The transformation of neural signals to muscle activity to behavioral output defines how the brain controls behavior, and a full account of brain function demands that we understand this transformation. Vocal motor control is critical to our ability to communicate, and yet we still do not understand how the brain controls vocal muscle activity and acoustic output. This gap in understanding hinders our ability to understand the general principles of vocal behavior and develop effective treatments for the various speech disorders affecting millions of Americans. The well-characterized and relatively simple organization of the songbird brain makes it an ideal model system for understanding normal and disordered vocal control. Furthermore, our lab has developed innovative behavioral paradigms that use auditory feedback manipulations to induce vocal error correction in adult songbirds, providing a model for the auditory feedback manipulations used to treat vocal disorders in humans. The research described in my proposal will include experimental approaches not possible in human subjects to learn how altered sensory feedback can modify patterns of vocal muscle activation during vocal error correction and reveal how such adaptive modifications are implemented by the brain. The proposed research will therefore significantly advance the songbird as an animal model for investigating the mechanisms and optimizing the design of behavioral paradigms for vocal rehabilitation. The objective of this proposal is to quantify how patterns of vocal muscle activity are transformed into acoustic output, reshaped during vocal error correction, and controlled by individual premotor neurons (i.e. those that directly activate motor neurons, which in turn activate the vocal muscles). This work will utilize electrophysiology to record premotor neurons and electromyography (EMG) to record vocal muscles. It is hypothesized that each premotor neuron controls multiple muscles, each of which, in turn, controls multiple acoustic parameters and, thus, subsets of vocal muscles must change their activity in concert to shift individual acoustic parameters of song during vocal learning.
Aim 1 wil reveal the mechanics of the transformation from vocal muscle activity to acoustic parameters. Acoustic features of song will be correlated with EMG activity recorded using intramuscular electrodes, and targeted electrical stimulation of single vocal muscles will be used to drive changes in those acoustic features.
Aim 2 will quantify changes in vocal muscle activity during vocal learning to demonstrate how the songbird system implements learning using the available mechanics of the vocal organ.
Aim 3 will characterize the functional projections from single premotor neurons to the vocal muscles using simultaneous neural and muscular recording. Quantitative analysis (spike-triggered EMG) will then be used to determine whether individual premotor neurons control single or multiple muscles to drive song. This work will provide insight into the neuromuscular mechanisms underlying vocal learning and motor control while laying a foundation for future studies in speech control and sensorimotor learning.
The generation of fluent speech is crucial to our ability to communicate, but the neural and muscular mechanisms behind vocal production are poorly understood. This research proposal will reveal how the brain generates vocal muscle activity and how that activity is altered when the brain corrects vocal errors. This work may increase our understanding of how the brain controls speech and how auditory-feedback-based treatments, which are used for various speech disorders that affect millions of Americans, alter vocal motor control.
|Srivastava, Kyle H; Elemans, Coen P H; Sober, Samuel J (2015) Multifunctional and Context-Dependent Control of Vocal Acoustics by Individual Muscles. J Neurosci 35:14183-94|
|Elemans, C P H; Rasmussen, J H; Herbst, C T et al. (2015) Universal mechanisms of sound production and control in birds and mammals. Nat Commun 6:8978|
|Tang, Claire; Chehayeb, Diala; Srivastava, Kyle et al. (2014) Millisecond-scale motor encoding in a cortical vocal area. PLoS Biol 12:e1002018|