Neurodiagnostics in sports: Investigating the athlete`s brain to augment performance and sport-specific skills
(Neurodiagnostik im Sport: Untersuchung des Sportlergehirns zur Steigerung der Leistung und der sportartspezifischen Fähigkeiten)
Enhancing performance levels of athletes during training and competition is a desired goal in sports. Quantifying training success is typically accompanied by performance diagnostics including the assessment of sports-relevant behavioral and physiological parameters. Even though optimal brain processing is a key factor for augmented motor performance and skill learning, neurodiagnostics is typically not implemented in performance diagnostics of athletes. We propose, that neurodiagnostics via non-invasive brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) will offer novel perspectives to quantify training-induced neuroplasticity and its relation to motor behavior. A better understanding of such a brain-behavior relationship during the execution of sport-specific movements might help to guide training processes and to optimize training outcomes. Furthermore, targeted non-invasive brain stimulation such as transcranial direct current stimulation (tDCS) might help to further enhance training outcomes by modulating brain areas that show training-induced neuroplasticity. However, we strongly suggest that ethical aspects in the use of non-invasive brain stimulation during training and/or competition need to be addressed before neuromodulation can be considered as a performance enhancer in sports.
© Copyright 2020 Frontiers in Human Neuroscience. Frontiers Media. Alle Rechte vorbehalten.
| Schlagworte: | |
|---|---|
| Notationen: | Biowissenschaften und Sportmedizin Trainingswissenschaft |
| Tagging: | Nahinfrarotspektroskopie |
| Veröffentlicht in: | Frontiers in Human Neuroscience |
| Sprache: | Englisch |
| Veröffentlicht: |
2020
|
| Online-Zugang: | https://www.frontiersin.org/article/10.3389/fnhum.2020.00133 |
| Jahrgang: | 14 |
| Seiten: | 133 |
| Dokumentenarten: | Artikel |
| Level: | hoch |