Predictive regulation and human design

Sterling, Peter

doi:10.7554/elife.36133

Cited by 14 publications

(6 citation statements)

References 43 publications

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“…This predictive regulation is called allostasis (Schulkin, 2011;Sterling, 2012Sterling, , 2018Sterling & Eyer, 1988), where a brain anticipates the needs of the body and attempts to satisfy those needs before they arise, minimizing costly errors. For instance, organisms should be motivated to forage before vital metabolic parameters (e.g.…”

Section: Allostatic Regulation: the Brain Is A Predictive Modelmentioning

confidence: 99%

The sense of should: A biologically-based framework for modeling social pressure

Theriault

Young

Barrett

2021

Physics of Life Reviews

107

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We develop a model of social pressure, based on the metabolic costs of information. • We propose that conformity regulates the predictability of social environments. • We suggest that the experience of obligation stems from anticipated uncertainty. • We integrate disparate theories of mental inference with an embodied account. • We discuss the emergent consequences of others' expectations motivating behavior.

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Section: Allostatic Regulation: the Brain Is A Predictive Modelmentioning

confidence: 99%

The sense of should: A biologically-based framework for modeling social pressure

Theriault

Young

Barrett

2021

Physics of Life Reviews

107

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“…When, following some effort, we find something better than expected, the circuit delivers a pulse of dopamine that allows a pause to our seeking--but only briefly--because seeking must resume in order to serve the next need. Dopamine cannot be commanded but only obtained from effortful activities that deliver positive surprises (Sterling 2018).…”

Section: Obesitymentioning

confidence: 99%

What Can the Health Humanities Contribute to Our Societal Understanding of and Response to the Deaths of Despair Crisis?

et al. 2023

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Deaths of Despair (DoD), or mortality resulting from suicide, drug overdose, and alcohol-related liver disease, have been rising steadily in the United States over the last several decades. In 2020, a record 186,763 annual despair-related deaths were documented, contributing to the longest sustained decline in US life expectancy since 1915–1918. This forum feature considers how health humanities disciplines might fruitfully engage with this era-defining public health catastrophe and help society better understand and respond to the crisis.

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“…Reactive homeostasis generates neural representations of internal body states (Quadt et al, 2018). These representations in turn are inputs for allostatic driven prediction (Sterling, 2018). These predictions are effective because they inevitably have a memorial basis, being largely derived from experiential‐based learning (Petzschner et al, 2021).…”

Section: Extensions: Human Thermoregulationmentioning

confidence: 99%

Depth and hierarchies in the predictive brain: From reaction to action

Muzik

Diwadkar

2023

WIRES Cognitive Science

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The human brain is a prediction device, a view widely accepted in neuroscience. Prediction is a rational and efficient response that relies on the brain's ability to create and employ generative models to optimize actions over unpredictable time horizons. We argue that extant predictive frameworks while compelling, have not explicitly accounted for the following: (a) The brain's generative models must incorporate predictive depth (i.e., rely on degrees of abstraction to enable predictions over different time horizons); (b) The brain's implementation scheme to account for varying predictive depth relies on dynamic predictive hierarchies formed using the brain's functional networks. We show that these hierarchies incorporate the ascending processes (driven by reaction), and the descending processes (related to prediction), eventually driving action. Because they are dynamically formed, predictive hierarchies allow the brain to address predictive challenges in virtually any domain. By way of application, we explain how this framework can be applied to heretofore poorly understood processes of human behavioral thermoregulation. Although mammalian thermoregulation has been closely tied to deep brain structures engaged in autonomic control such as the hypothalamus, this narrow conception does not translate well to humans. In addition to profound differences in evolutionary history, the human brain is bestowed with substantially increased functional complexity (that itself emerged from evolutionary differences). We argue that behavioral thermoregulation in humans is possible because, (a) ascending signals shaped by homeostatic sub‐networks, interject with (b) descending signals related to prediction (implemented in interoceptive and executive sub‐networks) and action (implemented in executive sub‐networks). These sub‐networks cumulatively form a predictive hierarchy for human thermoregulation, potentiating a range of viable responses to known and unknown thermoregulatory challenges. We suggest that our proposed extensions to the predictive framework provide a set of generalizable principles that can further illuminate the many facets of the predictive brain.This article is categorized under: Neuroscience > Behavior Philosophy > Action Psychology > Prediction

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Predictive regulation and human design

Cited by 14 publications

References 43 publications

The sense of should: A biologically-based framework for modeling social pressure

The sense of should: A biologically-based framework for modeling social pressure

What Can the Health Humanities Contribute to Our Societal Understanding of and Response to the Deaths of Despair Crisis?

Depth and hierarchies in the predictive brain: From reaction to action

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