Both stream segregation and temporal integration are considered important for auditory scene analysis in the brain. Several previous studies have indicated that stream segregation may precede temporal integration when both processes are required. In the present study, we utilized mismatch negativity (MMN)-which reflects automatic change detection-to systematically estimate the threshold of the frequency difference at which stream segregation occurs prior to temporal integration when these functions occur together during a state of inattention. Electroencephalography (EEG) data were recorded from 22 healthy Japanese men presented with six blocks of alternating high pure tones (high tones) and low pure tones (low tones). Only high tones were omitted with 5% probability in all blocks. Our results indicated that stream segregation should cancel temporal integration of close sounds, as indicated by omission-MMN elicitation, when the frequency difference is 1000 Hz or larger.

中文翻译：

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由遗漏失配负性反映的流分离先于时间积分的频率差估计

流分离和时间整合都被认为对大脑中的听觉场景分析很重要。之前的几项研究表明，当需要这两个过程时，河流分离可能先于时间整合。在本研究中，我们利用失配负性 (MMN)——反映自动变化检测——来系统地估计当这些功能在注意力不集中的状态下一起发生时，在时间整合之前发生流分离的频率差的阈值。记录了 22 名健康日本男性的脑电图 (EEG) 数据，这些男性呈现六组交替的高纯音（高音）和低纯音（低音）。在所有块中仅以 5% 的概率省略了高音调。