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|Title:||Prefrontal cortex activation reflects efficient exploitation of higher-order statistical structure|
|Keywords:||Action observation;Anterior prefrontal cortex;BA 10;Information theory;Statistical learning|
|Citation:||Journal of Cognitive Neuroscience, 28(12): pp. 1-14, (2016)|
|Abstract:||Since everyday actions are statistically structured, knowing which action a person has just completed allows predicting the most likely next action step. Taking even more than the preceding action into account improves this predictability, but also causes higher processing costs. Using fMRI, we investigated whether observers exploit 2nd-order statistical regularities preferentially if information on possible upcoming actions provided by 1st-order regularities is insufficient. We hypothesized that anterior prefrontal cortex balances whether or not 2nd order information should be exploited. Participants watched videos of actions that were structured by 1st- and 2nd-order conditional probabilities. Information provided by the 1st and by the 2nd order was manipulated independently. BOLD activity in the action observation network was more attenuated the more information on upcoming actions was provided by 1st- order structure, reflecting expectation suppression for more predictable actions. Activation in posterior parietal sites decreased further with 2nd-order information, but increased in temporal areas. As expected, 2nd-order information was integrated more when less 1st-order information was provided, and this interaction was mediated by anterior prefrontal cortex (BA 10). Observers spontaneously used both the present and the preceding action to predict the upcoming action, and integration of the preceding action was enhanced when the present action was uninformative.|
|Appears in Collections:||Dept of Life Sciences Research Papers|
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