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累积历史量化了神经适应在多稳态感知中的作用。

Cumulative history quantifies the role of neural adaptation in multistable perception.

作者信息

Pastukhov Alexander, Braun Jochen

机构信息

Cognitive Biology Laboratory, Otto-von-Guericke-Universität, Magdeburg, Germany.

出版信息

J Vis. 2011 Sep 19;11(10):12. doi: 10.1167/11.10.12.

Abstract

Neural adaptation plays an important role in multistable perception, but its effects are difficult to discern in sequences of perceptual reversals. Investigating the multistable appearance of kinetic depth and binocular rivalry displays, we introduce cumulative history as a novel statistical measure of adaptive state. We show that cumulative history-an integral of past perceptual states, weighted toward the most recent states-significantly and consistently correlates with future dominance durations: the larger the cumulative history measure, the shorter are future dominance times, revealing a robust effect of neural adaptation. The characteristic time scale of cumulative history, which may be computed by Monte Carlo methods, correlates with average dominance durations, as expected for a measure of neural adaptation. When the cumulative histories of two competing percepts are balanced, perceptual reversals take longer and their outcome becomes random, demonstrating that perceptual reversals are fluctuation-driven in the absence of adaptational bias. Our findings quantify the role of neural adaptation in multistable perception, which accounts for approximately 10% of the variability of reversal timing.

摘要

神经适应在多稳态感知中起着重要作用,但其影响在感知反转序列中难以辨别。通过研究动态深度和双眼竞争显示的多稳态外观,我们引入累积历史作为适应性状态的一种新的统计量度。我们表明,累积历史——过去感知状态的积分,对最近状态加权——与未来的主导持续时间显著且一致地相关:累积历史量度越大,未来的主导时间越短,这揭示了神经适应的强大作用。累积历史的特征时间尺度可以通过蒙特卡罗方法计算,它与平均主导持续时间相关,这符合作为神经适应量度的预期。当两个相互竞争的感知的累积历史平衡时,感知反转所需时间更长,其结果变得随机,这表明在没有适应性偏差的情况下,感知反转是由波动驱动的。我们的研究结果量化了神经适应在多稳态感知中的作用,它约占反转时间变异性的10%。

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