English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Identification of intended movement type and movement phase of hand graspshaping are critical features for the control of volitional neuroprosthetics.We demonstrate that neural dynamics during visually-guided imagined graspshaping can encode intended movement. We apply Procrustes analysis and LASSOregression to achieve 72% accuracy (chance = 25%) in distinguishing betweenvisually-guided imagined grasp trajectories. Further, we can predict the stageof grasp shaping in the form of elapsed time from start of trial (R2=0.4). Ourapproach contributes to more accurate single-trial decoding of higher-levelmovement goals and the phase of grasping movements in individuals not trainedwith brain-computer interfaces. We also find that the overall time-varyingtrajectory structure of imagined movements tend to be consistent withinindividuals, and that transient trajectory deviations within trials return tothe task-dependent trajectory mean. These overall findings may contribute tothe further understanding of the cortical dynamics of human motor imagery.

Electrocorticographic Dynamics Predict Visually Guided Motor Imagery of Grasp Shaping