Resting state cortical rhythms in athletes: A high-resolution EEG study

Claudio Babiloni, Nicola Marzano, Marco Iacoboni, Francesco Infarinato, Pierluigi Aschieri, Paola Buffo, Giuseppe Cibelli, Andrea Soricelli, Fabrizio Eusebi, Claudio Del Percio

Research output: Contribution to journalArticlepeer-review

Abstract

The present electroencephalographic (EEG) study tested the working hypothesis that the amplitude of resting state cortical EEG rhythms (especially alpha, 8-12 Hz) was higher in elite athletes compared with amateur athletes and non-athletes, as a reflection of the efficiency of underlying back-ground neural synchronization mechanisms. Eyes closed resting state EEG data were recorded in 16 elite karate athletes, 20 amateur karate athletes, and 25 non-athletes. The EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Statistical results showed that the amplitude of parietal and occipital alpha 1 sources was significantly higher in the elite karate athletes than in the non-athletes and karate amateur athletes. Similar results were observed in parietal and occipital delta sources as well as in occipital theta sources. Finally, a control confirmatory experiment showed that the amplitude of parietal and occipital delta and alpha 1 sources was stronger in 8 elite rhythmic gymnasts compared with 14 non-athletes. These results supported the hypothesis that cortical neural synchronization at the basis of eyes-closed resting state EEG rhythms is enhanced in elite athletes than in control subjects.

Original languageEnglish
Pages (from-to)149-156
Number of pages8
JournalBrain Research Bulletin
Volume81
Issue number1
DOIs
Publication statusPublished - Jan 15 2010

Keywords

  • Alpha rhythms
  • Electroencephalography (EEG)
  • Elite karate athletes
  • Low-resolution brain electromagnetic tomography (LORETA)

ASJC Scopus subject areas

  • Neuroscience(all)

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