the context of Gestalt psychology [1], and for coordination dynamics of the brain [2]. Periodic stimulus–off switching (toff < 1 s, ton = 300 ms) was introduced by Orbach et al. [3] as experimental paradigm to get more insight into the underlying perceptual dynamics. Their Necker cube experiments showed a maximum of the percept reversal rate R at Rmax =ca. 36 min-1 and toff 200 ms which was confirmed by recent experiments [4]. Noest et al. [5] demonstrated with a low level neural activation model [6] that a bifurcation of the percept choice dynamics during the ambiguous-stimulus on-off switching dominates the statistics of the reversal time series. Our simulations based on a macroscopic (behavioral) nonlinear dynamics model [7][8] (similar to [9]) support this finding. They show that the measured R vs. toff-time characteristics can be fitted with only a few model parameters: Thalamo-cortical reentrant delay T = 40 ms, attention fatigue (= adaptive feedback gain) time constant = 1 – 2 s, feedback-gain noise power J. Synchronisation of attention fatigue induced self-oscillations (yielding inter-stimulus transition time Ttr =ca. 4 – 5 T) in combination with stimulus-onset induced percept choice bifurcation appears to determine the percept-reversal rates and the toff-value at Rmax. A linear approximation of the dynamical equations allows for an analytical estimate of the reversal frequency and the cognitive damping time constant (≈ 1 s). By use of the Fluctuation-Dissipation theorem via noise power J itdefines an index of cognitive inertia (as suggested in [10]) as crucial parameter of the simulated dynamics. [1]Wagemans,J., Feldman, J., Gepshtein, S., Kimchi, R., Pomerantz, J. R., van der Helm, P.A., van Leeuwen, C. (2012) A century of Gestalt Psychology in visual perception: II. Conceptual and theoretical foundations, Psychological Bulletin 138 (6), 1218-1252 [2] Kelso J.A.S. (2012): Multistability and Metastability: Understanding dynamic coordination in the brain. Phil Trans. R. Soc. B vol. 367 pp. 906-918 [3] Orbach. J., Zucker, E., Olson, R. (1966). Reversibility of the Necker Cube: VII. Reversal rate as a function of figure-on and figure-off durations. Percept. Motor Skills (22), 615-618 [4] Kornmeier, J., Ehm, W. Bigalke, H., Bach, M. (2007): Discontinuous presentation of ambiguous figures: How interstimulus-interval durations affect reversal dynamics and ERP’s. Psychophysiology, 44, 552-560 [5] Noest, A.J., van Ee, R., Nijs, M.M., van Wezel, R.J.A. (2007). Percept-choice sequences driven by interrupted ambiguous stimuli: A low-level neural model. J of Vision 7, 1-14 [6] Amari, S. (1977): Dynamics of pattern formation in lateral-inhibition type neural fields. Biological Cybernetics vol. 27, 77-87 [7] Fürstenau, Norbert (2010). A nonlinear dynamics model for simulating long range correlations of cognitive multistability. Biol. Cybern., vol. 103. (3) 175-198 [8] Fürstenau, Norbert (2014). Simulating Bistable Perception with Interrupted Ambiguous Stimulus using Self-Oscillator Dynamics with Percept Choice Bifurcation. Cognitive Processing, 15 (4), 467-490 DOI: 10.1007/s10339-014-0630-4. [9] Ditzinger, T., Haken, H. (1989). Oscillations in the Perception of Ambiguous Patterns. Biol. Cybern. ( 61) 279-287 [10] Gao, J.B., Merk, I., Tung W. W., Billok V., White, K.D., Harris J G, Roychowdhury V P. (2006). Inertia and memory in visual perception. Cogn. Processing vol. 7 105-112
Simulating Bistable Perception with Interrupted Ambiguous Stimulus using Self-Oscillator Dynamics with Percept Choice Bifurcation
2015-03-01
Conference paper
Electronic Resource
German
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