title: Neural decoding of spoken vowels from human sensory-motor cortex with high-density electrocorticography.
abstract: We present the first demonstration of single-trial neural decoding of vowel acoustic features during speech production with high performance. The ability to predict trial-by-trial fluctuations in speech production was facilitated by using high-density, large-area electrocorticography (ECoG) combined with an adaptive principal components regression. In experiments from two human neurosurgical patients with a high-density 256-channel ECoG grid implanted over speech cortices, we demonstrate that as much as 81% of the acoustic variability across vowels could be accurately predicted from the spatial patterns of neural activity during speech production. These results demonstrate continuous, single-trial decoding of vowel acoustics.
authors.forename: Kristofer E
authors.initials: KE
authors.lastname: Bouchard
authors.forename: Edward F
authors.initials: EF
authors.lastname: Chang
mesh_terms: D004569:Electroencephalography / Q000379:methods; D065818:Gamma Rhythm; D006801:Humans; D066191:Sensorimotor Cortex / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013060:Speech / Q000502:physiology*