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Measuring nonlinear signal combination using EEG

Cunningham, Darren G.M.; Baker, Daniel H.; Peirce, Jonathan W.

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Darren G.M. Cunningham

Daniel H. Baker

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Professor of Psychology Research Methods


Relatively little is known about the processes, both linear and nonlinear, by which signals are combined beyond V1. By presenting two stimulus components simultaneously, flickering at different temporal frequencies (frequency tagging) while measuring steady-state visual evoked potentials, we can assess responses to the individual components, including direct measurements of suppression on each other, and various nonlinear responses to their combination found at intermodulation frequencies. The result is a rather rich dataset of frequencies at which responses can be found. We presented pairs of sinusoidal gratings at different temporal frequencies, forming plaid patterns that were "coherent" (looking like a checkerboard) and "noncoherent" (looking like a pair of transparently overlaid gratings), and found clear intermodulation responses to compound stimuli, indicating nonlinear summation. This might have been attributed to cross-orientation suppression except that the pattern of intermodulation responses differed for coherent and noncoherent patterns, whereas the effects of suppression (measured at the component frequencies) did not. A two-stage model of nonlinear summation involving conjunction detection with a logical AND gate described the data well, capturing the difference between coherent and noncoherent plaids over a wide array of possible response frequencies. Multistimulus frequency-tagged EEG in combination with computational modeling may be a very valuable tool in studying the conjunction of these signals. In the current study the results suggest a second-order mechanism responding selectively to coherent plaid patterns.

Journal Article Type Article
Acceptance Date Mar 3, 2017
Online Publication Date May 24, 2017
Publication Date Jun 30, 2017
Deposit Date Jun 30, 2017
Publicly Available Date Jun 30, 2017
Journal Journal of Vision
Electronic ISSN 1534-7362
Publisher Association for Research in Vision and Ophthalmology
Peer Reviewed Peer Reviewed
Volume 17
Issue 5
Article Number 10
Keywords Vision, EEG, VEP, ssVEP, Neuroscience
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