4.7 Article

Dynamic causal modelling of effective connectivity during perspective taking in a communicative task

Journal

NEUROIMAGE
Volume 76, Issue 1, Pages 116-124

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.02.072

Keywords

Dynamic causal modelling; Effective connectivity; Theory of mind; Perspective taking; Social brain; Exhaustive modelling; Hierarchical predictive coding

Funding

  1. Royal Society
  2. European Commission
  3. University College London
  4. Charlotte and Yule Bogue Research Fellowship

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Previous studies have shown that taking into account another person's perspective to guide decisions is more difficult when their perspective is incongruent from one's own compared to when it is congruent. Here we used dynamic causal modelling (DCM) for functional magnetic resonance imaging (fMRI) to investigate effective connectivity between prefrontal and posterior brain regions in a task that requires participants to take into account another person's perspective in order to guide the selection of an action. Using a new procedure to score model evidence without computationally costly estimation, we conducted an exhaustive search for the best of all possible models. The results elucidate how the activity in the areas from our previously reported analysis (Dumontheil et al., 2010) are causally linked and how the connections are modulated by both the social as well as executive task demands of the task. We find that the social demands modulate the backward connections from the medial prefrontal cortex (MPFC) more strongly than the forward connections from the superior occipital gyrus (SOG) and the medial temporal gyrus (MTG) to the MPFC. This was also the case for the backward connection from the MTG to the SOG. Conversely, the executive task demands modulated the forward connections of the SOG and the MTG to the MPFC more strongly than the backward connections. We interpret the results in terms of hierarchical predictive coding. (C) 2013 Elsevier Inc. All rights reserved.

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