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  Differential neural mechanisms for early and late prediction error detection

Malekshahi, R., Seth, A., Papanikolaou, A., Mathews, Z., Birbaumer, N., Verschure, P., et al. (2016). Differential neural mechanisms for early and late prediction error detection. Scientific Reports, 6(24350), 1-13. doi:10.1038/srep24350.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-79E6-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-79E7-4
Genre: Journal Article

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Malekshahi, R1, Author              
Seth, A, Author
Papanikolaou, A1, Author              
Mathews, Z, Author
Birbaumer, N, Author
Verschure, PF, Author
Caria, A, Author
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

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 Abstract: Emerging evidence indicates that prediction, instantiated at different perceptual levels, facilitate visual processing and enable prompt and appropriate reactions. Until now, the mechanisms underlying the effect of predictive coding at different stages of visual processing have still remained unclear. Here, we aimed to investigate early and late processing of spatial prediction violation by performing combined recordings of saccadic eye movements and fast event-related fMRI during a continuous visual detection task. Psychophysical reverse correlation analysis revealed that the degree of mismatch between current perceptual input and prior expectations is mainly processed at late rather than early stage, which is instead responsible for fast but general prediction error detection. Furthermore, our results suggest that conscious late detection of deviant stimuli is elicited by the assessment of prediction error’s extent more than by prediction error per se. Functional MRI and functional connectivity data analyses indicated that higher-level brain systems interactions modulate conscious detection of prediction error through top-down processes for the analysis of its representational content, and possibly regulate subsequent adaptation of predictive models. Overall, our experimental paradigm allowed to dissect explicit from implicit behavioral and neural responses to deviant stimuli in terms of their reliance on predictive models.

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 Dates: 2016-04
 Publication Status: Published in print
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 Identifiers: DOI: 10.1038/srep24350
BibTex Citekey: MalekshahiSPMBVC2016
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Title: Scientific Reports
Source Genre: Journal
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Pages: - Volume / Issue: 6 (24350) Sequence Number: - Start / End Page: 1 - 13 Identifier: -