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Bistable Perception Modeled as Competing Stochastic Integrations at Two Levels

机译:双稳态感知建模为两个层次上的竞争随机积分

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摘要

We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics – which is largely uncoupled from the time-scales that govern individual populations or neurons – explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.
机译:我们为双稳态感知提出了一种新颖的解释,即双亚稳态的多个神经种群的集体动力学。感觉输入和知觉状态的分布式表示通过这些人群中噪声驱动的过渡逐渐建立,直到替代表示之间的竞争由阈值机制解决。集体竞赛不断重复达到阈值会使感知成为双稳态。这种集体动力学与控制个体种群或神经元的时间尺度基本没有联系,解释了迄今为止关于双稳态感知的许多令人费解的观察结果:双稳态现象所表现出的平均轮替率范围广泛,连续的优势期持续变化,以及过去知觉状态的稳定作用。它还预测了表征双稳态感知的可观察量之间的许多先前未曾想到的关系。我们得出的结论是,双稳态感知反映的是神经决策的集体性质,而不是单个群体或神经元的性质。

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