The role of prediction in language development: perspectives from neuroscience

许多认知科学家认为，儿童和成人都能够预测句子中的下一个单词是什么，从而使他们在对话中处理和反应得更快。这一观察结果影响了认知科学中的许多关键理论。其中一个理论是基于错误的语言习得理论。它表明，人们总是将自己的预测与所听到的进行比较，并利用任何错误来更新自己的知识，使预测越来越准确。这个理论非常有影响力，因为它可以解释一些令人费解的语言现象，比如孩子们是如何学会自己说出“mouse”的正确复数（“mice”而不是“mouse”）的。然而，令人惊讶的是，几乎没有直接证据表明听众的错误预测实际上在语言学习中起作用。我的研究旨在为这种机制的存在提供具体的证据，并通过观察它的作用，更好地理解它是如何以及为什么起作用的。我的博士报告了三组研究，通过开发新的实验方法来为这一理论寻找证据。虽然我们发现了一些对基于错误的学习的有力支持，但其他结果对这一理论提出的机制的本质产生了怀疑。例如，当我们评估成年人是否表现出主要惊讶（重复令人惊讶的结构的可能性增加，这通常被视为基于错误的学习理论的证据）时，我们发现这种影响只出现在某些结构上，这表明这些机制可能不是在所有情况下都起作用。我们还使用神经成像技术来测量成年人在听令人惊讶或可预测的句子时的脑电活动。这项研究表明，在听不可预测的句子时，处理成本更高，但没有证据表明这种困难与预测失败有关。目前的奖学金将使我能够巩固这些成果并扩大其影响。我计划开展三套活动来实现这一目标：吸引新的受众，建立学术影响，培养与幼儿进行神经语言学研究的技能。公众参与：该奖学金将使我能够利用ESRC LuCiD中心广泛的研究传播网络。利物浦大学，曼彻斯特大学和兰开斯特大学之间的合作不仅进行了语言习得方面的最新研究，而且还提供了关于如何最好地促进学龄前儿童语言发展的循证建议，并与广泛的非学术受益人直接联系。学术影响：虽然前两组研究已经完成并在会议上发表，但第三组数据集需要进一步的工作才能使我能够将其作为高影响力的期刊文章发表。这个数据集来自我们的神经成像工作，对基于错误的理论有重要的意义，因为它质疑是主动预测还是其他一些处理困难驱动了学习。然而，为这项研究开发的新方法意味着我们需要在原始地点，即加州大学戴维斯分校，进行进一步的分析和一些有限的额外数据收集。通过最大限度地发挥这项研究的潜力，我将为我随后的职业规划奠定重要的基础。发展技能：我建议的导师Perrine Brusini博士是幼儿神经语言学研究方面的专家，她将为这一人群提供必要的软件和方法方面的培训。在研究结束时，我将能够在导师的指导下进行我自己的婴儿神经影像学研究。这不仅将拓宽我的技能，而且还将为ESRC新研究者拨款提案提供试点数据，该提案旨在调查预测编码在婴儿语言学习中的作用——这项工作将使我们更好地理解语言习得的过程。

Many cognitive scientists believe that children and adults are able to predict what the next word in a sentence will be, allowing them to process and respond more rapidly in conversation. This observation has come to influence many key theories in cognitive science. One such theory is the error-based theory of language acquisition. It suggests that people always compare their predictions to what they hear, and use any mistakes to update their knowledge, making predictions more and more accurate. This theory is highly influential as it can explain puzzling linguistic phenomena such as how children learn to produce the correct plural of 'mouse' ('mice' rather than 'mouses') on their own. However, there is surprisingly little direct evidence that listeners' incorrect predictions actually play a role in language learning. My research aims to provide concrete evidence for the existence of such a mechanism, and by observing it in action, better understand how and why it works.My PhD reported three sets of studies seeking evidence for this theory by developing new experimental approaches. While we found some strong support for error-based learning, other results cast doubt on the nature of the mechanism proposed by this theory. For example, when we assessed whether adults show prime surprisal (increased likelihood of repeating surprising structures, which is often taken as evidence for the error-based learning theory) we found that this effect only appears with certain structures, suggesting that these mechanisms might not operate under all circumstances. We also used neuroimaging to measure the brain's electrical activity while adults listened to surprising or predictable sentences. This study showed that there was a greater processing cost while listening to unpredictable sentences, but no evidence that this difficulty is related to failed predictions.The current fellowship would allow me to consolidate these results and increase their impact. I plan to carry out three sets of activities to achieve this: engaging with new audiences, building academic impact, and developing the skills to carry out neurolinguistics research with young children.Public engagement: The fellowship will allow me to utilise the ESRC LuCiD Centre's extensive research dissemination network. This collaboration between the Universities of Liverpool, Manchester and Lancaster not only conducts state-of-the art research on language acquisition, but also provides evidence-based advice about how best to foster language development in preschool children, and has direct links to a wide range of non-academic beneficiaries.Academic impact: While the first two sets of studies have already been written up and presented at conferences, the third dataset requires further work to allow me to publish it as a high-impact journal article. This dataset, resulting from our neuroimaging work, has important implications for error-based theory, as it questions whether active predictions or some other processing difficulty drives learning. However, the novel methods developed for this study mean that we need to carry out further analysis and some limited additional data collection at the original site, which was the University of California, Davis. By maximising the potential of this study, I will lay crucial groundwork for my subsequent career plans. Developing skills: My proposed mentor Dr Perrine Brusini is an expert in neurolinguistic research with young infants and will provide training in the software and methods necessary to work with this population. By the end of the fellowship I will be in a position to carry out my own infant neuroimaging study, under my mentors supervision. This will not only broaden my skillset but also provide pilot data for an ESRC New Investigator grant proposal aimed at investigating the role of predictive coding in infant language learning - work that will allow us to better understand the processes that enable language acquisition.