.png){kind=icon}
返回
Predictive processing models and affective neuroscience
.png){kind=icon}
OA
AI
DOI：10.1016/j.neubiorev.2021.09.009.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Predictive processing
Predictive coding
Subjective experience
Ecological validity
External validity
Valence
Degeneracy
Reverse inference
Experimental design
fMR
Arousal
Emotion
MVPA
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
N
IF:
7.9
论文数:
6.1K
被引数:
4.5W
机构
引用论文
分享收藏THE DOPAMINE SYNAPSE AND THE NOTION OF PLEASURE CENTERS IN THE BRAIN.png)
TRENDS IN NEUROSCIENCES
TRENDS IN NEUROSCIENCESIF15.1
PREAI
分享收藏
查看更多内容