When Anticipation Is Not Enough: A Mixture of Robust and Adaptive Feedback Control Strategies Improves Reaching in...

Successful goal-directed movements depend on the central nervous system's (CNS) ability to handle diverse physical interactions. The CNS is thought to handle different dynamical contexts through three mechanisms: (1) trial-by-trial adaptation when forces are predictable, (2) a model-free robust control strategy, and (3) online adaptation of feedback responses. While each has been studied independently, their relative contributions and the possibility that they are recruited to different extents across contexts is unknown. Here, we quantified all three strategies within the same individuals to examine how CNS exploits them under varying environmental conditions. Participants (19 female, 15 male) performed reaching tasks while interacting with robot-generated force fields that were either consistent or varied unpredictably. Trial-by-trial adaptation was measured using standard force channels to isolate anticipatory compensation. Robust control was assessed through movement velocity and corrective force magnitude. Online adaptive control was quantified by the temporal alignment between commanded and measured forces within a movement. Results showed that participants improved anticipatory compensation in consistent environments and relied on both robust and online adaptation when perturbations were unpredictable. Crucially, markers of robust control dominated the early movement phase, whereas online adaptation dominated later corrections. This temporal dissociation was confirmed by electromyographic recordings. Markers of robust and online adaptive feedback strategies also statistically predicted participants' ability to adapt across trials in consistent environments, revealing a common trait linking online control and adaptation. These findings reveal a rich and flexible combination of control mechanisms, offering a new framework for understanding the neurophysiological bases of reaching control.