Steady-State Visual Evoked Potentials Can Be Explained by Temporal Superposition of Transient Event-Related Responses
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Abstract
Background
One common criterion for classifying electrophysiological brain responses is based on the distinction between transient (i.e. event-related potentials, ERPs) and steady-state responses (SSRs). The generation of SSRs is usually attributed to the entrainment of a neural rhythm driven by the stimulus train. However, a more parsimonious account suggests that SSRs might result from the linear addition of the transient responses elicited by each stimulus. This study aimed to investigate this possibility.
Methodology/Principal Findings
We recorded brain potentials elicited by a checkerboard stimulus reversing at different rates. We modeled SSRs by sequentially shifting and linearly adding rate-specific ERPs. Our results show a strong resemblance between recorded and synthetic SSRs, supporting the superposition hypothesis. Furthermore, we did not find evidence of entrainment of a neural oscillation at the stimulation frequency.
Conclusions/Significance
This study provides evidence that visual SSRs can be explained as a superposition of transient ERPs. These findings have critical implications in our current understanding of brain oscillations. Contrary to the idea that neural networks can be tuned to a wide range of frequencies, our findings rather suggest that the oscillatory response of a given neural network is constrained within its natural frequency range
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Bibliographic citation
Capilla A, Pazo-Alvarez P, Darriba A, Campo P, Gross J (2011) Steady-State Visual Evoked Potentials Can Be Explained by Temporal Superposition of Transient Event-Related Responses. PLoS ONE 6(1): e14543
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https://doi.org/10.1371/journal.pone.0014543Sponsors
This work was supported by the Spanish Ministry of Science and Innovation (2008-0168 Postdoctoral Fellowship to A. Capilla; and RYC-2010-05748 Ramón y Cajal Fellowship to P. Campo)
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Copyright: © 2011 Capilla et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited







