Decoding spectrotemporal features of overt and covert speech from the human cortex

Stéphanie Martin, Peter Brunner, Chris Holdgraf, Hans Jochen Heinze, Nathan E. Crone, Jochem Rieger, Gerwin Schalk, Robert T. Knight, Brian N. Pasley

Research output: Contribution to journalArticlepeer-review

Abstract

Auditory perception and auditory imagery have been shown to activate overlapping brain regions. We hypothesized that these phenomena also share a common underlying neural representation. To assess this, we used electrocorticography intracranial recordings from epileptic patients performing an out loud or a silent reading task. In these tasks, short stories scrolled across a video screen in two conditions: subjects read the same stories both aloud (overt) and silently (covert). In a control condition the subject remained in a resting state. We first built a high gamma (70-150 Hz) neural decoding model to reconstruct spectrotemporal auditory features of self-generated overt speech. We then evaluated whether this same model could reconstruct auditory speech features in the covert speech condition. Two speech models were tested: a spectrogram and a modulation-based feature space. For the overt condition, reconstruction accuracy was evaluated as the correlation between original and predicted speech features, and was significant in each subject (p < 10-5; paired two-sample t-test). For the covert speech condition, dynamic time warping was first used to realign the covert speech reconstruction with the corresponding original speech from the overt condition. Reconstruction accuracy was then evaluated as the correlation between original and reconstructed speech features. Covert reconstruction accuracy was compared to the accuracy obtained from reconstructions in the baseline control condition. Reconstruction accuracy for the covert condition was significantly better than for the control condition (p < 0.005; paired two-sample t-test). The superior temporal gyrus, pre- and post-central gyrus provided the highest reconstruction information. The relationship between overt and covert speech reconstruction depended on anatomy. These results provide evidence that auditory representations of covert speech can be reconstructed from models that are built from an overt speech data set, supporting a partially shared neural substrate.

Original languageEnglish (US)
Article number14
JournalFrontiers in Neuroengineering
Volume7
Issue numberMAY
DOIs
StatePublished - May 27 2014

Keywords

  • Covert speech
  • Decoding model
  • Electrocorticography
  • Pattern recognition
  • Speech production

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biophysics
  • Biomedical Engineering

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