Detecting changes in dynamic and complex acoustic environments
Detecting changes in dynamic and complex acoustic environments
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DOI：
10.7554/elife.24910.001
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发表时间：
2017-03-06
期刊：
影响因子：
7.7
通讯作者：
Englitz, Bernhard
中科院分区：
文献类型：
--
作者：
Boubenec, Yves;Lawlor, Jennifer;Englitz, Bernhard
自然声音，如风或雨，以其成分的统计出现为特征。尽管它们很复杂，但监听者很容易检测到这些上下文中的变化。我们在这里使用心理物理学、脑电波和建模的组合来解决统计决策的神经基础。在基于质地的变化检测范式中，随着变化前暴露时间的延长，人类的表现和反应时间得到了改善，这与基线统计数据估计的改善是一致的。在头皮中央顶端位置发现了变化锁定和决策相关的脑电反应，其斜率取决于变化的大小，与感觉证据的积累一致。该电位的幅度随着改变前暴露的持续时间而扩大，这表明了一个依赖于时间的决定阈值。听觉皮质相关电位对这种变化没有反应。一个双时间尺度的统计估计模型考虑了受试者的表现。此外，决策增强的听觉皮质模型考虑了性能和反应时间，这表明初级皮质表征需要很少的后处理就能在复杂的声学环境中检测到变化。
Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centroparietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments.