In Frontiers in Integrative Neuroscience: Emotional Theory of Rationality

Emotional Theory of Rationality. Mario Garcés and Lucila Finkel. Front. in Integrative Neuroscience, April 5 2019. https://doi.org/10.3389/fnint.2019.00011

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.

Introduction

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 then emotions even exist?

Much scientific research has addressed the different areas and capabilities of the nervous system. Most of those research lines have been focused on developing models able to explain the brain’s cognitive capacities, together with its structure and dynamics at different levels (for a review see Kriegeskorte and Douglas, 2018). On the other side, emotions long stayed out of the neuroscience focus, like a collateral effect that had no easy fit within those cognitive models.

However, since the last decades of the past century, an intense debate has been active about the function and the primacy of emotion or cognition in the mental processes (Lazarus, 1984; Zajonc, 1984). These two highly polarized positions made impossible to state which of them was correct, or what was the relationship among emotion and cognition, as many necessary reasoning elements to integrate them were left apart. Wider approaches have tried to integrate both into a complete scheme (Leventhal and Scherer, 1987; de Houwer and Hermans, 2010; Gross and Barrett, 2011; Damasio and Carvalho, 2013; Li et al., 2014; Scherer and Moors, 2019), some of which have become widely spread (Moors et al., 2013), and some have been even formalized (Hudlicka, 2017; Cominelli et al., 2018). Others have also tried to derive the emotion-cognition structure from a more physiological approach (Pessoa and Adolphs, 2010; Yang et al., 2014) But until now, the exact matching between emotion and cognition has not actually been completely solved.

The main problem for the proposed models to achieve that goal is that they must clearly explain not only the dynamics of emotion-cognition interaction for the most standard behaviors but also for the most extreme ones, such as reality distortion that occurs in many pathologies like in anorexia nervosa (e.g., Body Dysmorphic Disorders). Trying to explain those extreme psychological phenomena forces the models to their limits, highlighting their structural and functional lacks and inconsistencies. Until date, none of those functional models have been able to clearly explain such phenomena from an emotion-cognition paradigm.

Finding new routes to move forward sometimes entails taking a step back and following another perspective hitherto unexplored. The numerous structures, networks, and functional levels involved in the study of the human brain require us to take that step, seek more general principles to facilitate the integration of all those elements, and deduce important implications that would otherwise go unnoticed.

In this article, we reason a new architectural framework that, while making use of simple and commonsensical elements already explored, we combine them in a different structural design, thus introducing emotions and attention as a segmentation mechanism in the information processing structure, to add to the understanding of how brain operations are optimized. This framework gives support to a new functional model which can clearly explain the existence and persistence of those extreme non-adaptive or even anti-adaptive behaviors, together with the more standard ones.

The article is divided into two complementary sections that describe the full reasoning behind the proposed model, its functional structure, and dynamics.

In the first section, we use evolutionary reasoning to find general hierarchical principles that allow us to justify the features of the nervous system and the key variables that determine the quality of its operation. We analyze the interdependence between these variables, justifying the automaticity process, and the existence of three different levels of response. We then reason the existence of intrinsic resource limitations in the system and how these limitations give rise to the attentional mechanism. From this perspective, we define the concept and role of emotions and how they control and optimize the activation and operation of advanced cognitive mechanisms.

In the second section, we analyze the structure and dynamics of the model and the interactions that occur between its different functional elements. Later, we analyze the spectrum of possible cognitive responses and how they can operate over different functional elements of the model, thus leading to different behaviors and psychological phenomena.

In this article, we explore the set of possible cognitive responses, rather than cognitive mechanisms because it is beyond the scope and length of this work and will be addressed specifically in a future article.