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Open Access Highly Accessed Research article

Do resting brain dynamics predict oddball evoked-potential?

Tien-Wen Lee12, Younger W-Y Yu3, Hung-Chi Wu4 and Tai-Jui Chen56*

Author Affiliations

1 Laureate Institute for Brain Research, Tulsa, Oklahoma, USA

2 College of Medicine, Chang Gung University, Taoyuan County, Taiwan

3 Yu's Psychiatric Clinic, Kaohsiung, Taiwan

4 Kai-Suan Psychiatric Hospital, Kaohsiung, Taiwan

5 Department of Psychiatry, E-DA Hospital, Kaohsiung County, Taiwan

6 Department of Occupational Therapy, I-Shou University, Kaohsiung County, Taiwan

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BMC Neuroscience 2011, 12:121  doi:10.1186/1471-2202-12-121

Published: 24 November 2011

Abstract

Background

The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations.

Results

Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain.

Conclusions

This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.