Musical perception scaling of AEPs from musicians, schizophrenia and normal people

Tsung Hao Hsieh, Ming Jian Sun, Sheng-Fu Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Music is one of the windows into investigate human cognition. Long-term training will change the musical perception, due to plasticity of the human brain. On the other hand, mental or neural disorders may affect musical perception. The aim of this study is to propose a musical perception experiment and the corresponding auditory evoked potentials (AEP) analysis strategy to distinguish musicians with long-term training, healthy controls and patients with psychiatric disorders. AEPs from 12 schizophrenia patients (defect), 12 musicians (enhancement) and 12 healthy people (regular) invoked by musical intervals and chords were recorded. AEP analysis results show that schizophrenia patients have reduced N1 and P2 amplitudes comparing with the other two groups. Musicians have enhanced N1, P2 and N1-P2 amplitudes. Basing on these observations, a two-layer hierarchical AEP classification method based on the linear discriminate analysis (LDA) is proposed to distinguish these different subject groups. Layer-1 classifies schizophrenia patients with others based on AEP elicited by musical intervals. Layer-2 distinguishes musicians and normal people based on stimuli of consonant intervals and chord. Accuracy of the proposed two-layer method can reach 91.63% through leave-one-out cross validation. Experimental results demonstrate the feasibility of scaling musical perception by analyzing brain AEPs elicited by musical stimuli with different complexity and consonance. These results can be applied to the development of musical training evaluation and psychiatric disorders diagnosis systems in the future.

Original languageEnglish
Title of host publicationTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781467396066
Publication statusPublished - 2016 Feb 12
EventConference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan
Duration: 2015 Nov 202015 Nov 22


OtherConference on Technologies and Applications of Artificial Intelligence, TAAI 2015

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

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