AFFECTIVE INTELLIGENCE: COGNITIVE-
EMOTIONAL ARCHITECTURE OF
INTERSUBJECTIVE COHERENCE
INTELIGÊNCIA AFETIVA: ARQUITETURA COGNITIVO-
EMOCIONAL DA COERÊNCIA INTERSUBJETIVA
Fabiano de Abreu Agrela Rodrigues
Centro de Pesquisa e Análises Heráclito (CPAH)
Adriel Pereira da Silva
Centro de Pesquisa e Análises Heráclito (CPAH)
Flávio da Silva Nunes
Faculdade Metropolitana de São Paulo

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DOI: https://doi.org/10.37811/cl_rcm.v9i3.18442
Affective Intelligence: Cognitive-Emotional Architecture of Intersubjective
Coherence
Dr. Fabiano de Abreu Agrela Rodrigues 1
contato@cpah.com.br
https://orcid.org/0000-0002-5487-5852
Centro de Pesquisa e Análises Heráclito (CPAH),
Departamento de Neurociências e Genômica,
Brasil & Portugal
Adriel Pereira da Silva
contato@cpah.com.br
https://orcid.org/0009-0003-1157-8318
Centro de Pesquisa e Análises Heráclito (CPAH)
Departamento de Física, Brasil & Portugal
Flávio da Silva Nunes
flavionunes.oficiall@gmail.com
https://orcid.org/0000-0001-8481-907X
Faculdade Metropolitana de São Paulo
ABSTRACT
This article proposes the concept of Affective Intelligence (AI) as a distinct neurofunctional capacity
responsible for the integration of affective states into processes of judgment, action, and applied
morality. AI is not limited to emotional regulation but encompasses the ability to incorporate emotions
into reasoning and complex social interaction. The neurobiological foundation of AI lies in the synergy
between cortical and subcortical systems, including the orbitofrontal cortex, ventromedial prefrontal
cortex, anterior cingulate cortex, temporoparietal junction, and anterior insula. The functional
architecture of AI involves the integration rather than suppression of emotions, empathic proactivity,
intrapersonal and interpersonal coherence, and moral affective signaling. This work delineates the
concept of AI in relation to emotional intelligence and empathy, exploring its clinical, social, and
cognitive implications. It concludes that AI broadens the paradigm of human cognition, integrating
emotion, morality, and social adaptability into a structuring function.
Keywords: affective intelligence, neuroscience, emotions, morality, social cognition
1 Autor Principal
Correspondencia: contato@cpah.com.br

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Inteligência Afetiva: Arquitetura Cognitivo-Emocional da Coerência
Intersubjetiva
RESUMO
Este artigo propõe o conceito de Inteligência Afetiva (IA) como uma capacidade neurofuncional distinta,
responsável pela integração de estados afetivos nos processos de julgamento, ação e moralidade
aplicada. A IA não se limita à regulação emocional, mas engloba a competência de incorporar emoções
ao raciocínio e à interação social complexa. A fundamentação neurobiológica da IA reside na sinergia
entre sistemas corticais e subcorticais, incluindo o córtex orbitofrontal, córtex ventromedial pré-frontal,
córtex cingulado anterior, junção temporoparietal e ínsula anterior. A arquitetura funcional da IA
envolve a integração e não supressão das emoções, a proatividade empática, a coerência intrapessoal e
interpessoal, e a sinalização afetiva moral. Este trabalho delimita o conceito de IA em relação à
inteligência emocional e à empatia, explorando suas implicações clínicas, sociais e cognitivas. Conclui-
se que a IA amplia o paradigma da cognição humana, integrando emoção, moralidade e adaptabilidade
social em uma função estruturante.
Palavras-chave: inteligência afetiva, neurociência, emoções, moralidade, cognição social
Artículo recibido 14 mayo 2025
Aceptado para publicación: 20 junio 2025

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Inteligencia Afectiva: Arquitectura Cognitivo-Emocional de la Coherencia
Intersubjetiva
RESUMEN
Este artículo propone el concepto de Inteligencia Afectiva (IA) como una capacidad neurofuncional
distinta, responsable de la integración de estados afectivos en los procesos de juicio, acción y moralidad
aplicada. La IA no se limita a la regulación emocional, sino que abarca la competencia de incorporar
emociones al razonamiento y a la interacción social compleja. La fundamentación neurobiológica de la
IA reside en la sinergia entre sistemas corticales y subcorticales, incluyendo el córtex orbitofrontal,
córtex ventromedial prefrontal, córtex cingulado anterior, la unión temporoparietal y la ínsula anterior.
La arquitectura funcional de la IA involucra la integración y no supresión de las emociones, la
proactividad empática, la coherencia intrapersonal e interpersonal, y la señalización afectiva moral. Este
trabajo delimita el concepto de IA en relación con la inteligencia emocional y la empatía, explorando
sus implicaciones clínicas, sociales y cognitivas. Se concluye que la IA amplía el paradigma de la
cognición humana, integrando emoción, moralidad y adaptabilidad social en una función estructurante.
Palabras clave: inteligencia afectiva, neurociencia, emociones, moralidad, cognición social

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INTRODUCTION
Understanding human intelligence has proven to be a vast and complex field, with diverse theoretical
perspectives and explanatory models. Traditionally, intelligence has been defined as the ability to
reason, solve problems, learn, and adapt to new situations. However, this view, focused primarily on
cognitive and logical abilities, consistently neglects the crucial role of emotions and affects in shaping
human behavior.
Historically, the focus on cognitive abilities measurable through Intelligence Quotient (IQ) tests has
dominated intelligence research. Brain structures such as the dorsolateral prefrontal cortex (DLPFC)
and frontoparietal networks have been identified as essential neural substrates for intelligence, fueling
the belief that rationality and logic were the cornerstones of higher cognition. However, this
dichotomous approach, which separates reason from emotion, has proven limiting in understanding the
complexity of adaptive human behavior.
The study of emotions, in turn, has progressed significantly, culminating in the popularization of the
concept of Emotional Intelligence (EI) by Daniel Goleman. EI, defined as the ability to recognize,
manage, and understand one's own emotions and the emotions of others, has highlighted the importance
of the affective world for personal and professional success. Although EI represents an important
advance, it focuses primarily on intrapersonal emotional regulation, without comprehensively
addressing the functional integration of emotions into moral judgment and social decision-making
processes.
More comprehensive models, such as Howard Gardner's Theory of Multiple Intelligences and
Rodrigues's (2022) Development of Wide Regions of Intellectual Interference (DWRI) model, have
expanded the concept of intelligence to include abilities such as interpersonal intelligence and subjective
creativity. However, there remains a need for a stand-alone construct specifically dedicated to the
functional integration of emotions as an essential component of human intelligence: Affective
Intelligence (AI).
Affective Intelligence, as proposed in this article, goes beyond simple emotional regulation. It refers to
the neurofunctional capacity to integrate affective states into processes of judgment, action, and applied
morality, allowing emotions to act as important guides for ethical and socially responsible decision-

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making. AI recognizes that emotions are not mere "noise" that interfere with rationality, but rather
crucial information that can enrich the decision-making process, leading to more adaptive choices
aligned with individual and social values.
The relevance of Affective Intelligence becomes even more evident in an increasingly complex and
interconnected world, where social interactions require a deep understanding of emotional nuances and
the ability to respond empathetically and altruistically. Leaders, educators, healthcare professionals, and
all those seeking to build healthy relationships and promote social well-being need to develop Affective
Intelligence to successfully navigate the complexities of modern life.
Therefore, this article aims to investigate the concept of Affective Intelligence in depth, examining its
neurobiological foundations, functional architecture, clinical, social, and cognitive implications, and its
relationship with other constructs such as Emotional Intelligence and empathy. We believe that
understanding Affective Intelligence can significantly contribute to the advancement of neuroscience,
psychology, and education, as well as provide valuable insights for promoting a more just,
compassionate, and empathetic society.
Throughout this article, we will demonstrate that Affective Intelligence is not just an interesting addition
to the field of human intelligence, but rather an essential element for understanding social cognition,
morality, and adaptive behavior. By including emotions as a core component of intelligence, we can
develop a more complete and accurate view of human potential and build a future where reason and
emotion work together for individual and collective well-being.
It's also crucial to emphasize that Affective Intelligence, by promoting coherence between what one
feels, thinks, and does, contributes to identity stability and moral reliability, essential elements for
building healthy relationships and creating a more just and equitable society. Individuals with high
Affective Intelligence are able to make decisions that consider the emotional impact of their actions on
others, making them more effective leaders, more caring parents, and more responsible citizens.
In short, Affective Intelligence represents a new paradigm in the understanding of human intelligence,
which recognizes the relevance of emotions as an essential factor in social cognition, morality and
adaptive behavior.

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In this context, this article aims to delve deeper into Affective Intelligence, exploring its neurobiological
foundations, functional architecture, clinical, social, and cognitive implications, and its relationship with
other constructs such as Emotional Intelligence and empathy. We believe that understanding Affective
Intelligence can significantly contribute to the advancement of neuroscience, psychology, and
education, as well as provide valuable insights for promoting a more just, compassionate, and empathetic
society.
In this way, we will delve into a detailed analysis of Affective Intelligence, seeking to unravel its
underlying mechanisms and behavioral manifestations, with the aim of providing a solid foundation for
future research and practical applications. We believe that Affective Intelligence has the potential to
transform how we understand ourselves and others, and to empower us to build a more connected,
compassionate, and just world.
Objectives
General Objective
Analyze Affective Intelligence as a distinct neurofunctional construct, exploring its neurobiological
foundation, functional architecture, and implications for social cognition, morality, and adaptive
behavior.
Specific Objectives
1. Identify and describe the brain areas and neural circuits involved in Affective Intelligence, including
the orbitofrontal cortex, ventromedial prefrontal cortex, anterior cingulate cortex, temporoparietal
junction, and anterior insula.
2. Elucidate the functional architecture of Affective Intelligence, detailing the processes of emotional
integration, empathic proactivity, intrapersonal and interpersonal coherence, and moral affective
signaling.
3. Discuss the clinical, social, and cognitive implications of Affective Intelligence, including its
relationship to psychopathology, education, leadership, and subjective creativity.
Literature Review
The quest for a comprehensive understanding of human intelligence has led researchers from various
fields to explore the complex interactions between cognition and emotion. Traditionally, intelligence

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was viewed as a solely rational capacity, focused on solving logical problems and adapting to the
environment. However, this view has proven incomplete, as it neglects the fundamental role of emotions
and affects in shaping human behavior and decision-making.
The concept of Emotional Intelligence (EI), popularized by Daniel Goleman, represented an important
milestone in the appreciation of emotions as an essential component of intelligence. Goleman (1995)
defined EI as the ability to recognize, understand, and manage one's own emotions and the emotions of
others, highlighting its importance for personal and professional success. EI has been associated with a
number of positive outcomes, such as better job performance, healthier relationships, and greater
psychological well-being (Mayer, Salovey, & Caruso, 2008).
However, EI focuses primarily on intrapersonal emotion regulation, without comprehensively
addressing the functional integration of emotions into moral judgment and social decision-making
processes. Furthermore, some critics argue that EI is a vague and ill-defined construct that overlaps with
other personality traits, such as extraversion and conscientiousness (Mayer, Roberts, & Barsade, 2008).
In contrast, moral neuroscience has demonstrated that emotions play a crucial role in ethical decision-
making. Studies of patients with lesions in the ventromedial prefrontal cortex (vmPFC) and orbitofrontal
cortex (OFC) have revealed that these brain regions are essential for integrating emotions into moral
judgment. Patients with lesions in these areas exhibit cold utilitarian behavior, characterized by an
inability to make fair decisions or decisions that are sensitive to the suffering of others (Koenigs, Young,
& Adolphs, 2007).
The temporoparietal junction (TPJ), in turn, has been identified as a brain region fundamental to theory
of mind—the ability to understand the mental states of others. Activation of the TPJ is directly associated
with understanding others as subjects with autonomous intentionality (Schurz et al., 2014). This ability
is essential for empathy and social decision-making that takes into account the needs and feelings of
others.
The anterior insula, another brain region important for Affective Intelligence, is responsible for
integrating internal body perception (interoception) with emotional awareness. The anterior insula plays
a fundamental role in building affective self-awareness consistent with practical empathy (Craig, 2009).
Its joint activation with the anterior cingulate cortex (ACC) forms the salience network, which guides

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attentional focus to emotionally relevant information, especially in complex social situations (Seeley et
al., 2007).
The anterior cingulate cortex (ACC) plays a role in resolving conflicts between emotion and logic and
is involved in detecting moral dissonance and making decisions under affective ambiguity (Shackman
et al., 2011). The ACC integrates emotional and cognitive information to guide behavior in situations
that require careful assessment of the emotional and moral consequences of actions.
The DWRI (Development of Wide Regions of Intellectual Interference) model proposed by Rodrigues
(2022) had already emphasized the importance of cross-activation of multiple functional nuclei for the
development of full intelligence. According to this model, intelligence is not limited to logical reasoning
but also encompasses subjective creativity, empathy, and the ability to adapt to complex contexts.
Recent studies on leadership and creativity have shown that the ability to anticipate others' emotional
reactions, act with affective responsibility, and maintain subjective coherence with the group is
associated with more sustainable and innovative results (Brackett, Rivers, & Salovey, 2011). Leaders
with high Affective Intelligence are better able to inspire trust, motivate their teams, and create a positive
and productive work environment.
In summary, the literature review indicates that the neurofunctional components of Affective
Intelligence are already understood separately. What we propose with this article is the unification of
these systems into a legitimate, autonomous, and measurable cognitive function, focused on ethical
coexistence, subjective creativity, and complex adaptive action. We believe that Affective Intelligence
represents a new paradigm in the understanding of human intelligence, recognizing the importance of
emotions as an essential agent of social cognition, morality, and adaptive behavior.
In this context, Affective Intelligence differs from emotional intelligence (Salovey, Mayer, & Caruso,
2002) in that it is not limited to the perception and regulation of emotions, but rather actively integrates
them into decision-making and moral judgment. Affective Intelligence also differs from empathy
(Decety & Jackson, 2004), which can be a passive or reactive emotional response to social stimuli, while
AI involves proactive and intentional action based on understanding others' emotions.
Furthermore, Affective Intelligence is distinct from affective decision-making (Koenigs, Kruepke, &
Newman, 2010), which can occur even in individuals with dysfunctional morality, influencing choices

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despite ethical deficits. Affective Intelligence, in turn, presupposes a solid ethical foundation and a
commitment to social well-being, guiding decision-making toward fair and equitable outcomes.
Therefore, Affective Intelligence represents a groundbreaking synthesis of concepts and discoveries
from different fields of neuroscience, psychology, and philosophy, which seeks to provide a more
complete and accurate understanding of the complexity of human intelligence. We believe that Affective
Intelligence has the potential to transform how we understand ourselves and others, and to prepare us to
build a more connected, compassionate, and just world.
METHODOLOGY
This article adopts a theoretical and exploratory approach, based on a comprehensive review of the
scientific literature on intelligence, emotions, moral neuroscience, and social cognition. The
methodology used involved the following steps:
1. Literature Review: Systematic searches in databases such as PubMed, Scopus, Web of Science, and
Google Scholar, using terms such as "emotional intelligence," "moral neuroscience," "social cognition,"
"empathy," "affective decision-making," and "prefrontal cortex."
2. Article Selection and Evaluation: Critical analysis of the identified articles, based on criteria of
relevance, methodological quality, and scientific rigor. Prioritization of empirical studies, systematic
reviews, and meta-analyses.
3. Synthesis and Integration of Results: Identification of patterns, convergences, and divergences in
the results of the analyzed studies. Construction of an integrative theoretical model of Affective
Intelligence, based on findings from neuroscience and psychology.
4. Conceptual Delimitation: Clear and precise definition of the concept of Affective Intelligence,
distinguishing it from other related constructs, such as emotional intelligence, empathy, and affective
decision-making.
5. Discussion of Implications: Exploration of the clinical, social, and cognitive implications of
Affective Intelligence, based on scientific literature and theoretical reflections.
6. Elaboration of Conclusions: Synthesis of the main findings of the study and presentation of
perspectives for future research and practical applications of Affective Intelligence.

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The selected articles were analyzed qualitatively, focusing on identifying the neurobiological
mechanisms underlying Affective Intelligence, describing its functional architecture, and discussing its
implications for human behavior and society. The results were interpreted from an interdisciplinary
perspective, integrating insights from neuroscience, psychology, philosophy, and education.
DISCUSSION
This proposal for Affective Intelligence (AI) seeks to fill a gap in the literature by offering a construct
that integrates cognition and emotion more comprehensively and functionally than traditional
approaches. Unlike emotional intelligence, which focuses primarily on regulating emotions, AI proposes
that emotions can and should be integrated into decision-making and moral judgment, enriching and
making them more adaptive.
The neurobiological foundation of AI, based on the synergy between cortical and subcortical systems,
such as the orbitofrontal cortex, ventromedial prefrontal cortex, anterior cingulate cortex,
temporoparietal junction, and anterior insula, provides a solid foundation for understanding the neural
mechanisms underlying the integration of emotion and cognition. These brain areas, together, enable
individuals to assess the emotional impact of their actions on others, make decisions that consider social
well-being, and act ethically and responsibly.
The functional architecture of AI, which involves the integration rather than suppression of emotions,
empathic proactivity, intrapersonal and interpersonal coherence, and moral affective signaling, describes
the cognitive and emotional processes that allow individuals to use emotions as a guide to action.
Empathic proactivity, for example, involves the ability to anticipate the emotional reactions of others
and act in ways that avoid causing harm or suffering.
Intrapersonal and interpersonal coherence, in turn, refers to the ability to align one's feelings, thoughts,
and actions, acting authentically and in accordance with one's values. This coherence is essential for
building healthy relationships and maintaining moral integrity.
Finally, affective moral signaling involves the ability to use emotions as a feedback system to evaluate
the morality of an action. This signaling can involve feelings of guilt, shame, or remorse when an action
is considered morally wrong, or feelings of pride, satisfaction, or joy when an action is considered
morally right.

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AI is distinct from empathy, which can be a passive or reactive emotional response to social stimuli,
while AI involves proactive and intentional action based on understanding others' emotions.
Furthermore, AI is distinct from affective decision-making, which can occur even in individuals with
dysfunctional morality, influencing choices despite ethical deficits. AI, in turn, presupposes a solid
ethical foundation and a commitment to social well-being, guiding decision-making toward fair and
equitable outcomes.
The clinical implications of IA are significant, as low levels of IA are associated with a range of
psychopathologies, such as compensatory narcissism, functional alexithymia, and externalizing
disorders. Therefore, assessing IA can be useful in the diagnosis and treatment of these conditions.
The social consequences of AI are also important, since AI is the foundation of mature moral judgment.
AI development should be encouraged in educational settings through the analysis of real-life dilemmas,
empathetic accountability, and the reinforcement of others' perspectives.
Ultimately, AI's cognitive inferences are relevant to understanding leadership and subjective creativity.
Leaders with high AI are better able to create sustainable solutions in complex human contexts, and
subjective creativity depends on sensitivity to human aspects and consequences, not just logical
originality.
Finally, AI represents a new way of thinking about human intelligence, one that recognizes the
importance of emotions as an essential element of social cognition, morality, and adaptive behavior.
It's important to emphasize that Affective Intelligence isn't limited to mere emotional "sensitivity," but
involves a complex set of cognitive and emotional skills that enable individuals to understand, evaluate,
and utilize emotions effectively in various situations. AI empowers individuals to make more informed
decisions, build healthier relationships, and contribute to a more just and equitable society.
Furthermore, Affective Intelligence is not a fixed and immutable trait, but rather a capacity that can be
developed and honed throughout life. Through education, practice, and reflection, individuals can learn
to integrate emotions into their decision-making process, develop empathy, and act more ethically and
responsibly.
AI, therefore, represents a promising path for promoting individual and collective well-being and
deserves to be explored in depth by scientific research and educational and social practices. By

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recognizing and valuing the importance of emotions, we can build a more connected, compassionate,
and just world.
Intelligence, in its functional totality, is best understood when considering both IQ and Affective
Intelligence (AI). The higher both are, the more functional and comprehensive an individual's
intelligence. Therefore, intelligence is not simply the result of psychometric scores, but of a
neurofunctional integration that allows for coherence between logic, affectivity, creativity, and
adaptability.
Having a high IQ but low affective intelligence corresponds to the partial development of certain
cognitive domains, which prevents comprehensive brain homeostasis. It's a fragmented, non-linear
intelligence that compromises adaptive and social efficiency.
It's crucial to consider what we truly value: possessing high specific cognitive abilities with high
affective intelligence, even without formal giftedness, or having psychometric giftedness (IQ ≥ 130)
with low affective intelligence and interpersonal maladjustment. The goal should be the DWRI standard:
high brain connectivity, high IQ, equally high affective intelligence, with neurofunctional homeostasis
above the linear average.
In a hypothetical example of a linear distribution for homeostasis (IQ + AI combined):
• Linear 5: IQ 5 + AI 5 → average functional threshold
• Linear 8: IQ 8 + AI 8 → high adaptive functionality
• Linear 10: IQ 10 + AI 10 → DWRI pattern (high intellectual interference with affective balance)
Maladjustments arise when there is disparity:
• IQ 5 + AI 3 → low affective interference: relational instability, low impact
• IQ 8 + AI 10 → highly adaptive functional intelligence, even without formal giftedness
In the graphical interpretation of the DWRI model, full intelligence is manifested when the IQ curve
follows the AI curve in ascending linear parallelism. The greater the congruence between the two
variables, the greater the overall efficiency of the mind, which characterizes true intelligence according
to the DWRI model.

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CONCLUSION
This study proposed the concept of Affective Intelligence as a distinct neurofunctional capacity
responsible for integrating affective states into processes of judgment, action, and applied morality. AI
is not limited to emotional regulation but encompasses the ability to incorporate emotions into reasoning
and complex social interaction.
Future validation of this concept requires empirical studies with functional brain mapping, genetic
analysis of correlation with practical empathy traits, and differentiation of functional connectivity
patterns in individuals with different levels of IA.
Affective Intelligence is the neurofunctional capacity to integrate emotions with cognition to act with
intersubjective coherence, anticipating social impacts and making ethical decisions based on
understanding the other as a legitimate part of the decision-making process itself.
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