Human cortical sensorimotor network underlying feedback control of vocal pitch

Abstract

The control of vocalization is critically dependent on auditory feedback. Here, we determined the human peri-Sylvian speech network that mediates feedback control of pitch using direct cortical recordings. Subjects phonated while a real-time signal processor briefly perturbed their output pitch (speak condition). Subjects later heard the same recordings of their auditory feedback (listen condition). In posterior superior temporal gyrus, a proportion of sites had suppressed responses to normal feedback, whereas other spatially independent sites had enhanced responses to altered feedback. Behaviorally, speakers compensated for perturbations by changing their pitch. Single-trial analyses revealed that compensatory vocal changes were predicted by the magnitude of both auditory and subsequent ventral premotor responses to perturbations. Furthermore, sites whose responses to perturbation were enhanced in the speaking condition exhibited stronger correlations with behavior. This sensorimotor cortical network appears to underlie auditory feedback-based control of vocal pitch in humans.

Fig. 1.

Apparatus and behavior. (A) Diagram of the pitch perturbation apparatus. A DSP shifted the pitch of subjects’ vocalizations (red line) and delivered this auditory feedback (blue line) to subjects’ earphones. (B) Spectrogram (Upper) and pitch track (Lower) of an example trial with pitch perturbation applied. (C) Histogram of compensatory responses as a percentage of pitch shift. The green arrow denotes the trial shown in B.

Fig. 2.

Four ECoG channels from a single subject (GP35). (A) Location of the four electrodes on the cortical surface. (B and C) Spectrograms and high-γ line plots for each electrode in the speak (red) and listen (blue) conditions. Vertical lines represent speech onset in B and perturbation onset and offset in C.

Fig. 3.

Correlations between high-γ activity and compensation in a single subject (GP35). Asterisks denote statistical significance (*P < 0.05; **P < 0.01; ***P < 0.001). (A) Single-trial rasters of high-γ activity, ordered by descending compensation, for the four electrodes shown in Fig. 2. The vertical white line marks the time of peak compensation. (B) Per-trial correlations for the same four electrodes. Gray horizontal lines indicate the zero compensation level, with compensatory responses above and following responses below the line. (C) Spatial distribution of significantly correlated electrodes (circled) and SPRE electrodes (red; opacity denotes degree of SPRE). The white box contains electrodes labeled “temporal” and used in the analysis in D. (D) Mean SPRE correlated with Pearson's r for each electrode. The solid black line is the best-fit line to all temporal electrodes (P < 0.001). The dashed red line is the best-fit line to SPRE electrodes alone (P = 0.033).

Fig. 4.

Correlations between high-γ activity and compensation. (A and D) Per-subject correlation scores averaged across non-SPRE and SPRE temporal electrodes for the left- (A) and right- (D) hemisphere grids. Each linked pair of points represents data from a single subject. (B and E) Histogram of electrodes categorized by response properties for the left (B) and right (E) hemisphere. Error bars show SE. (C and F) Mean SPRE correlated with maximum Pearson's r for each electrode for the left (C) and right (F) hemisphere. Asterisks denote statistical significance as in Fig. 3, and the black and red lines are best-fit lines.

Fig. 5.

Spatial distribution of SPRE and SIS electrodes. Points were mapped from individual subject’s brains to an average surface; any electrodes that appear to be positioned in the sulci are the result of surface coregistration inaccuracies. Gyri are light gray; sulci are dark gray.