Degeneracy and Redundancy in Active Inference.
Degeneracy and Redundancy in Active Inference.
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DOI：
10.1093/cercor/bhaa148
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发表时间：
2020-10-01
期刊：
影响因子：
--
通讯作者：
Friston KJ
中科院分区：
文献类型：
--
作者：
Sajid N;Parr T;Hope TM;Price CJ;Friston KJ
从基因组学到网络科学，简并和冗余的概念在许多领域都是重要的概念。退化在神经科学中发挥着强大的作用，它解释了大脑中分布式处理和结构-功能关系的关键方面。例如，在“多对一”的结构-功能映射中，退化解释了病变对功能缺陷的超加性效应。在这篇文章中，我们提供了一个原则性的解释，当函数被主动推理操作时，即在世界的生成模型下，感知和行动作为信念更新的公式。简而言之，“退化”是由关于感觉原因的后验信念的“熵”来量化的，而“冗余”是形成这些信念所产生的“复杂性”成本。从这个角度来看，简并性和冗余性是互补的：主动推理试图在保持简并性的同时尽量减少冗余。这一表述使用退化映射和统计效率的统计和数学概念得到了证实。然后，我们举例说明在单词重复任务的学习过程中简并性和冗余性的变化。最后，我们描述了硅胶断开中损伤对内在和外在连接的影响。这些数字分析突出了退化和冗余之间的根本区别--以及它们如何为与合成和生物智能相关的知觉推理和结构学习的不同需求评分。
The notions of degeneracy and redundancy are important constructs in many areas, ranging from genomics through to network science. Degeneracy finds a powerful role in neuroscience, explaining key aspects of distributed processing and structure–function relationships in the brain. For example, degeneracy accounts for the superadditive effect of lesions on functional deficits in terms of a “many-to-one” structure–function mapping. In this paper, we offer a principled account of degeneracy and redundancy, when function is operationalized in terms of active inference, namely, a formulation of perception and action as belief updating under generative models of the world. In brief, “degeneracy” is quantified by the “entropy” of posterior beliefs about the causes of sensations, while “redundancy” is the “complexity” cost incurred by forming those beliefs. From this perspective, degeneracy and redundancy are complementary: Active inference tries to minimize redundancy while maintaining degeneracy. This formulation is substantiated using statistical and mathematical notions of degenerate mappings and statistical efficiency. We then illustrate changes in degeneracy and redundancy during the learning of a word repetition task. Finally, we characterize the effects of lesions—to intrinsic and extrinsic connections—using in silico disconnections. These numerical analyses highlight the fundamental difference between degeneracy and redundancy—and how they score distinct imperatives for perceptual inference and structure learning that are relevant to synthetic and biological intelligence.
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影响因子：
16.2
作者：
Bastos AM;Usrey WM;Adams RA;Mangun GR;Fries P;Friston KJ
通讯作者：
Friston KJ
影响因子：
5.7
作者：
Cropper EC;Dacks AM;Weiss KR
通讯作者：
Weiss KR
影响因子：
2.9
作者：
Friston, Karl;FitzGerald, Thomas;Pezzulo, Giovanni
通讯作者：
Pezzulo, Giovanni
影响因子：
2.5
作者：
Burton, MW;Noll, DC;Small, SL
通讯作者：
Small, SL
DOI：
10.1016/j.clinph.2008.11.029
发表时间：
2009-03
期刊：
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
影响因子：
--
作者：
Garrido MI;Kilner JM;Stephan KE;Friston KJ
通讯作者：
Friston KJ