The modulation of cognitive load on speech normalization: A neurophysiological perspective

IF 2.1 2区 心理学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Kaile Zhang, Gang Peng
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引用次数: 0

Abstract

Extrinsic normalization, wherein listeners utilize context cues to adapt to speech variability, is essential for maintaining perceptual constancy. In daily communication, distractions are ubiquitous, raising questions about the influence of cognitive load on this process, particularly at the cortical level. This study investigates how cognitive load modulates extrinsic normalization using electroencephalography (EEG). Native Cantonese speakers were asked to perceive Cantonese tones from multiple speakers with context cues in both single- and dual-task conditions. The secondary task did not hinder listeners’ normalization process at the behavioral level. However, EEG data revealed significant modulations of extrinsic normalization under cognitive load. Extrinsic normalization elicited P2, N400, and LFN, suggesting that extrinsic normalization encompasses multiple perceptual adjustments at stages of phonological processing, lexical retrieval, and decision-making. Cognitive load influenced extrinsic normalization at all these stages, as evidenced by smaller P2, larger N400, and larger LFN, highlighting the active and controlled nature of this process.
认知负荷对语音正常化的调节:神经生理学视角
外在归一化,即听者利用语境线索来适应言语的可变性,对于保持感知恒定是必不可少的。在日常交流中,干扰无处不在,这就提出了认知负荷对这一过程的影响的问题,特别是在皮层水平上。本研究利用脑电图(EEG)研究认知负荷如何调节外在归一化。在单任务和双任务条件下,要求以广东话为母语的人在语境提示下感知来自多个说话人的广东话声调。次要任务在行为层面上不影响听者的规范化过程。然而,脑电图数据显示认知负荷下的外在归一化显著调节。外在归一化诱发P2、N400和LFN,表明外在归一化包含语音加工、词汇检索和决策阶段的多重知觉调节。认知负荷影响了所有这些阶段的外在正常化,如较小的P2、较大的N400和较大的LFN所证明的那样,突出了这一过程的主动性和控制性。
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来源期刊
Brain and Language
Brain and Language 医学-神经科学
CiteScore
4.50
自引率
8.00%
发文量
82
审稿时长
20.5 weeks
期刊介绍: An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.
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