Continuous Diffusion-Detected Neuroplasticity during Motor Learning

How does our brain transform when we encounter a new task? To fully answer this question, comparing brain states before and after learning may not be enough, but rather an ongoing, continuous monitoring of brain changes during learning is required. While such continuous examinations of functional learning-induced changes are widely available using functional magnetic resonance imaging (MRI), a continuous investigation of diffusion-detected brain modifications during learning is yet to be reported. Here, we continuously acquire diffusion MRI images during task performance. We then compute the mean diffusivity (MD) using a sliding-window approach, resulting in a continuous measure of diffusivity changes throughout learning. We demonstrate the utility of this method on a motor sequence learning (finger tapping) task (<i>n</i> = 58, 30 females). MD decrease was detected in task-related brain regions, including the parahippocampal gyrus (PHG), hippocampus, inferior temporal gyrus, and cerebellum. Analysis of the temporal patterns of decrease revealed a rapid MD reduction in the right temporal gyrus after 11 min of training, with additional decrease in the right PHG and left cerebellum after 22 min. We further 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 spatiotemporal dynamics of diffusion-detected neuroplasticity by demonstrating continuous modifications during the encoding phase of learning itself rather than comparing pre- and postlearning states.