Abstract
In recent decades, the existence of a close relationship between emotional phenomena and rational processes has certainly been established, yet there is still no unified definition or effective model to describe them. To advance our understanding of the mechanisms governing the behavior of living beings, we must integrate multiple theories, experiments, and models from both fields. In this article we propose a new theoretical framework that allows integrating and understanding the emotion–cognition duality, from a functional point of view. Based on evolutionary principles, our reasoning adds to the definition and understanding of emotion, justifying its origin, explaining its mission and dynamics, and linking it to higher cognitive processes, mainly with attention, cognition, decision-making, and consciousness. According to our theory, emotions are the mechanism for brain function optimization, aside from the contingency and stimuli prioritization system. As a result of this approach, we have developed a dynamic systems-level model capable of providing plausible explanations for certain psychological and behavioral phenomena and establishing a new framework for the scientific definition of some fundamental psychological terms.
Highlights
What is the relationship between emotion and cognition? If emotions have been historically considered as a ‘‘noisy interference’’ for cognitive processes (Simon, 1967), why does emotions even exist?Much scientific research has addressed the different areas and capabilities of the nervous system
If we take the sensations, perceptions, concepts, metaconcepts, and their associations and consider the different emotional–cognitive processes that act on them as agents competing to minimize their own emotional tension, we can postulate that the brain process of decision-making takes the form of what in game theory is known as a Nash equilibrium (Nash, 1950, 1951)
Throughout this article, we have followed a logical reasoning to support our hypothesis that emotions are an innate resource for nervous system optimization
Summary
What is the relationship between emotion and cognition? If emotions have been historically considered as a ‘‘noisy interference’’ for cognitive processes (Simon, 1967), why does emotions even exist?. The most significant characteristics of automated responses are that the sensory events almost always elicit behavior; are resistant to dual-task interference, that is, the behavior can be executed successfully while the subject is simultaneously engaged in some other demanding secondary task (Posner and Snyder, 1975; Logan, 1979); are behaviorally inflexible; and are unaffected by reward devaluation (Ashby and Crossley, 2012) Based on this definition, we outline the Automaticity Principle as follows: as a result of its own mechanisms of growth and development, and in order to fully optimize their effectiveness and efficiency, the nervous system will automate, as much as possible, the new circuits and neural networks that encode a stimulus recognition, calculation, and execution of the response associated with it. We have seen how, to improve performance, the nervous system has developed multiple biological mechanisms in architecture and dynamics (memory, pattern recognition, predictive systems, feedback, feedforward, mirror system, automaticity) and different levels of response (innate, cognitive, and automated) that allow it to optimize the three critical variables (activation threshold, reaction time and accuracy) and their interdependence. Consciousness will be considered as an emergent phenomenon and a final stage in information processing, which shows the results of lower levels of processing (Libet et al, 1983; Libet, 1999, 2004; Haynes and Rees, 2006; Soon et al, 2008; Haynes, 2011)
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