Western University, Department of Psychology, Brain & Mind Institute, London, ON, Canada; Northwestern University, Department of Psychology, Evanston, IL, USA.
Northwestern University, Department of Psychology, Evanston, IL, USA.
Cortex. 2019 Jun;115:56-71. doi: 10.1016/j.cortex.2019.01.013. Epub 2019 Jan 28.
Statistical learning, the process of extracting regularities from the environment, plays an essential role in many aspects of cognition, including speech segmentation and language acquisition. A key component of statistical learning in a linguistic context is the perceptual binding of adjacent individual units (e.g., syllables) into integrated composites (e.g., multisyllabic words). A second, conceptually dissociable component of statistical learning is the memory storage of these integrated representations. Here we examine whether these two dissociable components of statistical learning are differentially impacted by top-down, voluntary attentional resources. Learners' attention was either focused towards or diverted from a speech stream made up of repeating nonsense words. Building on our previous findings, we quantified the online perceptual binding of individual syllables into component words using an EEG-based neural entrainment measure. Following exposure, statistical learning was assessed using offline tests, sensitive to both perceptual binding and memory storage. Neural measures verified that our manipulation of selective attention successfully reduced limited-capacity resources to the speech stream. Diverting attention away from the speech stream did not alter neural entrainment to the component words or post-exposure familiarity ratings, but did impact performance on an indirect reaction-time based memory test. We conclude that theoretically dissociable components of statistically learning are differentially impacted by attention and top-down processing resources. A reduction in attention to the speech stream may impede memory storage of the component words. In contrast, the moment-by-moment perceptual binding of speech regularities can occur even while learners' attention is focused on a demanding concurrent task, and we found no evidence that selective attention modulates this process. These results suggest that learners can acquire basic statistical properties of language without directly focusing on the speech input, potentially opening up previously overlooked opportunities for language learning, particularly in adult learners.
统计学习是从环境中提取规律的过程，在认知的许多方面都起着至关重要的作用，包括语音分割和语言习得。在语言环境中，统计学习的一个关键组成部分是将相邻的单个单元（例如音节）感知绑定为集成的组合（例如多音节词）。统计学习的第二个概念上可分离的组成部分是这些集成表示的记忆存储。在这里，我们研究这两个可分离的统计学习成分是否受到自上而下的自愿注意资源的不同影响。学习者的注意力要么集中在由重复的无意义单词组成的语音流上，要么分散在该语音流上。基于我们之前的发现，我们使用基于 EEG 的神经同步测量来量化单个音节在线感知绑定到组成单词的情况。在暴露之后，使用对感知绑定和记忆存储均敏感的离线测试来评估统计学习。神经测量验证了我们对选择性注意的操纵成功地减少了语音流的有限容量资源。将注意力从语音流上转移开不会改变对组成单词的神经同步或暴露后熟悉度评分，但会影响基于间接反应时间的记忆测试的表现。我们得出的结论是，从理论上可分离的统计学习成分受到注意力和自上而下处理资源的不同影响。对语音流的注意力减少可能会阻碍对组成单词的记忆存储。相比之下，即使学习者的注意力集中在一项要求很高的并发任务上，语音规则的逐点感知绑定也可以发生，我们没有发现选择性注意会调节这一过程的证据。这些结果表明，学习者可以在不直接关注语音输入的情况下获得语言的基本统计属性，这可能为语言学习开辟了以前被忽视的机会，尤其是在成年学习者中。
