Neuronal Self-Organization of Motion Percepts

Zusammenfassung A neural network which models multi-stable perception is presented. The network consists of sensor and inner neurons. The dynamics is established by a stochastic neuronal dynamics, a formal Hebb-type coupling dynamics and a resource mechanism that corresponds to saturation eeects in perception. From this a system of coupled diierential equations is derived and analyzed. Single stimuli are bound to exactly one percept, even in ambiguous situations where multi-stability occurs. The network exhibits discontinuous as well as continuous phase transitions and models various empirical ndings, including the percepts of succession, alternative motion and simultaneity; while the percept of oscillation is explained by oscillating percepts at a continuous phase transition.