Steady-state visual evoked potentials: distributed local sources and wave-like dynamics are sensitive to flicker frequency.
Steady-state visual evoked potentials (SSVEPs) are used in cognitive and clinical studies of brain function because of excellent signal-to-noise ratios and relative immunity to artifacts. SSVEPs also provide a means to characterize preferred frequencies of neocortical dynamic processes. In this study, SSVEPs were recorded with 110 electrodes while subjects viewed random dot patterns flickered between 3 and 30 Hz. Peaks in SSVEP power were observed at delta (3 Hz), lower alpha (7 and 8 Hz), and upper alpha band (12 and 13 Hz) frequencies; the spatial distribution of SSVEP power is also strongly dependent on the input frequency suggesting cortical resonances. We characterized the cortical sources that generate SSVEPs at different input frequencies by applying surface Laplacians and spatial spectral analysis. Laplacian SSVEPs recorded are sensitive to small changes (1-2 Hz) in the input frequency at occipital and parietal electrodes indicating distinct local sources. At 10 Hz, local source activity occurs in multiple cortical regions; Laplacian SSVEPs are also observed in lateral frontal electrodes. Laplacian SSVEPs are negligible at many frontal electrodes that elicit strong potential SSVEPs at delta, lower alpha, and upper alpha bands. One-dimensional (anterior-posterior) spatial spectra indicate that distinct large-scale source distributions contribute SSVEP power in these frequency bands. In the upper alpha band, spatial spectra indicate the presence of long-wavelength (> 15 cm) traveling waves propagating from occipital to prefrontal electrodes. In the delta and lower alpha band, spatial spectra indicate that long-wavelength source distributions over posterior and anterior regions form standing-wave patterns. These results suggest that the SSVEP is generated by both (relatively stationary) localized sources and distributed sources that exhibit characteristics of wave phenomena.
Srinivasan
Ramesh
R
Department of Cognitive Sciences, University of California, Irvine, 92617, USA. srinivar@uci.edu
Bibi
F Alouani
FA
Nunez
Paul L
PL
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001931:Brain Mapping / Q000379:methods; D004566:Electrodes / Q000592:standards; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D014793:Visual Cortex / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology