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Interpreting the Mismatch Negativity

机译:解释不匹配的消极性

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The widely accepted “memory-mismatch” interpretation of the mismatch negativity (MMN) event-related brain potential (ERP) suggests that an MMN is elicited when an acoustic event deviates from a memory record describing the immediate history of the sound sequence. The first variant of the memory-mismatch theory suggested that the memory underlying MMN generation was a strong auditory sensory memory trace, which encoded the repetitive standard sound. This “trace-mismatch” explanation of MMN has been primarily based on results obtained in the auditory oddball paradigm. However, in recent years, MMN has been observed in stimulus paradigms containing no frequently repeating sound. We now suggest a different variant of the memory-mismatch interpretation of MMN in order to provide a unified explanation of all MMN phenomena. The regularity-violation explanation of MMN assumes that the memory records retaining the history of auditory stimulation are regularity representations. These representations encode rules extracted from the regular intersound relationships, which are mapped to the concrete sound sequence by finely detailed auditory sensory information. Auditory events are compared with temporally aligned predictions drawn from the regularity representations (predictive models) and the observable MMN response reflects a process updating the representations of those detected regularities whose prediction was mismatched by the acoustic input. It is further suggested that the auditory deviance detection system serves to organize sound in the brain: The predictive models maintained by the MMN-generating process provide the basis of temporal grouping, a crucial step in the formation of auditory objects.
机译:广泛接受的“记忆失匹配”解释不匹配消极性(MMN)与事件相关的大脑电位(ERP)建议当声学事件偏离描述声音序列的立即历史的存储器记录时,引发MMN。内存失配理论的第一变体表明,内部MMN生成的内存是一个强烈的听觉感官存储器迹线,其编码重复标准声音。这种“True-Mismatch”的MMN解释主要基于在听觉奇怪范式范式中获得的结果。然而,近年来,在不频繁地重复声音的刺激范例中观察到MMN。我们现在建议了MMN的内存不匹配解释的不同变体,以便提供所有MMN现象的统一解释。 MMN的规律性违规说明假设保留听觉刺激历史的记忆记录是规律性表示。这些表示编码从常规分部关系中提取的规则,通过精细详细的听觉感官信息映射到具体声音序列。将检测事件与从规则性表示(预测模型)汲取的时间对齐预测进行比较,并且可观察MMN响应反映了更新的过程更新其预测由声学输入不匹配的那些检测到的规则的表示。进一步建议,听觉偏差检测系统用于组织大脑中的声音:由MMN生成过程维持的预测模型提供了时间分组的基础,在形成听觉物体的关键步骤。

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