Neural markers of predictive coding under perceptual uncertainty revealed with Hierarchical Frequency Tagging
Abstract
There is a growing understanding that both top-down and bottom-up signals underlie perception. But it is not known how these signals integrate with each other and how this depends on the perceived stimuli's predictability. 'Predictive coding' theories describe this integration in terms of how well top-down predictions fit with bottom-up sensory input. Identifying neural markers for such signal integration is therefore essential for the study of perception and predictive coding theories. To achieve this, we combined EEG methods that preferentially tag different levels in the visual hierarchy. Importantly, we examined intermodulation components as a measure of integration between these signals. Our results link the different signals to core aspects of predictive coding, and suggest that top-down predictions indeed integrate with bottom-up signals in a manner that is modulated by the predictability of the sensory input, providing evidence for predictive coding and opening new avenues to studying such interactions in perception.
Article and author information
Author details
Funding
Australian Research Council (DP130100194)
- Roger Koenig-Robert
- Naotsugu Tsuchiya
Australian Research Council (FT120100619)
- Naotsugu Tsuchiya
Australian Research Council (FT100100322)
- Jakob Hohwy
Australian Research Council (DP160102770)
- Jakob Hohwy
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Participants gave their written consent to participate in the experiment. Experimental procedures were approved by the Monash University Human Research Ethics Committee (CF12/2542 - 2012001375)
Reviewing Editor
- Klaas Enno Stephan, University of Zurich and ETH Zurich, Switzerland
Publication history
- Received: October 27, 2016
- Accepted: February 26, 2017
- Accepted Manuscript published: February 28, 2017 (version 1)
- Version of Record published: March 21, 2017 (version 2)
Copyright
© 2017, Gordon et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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