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

PHILLIPS HOLLY; BLENKMANN ALEJANDRO; HUGHES LAURA; BEKINSCHTEIN TRISTAN; ROWE JAMES

Brisbane

Conferencia; XII International Conference on Cognitive Neuroscience (ICON-XII); 2014

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.