@inproceedings{8f129d50746e447e8a6c4c4e42c59776,
title = "Assessment of musical training induced neuroplasticity by auditory event related potentials and neural networks",
abstract = "Music provides a tool to study numerous aspects of neuroscience from motion-skill to emotion since listening to and producing music involves many brain functions. The musician's brain is also regarded as an ideal model to investigate plasticity of the human brain. In this paper, an EEG-based neural network is proposed to assess neuroplasticity induced by musical training. A musical chord perception experiment is designed to acquire and compare the behavioral and neural responses of musicians and non-musicians. The ERPs elicited by the consonant and dissonant chords are combined together as the features of the model. The principle component analysis (PCA) is used to reduce feature dimensions and the dimension-reduced features are input to a feedforward neural network to recognize the brain potentials belong to a musician or a non-musician. The accuracy can reach 97% in average for leave-one-out cross validation of six subjects in this experiment. It demonstrates the feasibility of assessing effects of musical training by ERP signals elicited by musical chord perception.",
author = "Liang, {Sheng Fu} and Liu, {Chi Sheng} and Chang, {Wan Lin} and Tsao, {Yu Hsiang} and Ko, {Li Wei} and Lin, {Chin Teng}",
year = "2009",
month = nov,
day = "18",
doi = "10.1109/IJCNN.2009.5179029",
language = "English",
isbn = "9781424435531",
series = "Proceedings of the International Joint Conference on Neural Networks",
pages = "1797--1801",
booktitle = "2009 International Joint Conference on Neural Networks, IJCNN 2009",
note = "2009 International Joint Conference on Neural Networks, IJCNN 2009 ; Conference date: 14-06-2009 Through 19-06-2009",
}