Recent years have witnessed rapidly increasing interests in developing quantum theoretical models of human cognition. Quantum mechanisms have been taken seriously to describe how the mind reasons and decides. Papers in this special issue report the newest results in the field. Here we discuss why the two levels of commitment, treating the human brain as a quantum computer and merely adopting abstract quantum probability principles to model human cognition, should be integrated. We speculate that quantum cognition models gain greater modeling power due to a richer representation scheme.
Recent years have witnessed rapidly increasing interests in developing quantum theoretical models of human cognition. Quantum mechanisms have been taken seriously to describe how the mind reasons and decides. Papers in this special issue report the newest results in the field. Here we discuss why the two levels of commitment, treating the human brain as a quantum computer and merely adopting abstract quantum probability principles to model human cognition, should be integrated. We speculate that quantum cognition models gain greater modeling power due to a richer representation scheme.
ABSTRACT Recent advances at the intersection of quantum physics, neuroscience, and cognitive science have renewed interest in whether quantum phenomena and quantum‐inspired formalisms can inform models of human cognition and decision‐making. While classical neural and computational models explain many aspects of perception and behavior, they face limitations in accounting for contextuality, order effects, probabilistic reasoning violations, ambiguity resolution, and rapid information integration. This review synthesizes evidence and theoretical frameworks linking quantum‐related principles to cognition, with emphasis on quantum sensing in biological systems, molecular and subcellular quantum‐relevant mechanisms, quantum‐to‐classical transition pathways, quantum‐inspired models of perception and decision‐making, and quantum‐inspired computational approaches. It also extends beyond the probabilistic arm of quantum cognition by considering emerging equilibrium‐based and causal‐logical theories, including mental equilibrium, brain‐universe similarity, mind‐light‐matter unity, quantum emergence, and quantum intelligence. Throughout, the review distinguishes physically instantiated quantum mechanisms from abstract quantum‐like formalisms that model contextuality, mental entanglement, and non‐separable cognitive dynamics without requiring sustained macroscopic quantum coherence in the brain. Finally, it identifies methodological challenges and future directions for advancing quantum cognitive science toward experimentally testable and biologically meaningful theories.
In recent decades it has become common throughout the social sciences to think of the human mind simply as a very complex computer. Drawing on an older materialist metaphor of the mind as a machine, the “computational” model of the mind took off after the mid-century invention of the computer and subsequent cognitive revolution in psychology, and has since permeated the social sciences in the form of rational choice and other prominent social theories. The contributions of this model have been huge; but it has always been assumed that the computations going on inside our heads are classical. Quantum brain theory challenges this assumption by proposing that the mind is actually a quantum computer. Classical computers are based on binary digits or “bits” with well defined values (0 or 1), which are transformed in serial operations by a program into an output. Quantum computers in contrast are based on “qubits” that can be in superpositions of 0 and 1 at the same time and also interact non-locally, enabling every qubit to be operated on simultaneously. The idea of a quantum computer was first proposed in the 1980s and is still far from being realized technologically, but it has fired the imagination of scientists by raising the prospect of unimaginable increases in computational power, and other neat tricks besides. If quantum brain theory is true, then our model of the mind would be similarly radically altered, irrespective of the issue of consciousness. Quantum brain theory hypothesizes that quantum processes at the elementary level are amplified and kept in superposition at the level of the organism, and then, through downward causation constrain what is going on deep within the brain. On this view, information from the environment is continuously transformed from the macro- to the micro-level, and then channeled back upward into an “internal quantum state,”
Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature.
The quantum mind or quantum consciousness group of hypotheses propose that classical mechanics cannot explain consciousness. Quantum theory is used to insert models of cognition that target to be more innovative than models based on traditional classical probability theory, which includes cognitive modeling phenomena in science. At the moment we can say that there is no clearly defined neurophysiological mechanisms of creation of the quantum-like representation of information in the brain, but we can mention the hypothesis of matching the information processing in the brain with quantum information and probability with contextuality as the key word. Using limited cognitive resources, incompatibility provides humans the means for answering an unlimited number of questions, thus promoting parsimony and cognitive economy.
The quantum mind or quantum consciousness group of hypotheses propose that classical mechanics cannot explain consciousness. Quantum theory is used to insert models of cognition that target to be more innovative than models based on traditional classical probability theory, which includes cognitive modeling phenomena in science. At the moment we can say that there is no clearly defined neurophysiological mechanisms of creation of the quantum-like representation of information in the brain, but we can mention the hypothesis of matching the information processing in the brain with quantum information and probability with contextuality as the key word. Using limited cognitive resources, incompatibility provides humans the means for answering an unlimited number of questions, thus promoting parsimony and cognitive economy.
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.