Sentence examples for model of rivalry from inspiring English sources

Here, we propose to exploit the structural similarity between rivalry and attention as forms of competition and present a WTA model of rivalry.

Our aim is to construct a comprehensive model of rivalry that replicates the three key features common to all rivalry processes: leptokurtic dominance distributions, Levelt's propositions, and the role of memory, in particular for the phenomena related to stimulus blanking.

Lee and Blake [21] reexamine IOG during rivalry, and argue that, whereas IOG rules out models of rivalry in which one eye or the other is completely dominant at any given moment, IOG can be explained by simultaneous dominance of local eye-based regions distributed between the eyes.

Many models of rivalry replicate the leptokurtic distribution of dominance durations.

To compare different computational models of rivalry, we simulated three different networks of increasing complexity.

This model introduces a form of memory by forming discrete states and explains experimental data better than competitive models of rivalry without memory.

Many models of rivalry assume a form of "fatigue" or habituation; that is, if a percept has been dominant for some time, its representation fatigues and thus the other percept becomes dominant.

Specifically, we here compare three models of rivalry (Fig. 1), which serve as prototypes for broad classes of rivalry models: first, networks of self-exciting units with mutual inhibition (model 1); second, the same network augmented with an adaptation mechanism in the excitatory units (model 2); third, our new approach, two coupled networks that implicitly form a memory state (model 3).

Various generalizations of such front solutions have also been developed in order to take into account the effects of network in-homogeneities [41 43], external stimuli [44, 45], and network competition in a model of binocular rivalry waves [38].

On the other hand, Laing and Chow [59] considered a deterministic spiking neuron model of binocular rivalry in which the statistics of the resulting dominance times appeared noisy due to the aperiodicity of the high-dimensional system's trajectories.

Any computational model of visual rivalry needs to be tested against experimentally established characteristics.