Bayesian inference of state feedback control parameters forfoperturbation responses in cerebellar ataxia
Authors: Gaines Jessica L. , Kim Kwang S. , Parrell Ben , Ramanarayanan Vikram , Pongos Alvincé L. , Nagarajan Srikantan S. , Houde John F. 
Published: March 2024

AbstractBehavioral speech tasks have been widely used to understand the mechanisms of speech motor control in healthy speakers as well as in various clinical populations. However, determining which neural functions differ between healthy speakers and clinical populations based on behavioral data alone is difficult because multiple mechanisms may lead to the same behavioral differences. For example, individuals with cerebellar ataxia (CA) produce abnormally large compensatory responses to pitch perturbations in their auditory feedback, compared to controls, but this pattern could have many explanations.Here, computational modeling techniques were used to address this challenge. Bayesian inference was used to fit a state feedback control (SFC) model of voice fundamental frequency (fo) control to the behavioral pitch perturbation responses of individuals with CA and healthy controls. This fitting process resulted in estimates of posterior likelihood distributions of five model parameters (sensory feedback delays, absolute and relative levels of auditory and somatosensory feedback noise, and controller gain), which were compared between the two groups. Results suggest that the CA group may proportionally weight auditory and somatosensory feedback differently from the control group. Specifically, the CA group showed a greater relative sensitivity to auditory feedback than the control group. There were also large group differences in the controller gain parameter, suggesting increased motor output responses to target errors in the CA group. These modeling results generate hypotheses about how CA may affect the speech motor system, which could help guide future empirical investigations in CA. This study also demonstrates the overall proof-of-principle of using this Bayesian inference approach to understand behavioral speech data in terms of interpretable parameters of speech motor control models.Author summaryCerebellar ataxia is a condition characterized by a loss of coordination in the control of muscle movements, including those required for speech, due to damage in the cerebellar region of the brain. Behavioral speech experiments have been used to understand this disorder’s impact on speech motor control, but the results can be ambiguous to interpret. In this study, we fit a computational model of the neural speech motor control system to the speech data of individuals with cerebellar ataxia and that of healthy controls to determine what differences in model parameters best explain how the two groups differ in their control of vocal pitch. We found that group differences may be explained by increased sensitivity toauditory feedback prediction errors(differences between the actual sound speakers hear of their own speech as they produce it and the sound they expected to hear) and increased motor response in individuals with cerebellar ataxia. These computational results help us understand how cerebellar ataxia impacts speech motor control, and this general approach can also be applied to study other neurological speech disorders.