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  Dissociating dynamic probability and predictability in observed actions: An fMRI study

Ahlheim, C., Stadler, W., & Schubotz, R. I. (2014). Dissociating dynamic probability and predictability in observed actions: An fMRI study. Frontiers in Human Neuroscience, 8: 273. doi:10.3389/fnhum.2014.00273.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-001A-27E0-D Version Permalink: http://hdl.handle.net/21.11116/0000-0003-8026-1
Genre: Journal Article

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 Creators:
Ahlheim, Christiane1, 2, Author
Stadler, Waltraud3, 4, Author              
Schubotz, Ricarda Ines1, 2, Author              
Affiliations:
1Institute for Psychology, Münster University, Germany, ou_persistent22              
2Motor Cognition Group, Max Planck Institute for Neurological Research, Cologne, Germany, ou_persistent22              
3Department of Sport and Health Science, TU Munich, Germany, ou_persistent22              
4Department Psychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634564              

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Free keywords: Statistical learning; Action observation; Orbitofrontal cortex; dmPFC; fMRI; Information theory
 Abstract: The present fMRI study investigated whether human observers spontaneously exploit the statistical structure underlying continuous action sequences. In particular, we tested whether two different statistical properties can be distinguished with regard to their neural correlates: an action step’s predictability and its probability. To assess these properties we used measures from information theory. Predictability of action steps was operationalized by its inverse, conditional entropy, which combines the number of possible action steps with their respective probabilities. Probability of action steps was assessed using conditional surprisal, which increases with decreasing probability. Participants were trained in an action observation paradigm with video clips showing sequences of 9–33s length with varying numbers of action steps that were statistically structured according to a Markov chain. Behavioral tests revealed that participants implicitly learned this statistical structure, showing that humans are sensitive toward these probabilistic regularities. Surprisal (lower probability) enhanced the BOLD signal in the anterior intraparietal sulcus. In contrast, high conditional entropy, i.e., low predictability, was correlated with higher activity in dorsomedial prefrontal cortex, orbitofrontal gyrus, and posterior intraparietal sulcus. Furthermore, we found a correlation between the anterior hippocampus’ response to conditional entropy with the extent of learning, such that the more participants had learnt the structure, the greater the magnitude of hippocampus activation in response to conditional entropy. Findings show that two aspects of predictions can be dissociated: an action’s predictability is reflected in a top-down modulation of attentional focus, evident in increased fronto-parietal activation. In contrast, an action’s probability depends on the identity of the stimulus itself, resulting in bottom-up driven processing costs in the parietal cortex.

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Language(s): eng - English
 Dates: 2014-02-102014-04-122014-05-07
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.3389/fnhum.2014.00273
PMID: 24847235
PMC: PMC4019881
Other: eCollection 2014
 Degree: -

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Title: Frontiers in Human Neuroscience
  Abbreviation : Front Hum Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 8 Sequence Number: 273 Start / End Page: - Identifier: ISSN: 1662-5161
CoNE: https://pure.mpg.de/cone/journals/resource/1662-5161