Changes in resting state functional connectivity associated with dynamic adaptation of wrist movements

Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics. Adapted motor plans are consolidated into motor memories that contribute to better performance on re-exposure to the same dynamic condition. In parallel, dynamic perturbations can be compensated for by alternate motor control processes, such as co-contraction, that contribute to error reduction. Whether these control strategies share the same neural resources for memory formation is unclear. To address this gap in knowledge, we used a novel fMRI-compatible wrist robot, the MR-SoftWrist, to identify neural processes specific to dynamic adaptation and subsequent memory formation. Using the MR-SoftWrist, we acquired fMRI during a motor performance and a dynamic perturbation task to localize brain networks of interest. Resting state fMRI scans were acquired immediately before and after task performance to quantify changes in resting state functional connectivity (rsFC) within these networks. Twenty-four hours later, we assessed behavioral retention of training. A variance decomposition analysis was used to isolate behavior associated with adaptation versus alternate error reduction strategies. Immediately after the dynamic perturbation task, rsFC significantly increased within the cortico-thalamic-cerebellar network of the trained wrist and decreased interhemispherically within the cortical sensorimotor network. These changes were associated to behavioral measures of initial acquisition and retention, indicative of memory formation. Variance decomposition analysis revealed that increases within the cortico-thalamic-cerebellar network were associated with adaptation, while interhemispheric decreases in rsFC within the sensorimotor network were associated with alternate error reduction processes.

Visuomotor information drives interference between the hands more than dynamic motor information during bimanual reaching

During complex bimanual movements, interference can occur in the form of one hand influencing the action of the contralateral hand. Interference likely results from conflicting sensorimotor information shared between brain regions controlling hand movements via neural crosstalk. However, how visual and force-related feedback processes interact with each other during bimanual reaching is not well understood. In this study, four groups experienced either a visuomotor perturbation, dynamic perturbation, combined visuomotor and dynamic perturbation, or no perturbation in their right hand during bimanual reaches, with each hand controlling its own cursor. The left hand was examined for interference as a consequence of the right-hand perturbation. The results indicated that the visuomotor and combined perturbations showed greater interference in the left hand than the dynamic perturbation, but that the combined and visuomotor perturbations were equivalent. This suggests that dynamic sensorimotor and visuomotor processes do not interact between hemisphere-hand systems, and that primarily visuomotor processes lead to interference between the hands.

Dynamics of Simulated High-Shear Low-CAPE Supercells

High-shear low-CAPE environments prevalent in the southeastern U.S. account for a large fraction of tornadoes and pose challenges for operational meteorologists. Yet, existing knowledge of supercell dynamics, particularly in the context of cloud-resolving modeling, is dominated by moderate- to high-CAPE environments typical of the Great Plains. This study applies high-resolution modeling to clarify the behavior of supercells in the more poorly understood low-CAPE environments, and compares them to a benchmark simulation in a higher-CAPE environment. Simulated low-CAPE supercells’ main updrafts do not approach the theoretical equilibrium level; their largest vertical velocities result not from buoyancy, but from dynamic accelerations associated with low-level mesocyclones and vortices. Surprisingly, low-CAPE tornado-like vortex parcels also sometimes stop ascending near the vortex top instead of carrying large vorticity upward into the midlevel updraft, contributing to vortex shallowness. Each of these low-CAPE behaviors is attributed to dynamic perturbation pressure gradient accelerations that are maximized in low levels, which predominate when the buoyancy is small.