Abstract
AbstractLearning is a complex, continuously evolving process which induces widespread structural and functional brain alterations. In recent years, diffusion magnetic resonance imaging (dMRI) has been used to detect microstructural modifications after short learning periods. While previous studies primarily explored changesfollowinglearning (i.e., by comparing images acquired before and after learning), the continuous temporal dynamics of microstructural alterationsduringthe encoding phase of learning itself are yet to be examined. Here, we introduce a novel approach for continuous acquisition of dMRI images which allow tracking microstructural changes throughout learning and demonstrate the utility of this approach on a motor sequence learning (finger tapping) task (n=58). Voxel-wise analysis revealed a decrease in mean diffusivity (MD) in task-related brain regions, including the parahippocampal gyrus, hippocampus, inferior temporal gyrus, and cerebellum. Further analysis of the temporal patterns of decrease revealed a rapid MD reduction in the right temporal gyrus after 11 minutes of learning, with additional decrease in the right parahippocampal gyrus and left cerebellum after 22 minutes. We computed "neuroplasticity networks" of brain areas showing similar change patterns and detected similarities between these networks and canonical functional connectivity networks. Our findings offer novel insights on the spatio-temporal dynamics of neuroplasticity and advance our understanding of motor learning by demonstrating continuous microstructural modifications from the very first minutes of training.
Publisher
Cold Spring Harbor Laboratory