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

TitleDecoding spectrotemporal features of overt and covert speech from the human cortex.
Publication TypeJournal Article
Year of Publication2014
AuthorsMartin, S, Brunner, P, Holdgraf, C, Heinze, H-J, Crone, NE, Rieger, J, Schalk, G, Knight, RT, Pasley, BN
JournalFront Neuroeng
Date Published05/2014

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

Alternate JournalFront Neuroeng
PubMed ID24904404
PubMed Central IDPMC4034498
Grant ListP41 EB018783 / EB / NIBIB NIH HHS / United States
R01 EB000856 / EB / NIBIB NIH HHS / United States
R37 NS021135 / NS / NINDS NIH HHS / United States
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