Paper Info
Title
Use of a steady-state baseline to address evoked vs. oscillation models of visual evoked potential origin.
Abstract
There has been a long debate about the neural mechanism of event-related potentials (ERPs). Previously, no evidence or method was apparent to validate the two competing models, the evoked model and the oscillation model. One argument is whether the pre-stimulus brain oscillation could influence the following ERP. This study carried out an innovative visual oddball task experiment to investigate the dynamic process of visual evoked potentials. A period of stable oscillations of specified dominant frequencies and initial phases, i.e. the steady-state baseline, would be induced before responses to transient stimuli of different contrasts, which could overcome the artifact problem caused by the ‘sorting’ method. The result first revealed a ‘three-period-transition’ for the generation of visual evoked potentials by an objective decomposition. The ERP almost retained the preceding oscillation during the first period, provided an unstable negative potential in the second period, and generated the N1 component in the third period. The cross term analysis showed that the evoked model couldn't be the whole explanation for the ERP generation. Furthermore, the component analysis revealed that the N1 latency was sensitive to the initial phase under the low stimulus contrast (supporting the oscillation model) but not under the high stimulus contrast (supporting the evoked model). It demonstrated that the external stimulus contrast is a significant factor deciding the explicit model for ERPs. Our method and preliminary results may help reconcile the previous, seemly contradictory findings on the ERP mechanism.
Year
DOI
Venue
2016
10.1016/j.neuroimage.2016.03.073
NeuroImage
Keywords
Field
DocType
ERP,SSVEP,Neural mechanism,Phase resetting,Period transition,Cross term analysis
Neuroscience,Oscillation,Visual cortex,Psychology,Oddball paradigm,Cognitive psychology,Contrast (statistics),Visual N1,Evoked potential,Artificial intelligence,Stimulus (physiology),Visual perception
Journal
Volume
ISSN
Citations 
134
1053-8119
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Minpeng Xu12717.17
Yihong Jia200.34
Hongzhi Qi34920.61
Yong Hu400.34
Feng He5169.45
Xin Zhao664.16
Peng Zhou7136.25
Lixin Zhang823.75
Baikun Wan910416.90
Wei Gao10917.05
Dong Ming1110551.47