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  Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making

Park, H., Lueckmann, J.-M., von Kriegstein, K., Bitzer, S., & Kiebel, S. J. (2016). Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making. Scientific Reports, 6: 18832. doi:10.1038/srep18832.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-29F8-B Version Permalink: http://hdl.handle.net/21.11116/0000-0003-1DEA-6
Genre: Journal Article

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 Creators:
Park, Hame1, 2, Author              
Lueckmann, Jan-Matthis2, 3, Author
von Kriegstein, Katharina4, 5, Author              
Bitzer, Sebastian1, 2, Author              
Kiebel, Stefan J.1, 2, Author              
Affiliations:
1Department of Psychology, TU Dresden, Germany, ou_persistent22              
2Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
3Neural Computation and Behaviour Group, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ou_persistent22              
4Department of Psychology, Humboldt University Berlin, Germany, ou_persistent22              
5Max Planck Research Group Neural Mechanisms of Human Communication, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634556              

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 Abstract: Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models.

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Language(s): eng - English
 Dates: 2015-08-102015-11-182016-01-11
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/srep18832
PMID: 26752272
PMC: PMC4707533
 Degree: -

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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 6 Sequence Number: 18832 Start / End Page: - Identifier: Other: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322