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Robert Shapley, Valerie Nunez, Peter Schuette, Aneliya Hanineva, Afsana Amir, James Gordon; Non-linear Dynamics of Cortical Responses to Color in the cVEP . Journal of Vision 2016;16(12):391. doi: https://doi.org/10.1167/16.12.391.
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© ARVO (1962-2015); The Authors (2016-present)
Neurons in primary visual cortex (V1) have characteristics that link them to the processing of fundamental aspects of color perception, for instance enhanced sensitivity for the edges of colored objects. We examined human cortical responses to color patterns quantitatively by studying the chromatic visual evoked potential (cVEP) as a measure of neural activity. The stimuli were isoluminant appearance-disappearance checkerboards that were square-wave modulated (0.5s on, 1.5s off) from gray to color and back to gray. The patterns had chromatic excitation purities ranging from 0.03 to 0.53. The square stimulus field was 10° across and the checks were 18.75'. Luminance was 31.5 cd/m2. We recorded cVEPs with a 64-channel BioSemi system. Responses were signal-averaged (30 repeats) and Fourier-transformed. Cortical topography indicated that cVEPs were highly localized at electrodes near Oz, pointing to V1 cortex as the major source of these responses. This agrees with previous work that had indicated the cVEP is driven mainly by neurons in V1. cVEP peak amplitude grew rapidly with purity and then hit a ceiling response at relatively low purities. Notably, the cVEP waveform was non-linear; its time- to-peak was shorter with increasing excitation purity. The non-linear change in cVEP waveform was also seen as a phase-advance in most Fourier components of the response as color purity increased. Harmonic analysis of the cVEP also revealed that the amplitude spectrum of Fourier components of the cVEP in the 2-30 Hz range varied with color excitation purity; the spectrum shifted to higher temporal frequencies with increasing color purity. The spectral shift is another manifestation of color-contrast-dependent non- linear dynamics. Since the parvocellular LGN input to the cortex is known to be highly linear, the observed non-linear characteristics of the EEG response point to cortical nonlinearities.
Meeting abstract presented at VSS 2016
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