BCIwiki (bciwiki.com) — The study was published in Computers in biology and medicine on June 9, 2026. Researchers recorded EEG during precision and power reach-to-grasp tasks and used cross-frequency bispectral analysis to compute complex bicoherence matrices. Magnitude- and phase-based features were then extracted to compare neural activity during grasp planning and execution.
Classification, permutation-based feature selection, and within-subject statistical testing showed stronger nonlinear coupling during execution than planning, with dominant contributions from beta- and gamma-driven interactions. Decoding precision versus power grasps performed similarly during planning and execution, suggesting that grasp-type representations emerge during planning and persist into execution. Compared with conventional analytical baselines, bispectral features offered consistent advantages for grasp-type discrimination and multiclass classification. The researchers conclude that nonlinear cross-frequency coupling can serve as an informative marker of motor stages and support future brain-computer interface and neuroprosthetic research.