Variance Dynamics: Exploring Force-stabilizing Synergies Through Inter- and Intra-Trial Analysis
Research Poster Health & Life Sciences 2025 Graduate ExhibitionPresentation by Saad Khan
Copresented by Sayan De
Exhibition Number 88
Abstract
This study examined how a hierarchical control scheme accounts for stability during multi-finger force production. We hypothesized that variance within the solution space, uncontrolled manifold (Vucm), comprises two contributors: feed-forward variance in sharing (Vucm-sh) derived from practice, and feedback-driven negative covariation of elements, manifested in both inter- and intra-trial variance. Young adults performed four-finger force tasks, with the index and middle fingers of both hands. Participants saw targets for total force (F-TOT), individual finger-pair forces (F-PAIR), or a combination of both (F-TOT+PAIR), under conditions of continuous (FB-ON) or intermittent (FB-OFF) visual feedback. Inter-trial and intra-trial Vucm and orthogonal to the UCM Vort were quantified to calculate the synergy index (deltaV). Inter-trial analysis revealed positive deltaV across all conditions with explicit targets, with significantly higher V in FB-ON condition compared to FB-OFF. Without visual feedback, deltaV approached zero. Under the F-TOT+PAIR condition, deltaV was positive but reduced compared to F-TOT or F-PAIR alone, primarily due to changes in the Vucm component. Intra-trial analysis showed lower deltaV for 50:50 force sharing, but higher deltaV for 75:25 and 25:75. Results support the two sources of Vucm and the importance of continuous visual feedback for performance-stabilizing synergy. Furthermore, they demonstrate a trade-off between synergies at the level of two hands and pairs of fingers, though they can co-exist. Combining inter- and intra-trial analyses enhances understanding of synergy origins, potentially aiding in the study of neurological disorders.
Importance
This study explores how the brain coordinates actions of multiple fingers to perform force production tasks. We discovered that the brain uses both practice and real-time visual feedback to make these movements smooth and accurate. Think of it like learning to ride a bike; you need practice, but also constant adjustments based on what you see and feel. Our research also shows how the brain manages the balance of control between hands and fingers. This is important because it could help us develop better ways to help people who struggle with movement, like after a brain injury. By understanding how the brain normally coordinates these movements, we can create more effective rehabilitation exercises to help patients regain their abilities.