Recent evidence suggests that language processing is well-adapted to noise in the input (e.g., spelling or speech errors, misreading or mishearing) and that comprehenders readily correct the input via rational inference over possible intended sentences given probable noise corruptions. In the current study, we probed the processing of noisy linguistic input, asking whether well-studied ERP components may serve as useful indices of this inferential process. In particular, we examined sentences where semantic violations could be attributed to noise—for example, in “The storyteller could turn any incident into an amusing antidote”, where the implausible word “antidote” is orthographically and phonologically close to the intended “anecdote”. We found that the processing of such sentences—where the probability that the message was corrupted by noise exceeds the probability that it was produced intentionally and perceived accurately—was associated with a reduced (less negative) N400 effect and an increased P600 effect, compared to semantic violations which are unlikely to be attributed to noise (“The storyteller could turn any incident into an amusing hearse”). Further, the magnitudes of these ERP effects were correlated with the probability that the comprehender retrieved a plausible alternative. This work thus adds to the growing body of literature that suggests that many aspects of language processing are optimized for dealing with noise in the input, and opens the door to electrophysiologic investigations of the computations that support the processing of imperfect input.

最近的证据表明，语言处理很好地适应输入中的噪声（例如，拼写或语音错误、误读或误听），并且理解者很容易通过对可能的预期句子的理性推理来纠正输入，因为可能存在噪声破坏。在当前的研究中，我们探讨了嘈杂语言输入的处理，询问经过充分研究的 ERP 组件是否可以作为这一推理过程的有用指标。特别是，我们检查了语义违规可归因于噪音的句子——例如，在“讲故事的人可以把任何事件变成有趣的解药””，其中“解毒剂”这个令人难以置信的词在拼写和语音上都接近于预期的“轶事”。我们发现处理这些句子——其中信息被噪音破坏的概率超过了有意产生和准确感知的概率——与减少的（不太消极的）N400 效应和增加的 P600 效应相关，与不太可能归因于噪音的语义违规（“讲故事的人可以将任何事件变成有趣的灵车”）。此外，这些 ERP 效应的大小与理解者检索到一个合理的替代方案的概率相关。因此，这项工作增加了越来越多的文献，这些文献表明语言处理的许多方面都经过优化以处理输入中的噪声，并为支持处理不完美输入的计算的电生理研究打开了大门。