|2016/07/01 - 2017/10/31||30.000 Euro|
Ph.D. project (Scholarship by the Ministry of Education, Taiwan & CITEC)
Neurofeedback training (NFT) is a technique for training the brain to improve its functioning through self-regulation of the electroencephalogram (EEG). Previous findings have found that training participants to increase sensorimotor rhythm (SMR) power was associated with improvements in motor performance. However, novel insights can be obtained from a measurement which can investigate the cognitive measure of the memory structure of the movements through NFT. The SDA-M (Structural Dimension Analysis of Mental Representation) is an ideal approach which probes the changes on mental representation. This project is designed to evaluate the effect of SMR NFT on golf putting performance by employing the SDA-M methodology. We predict that the participants in SMR NFT group will improve putting performance after training in contrast to Mock NFT group. Furthermore, we predict a more hierarchical structure of the mental representation will be observed in the SMR NFT group after training compare to the Mock NFT group.
For more information, see [ here ] .