The present article explores the modeling of human cognitive activity in response to external informational stimuli of varying modalities. The mathematical foundation of the proposed model is based on elements of the mathematical apparatus of quantum mechanics, the theory of information images/representations, as well as a new approach to the description of information objects using. The theory of informational images/representations is employed to describe the mechanisms of information transmission, processing, and generation. A brief overview of this theoretical framework is provided in the article. The cognitive activity under investigation is modeled using a one-dimensional potential well with walls of differing heights. Within this interpretation, the internal barrier symbolizes the boundary between the conscious and subconscious levels of the mind. The proposed theoretical approach was then utilized to parametrize the studied cognitive systems. A mathematical model was subsequently formulated, using the principles of self-oscillatory quantum mechanics, leading to the formulation of an equation that describes the state function of an informational image during cognitive processes. In order to investigate various scenarios of informational influence, computer-based simulations were conducted. Consequently, characteristic patterns were identified, including the oscillatory nature of changes in the state function of informational images and the emergence of distinct threshold effects. These findings are in agreement with existing experimental data.
The present article explores the modeling of human cognitive activity in response to external informational stimuli of varying modalities. The mathematical foundation of the proposed model is based on elements of the mathematical apparatus of quantum mechanics, the theory of information images/representations, as well as a new approach to the description of information objects using. The theory of informational images/representations is employed to describe the mechanisms of information transmission, processing, and generation. A brief overview of this theoretical framework is provided in the article. The cognitive activity under investigation is modeled using a one-dimensional potential well with walls of differing heights. Within this interpretation, the internal barrier symbolizes the boundary between the conscious and subconscious levels of the mind. The proposed theoretical approach was then utilized to parametrize the studied cognitive systems. A mathematical model was subsequently formulated, using the principles of self-oscillatory quantum mechanics, leading to the formulation of an equation that describes the state function of an informational image during cognitive processes. In order to investigate various scenarios of informational influence, computer-based simulations were conducted. Consequently, characteristic patterns were identified, including the oscillatory nature of changes in the state function of informational images and the emergence of distinct threshold effects. These findings are in agreement with existing experimental data.
The emergence of quantum computing has prompted researchers to examine potential parallels between quantum mechanical principles and human cognitive processes. This article explores the theoretical framework of quantum cognition, examining how concepts from quantum mechanics, including superposition, entanglement, and measurement, might inform our understanding of human decision-making, memory, and consciousness. While quantum computing operates on fundamentally different physical principles than biological neural networks, the mathematical formalisms of quantum mechanics offer novel perspectives on cognitive phenomena that classical probability theory struggles to explain. This review critically examines the current state of quantum cognition research, its applications in computational modeling, and the ongoing debates regarding the validity of quantum mechanical analogies in psychological theory. The analysis reveals both promising theoretical insights and significant limitations in applying quantum principles to human cognition, highlighting the need for empirical validation and careful distinction between mathematical analogy and physical reality.
In this article, a novel approach to cognition inspired by quantum mechanical principles is proposed. It is based on an analogy between the physical objects at the quantum level and the human's mental states. Specifically, symbols in various cognitive functions are to be treated as eigenstates with respect to a particular quantum experimental arrangement. The arrangement is associated with an operator (called a formulation) corresponding to an observable of quantum mechanics. A state of affairs is treated as a superposition of eigenstates. Based on these assumptions, the quantum mechanical formalism can be straightforwardly applied to cognitive processes. As in quantum mechanics, there is an analogous Uncertainty Principle in representation. Furthermore, it is shown that non-monotonicity and counterfactual conditionals can be accommodated in a quantum mechanical framework.
The article presents a review of foreign scientific literature on the quantum-like approach to understanding the modeling of cognition and decision-making processes. It is shown that the current application of quantum physics approaches to consciousness, psychological approaches such as perception, cognition, emotions, consciousness and learning, involves the search for a single objective mathematical model of what underlies the experience of the brain. The use of quantum physics algorithms can help in understanding the mechanisms of brain malfunctions and memory impairments that are found in pathologies such as dementia caused by Alzheimer's disease, schizophrenia, etc. Quantum physics approaches are applicable to issues of modeling cognition and decision-making processes, as well as in cognitive research, information processing by the human brain, artificial intelligence development, psychology, social and political sciences. Application of the abstract mathematical principles of quantum theory can help in understanding human consciousness and behavior. Quantum probability theory is applied to modeling human behavior due to the prevalence of uncertainty in human interaction with the world. Quantum cognitive models are especially useful in research in such areas as errors in decision making, order effects of questions, conceptual combinations, accumulation of evidence, perception, etc. Of particular interest to researchers are issues of quantum-like modeling of cognition and decision-making processes, the apparatus of quantum information and probability theory, useful for such modeling, as well as the use of such apparatus in cognitive research, the development of artificial intelligence, psychology, social and political sciences.
Quantum-like (QL) modeling, one of the outcomes of the quantum information revolution, extends quantum theory methods beyond physics to decision theory and cognitive psychology. While effective in explaining paradoxes in decision making and effects in cognitive psychology, such as conjunction, disjunction, order, and response replicability, it lacks a direct link to neural information processing in the brain. This study bridges neurophysiology, neuropsychology, and cognitive psychology, exploring how oscillatory neuronal networks give rise to QL behaviors. Inspired by the computational power of neuronal oscillations and quantum-inspired computation (QIC), we propose a quantum-theoretical framework for coupling of cognition/decision making and neural oscillations - QL oscillatory cognition. This is a step, may be very small, toward clarification of the relation between mind and matter and the nature of perception and cognition. We formulate four conjectures within QL oscillatory cognition and in principle they can be checked experimentally. But such experimental tests need further theoretical and experimental elaboration. One of the conjectures (Conjecture 4) is on resolution of the binding problem by exploring QL states entanglement generated by the oscillations in a few neuronal networks. Our findings suggest that fundamental cognitive processes align with quantum principles, implying that humanoid AI should process information using quantum-theoretic laws. Quantum-Like AI (QLAI) can be efficiently realized via oscillatory networks performing QIC.
Quantum-like (QL) modeling, one of the outcomes of the quantum information revolution, extends quantum theory methods beyond physics to decision theory and cognitive psychology. While effective in explaining paradoxes in decision making and effects in cognitive psychology, such as conjunction, disjunction, order, and response replicability, it lacks a direct link to neural information processing in the brain. This study bridges neurophysiology, neuropsychology, and cognitive psychology, exploring how oscillatory neuronal networks give rise to QL behaviors. Inspired by the computational power of neuronal oscillations and quantum-inspired computation (QIC), we propose a quantum-theoretical framework for coupling of cognition/decision making and neural oscillations - {\it QL oscillatory cognition.} This is a step, may be very small, towards clarification of the relation between mind and matter and the nature of perception and cognition. We formulate four conjectures within QL oscillatory cognition and in principle they can checkedAsanoexperimentally. But such experimental tests need further theoretical and experimental elaboration. One of the conjectures (Conjecture 4) is on resolution of the binding problem by exploring QL states entanglement generated by the oscillations in a few neuronal networks. Our findings suggest that fundamental cognitive processes align with quantum principles, implying that humanoid AI should process information using quantum-theoretic laws. Quantum-Like AI (QLAI) can be efficiently realized via oscillatory networks performing QIC.
The conceptuality interpretation of quantum mechanics proposes that quantum entities have a conceptual nature, interacting with the material world through processes that are the physical counterpart of the meaning-based processes, which typically occur in human cognition. This interpretation emerged from the early developments in quantum cognition , a field that uses quantum mathematics to model human cognitive activity. It benefited from the specific approach taken by the Brussels research group , modelling concepts themselves as quantum entities and minds as measuring apparatus. The article sketches the essential steps of the intellectual journey, going from the first applications of quantum notions and formalisms to human cognition to the proposal of a potentially groundbreaking interpretation of quantum mechanics, offering profound explanations for major quantum phenomena. This was done by drawing numerous parallels with the human conceptual domain and suggesting the existence of a level of cognitive activity that would underlie our physical reality. This means that an increased cross-fertilization between the conceptuality interpretation and quantum cognition is to be expected in the future, both of which are synergistic in furthering our understanding of the nature of reality. This is the first part of a two-part article. In the second part, which can be read independently of the first, the successes of the interpretation will be described in a more systematic way, providing a brief overview of what has been achieved so far. This article is part of the theme issue ‘Quantum theory and topology in models of decision making (Part 1)’.