Reconstructing Speech from Human Auditory Cortex

TLDR

The human auditory system’s extraction of perceptually relevant acoustic features of speech remains poorly understood. The study aims to determine which acoustic information in speech can be reconstructed from population neural activity recorded in nonprimary auditory cortex of the human superior temporal gyrus. The authors used intracranial recordings from this region to reconstruct acoustic information from population neural activity. They demonstrated that slow and intermediate temporal fluctuations (e.g., syllable rate) could be accurately reconstructed with a linear auditory spectrogram model, while fast fluctuations (syllable onsets/offsets) required a nonlinear temporal modulation energy representation, achieving highest accuracy for spectro‑temporal ranges critical to intelligibility and enabling word identification from single‑trial brain activity, thereby revealing neural encoding mechanisms of speech acoustic parameters in higher‑order auditory cortex.

Abstract

How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.