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Predictive processing models and affective neuroscience
[摘要] The neural bases of affective experience remain elusive. Early neuroscience models of affect searched for specific brain regions that uniquely carried out the computations that underlie dimensions of valence and arousal. However, a growing body of work has failed to identify these circuits. Research turned to multivariate analyses, but these strategies, too, have made limited progress. Predictive processing models offer exciting new directions to address this problem. Here, we use predictive processing models as a lens to critique prevailing functional neuroimaging research practices in affective neuroscience. Our review highlights how much work relies on rigid assumptions that are inconsistent with a predictive processing approach. We outline the central aspects of a predictive processing model and draw out their implications for research in affective and cognitive neuroscience. Predictive models motivate a reformulation of reverse inference in cognitive neuroscience, and placing a greater emphasis on external validity in experimental design.
[发布日期] 2021-12-01 [发布机构] 
[效力级别]  [学科分类] 
[关键词] Predictive processing;Predictive coding;Subjective experience;Ecological validity;External validity;Valence;Degeneracy;Reverse inference;Experimental design;fMR;Arousal;Emotion;MVPA [时效性] 
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