Publications

Chunking of phonological units in speech sequencing

Published in Brain and Language, 2019

Abstract: Efficient speech communication requires rapid, fluent production of phoneme sequences. To achieve this, our brains store frequently occurring subsequences as cohesive "chunks" that reduce phonological working memory load and improve motor performance. The current study used a motor-sequence learning paradigm in which the generalization of two performance gains (utterance duration and errors) from practicing novel phoneme sequences was used to infer the nature of these speech chunks. We found that performance improvements in duration from practicing syllables with non-native consonant clusters largely generalized to new syllables that contained those clusters. Practicing the whole syllable, however, resulted in larger performance gains in error rates compared to practicing just the consonant clusters. Collectively, these findings are consistent with theories of speech production that posit the consonant cluster as a fundamental unit of phonological working memory and speech sequencing as well as those positing the syllable as a fundamental unit of motor programming.

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Comparison of steady-state visual and somatosensory evoked potentials for brain-computer interface control

Published in 2014 36th Annual Internal Conference of the IEEE in Engineering in Medicine and Biology Society, 2014

Abstract: Many proposed EEG-based brain-computer interfaces (BCIs) make use of visual stimuli to elicit steady-state visual evoked potentials (SSVEP), the frequency of which can be mapped to a computer input. However, such a control scheme can be ineffective if a user has no motor control over their eyes and cannot direct their gaze towards a flashing stimulus to generate such a signal. Tactile-based methods, such as somatosensory steady-state evoked potentials (SSSEP), are a potentially attractive alternative in these scenarios. Here, we compare the neural signals elicited by SSSEP to those elicited by SSVEP in naiive BCI users towards evaluating the feasibility of SSSEP-based control of an EEG BCI.

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