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违规检测与听觉流分离中的预测性规律表征:从概念模型到计算模型

Predictive regularity representations in violation detection and auditory stream segregation: from conceptual to computational models.

作者信息

Schröger Erich, Bendixen Alexandra, Denham Susan L, Mill Robert W, Bőhm Tamás M, Winkler István

机构信息

Institute of Psychology, University of Leipzig, Leipzig, Germany,

出版信息

Brain Topogr. 2014 Jul;27(4):565-77. doi: 10.1007/s10548-013-0334-6. Epub 2013 Nov 24.

DOI:10.1007/s10548-013-0334-6
PMID:24271978
Abstract

Predictive accounts of perception have received increasing attention in the past 20 years. Detecting violations of auditory regularities, as reflected by the Mismatch Negativity (MMN) auditory event-related potential, is amongst the phenomena seamlessly fitting this approach. Largely based on the MMN literature, we propose a psychological conceptual framework called the Auditory Event Representation System (AERS), which is based on the assumption that auditory regularity violation detection and the formation of auditory perceptual objects are based on the same predictive regularity representations. Based on this notion, a computational model of auditory stream segregation, called CHAINS, has been developed. In CHAINS, the auditory sensory event representation of each incoming sound is considered for being the continuation of likely combinations of the preceding sounds in the sequence, thus providing alternative interpretations of the auditory input. Detecting repeating patterns allows predicting upcoming sound events, thus providing a test and potential support for the corresponding interpretation. Alternative interpretations continuously compete for perceptual dominance. In this paper, we briefly describe AERS and deduce some general constraints from this conceptual model. We then go on to illustrate how these constraints are computationally specified in CHAINS.

摘要

在过去20年里,预测性感知理论受到了越来越多的关注。通过失匹配负波(MMN)听觉事件相关电位反映出的对听觉规律的违反检测,是与这种方法无缝契合的现象之一。主要基于MMN相关文献,我们提出了一个名为听觉事件表征系统(AERS)的心理学概念框架,该框架基于这样一种假设,即听觉规律违反检测和听觉感知对象的形成基于相同的预测性规律表征。基于这一概念,已经开发了一种名为CHAINS的听觉流分离计算模型。在CHAINS中,每个传入声音的听觉感觉事件表征被视为序列中前序声音可能组合的延续,从而为听觉输入提供了多种解释。检测重复模式可以预测即将到来的声音事件,从而为相应的解释提供检验和潜在支持。多种解释不断竞争感知主导地位。在本文中,我们简要描述了AERS,并从这个概念模型中推导出一些一般约束条件。然后我们继续说明这些约束条件在CHAINS中是如何通过计算来确定的。

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