Revealing the brain signal complexity underlying superior putting performance in expert golfers: A multiscale entropy study with supplemental connectivity analyses

Abstract

This study aimed to investigate brain signal complexity associated with superior putting performance in expert golfers. Fifty expert golfers (handicap = −2.8 ± 3) each performed 60 putts at a distance of 10 feet. Putting performance was categorized as either a successful or unsuccessful putt (SP vs. UP), based on whether the ball was holed. Electroencephalography (EEG) was recorded during the motor preparatory period (−2 to 0 s) preceding swing onset. Multiscale Entropy (MSE) analysis was employed to quantify EEG signal complexity across six electrode sites: Fz, Cz, Pz, Oz, T3, and T4. Results revealed significantly higher neural complexity for SP compared to UP at Pz (scales 12, 15–17, 19, 21–25) and Oz (scales 20, 22, 25), but significantly lower complexity at T3 (scales 20, 23, and 24). These findings suggest that the involvement of long-timescale integrative processes of visuospatial regions, alongside reduced neural complexity in verbal-analytic regions may characterize optimal putting performance states. Supplemental cortical connectivity analyses further support the MSE findings, demonstrating that superior putting performance was associated with reduced cortical–cortical communication between T3 and midline regions (i.e., Fz, Cz, and Pz). The present findings advance previous EEG research by moving beyond traditional linear analytic methods and align with the psychomotor efficiency hypothesis, which proposes that superior cognitive-motor performance is supported by more refined neural states that enhance task-relevant processing while minimizing interference from task-irrelevant activity. This study suggests that MSE may serve as a valuable neural indicator of the mechanisms underlying optimal cognitive-motor performance in precision sports.