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Uncovering perceptual awareness of visual stimulus with adaptive multiscale entropy

To probe the perceptual awareness of a visual stimulus, we use the paradigm of generalized flash suppression (GFS) to dissociate physical stimulation from perceptual experience. This perceptual suppression approach has previously been used to investigate perceptual visibility correlates in visual cortex, mainly with linear methods, such as spectral analysis. While meaningful, the linear method alone may be insufficient for the full assessment of neural dynamics due to the fundamentally nonlinear nature of neural signal. In this contribution, we set forth to analyze local field potential (LFP) data collected from the multiple visual areas in V1, V2 and V4 of a macaque monkey while performing the GFS task using nonlinear method - adaptive multiscale entropy (AME) - to study the neural dynamics of perceptual suppression. We also propose a new cross-entropy measure at multiple scales, namely adaptive multiscale cross-entropy (AMCE), to assess the nonlinear interdependency between cortical areas. We show that: (1) multiscale entropy exhibits perception-related changes in all three areas, with higher entropy (i.e. higher complexity) observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating decreased neuronal interdependency between areas. Our findings demonstrate that the adaptive multiscale entropy is a sensitive measure of perceptual visibility, and thus can be used to uncover perceptual awareness of a stimulus.