Speech Motor Learning and Sensory Plasticity in Children and Adults

Haskins Laboratories, Inc., New Haven CT

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): The proposed studies will focus on the neural substrates of speech motor development in children. Our plan is to use a multi-modal approach that combines advanced psychophysical and neuroimaging techniques. In our work with adults, in the context of human arm movement, we have developed a powerful new technique to identify changes in brain activity that are specifically related to behavioral measures of learning We have found that changes in brain networks that occur in conjunction with motor learning can be partitioned into those that are primarily motor in nature and those that reflect the perceptual changes that occur in conjunction with motor learning. For the proposed project, we will study healthy children from ages 5 to 12 and healthy adults. We will use fMRI measures of functional connectivity to identify the brain networks that are associated with motor and perceptual changes that occur in association with speech motor learning. We will test the hypothesis that the brain networks associated with speech motor learning can be partitioned, as in limb movement, into those that are primarily associated with the changes in motor function and those involved in the perceptual and sensory aspects of speech motor learning. We propose that the sensory and motor networks active during speech motor learning may function more independently in younger children, becoming more tightly coupled as these systems mature. We will also determine how the brain activity that accompanies speech motor learning is related to the more durable changes in brain networks that are observed under-resting state conditions following training. The hypothesis is that brain activity during speech motor learning involves networks that process sensory errors and those that code predictive or feedforward adjustments associated with adaptation and learning. We will test the idea that patterns of brain activity during task based learning that are related to the these measures can be used to predict durable changes in functional connectivity that are observed after the completion of the learning task.