Decoding of articulatory gestures during word production using speech motor and premotor cortical activity

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Brain-machine interfaces that directly translate attempted speech from the speech motor areas could change the lives of people with complete paralysis. However, it remains uncertain exactly how speech production is encoded in cortex. Improving this understanding could greatly improve brain-machine interface design. Specifically, it is not clear to what extent the different levels of speech production (phonemes, or speech sounds, and articulatory gestures, which describe the movements of the articulator muscles) are represented in the motor cortex. Using electrocorticographic (ECoG) electrodes on the cortical surface, we recorded neural activity from speech motor and premotor areas during speech production. We decoded both gestures and phonemes using the neural signals. Overall classification accuracy was higher for gestures than phonemes. In particular, gestures were better represented in the primary sensorimotor cortices, while phonemes were better represented in more anterior areas.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5339-5342
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period8/25/158/29/15

Funding

ASJC Scopus subject areas

  • Signal Processing
  • Health Informatics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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