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Statistical segmentation of streams of syllables: a pilot EEG study

Leidy J. Castro-Meneses1*, Paul Sowman1 and Blake W. Johnson1
  • 1 Macquarie University, Department of Cognitive Science, Australia

Previous studies have claimed that before infants learn prosodic patterns (e.g., stress, pitch) our brain uses statistical mechanisms that support word segmentation by tracing the transitional probabilities of syllables. We were interested in exploring whether word extraction is affected when word components are separated by silence gaps. Thus, although the word syllables are adjacent, they may be processed individually and not grouping into a word-like unit. It was hypothesised that word segmentation would be highly disrupted when silence gaps are either longer than the syllable length or have unsystematic lengths. We record electrophysiological brain signals from 8 Native English speakers while they learned 8 artificial languages presented randomly. Each artificial language consisted of nine trisyllabic pseudowords (made up of consonant + vowel= cv + cv + cv). After that, learning of each language was assessed in a two alternative forced choice paradigm.
The analysis of the event-related potentials (ERPs) showed the N400 component, which was enhanced for word onsets in those languages that were better recognised behaviourally. The behavioural analysis showed that participants were able to learn the words of those artificial languages when the silence gaps were shorter than a syllable length. When the gaps where longer or mixed, the responses do not differ from chance. These findings show that the brain is able to learn/group temporary non-adjacent elements. A useful learning mechanism when infants are learning for example phrases. However, further research will be required to extend these results.

Acknowledgements

This research was funded by the Australian Research Council Centre of Excellence in Cognition and its Disorders (CE110001021) http://www.ccd.edu.au.

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Keywords: statistical learning, word segmentation, artificial language, EEG, Transitional probabilities

Conference: ACNS-2012 Australasian Cognitive Neuroscience Conference, Brisbane, Australia, 29 Nov - 2 Dec, 2012.

Presentation Type: Poster Presentation

Topic: Language

Citation: Castro-Meneses LJ, Sowman P and Johnson BW (2012). Statistical segmentation of streams of syllables: a pilot EEG study. Conference Abstract: ACNS-2012 Australasian Cognitive Neuroscience Conference. doi: 10.3389/conf.fnhum.2012.208.00129

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Received: 13 Oct 2012; Published Online: 17 Nov 2012.

* Correspondence: Mrs. Leidy J Castro-Meneses, Macquarie University, Department of Cognitive Science, Sydney, Australia, l.castro-meneses@westernsydney.edu.au