Predictive processing account of action perception: evidence from effective connectivity in the actionobservation network

buir.contributor.authorÜrgen, Burcu A.
dc.citation.epage142en_US
dc.citation.spage132en_US
dc.citation.volumeNumber128en_US
dc.contributor.authorÜrgen, Burcu A.
dc.contributor.authorSaygın, A. P.
dc.date.accessioned2021-02-25T06:10:21Z
dc.date.available2021-02-25T06:10:21Z
dc.date.issued2020en_US
dc.departmentDepartment of Psychologyen_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.description.abstractVisual perception of actions is supported by a network of brain regions in the occipito-temporal, parietal, and premotor cortex in the primate brain, known as the Action Observation Network (AON). Although there is a growing body of research that characterizes the functional properties of each node of this network, the communication and direction of information flow between the nodes is unclear. According to the predictive coding account of action perception (Kilner, Friston, & Frith, 2007a; 2007b), this network is not a purely feedforward system but has backward connections through which prediction error signals are communicated between the regions of the AON. In the present study, we investigated the effective connectivity of the AON in an experimental setting where the human subjects' predictions about the observed agent were violated, using fMRI and Dynamical Causal Modeling (DCM). We specifically examined the influence of the lowest and highest nodes in the AON hierarchy, pSTS and ventral premotor cortex, respectively, on the middle node, inferior parietal cortex during prediction violation. Our DCM results suggest that the influence on the inferior parietal node is through a feedback connection from ventral premotor cortex during perception of actions that violate people's predictions.en_US
dc.description.provenanceSubmitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2021-02-25T06:10:21Z No. of bitstreams: 1 Predictive_processing_account_of_action_perception_Evidence_from_effective_connectivity_in_the_action_observation_network.pdf: 1782505 bytes, checksum: 4f838899ba6a10a7a3f8bdc99f289cbc (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-25T06:10:21Z (GMT). No. of bitstreams: 1 Predictive_processing_account_of_action_perception_Evidence_from_effective_connectivity_in_the_action_observation_network.pdf: 1782505 bytes, checksum: 4f838899ba6a10a7a3f8bdc99f289cbc (MD5) Previous issue date: 2020-03en
dc.embargo.release2021-03-17
dc.identifier.doi10.1016/j.cortex.2020.03.014en_US
dc.identifier.issn0010-9452
dc.identifier.urihttp://hdl.handle.net/11693/75569
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/j.cortex.2020.03.014en_US
dc.source.titleCortexen_US
dc.subjectAction perceptionen_US
dc.subjectfMRIen_US
dc.subjectDynamical causal modelingen_US
dc.subjectPredictive codingen_US
dc.titlePredictive processing account of action perception: evidence from effective connectivity in the actionobservation networken_US
dc.typeArticleen_US

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