The impact of visual contexts dynamics on anticipation: Neurocomputational evidence of expert advantage

Sports anticipation represents a crucial perceptual-decision skill requiring rapid judgment of opponents' actions under temporal pressure. While previous research has established expert advantage in anticipatory performance, the underlying neural computational mechanisms remain unclear, particularly regarding how expertise modulates processing across different visual contexts. This study employed a multi-level approach integrating behavioral measurements, electroencephalography, and hierarchical drift diffusion modeling to investigate expert advantage in basketball action anticipation. Participants performed a pass-versus-shot task using schematic moving-dots plays, clarifying that the paradigm indexes pattern recognition rather than advance-cue utilization from postural kinematics. Results revealed context-dependent manifestations of expert advantage: behaviorally, experts demonstrated superior anticipatory accuracy and shorter reaction times, with distinctive response bias patterns in dynamic contexts. Neural data uncovered a dual adaptation mechanism: in static contexts, experts maintained performance through compensatory enhancement of frontal N2 components, while in dynamic contexts, they achieved efficient processing through economized modulation of parietal P3 amplitude. Computational modeling revealed expertise-specific mapping between P3 components and decision parameters, suggesting functional reorganization of perception-decision networks through professional training. These findings provide the first quantitative characterization of the neural computational foundations underlying expert anticipatory advantage, demonstrating how professional training reshapes brain decision networks to enable flexible adaptation across visual contexts. This integrated analysis advances our understanding of sports expertise while establishing new methodological frameworks for investigating complex perceptual-decision processes.