Suppr超能文献

理解对于错误检测是否必要?言语产生中监控的基于冲突的观点。

Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production.

机构信息

Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Matthews Ave., Urbana, IL 61801, USA.

出版信息

Cogn Psychol. 2011 Aug;63(1):1-33. doi: 10.1016/j.cogpsych.2011.05.001. Epub 2011 Jun 7.

Abstract

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the double dissociation between comprehension and error-detection ability observed in the aphasic patients. We propose a new theory of speech-error detection which is instead based on the production process itself. The theory borrows from studies of forced-choice-response tasks the notion that error detection is accomplished by monitoring response conflict via a frontal brain structure, such as the anterior cingulate cortex. We adapt this idea to the two-step model of word production, and test the model-derived predictions on a sample of aphasic patients. Our results show a strong correlation between patients' error-detection ability and the model's characterization of their production skills, and no significant correlation between error detection and comprehension measures, thus supporting a production-based monitor, generally, and the implemented conflict-based monitor in particular. The successful application of the conflict-based theory to error-detection in linguistic, as well as non-linguistic domains points to a domain-general monitoring system.

摘要

尽管存在言语错误,言语交流仍是成功的,因为说话者能够检测(并纠正)自己的错误。言语错误检测的标准理论——感知环理论,假定理解系统会监测产出的错误。然而,这种基于理解的监测器无法解释在失语症患者中观察到的理解和错误检测能力之间的双重分离现象。我们提出了一种新的言语错误检测理论,该理论是基于产生过程本身的。该理论借鉴了强制选择反应任务的研究成果,提出错误检测是通过监测前脑结构(如前扣带回皮质)中的反应冲突来实现的。我们将这个想法应用于单词产生的两步模型,并在一组失语症患者样本上测试模型的预测。我们的结果显示,患者的错误检测能力与模型对其产生技能的描述之间存在很强的相关性,而错误检测与理解测量之间没有显著的相关性,因此支持基于产生的监测器,特别是基于冲突的监测器。基于冲突的理论在语言和非语言领域的错误检测中的成功应用表明存在一种通用的监测系统。

相似文献

3
Phonological errors in aphasic naming: comprehension, monitoring and lexicality.
Cortex. 1995 Jun;31(2):209-37. doi: 10.1016/s0010-9452(13)80360-7.

引用本文的文献

5
Cortico-Cerebellar Monitoring of Speech Sequence Production.言语序列产生的皮质-小脑监测
Neurobiol Lang (Camb). 2024 Aug 15;5(3):701-721. doi: 10.1162/nol_a_00113. eCollection 2024.
6
Inner speech in the daily lives of people with aphasia.失语症患者日常生活中的内心言语。
Front Psychol. 2024 Mar 21;15:1335425. doi: 10.3389/fpsyg.2024.1335425. eCollection 2024.
7
Neurocomputational modeling of speech motor development.言语运动发育的神经计算建模。
J Child Lang. 2023 Nov;50(6):1318-1335. doi: 10.1017/S0305000923000260. Epub 2023 Jun 20.
8
Predictive Coding and Internal Error Correction in Speech Production.言语产生中的预测编码与内部错误校正
Neurobiol Lang (Camb). 2023 Mar 8;4(1):81-119. doi: 10.1162/nol_a_00088. eCollection 2023.

本文引用的文献

4
Decision processes in human performance monitoring.人类绩效监测中的决策过程。
J Neurosci. 2010 Nov 17;30(46):15643-53. doi: 10.1523/JNEUROSCI.1899-10.2010.
5
Models of errors of omission in aphasic naming.失语症命名错误的模型。
Cogn Neuropsychol. 2004 Mar 1;21(2):125-45. doi: 10.1080/02643290342000320.
9
General-purpose monitoring during speech production.言语产生时的通用监测。
J Cogn Neurosci. 2011 Jun;23(6):1419-36. doi: 10.1162/jocn.2010.21467. Epub 2010 Mar 29.
10

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验