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Phasic and sustained interactions of multisensory interplay and temporal expectation

机译:多感官相互作用和时间期望的阶段性和持续性相互作用

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摘要

Every moment organisms are confronted with complex streams of information which they use to generate a reliable mental model of the world. There is converging evidence for several optimization mechanisms instrumental in integrating (or segregating) incoming information; among them are multisensory interplay (MSI) and temporal expectation (TE). Both mechanisms can account for enhanced perceptual sensitivity and are well studied in isolation; how these two mechanisms interact is currently less well-known. Here, we tested in a series of four psychophysical experiments for TE effects in uni- and multisensory contexts with different levels of modality-related and spatial uncertainty. We found that TE enhanced perceptual sensitivity for the multisensory relative to the best unisensory condition (i.e. multisensory facilitation according to the max-criterion). In the latter TE effects even vanished if stimulus-related spatial uncertainty was increased. Accordingly, computational modelling indicated that TE, modality-related and spatial uncertainty predict multisensory facilitation. Finally, the analysis of stimulus history revealed that matching expectation at trial n-1 selectively improves multisensory performance irrespective of stimulus-related uncertainty. Together, our results indicate that benefits of multisensory stimulation are enhanced by TE especially in noisy environments, which allows for more robust information extraction to boost performance on both short and sustained time ranges.
机译:生物每时每刻都面临着复杂的信息流,它们利用它们来生成可靠的世界心理模型。越来越多的证据表明,有几种优化机制可用于整合(或隔离)传入的信息。其中包括多感官互动(MSI)和时间期望(TE)。两种机制都可以解释增强的感知灵敏度,并且在单独研究中得到了很好的研究。这两种机制如何相互作用目前尚不为人所知。在这里,我们在一系列四个心理物理实验中测试了单感觉和多感觉语境中TE效应的情况,这些情形具有与模态相关和空间不确定性不同的水平。我们发现,相对于最佳单感状态(即根据最大标准的多感化促进),TE增强了对多感官的感知敏感性。在后者中,如果增加与刺激相关的空间不确定性,则TE效应甚至消失。因此,计算模型表明TE,模态相关和空间不确定性预测了多感官促进。最后,对刺激历史的分析表明,与刺激相关的不确定性无关,试验n-1的预期匹配选择性地提高了多感官性能。在一起,我们的结果表明TE增强了多感觉刺激的好处,尤其是在嘈杂的环境中,它允许更强大的信息提取来提高短时间和持续时间范围内的性能。

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