Recent neurophysiological accounts of predictive coding hypothesized that a mismatch of prediction and sensory evidence-a prediction error (PE)-should be signaled by increased gamma-band activity (GBA) in the cortical area where prediction and evidence are compared. This hypothesis contrasts with alternative accounts where violated predictions should lead to reduced neural responses. We tested these hypotheses by violating predictions about face orientation and illumination direction in a Mooney face-detection task, while recording magnetoencephalographic responses in a large sample of 48 human subjects. The investigated predictions, acquired via lifelong experience, are known to be processed at different time points and brain regions during face recognition.Behavioral responses confirmed the induction of PEs by our task. Beamformer source analysis revealed an early PE signal for unexpected orientation in visual brain areas followed by a PE signal for unexpected illumination in areas involved in 3D shape from shading and spatial working memory. Both PE signals were reflected by increases in high-frequency (68 -140 Hz) GBA. In high-frequency GBA we also observed a late interaction effect in visual brain areas, probably corresponding to a high-level PE signal. In addition, increased high-frequency GBA for expected illumination was observed in brain areas involved in attention to internal representations. Our results strongly support the hypothesis that increased GBA signals PEs. Additionally, GBA may represent attentional effects.

Predictive coding suggests that the brain infers the causes of its sensations by combining sensory evidence with internal predictions based on available prior knowledge. However, the neurophysiological correlates of (pre)activated prior knowledge serving these predictions are still unknown. Based on the idea that such preactivated prior knowledge must be maintained until needed, we measured the amount of maintained information in neural signals via the active information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed source time courses from MEG recordings of 52 human subjects during the baseline of a Mooney face/house detection task. Preactivation of prior knowledge for faces showed as α-band-related and β-band-related AIS increases in content-specific areas; these AIS increases were behaviorally relevant in the brain's fusiform face area. Further, AIS allowed decoding of the cued category on a trial-by-trial basis. Our results support accounts indicating that activated prior knowledge and the corresponding predictions are signaled in low-frequency activity (<30 Hz). Our perception is not only determined by the information our eyes/retina and other sensory organs receive from the outside world, but strongly depends also on information already present in our brains, such as prior knowledge about specific situations or objects. A currently popular theory in neuroscience, predictive coding theory, suggests that this prior knowledge is used by the brain to form internal predictions about upcoming sensory information. However, neurophysiological evidence for this hypothesis is rare, mostly because this kind of evidence requires strong a priori assumptions about the specific predictions the brain makes and the brain areas involved. Using a novel, assumption-free approach, we find that face-related prior knowledge and the derived predictions are represented in low-frequency brain activity.

max 150 words) 14Predictive coding suggests that the brain infers the causes of its sensations by combining sensory 15 evidence with internal predictions based on available prior knowledge.However, the 16 neurophysiological correlates of (pre-)activated prior knowledge serving for predictions are still 17 unknown. Based on the idea that such pre-activated prior-knowledge must be maintained until 18 needed we measured the amount of maintained information in neural signals via the active 19 information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed 20 source time-courses from magnetoencephalography recordings of 52 human subjects during the 21 baseline of a Mooney face/house detection task. Pre-activation of prior knowledge for faces 22 showed as alpha-and beta-band related AIS increases in content specific areas; these AIS 23 increases were behaviourally relevant. Moreover, top-down transfer of predictions estimated by 24 transfer entropy was associated with beta frequencies. Our results support accounts that activated 25 prior knowledge and the corresponding predictions are signalled in low frequency activity (<30 Hz). 26 Acknowledgements: 27ABG received support by Ernst Ludwig Ehrlich Studienwerk (BMBF scholarship for graduate 28 students). GFP received support by Villigst Studienwerk (BMBF scholarship for graduate students). ). Predictive 35coding theory proposes that the brain constantly makes inferences about the state of the outside 36 world. This is supposed to be accomplished by building hierarchical internal predictions based on 37 2 prior knowledge which are compared to incoming information at each level of the cortical hierarchy 38 in order to continuously adapt and update these internal models (Mumford, 1992; Rao et al., 1999; 39 Friston, 2005Friston, , 2010 40The postulated use of predictions for inference requires several preparatory steps: First, task 41 relevant prior knowledge passively stored in synaptic weights needs to be transferred into activated 42 prior knowledge, i.e. information represented in neural activity in order to make this knowledge 43 available to other parts of the brain (see Zipser et al., 1993 for a distinction of active and passive 44 storage). Subsequently, (pre-)activated prior knowledge needs to be maintained until needed and 45 to be constantly transferred as a prediction in top-down direction to a lower area of the cortical 46 hierarchy, where it will be matched with the incoming information (e.g. Mumford, 1992; Friston, 47 2005 Friston, 47 , 2010. 48With respect to the neural correlates of activated prior knowledge and predictions we know that the 49 prediction of specific features or object categories increases fMRI BOLD activity in the brain region 50 at which the feature or category is usually processed (Puri et al., 2009; Esterman and Yantis, 2009; 51 Kok et al., 2014). However, only little is known about how the maintenance of pre-activated prior 52 knowledge and the corresponding transfer of predictions are actuall...