The Biological and Neural Mechanisms of Emotions in Shaping the Unified Dynamic Model of Mind
Year: 2025
Type: article
Abstract: Introduction The endeavor to construct a comprehensive model of the mind has long been a central pursuit in both cognitive science and neuroscience. While early approaches often emphasized purely rational and logical processes, there is a growing recognition of the indispensable role that emotions play in shaping our cognitive landscape and the inherently dynamic nature of mental processes. Rather than being viewed as disruptive forces, emotions are increasingly understood as integral components of how we perceive, learn, decide, and interact with the world. This report aims to delve into the biological and neural mechanisms underlying emotions and their profound influence in shaping a Unified Dynamic Model of Mind (UDMM). The concept of a UDMM suggests an integrated framework capable of encompassing the multifaceted aspects of cognition, with emotions occupying a pivotal position rather than a peripheral one. By exploring current research and theoretical perspectives, this analysis will examine the definition of UDMM, the foundational role of interoception, evolutionary origins, the predictive functions of emotions, their connection to primitive cognition, their integration with higher-order cognitive functions, the implications for diverse fields, and existing critiques of such unified models. The Unified Dynamic Model of the Mind (UDMM) presents a theoretical framework that conceptualizes the mind as an active, predictive, and continuously evolving system. It integrates principles from neuroscience, psychology, and artificial intelligence to explain how cognitive processes emerge dynamically through the interplay of sensory input, emotion, prediction, and error correction. At its core, UDMM emphasizes: Dynamic Cognition: The mind continuously updates internal models based on environmental stimuli and emotional feedback. Predictive Processing: Mental processes generate expectations about incoming data, with prediction errors driving learning and adaptation. Sensory-Emotional Integration: Emotions act as active filters, prioritizing biologically significant information. Active Inference: Cognitive and motor actions minimize uncertainty by reducing prediction errors. Neural Synchrony: Distributed brain networks dynamically coordinate to facilitate complex cognition. UDMM aligns with the predictive processing paradigm but extends it by incorporating emotional modulation, multisensory integration, and the role of memory reconsolidation. It has applications in artificial intelligence, education, psychotherapy, and cognitive neuroscience.
Author: Aidaros, Mohamed
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6949155582
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