Publications

Abstract

Hearing one’s own voice is critical for fluent speech production as it allows for the detection and correction of vocalization errors in real time. This behavior known as the auditory feedback control of speech is impaired in various neurological disorders ranging from stuttering to aphasia; however, the underlying neural mechanisms are still poorly understood. Computational models of speech motor control suggest that, during speech production, the brain uses an efference copy of the motor command to generate an internal estimate of the speech output. When actual feedback differs from this internal estimate, an error signal is generated to correct the internal estimate and update necessary motor commands to produce intended speech. We were able to localize the auditory error signal using electrocorticographic recordings from neurosurgical participants during a delayed auditory feedback (DAF) paradigm. In this task, participants hear their voice with a time delay as they produced words and sentences (similar to an echo on a conference call), which is well known to disrupt fluency by causing slow and stutter-like speech in humans. We observed a significant response enhancement in auditory cortex that scaled with the duration of feedback delay, indicating an auditory speech error signal. Immediately following auditory cortex, dorsal precentral gyrus (dPreCG), a region that has not been implicated in auditory feedback processing before, exhibited a markedly similar response enhancement, suggesting a tight coupling between the 2 regions. Critically, response enhancement in dPreCG occurred only during articulation of long utterances due to a continuous mismatch between produced speech and reafferent feedback. These results suggest that dPreCG plays an essential role in processing auditory error signals during speech production to maintain fluency.

Abstract

Although humans can understand speech using the auditory modality alone, in noisy environments visual speech information from the talker’s mouth can rescue otherwise unintelligible auditory speech. To investigate the neural substrates of multisensory speech perception, we compared neural activity from the human superior temporal gyrus (STG) in two datasets. One dataset consisted of direct neural recordings (electrocorticography, ECoG) from surface electrodes implanted in epilepsy patients (this dataset has been previously published). The second dataset consisted of indirect measures of neural activity using blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI). Both ECoG and fMRI participants viewed the same clear and noisy audiovisual speech stimuli and performed the same speech recognition task. Both techniques demonstrated a sharp functional boundary in the STG, spatially coincident with an anatomical boundary defined by the posterior edge of Heschl’s gyrus. Cortex on the anterior side of the boundary responded more strongly to clear audiovisual speech than to noisy audiovisual speech while cortex on the posterior side of the boundary did not. For both ECoG and fMRI measurements, the transition between the functionally distinct regions happened within 10 mm of anterior-to-posterior distance along the STG. We relate this boundary to the multisensory neural code underlying speech perception and propose that it represents an important functional division within the human speech perception network.

Abstract

Human cognition is traditionally studied in experimental conditions wherein confounding complexities of the natural environment are intentionally eliminated. Thus, it remains unknown how a brain region involved in a particular experimental condition is engaged in natural conditions. Here we use electrocorticography to address this uncertainty in three participants implanted with intracranial electrodes and identify activations of neuronal populations within the intraparietal sulcus region during an experimental arithmetic condition. In a subsequent analysis, we report that the same intraparietal sulcus neural populations are activated when participants, engaged in social conversations, refer to objects with numerical content. Our prototype approach provides a means for both exploring human brain dynamics as they unfold in complex social settings and reconstructing natural experiences from recorded brain signals.