Quantum mechanical models have been proposed for biological processes and for cognition and decision in domains that appear to be beyond the de Broglie wavelength. The basis of such quantum behavior is seen variously as quantum fields and virtual and entangled particles, and the determination that the behavior is quantum is made on coherence, order and interference effects, and non-local behavior. This paper proposes that biological memories and cognitive agents are collectives of quantum objects. Statistical and informational properties of the collectives that need to be taken into consideration are identified. Issues related to mapping of collectives into various energy states and resistance to noise are examined.
NeuroQuantology | September 2013 | Volume 11 | Issue 3 | Page 391-398
Quantum mechanical models have been proposed for biological processes and for cognition and decision in domains that appear to be beyond the de Broglie wavelength. The basis of such quantum behavior is seen variously as quantum fields and virtual and entangled particles, and the determination that the behavior is quantum is made on coherence, order and interference effects, and non-local behavior. This paper proposes that biological memories and cognitive agents are collectives of quantum objects. Statistical and informational properties of the collectives that need to be taken into consideration are identified. Issues related to mapping of collectives into various energy states and resistance to noise are examined.
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.
An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self- measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective.
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.
Contemporary physics increasingly challenges the classical assumption that information is stored locally within isolated physical systems. Quantum entanglement, relational interpretations of quantum mechanics, spacetime dynamics, and holographic approaches to information all suggest that persistence in nature may be fundamentally relational rather than object-bound. In this paper, we develop a multi-scale interpretive framework in which “memory” is understood not as internal storage within particles or systems, but as the persistence of correlations across quantum states, fields, spacetime geometry, biological organization, and cognitive processes.At the quantum level, relational correlations and entanglement are examined as forms of distributed informational persistence that do not require localized memory carriers. At the spacetime level, curvature and holographic structure are interpreted as persis-tent geometric constraints encoding the historical influence of interactions. Extending beyond physics, biological systems are treated as active stabilizers of relational infor-mation through genetic, metabolic, and neural organization, while consciousness is ex-plored as a higher-order form of integrated relational memory arising from hierarchical informational integration.The framework integrates established theoretical approaches—including relational quantum mechanics, holographic information theory, decoherence theory, and inte-grated information theory—with clearly demarcated speculative hypotheses concerning field-mediated persistence, frequency-based encoding, and cross-scale informational coherence. Throughout, explicit distinctions are maintained between accepted physical formalism, interpretive extension, and speculative proposal.Rather than introducing a new physical theory, this work proposes a unifying concep-tual platform for understanding information persistence across scales. Within this per-spective, memory becomes a distributed structural feature of reality itself: not a proper-ty stored inside isolated objects, but a persistent relational constraint shaping how physical, biological, and cognitive systems evolve through time.
The question of whether quantum mechanical phenomena play a functional role in brain activity and the emergence of consciousness remains one of the most controversial yet intellectually stimulating debates at the intersection of physics, neuroscience, and philosophy of mind. This review systematically examines the principal theoretical frameworks proposing quantum-level mechanisms in neural computation, including the Orchestrated Objective Reduction (Orch OR) hypothesis by Penrose and Hameroff, the quantum brain hypothesis of Stapp, quantum coherence models in microtubules, and quantum field theories of consciousness. We critically evaluate the current state of empirical evidence—including recent quantum biology findings, the challenge of decoherence in warm, biological systems, and experimental observations of quantum effects in biological systems—alongside computational models that bridge quantum formalism and neural network dynamics. Furthermore, we discuss the implications of quantum cognition models for understanding perception, decision-making, and memory. Despite significant scientific skepticism, emerging evidence from quantum biology and advanced neuroimaging technologies provides tentative support for quantum processes in neural substrates. We conclude by identifying critical gaps in current knowledge and outlining future research directions that may resolve the debate, including proposals for experimental paradigms using quantum sensing technologies applied to neural tissue. This review aims to serve as a foundational reference for researchers across disciplines approaching the quantum mind hypothesis with scientific rigor.
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.