Hierarchical predictive coding in frontotemporal networks with pacemaker expectancies: evidence from dynamic causal modelling of Magnetoencephalography (MEG)

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Event Abstract Back to Event Hierarchical predictive coding in frontotemporal networks with pacemaker expectancies: evidence from dynamic causal modelling of Magnetoencephalography (MEG) Holly Phillips1, 2*, Alejandro Blenkmann3, 4, Laura Hughes2, 5, Tristan Bekinschtein2 and James Rowe2, 5 1 University of Cambridge, Department of Clinical Neurosciences, United Kingdom 2 University of Cambridge, MRC - Cognition and Brain Sciences Unit, UK 3 University of Buenos Aires, Center for Clinical and Experimental Neurosciences, IBCN ‘‘Dr. E. de Robertis’’, School of Medicine, Argentina 4 Ramos Mejía Hospital, Epilepsy Center, Department of Neurology, Argentina 5 University of Cambridge, Department of Clinical Neurosciences, UK Unexpected sensory events engage automatic local and distributed neurophysiological responses, evident in temporal and frontal cortical sources underlying the mismatch negativity (MMN, Näätänen et al. 2007). Dynamic causal modelling (DCM) of the MMN in electroencephalography (EEG, Garrido et al. 2009) and magnetoencephalography (MEG, Hughes et al. 2013) indicate a hierarchy of feedback sensory predictions and feedforward prediction errors, between primary auditory cortex (A1), superior temporal gyrus (STG) and prefrontal cortex (PFC). We posited that where temporal regularities in stimuli exist, an internal pacemaker may provide conditional expectations in PFC that supports high level predictions of auditory events in temporal cortices. Magnetoencephalography (MEG) in healthy adults was recorded during an auditory MMN paradigm (Näätänen et al. 2004), that alternated a standard tone with five deviant tone types (differing by frequency, intensity, location, duration or silent gap). 12 dynamic causal models (SPM8-DCM10) of networks among A1, STG and PFC, were compared using Bayesian model selection to examine first, the net effect of all deviants vs. standard tones, and second, the connectivity associated with the specific deviant types. The models of all deviant types that had greatest evidence included features of (i) bidirectional modulation of frontotemporal connectivity and (ii) a pacemaker signal acting on PFC. In the deviant specific models, those with the greatest evidence of a pacemaker signal, were those of the deviants defined by temporal structure differences (duration and gap), whereas other deviants had greater evidence without it. We confirm the presence of hierarchical frontotemporal networks in agreement with the prediction coding hypothesis, and provide new evidence for an internal pacemaker into PFC, which supports temporally defined predictions of sensory inputs. Keywords: Magnetoencephalography, predictive coding, effective connectivity, mismatch negativity, dynamic casual modelling Conference: XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014. Presentation Type: Poster Topic: Sensation and Perception Citation: Phillips H, Blenkmann A, Hughes L, Bekinschtein T and Rowe J (2015). Hierarchical predictive coding in frontotemporal networks with pacemaker expectancies: evidence from dynamic causal modelling of Magnetoencephalography (MEG). Conference Abstract: XII International Conference on Cognitive Neuroscience (ICON-XII). doi: 10.3389/conf.fnhum.2015.217.00377 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Feb 2015; Published Online: 24 Apr 2015. * Correspondence: Miss. Holly Phillips, University of Cambridge, Department of Clinical Neurosciences, Cambridge, United Kingdom, holly.phillips@mrc-cbu.cam.ac.uk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Holly Phillips Alejandro Blenkmann Laura Hughes Tristan Bekinschtein James Rowe Google Holly Phillips Alejandro Blenkmann Laura Hughes Tristan Bekinschtein James Rowe Google Scholar Holly Phillips Alejandro Blenkmann Laura Hughes Tristan Bekinschtein James Rowe PubMed Holly Phillips Alejandro Blenkmann Laura Hughes Tristan Bekinschtein James Rowe Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.