Aging-related Changes in the Neural Mechanisms Underlying Speech Motor Learning

SUMMARY Aging is associated with a decline in the neural substrates and sensorimotor processes subserving speech motor control. In addition, aging-related neurodegenerative diseases such as Parkinson’s disease may lead to severe motor speech impairments. Prior efforts to incorporate known principles of motor learning into motor

speech treatment programs are impeded by the lack of empirical data on how the aging process affects different forms of speech motor learning at both the behavioral and neural level. In my predoctoral work at the University of Washington (F99 phase), my dissertation focuses on two distinct forms of speech motor learning:

auditory-motor adaptation and syllable sequence learning. No previous studies have directly compared the neural bases of these forms of motor learning or investigated how they are affected by aging. The central hypothesis of this project is that speech adaptation and syllable sequence learning rely largely on distinct

cortical-subcortical networks and, therefore, are differentially affected by the aging process. In Aim 1.1, I investigate the subcortical contributions to both forms of motor learning by comparing individuals with Parkinson’s disease who have DBS electrodes implanted in the subthalamic nucleus (STN) in the cortico-basal

ganglia circuit, individuals with essential tremor who have DBS electrodes implanted in the ventrolateral nucleus of the thalamus (Vim) in the cortico-cerebellar circuit, and age-matched control participants. Analyses are based on both behavioral data from DBS ON/OFF conditions and neural data from a subgroup of patients

whose DBS device allows sensing from the implanted nuclei. In Aim 1.2, I directly study the effects of aging itself on speech motor learning by using EEG to compare cortical neural activity associated with speech auditory-motor adaptation and syllable sequence learning in healthy older adults versus healthy younger

adults. In the postdoctoral phase at the University of California San Franciso (K00 phase), I will then further expand my expertise and skills in aging research as applied to speech neuroscience. In Aim 2, I will focus on multimodal neuroimaging and computational modeling to investigate how sensorimotor neuronal networks in

the aging brain support different forms of speech motor learning through functional reorganization, and how such reorganization can be accounted for in computational models of speech motor control. This program of training and research will prepare me for a productive career in aging research and speech neuroscience.

Findings from the series of studies will advance our understanding of aging-related changes in the speech sensorimotor system and inform the development of effective behavioral and neuromodulation treatments for aging-related motor speech disorders.