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多感官时间数字判断

Multisensory temporal numerosity judgment.

作者信息

Philippi Tom G, van Erp Jan B F, Werkhoven Peter J

机构信息

Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands.

出版信息

Brain Res. 2008 Nov 25;1242:116-25. doi: 10.1016/j.brainres.2008.05.056. Epub 2008 May 29.

DOI:10.1016/j.brainres.2008.05.056
PMID:18620342
Abstract

In temporal numerosity judgment, observers systematically underestimate the number of pulses. The strongest underestimations occur when stimuli are presented with a short interstimulus interval (ISI) and are stronger for vision than for audition and touch. We investigated if multisensory presentation leads to a reduction of underestimation. Participants were presented with 2 to 10 (combinations of) auditory beeps, tactile taps to the index finger and visual flashes at different ISIs (20 to 320 ms). For all presentation modes, we found underestimation, except for small number of pulses. A control experiment showed that the latter is due to a (cognitive) range effect. Averaged over conditions, the order of performance of sensory modalities is touch, audition and last vision. Generally, multisensory presentation improves performance over the unisensory presentations. For larger ISIs (160 and 320 ms), we found a tendency toward a reduction in variance for the multisensory presentation modes. For smaller ISIs (20 and 40 ms), we found a reduction in underestimation, but an increase in variance for the multisensory presentation modes. In the discussion, we relate these two findings to Maximum Likelihood Estimation (MLE) models predicting that multisensory integration reduces variance.

摘要

在时间数字判断中,观察者会系统性地低估脉冲数量。当刺激以较短的刺激间隔(ISI)呈现时,低估最为明显,且视觉的低估程度强于听觉和触觉。我们研究了多感官呈现是否会减少低估现象。向参与者呈现2至10个(组合的)听觉哔哔声、食指上的触觉轻拍以及不同ISI(20至320毫秒)下的视觉闪光。对于所有呈现模式,我们都发现了低估现象,除了少量脉冲情况。一项对照实验表明,后者是由于(认知)范围效应所致。综合各种条件来看,感官模式的表现顺序为触觉、听觉,最后是视觉。一般来说,多感官呈现比单感官呈现的表现更好。对于较大的ISI(160和320毫秒),我们发现多感官呈现模式的方差有减小趋势。对于较小的ISI(20和40毫秒),我们发现低估现象减少了,但多感官呈现模式的方差增加了。在讨论中,我们将这两个发现与预测多感官整合会减少方差的最大似然估计(MLE)模型联系起来。

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