[PS-1.3] Babies and beeps - relating infants' sensitivity to rhythm to their speech segmentation ability

Snijders, T. M. 1, 2 , Benders, T. 3, 4 , Junge, C. 5 , Haegens, S. 2, 6 & Fikkert, P. 7

1 Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
2 Donders Institute for Brain, Cognition, and Behaviour; Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
3 Department of Linguistics, Macquarie University, Sydney, Australia
4 ARC Centre of Excellence in Cognition and its Disorders
5 Department of Social and Behavioral Sciences, Utrecht University, the Netherlands
6 Columbia University College of Physicians and Surgeons, New York, USA
7 Centre for Language Studies, Radboud University, Nijmegen, the Netherlands

Rhythm is an important early cue to speech segmentation (e.g. Johnson & Jusczyk, 2001). A proposed underlying neural mechanism for this is neuronal entrainment, i.e., the resonation of brain rhythms with rhythms in auditory input. Neuronal entrainment is thought to facilitate predictive processing of input, including (stressed syllables in) speech (ZionGolumbic et al 2012).

The present study investigates whether individual differences in neuronal entrainment at 7.5 months are predictive of word segmentation ability at 9 months. Infants' entrainment at 7.5 months was assessed in an EEG experiment (current N=54), in which infants listened to rhythmically regular and irregular trains of complex tones (beeps) from which 9% of beeps were omitted. It is expected that infants will predict omitted beeps, evidenced by a clear ERP, in the regular but not the irregular beep trains. The same infants' word segmentation ability at 9 months was tested in a headturn-preference procedure. Individual differences in neuronal entrainment, and the predictive ERP response at 7.5 months will be related to speech segmentation ability at 9 months. Results will be presented at the meeting. We discuss the implications of entrainment and predictive auditory processing in infants for language learning in general, and word segmentation in particular.