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首页> 外文期刊>Journal of vision >Unstable mean context causes sensitivity loss and biased estimation of variability
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Unstable mean context causes sensitivity loss and biased estimation of variability

机译:平均环境不稳定会导致灵敏度损失和变异性的估计偏差

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A recent study has suggested that statistical representations of ensemble objects may provide contextual stability to facilitate perception. The present study investigated whether facilitating such perception occurs in the extraction of variability information and how the stability of context mean values influences variability perception. We designed two tasks in which participants directly judged the variability of stimuli. In Experiment 1, we manipulated both the stability of the mean values and the exposure time to observe the time course of stability facilitation. In Experiment 2, we decomposed the stability of the context mean values into between-trials and within-trial levels to further investigate the mechanism of such facilitation. The results revealed that stable mean contexts do facilitate variability perception. In particular, unstable long-term mean context causes loss of sensitivity to variability whereas response bias is determined by the interaction between long-term and transient mean stability.
机译:最近的一项研究表明,合奏对象的统计表示可以提供上下文稳定性以促进感知。本研究调查了在可变性信息的提取中是否促进了这种感知,以及上下文平均值的稳定性如何影响可变性感知。我们设计了两个任务,参与者可以直接判断刺激的变异性。在实验1中,我们操纵了平均值的稳定性和暴露时间,以观察促进稳定性的时间过程。在实验2中,我们将上下文平均值的稳定性分解为试验间和试验内级别,以进一步研究这种促进机制。结果表明,稳定的均值上下文确实有助于变异性感知。特别是,不稳定的长期均值环境会导致对变异性的敏感性下降,而响应偏差则由长期和瞬态均值稳定性之间的相互作用确定。

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