Learning and adaptation in speech production without a vocal tract

How is the complex audiomotor skill of speaking learned? To what extent does it depend on the specific characteristics of the vocal tract? Here, we developed a touchscreen-based speech synthesizer to examine learning of speech production independent of the vocal tract. Participants were trained to reproduce heard vowel targets by reaching to locations on the screen without visual feedback and receiving endpoint vowel sound auditory feedback that depended continuously on touch location. Participants demonstrated learning as evidenced by rapid increases in accuracy and consistency in the production of trained targets. This learning generalized to productions of novel vowel targets. Subsequent to learning, sensorimotor adaptation was observed in response to changes in the location-sound mapping. These findings suggest that participants learned adaptable sensorimotor maps allowing them to produce desired vowel sounds. These results have broad implications for understanding the acquisition of speech motor control.Published versio

Speech Production as State Feedback Control

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e.g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations – limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model

Sensorimotor adaptation of speech I: Compensation and adaptation

When motor actions (e.g., reaching with your hand) adapt to altered sensory feedback (e.g., viewing a shifted image of your hand through a prism), the phenomenon is called sensorimotor adaptation (SA). In the study reported here, SA was observed in speech. In two 2-hour experiments (adaptation and control), participants whispered a variety of CVC words. For those words containing the vowel /E/, participants heard auditory feedback of their whispering. A DSPbased vocoder processed the participants' auditory feedback in real time, allowing the formant frequencies of participants' auditory speech feedback to be shifted. In the adaptation experiment, formants were shifted along one edge of the vowel triangle. For half the participants, formants were shifted so participants heard /A/ when they produced /E/; for the other half, the shift made participants hear /i/ when they produced /E/. During the adaptation experiment, participants altered their production of /E/ to compensate for the altered feedback, and these production changes were retained when participants whispered with auditory feedback blocked by masking noise. In a control experiment, in which the formants were not shifted, participants' production changes were small and inconsistent. Participants exhibited a range of adaptations in response to the altered feedback, with some participants adapting almost completely, and other participants showing very little or no adaptation

Abnormal Speech Motor Control in Individuals with 16p11.2 Deletions.

Speech and motor deficits are highly prevalent (>70%) in individuals with the 600 kb BP4-BP5 16p11.2 deletion; however, the mechanisms that drive these deficits are unclear, limiting our ability to target interventions and advance treatment. This study examined fundamental aspects of speech motor control in participants with the 16p11.2 deletion. To assess capacity for control of voice, we examined how accurately and quickly subjects changed the pitch of their voice within a trial to correct for a transient perturbation of the pitch of their auditory feedback. When compared to controls, 16p11.2 deletion carriers show an over-exaggerated pitch compensation response to unpredictable mid-vocalization pitch perturbations. We also examined sensorimotor adaptation of speech by assessing how subjects learned to adapt their sustained productions of formants (speech spectral peak frequencies important for vowel identity), in response to consistent changes in their auditory feedback during vowel production. Deletion carriers show reduced sensorimotor adaptation to sustained vowel identity changes in auditory feedback. These results together suggest that 16p11.2 deletion carriers have fundamental impairments in the basic mechanisms of speech motor control and these impairments may partially explain the deficits in speech and language in these individuals

Speech target modulates speaking induced suppression in auditory cortex

BACKGROUND: Previous magnetoencephalography (MEG) studies have demonstrated speaking-induced suppression (SIS) in the auditory cortex during vocalization tasks wherein the M100 response to a subject's own speaking is reduced compared to the response when they hear playback of their speech. RESULTS: The present MEG study investigated the effects of utterance rapidity and complexity on SIS: The greatest difference between speak and listen M100 amplitudes (i.e., most SIS) was found in the simple speech task. As the utterances became more rapid and complex, SIS was significantly reduced (p = 0.0003). CONCLUSION: These findings are highly consistent with our model of how auditory feedback is processed during speaking, where incoming feedback is compared with an efference-copy derived prediction of expected feedback. Thus, the results provide further insights about how speech motor output is controlled, as well as the computational role of auditory cortex in transforming auditory feedback

What Does Motor Efference Copy Represent? Evidence from Speech Production

How precisely does the brain predict the sensory consequences of our actions? Efference copy is thought to reflect the predicted sensation of self-produced motor acts, such as the auditory feedback heard while speaking. Here, we use magnetoencephalographic imaging (MEG-I) in human speakers to demonstrate that efference copy prediction does not track movement variability across repetitions of the same motor task. Specifically, spoken vowels were less accurately predicted when they were less similar to a speaker's median production, even though the prediction is thought to be based on the very motor commands that generate each vowel. Auditory cortical responses to less prototypical speech productions were less suppressed, resembling responses to speech errors, and were correlated with later corrective movement, suggesting that the suppression may be functionally significant for error correction. The failure of the motor system to accurately predict less prototypical speech productions suggests that the efferent-driven suppression does not reflect a sensory prediction, but a sensory goal

Abnormal speech motor control in individuals with 16p11.2 deletions

Speech and motor deficits are highly prevalent (\u3e70%) in individuals with the 600 kb BP4-BP5 16p11.2 deletion; however, the mechanisms that drive these deficits are unclear, limiting our ability to target interventions and advance treatment. This study examined fundamental aspects of speech motor control in participants with the 16p11.2 deletion. To assess capacity for control of voice, we examined how accurately and quickly subjects changed the pitch of their voice within a trial to correct for a transient perturbation of the pitch of their auditory feedback. When compared to controls, 16p11.2 deletion carriers show an over-exaggerated pitch compensation response to unpredictable mid-vocalization pitch perturbations. We also examined sensorimotor adaptation of speech by assessing how subjects learned to adapt their sustained productions of formants (speech spectral peak frequencies important for vowel identity), in response to consistent changes in their auditory feedback during vowel production. Deletion carriers show reduced sensorimotor adaptation to sustained vowel identity changes in auditory feedback. These results together suggest that 16p11.2 deletion carriers have fundamental impairments in the basic mechanisms of speech motor control and these impairments may partially explain the deficits in speech and language in these individuals

Alignment between Flattened Protostellar Infall Envelopes and Ambient Magnetic Fields

We present 350 μm polarization observations of four low-mass cores containing Class 0 protostars: L483, L1157, L1448-IRS2, and Serp-FIR1. This is the second paper in a larger survey aimed at testing magnetically regulated models for core-collapse. One key prediction of these models is that the mean magnetic field in a core should be aligned with the symmetry axis (minor axis) of the flattened young stellar object inner envelope (aka pseudodisk). Furthermore, the field should exhibit a pinched or hourglass-shaped morphology as gravity drags the field inward toward the central protostar. We combine our results for the four cores with results for three similar cores that were published in the first paper from our survey. An analysis of the 350 μm polarization data for the seven cores yields evidence of a positive correlation between mean field direction and pseudodisk symmetry axis. Our rough estimate for the probability of obtaining by pure chance a correlation as strong as the one we found is about 5%. In addition, we combine together data for multiple cores to create a source-averaged magnetic field map having improved signal-to-noise ratio, and this map shows good agreement between mean field direction and pseudodisk axis (they are within 15°). We also see hints of a magnetic pinch in the source-averaged map. We conclude that core-scale magnetic fields appear to be strong enough to guide gas infall, as predicted by the magnetically regulated models. Finally, we find evidence of a positive correlation between core magnetic field direction and bipolar outflow axis