Optimal Inter-Session Intervals in Neurofeedback Training: A Randomized Trial of Retention and Individual Response Patterns in Elite Judo Athletes

Background: Neurofeedback training (NFT) enhances athletic performance through alpha modulation, but optimal inter-session intervals and individual response variability remain poorly understood. Objective: This is the first randomized controlled trial to systematically compare neurofeedback periodization (2-day vs. 3-day inter-session intervals) on neurophysiological adaptations, strength performance, and retention in elite judo athletes. Methods: Thirty-one national-level judokas completed 15 alpha enhancement sessions in 2-day (n = 12), 3-day (n = 12), or control (n = 7) groups, receiving pseudo-neurofeedback with randomized, non-contingent feedback. Primary outcomes included Frontal Alpha Index changes (ΔFAI; frontal alpha power modulation ratio) and squat performance (35–100% 1RM), with secondary assessment of 48/72 h retention and response phenotypes. Results: Mean ΔFAI was modest (E15G-2d: 0.005 ± 0.205; E15G-3d: 0.052 ± 0.202), with early peak responses followed by stabilization. E15G-3d demonstrated superior retention (90.2 ± 3.4% at 72 h vs. 76.8 ± 4.1% at 48 h; p < 0.001) despite similar peaks. Both training groups showed significant strength improvements versus controls (E15G-2d: 2.37 ± 0.66 reps; E15G-3d: 2.00 ± 0.53 reps), yet neurophysiological-performance correlations were non-significant (p > 0.072), indicating strength adaptations via mechanisms independent of alpha modulation. Three response phenotypes emerged (high: 29.0%, moderate: 51.6%, low: 19.4%), representing the first empirical classification of neurofeedback responsiveness in athletes. Conclusions: Three-day intervals uniquely optimize retention through enhanced consolidation, establishing evidence-based periodization guidelines for elite athletes. The dissociation between neural and performance adaptations challenges traditional neurofeedback theory, while individual heterogeneity necessitates personalized protocols for optimal NFT periodization.