128
Views
5
CrossRef citations to date
0
Altmetric
Research Article

Toward an understanding of auditory evoked cortical event-related potentials: Characteristics and classification

, , , , &
Pages 16-25 | Accepted 01 Nov 2010, Published online: 20 Jan 2011
 

Abstract

Objective: To investigate the characteristics of auditory evoked cortical ERP components P1-N1-P2 and MMN and explore a practical way for ERP waveform identification and classification. Methods: Thirty right-handed normally hearing volunteers participated in the present study, age ranging from 20 to 40 years old, 14 males and 16 females. All the volunteers reported no history of auditory, neurological or mental disorder. The event related potential (ERP) components (i.e. P1-N1-P2 complex and mismatch negativity (MMN)) were measured using the 128-electrode channels EGI system. Results: Three different categories of ERP responses were classified on the basis of waveform configuration, size of the peak amplitude and the number of peaks together with scalp distribution of MMN. Ten participants (33.3%) had well defined ERP responses, 13 (43.3%) showed moderately defined ERP responses, and seven (23.3%) had poorly defined ERP responses. Although there were no significant differences in P1, P2, and MMN latencies, participants with the poorly defined ERP waves had significantly longer N1 latency than that in subjects with well defined ERP waves. In addition, significantly lower MMN amplitudes were also found in this group. Conclusion: Combining a waveform classification method and the MMN scalp distribution pattern, together with quantitative ERP response analysis, may provide more reliable and practical means for clinical application.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.