Attentional network efficiency in elite biathletes and cross-country skiers

This study provides the first investigation of attentional network efficiency in elite winter endurance athletes, comparing biathletes and cross-country skiers. Utilizing the Attention Network Test (ANT), we assessed the orienting, alerting, and executive networks in 44 elite athletes (15 biathletes, 29 skiers) and 20 sedentary controls. The key findings reveal that the winter elite athletes together demonstrated a significantly lower alerting score compared to controls [13.1 ± 2.9 vs. 25.9 ± 5.2, Welsh's t(63) = 2.134, p = 0.041, Cohen d = 0.592], interpreted as a neural signature of sustained readiness, where the nervous system is perpetually primed, diminishing the benefit of external warning cues. This capacity was manifested even more in biathletes than cross-country skiers and was also extended to spatiotemporal cues [combined score of alerting and orienting: 61.3 ± 9.4 vs. 90.2 ± 4.7, Welsh's t(43) = 2.740, p = 0.012, Cohen d = 0.918]. This attenuated response to both temporal and spatial cues is posited as a trained "cognitive shield," enabling biathletes to suppress automatic shifts of attention to spatial cues in parallel with sustained alerting state—a critical adaptation for maintaining precise marksmanship amidst the physiological noise and environmental distractions of shooting under high cardiovascular load. No group differences were found in executive attention networks and overall reaction time, underscoring the relevance of specific components of attention to these sports. The results demonstrate that the attentional architecture of elite athletes is not broadly enhanced but is precisely calibrated by their sport's unique demands, highlighting a remarkable degree of task-specific performance optimization under pressure.
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Bibliographic Details
Subjects:
Notations:endurance sports social sciences
Tagging:Aufmerksamkeit
Published in:Frontiers in Sports and Active Living
Language:English
Published: 2026
Volume:8
Pages:1757734
Document types:article
Level:advanced