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However, in most studies this cannot be disentangled from the valence as the prediction error associated with a negative stimulus per se cannot be disentangled from the prediction error in the individual experimental setting. general low probability of a negative encounter) that negative stimuli entail. Results interpreting the effects of negative valence in the gamma band could be associated with the surprise (i.e. a negative and thus unexpected state) produce larger gamma responses than neutral and positive visual stimuli 7, 8, 9, 10, 11, 12, 13, 14, 15, 16. With regards to affective stimuli, this agrees with findings showing that visual stimuli with a negative valence (i.e.
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The Free Energy principle including aspects of predictive coding specifically posits the minimization of “free energy” (and thus, indirectly prediction errors) as a mechanism to ensure that agents spend most of their time in a small number of valuable (i.e. Consequently, a system can refine models with better predictions by minimizing prediction errors regarding the sensory environment, leading to a more efficient encoding of information 6. Predictive coding of perception assumes that neuronal circuits implement perception and learning by constantly matching incoming sensory data with the top-down predictions of an internal or generative model 3, 4, 5.
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Utilizing time–frequency analysis of brain data, it has been shown for example that famous faces elicit larger gamma responses as compared to unfamiliar faces 1, 2. People see hundreds of unfamiliar faces in daily life, while seeing famous faces is very rare and surprising and-in terms of predictive coding-unexpected, leading to a large prediction error. This study provides direct experimental evidence that negative affective picture processing can be described by neuronal predictive coding computations. This demonstrates that top-down predictions and bottom-up prediction errors are represented in typical spectral patterns associated with affective picture processing. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to increases in alpha, beta and gamma band activity. Our data show that alpha-to-beta band activity after stimulus presentation was related to the expected valence of the stimulus as predicted by a cue. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS).