Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means that the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes.

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旧思想的新标签：预测处理和神经信号的解释

预测处理的哲学支持者根据神经信号的功能作用和信息内容方面的差异，铸造了感知预测模型的新颖性。但是，它们无法为如何确定从信号到其信息内容的关键语义映射提供约束。除了在神经信号上具有新颖的解释性含义外，它们对于系统的因果结构甚至信号所携带的统计信息几乎没有什么新鲜的说法。这意味着可以用传统的非预测性术语重新标记感知的预测框架，而不会与现有或未来数据相关的经验后果。在某种程度上，基于预测性处理的神经科学研究既具有创新性又能产生成果，