Resolving the Mystery of Emotions: The Evolutionary Purpose of Emotions

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Auteur principal: Biro, Chris
Format: Recurso digital
Langue:anglais
Publié: Zenodo 2026
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author Biro, Chris
author_facet Biro, Chris
contents <p>This article establishes in comprehensive detail the evolutionary history, purpose, and function of emotions within the self-interest framework introduced in the companion papers [1,2,3]. Emotions are conceptualized as an ultra-fast subcortical categorization system that originated from single-cell self/not-self valuation mechanisms and were augmented, but not replaced, by subsequent brain evolution. This system enables rapid classification of stimuli into categories critical for survival: things to ignore, things to pursue, things to avoid, things to keep close, and things to escape. Distinct from conscious feelings, which serve as neocortical gauges of emotional states, emotions function as physical, pre-conscious modulators that prune perceptual chaos, optimizing behavioral efficiency without prohibitive energetic costs. Drawing from first principles and empirical insights from parrot reintroduction projects, this framework fully explicates emotions as a foundational component of agency behaviors, distinguishing them from non-agentic reactions and reflexes. The article also details the interaction of emotions with single-repetition and multi-repetition learning processes, where emotions facilitate speed in threat detection and accuracy in routine refinement, with supporting evidence from pharmacological studies using propranolol that demonstrate the role of noradrenergic signaling in emotional tagging and memory enhancement. Implications extend to artificial systems, where current emerging artificial behavior lacks equivalent tagging mechanisms, leading to brittleness and inefficiency, while thresholds for machine intelligence require incorporating emotion analogs for motive-driven pruning and ethical alignment. By providing detailed explanations of each concept—this paper modifies psychological concepts of emotions, emphasizing their emergence from self-interest-driven automation.</p>
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language eng
publishDate 2026
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spellingShingle Resolving the Mystery of Emotions: The Evolutionary Purpose of Emotions
Biro, Chris
emotions
evolutionary history
rapid classification system
machine intelligence
artificial behavior
behavioral theory
single-repetition learning
multi-repetition learning
self-interest
perceptual pruning
propranolol
noradrenergic modulation
parrot conservation
cached pattern library
CPL
RSC
congruence verification architecture
energy efficiency
beginning stages of genuine behavior
<p>This article establishes in comprehensive detail the evolutionary history, purpose, and function of emotions within the self-interest framework introduced in the companion papers [1,2,3]. Emotions are conceptualized as an ultra-fast subcortical categorization system that originated from single-cell self/not-self valuation mechanisms and were augmented, but not replaced, by subsequent brain evolution. This system enables rapid classification of stimuli into categories critical for survival: things to ignore, things to pursue, things to avoid, things to keep close, and things to escape. Distinct from conscious feelings, which serve as neocortical gauges of emotional states, emotions function as physical, pre-conscious modulators that prune perceptual chaos, optimizing behavioral efficiency without prohibitive energetic costs. Drawing from first principles and empirical insights from parrot reintroduction projects, this framework fully explicates emotions as a foundational component of agency behaviors, distinguishing them from non-agentic reactions and reflexes. The article also details the interaction of emotions with single-repetition and multi-repetition learning processes, where emotions facilitate speed in threat detection and accuracy in routine refinement, with supporting evidence from pharmacological studies using propranolol that demonstrate the role of noradrenergic signaling in emotional tagging and memory enhancement. Implications extend to artificial systems, where current emerging artificial behavior lacks equivalent tagging mechanisms, leading to brittleness and inefficiency, while thresholds for machine intelligence require incorporating emotion analogs for motive-driven pruning and ethical alignment. By providing detailed explanations of each concept—this paper modifies psychological concepts of emotions, emphasizing their emergence from self-interest-driven automation.</p>
title Resolving the Mystery of Emotions: The Evolutionary Purpose of Emotions
topic emotions
evolutionary history
rapid classification system
machine intelligence
artificial behavior
behavioral theory
single-repetition learning
multi-repetition learning
self-interest
perceptual pruning
propranolol
noradrenergic modulation
parrot conservation
cached pattern library
CPL
RSC
congruence verification architecture
energy efficiency
beginning stages of genuine behavior
url https://doi.org/10.5281/zenodo.19617033