Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Science

Program

Psychology

Supervisor

Joanisse, Marc F.

Abstract

Statistical learning is proposed as a mechanism for discovering structural patterns in speech through incidental exposure. However, studies have largely relied on assessing explicit memory after learning has occurred, which does not capture the time course and process of statistical learning per se. To better understand the dynamics of statistical learning, we assessed 8- to 12-year-old children using an EEG measure of learning, which captures changes in neural entrainment to words embedded in a continuous artificial language. Statistical learning was assessed post-learning using implicit and explicit behavioural tests. The neural entrainment results demonstrated rapid learning of word-level information, while post-learning tasks demonstrated syllable prediction and recognition of the trisyllabic words. These results replicate findings in adults and hint to the possibility that children and adults use similar language learning mechanisms. Importantly, this is the first study to demonstrate that neural entrainment is a sensitive indicator of statistical learning in children.

Summary for Lay Audience

The ability to learn language relies on our sensitivity to structural patterns in speech. Statistical learning is proposed as a mechanism for discovering these patterns through incidental exposure. This means that language is implicitly learned and does not require explicit learning strategies. Statistical learning has largely been assessed through a single explicit memory task and has been assessed only after learning has occurred. This approach does not capture the time course and process of statistical learning on its own. Additionally, while prior studies have demonstrated that children do as well as adults on statistical learning tasks, we do not know the degree of statistical learning in children. To better understand the dynamics of statistical learning, we assessed the degree of learning to a six-minute artificial language in 8- to 12-year-old children. The artificial language was made up of pseudowords and knowledge of the language was tested via implicit and explicit post-learning behavioural tests. We also assessed the time course of learning by using a direct electroencephalography (EEG) measure, which records electrical potentials in the brain created by external stimuli. The EEG measure captured changes in neural entrainment to words embedded in a continuous artificial language stream. Neural entrainment is an especially useful measure of EEG as it determines whether brainwave frequencies are temporally synchronizing to the external stimuli. The neural entrainment results demonstrated rapid implicit learning of word-level information, while post-learning behavioural tasks demonstrated significant syllable prediction and recognition of the trisyllabic words. Importantly, this is the first study to demonstrate that neural entrainment is a sensitive indicator of statistical learning in children. These results replicate previous findings in adults and hint to the possibility that children and adults use similar language learning mechanisms. Our results also demonstrate that there are age-related differences in statistical learning that may be due to the development of attention.

Download

Share

COinS