Human regulatory systems in the age of abundance: A predictive processing perspective

IF 4.1 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Otto Muzik, Vaibhav A. Diwadkar
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引用次数: 0

Abstract

Human regulatory systems largely evolved under conditions of food and information scarcity but are now being forced to deal with abundance. The impact of abundance and the inability of human regulatory systems to adapt to it have fed a surge in dual health challenges: (1) a rise in obesity related to food abundance and (2) a rise in stress and anxiety related to information abundance. No single framework has been developed to describe why and how the transition from scarcity to abundance has been so challenging. Here, we provide a speculative model based on predictive processing. We suggest that whereas scarcity (above destructive lower bounds like famine or information voids) preserves the fidelity of the relationship between prediction errors and predictions, abundance distorts this relationship. Furthermore, prediction error minimization is enhanced under scarcity (as the number of competing states in the niche is restricted), whereas the opposite is true under abundance. We also discuss how abundance warps the fundamental drive for seeking novelty by fueling the brain's exploration (as opposed to exploitation) mode. Ameliorative strategies for regulating food and information abundance may largely depend on simulating scarcity, that environmental condition to which human regulatory systems have adapted over millennia.

Abstract Image

Abstract Image

丰富时代的人类调节系统:预测处理视角
人类调节系统在很大程度上是在食物和信息匮乏的条件下发展起来的,但现在却被迫应对食物和信息的丰富。丰富的影响和人类调节系统无法适应它,导致了双重健康挑战的激增:(1)与食物丰富相关的肥胖增加;(2)与信息丰富相关的压力和焦虑增加。目前还没有一个单一的框架来描述为什么以及如何从稀缺到丰富的转变如此具有挑战性。在这里,我们提供了一个基于预测处理的推测模型。我们认为,尽管稀缺性(高于饥荒或信息缺失等破坏性下限)保留了预测误差和预测之间关系的保真度,但丰富性扭曲了这种关系。此外,在稀缺条件下(生态位中竞争状态的数量受到限制),预测误差最小化得到增强,而在丰富条件下则相反。我们还讨论了丰富是如何通过刺激大脑的探索(而不是利用)模式来扭曲寻求新奇事物的基本动力的。调节食物和信息丰富性的改良策略可能在很大程度上依赖于模拟稀缺性,这是人类调节系统几千年来已经适应的环境条件。
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来源期刊
Annals of the New York Academy of Sciences
Annals of the New York Academy of Sciences 综合性期刊-综合性期刊
CiteScore
11.00
自引率
1.90%
发文量
193
审稿时长
2-4 weeks
期刊介绍: Published on behalf of the New York Academy of Sciences, Annals of the New York Academy of Sciences provides multidisciplinary perspectives on research of current scientific interest with far-reaching implications for the wider scientific community and society at large. Each special issue assembles the best thinking of key contributors to a field of investigation at a time when emerging developments offer the promise of new insight. Individually themed, Annals special issues stimulate new ways to think about science by providing a neutral forum for discourse—within and across many institutions and fields.
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