Pauline M. Hilt

This study uses machine learning to analyze muscle modulation patterns during reach-and-grasp tasks with different hand orientations, revealing complex dynamics and proximo-distal organization.

This study compares arm and whole-body motor control in younger and older adults to determine if age-related changes reflect deterioration or compensation, finding that reduced whole-body movement efficiency correlates with balance control.

This study quantifies hierarchical muscle interactions' contributions to motor function using Partial Information Decomposition, revealing networks linked to balance and motor variability.

This study shows that motor imagery training improves motor memory in very old adults, maintaining performance in manual dexterity and enhancing sequential stepping tasks compared to a control group.

This study investigates whether sensorimotor predictions underlie action observation by comparing timing processes in locomotion inference and mental locomotion tasks using sensory illusions.

The paper investigates how individual subjective values influence movement planning in a vertical plane task, finding that energy minimization is not the sole factor guiding motor behavior.

This study shows that evening training leads to better skill consolidation compared to morning or afternoon training, with sleep contributing to this effect.

This study investigates how time-of-day affects motor skill acquisition and consolidation after physical and mental practice, finding better consolidation in the afternoon for both types of practice.

The paper compares movement smoothness between physical and motor imagery practice, finding that physical practice leads to smoother movements as indicated by fewer velocity peaks.

This study shows that visual detection is enhanced when cortico-motor alpha synchronization is increased before stimulus onset, revealing an internal visuomotor loop.

The paper evaluates a space-by-time decomposition method to assess modularity in muscle activity during whole-body reaching tasks, finding it effective for data approximation and task discrimination.