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An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System

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Cognitive Neuroscience in Alpine Skiing: Introducing Computational Sports Medicine for Performance Optimization.

Carl-Johan Boraxbekk^1,2, Matej Supej³, Hans-Christer Holmberg^4,5

¹Department of Neurology, Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark.

Scandinavian Journal of Medicine & Science in Sports

|January 11, 2026

Summary

Computational Sports Medicine integrates brain science with physical training to enhance athletic performance. This new framework offers personalized strategies for injury prevention and optimizing recovery for athletes.

Keywords:

athlete development brain predictive modeling working memory updating

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Area of Science:

Sports Medicine
Cognitive Neuroscience
Computational Biology

Background:

Traditional sports medicine focuses on physical aspects, neglecting the brain's role in athletic performance.
Sport psychology emphasizes mental and cognitive factors but lacks integration with physiological measures.
A gap exists in unifying cognitive and physiological data for a holistic view of athletic performance.

Purpose of the Study:

Introduce Computational Sports Medicine, a novel framework integrating cognitive neuroscience with physiological and biomechanical data.
Examine the role of working memory updating and neural adaptation in dynamic sports environments, using alpine skiing as a model.
Propose a unifying predictive framework for objective, quantifiable metrics and simulation of "what-if" scenarios in sports.

Main Methods:

Narrative review synthesizing literature from sport psychology, sports medicine, and cognitive neuroscience.
Analysis of alpine skiing as a case study to illustrate the application of the framework.
Conceptual development of Computational Sports Medicine as a predictive and simulation-based approach.

Main Results:

Working memory updating is critical for performance in dynamic environments.
Neural processes are key to adaptation in athletic performance.
Computational Sports Medicine offers a brain-inclusive, personalized approach beyond descriptive analysis.

Conclusions:

Computational Sports Medicine provides a unifying, predictive framework for optimizing athletic performance.
Practical training implications include sport-specific cognitive tasks and leveraging technology (VR, wearables).
This brain-centric approach is crucial for personalized performance optimization, injury prevention, and return-to-play decisions.