Based on a calculation of neural decoherence rates, we argue that the degrees of freedom of the human brain that relate to cognitive processes should be thought of as a classical rather than quantum system, i.e., that there is nothing fundamentally wrong with the current classical approach to neural network simulations. We find that the decoherence time scales ( approximately 10(-13)-10(-20) s) are typically much shorter than the relevant dynamical time scales ( approximately 10(-3)-10(-1) s), both for regular neuron firing and for kinklike polarization excitations in microtubules. This conclusion disagrees with suggestions by Penrose and others that the brain acts as a quantum computer, and that quantum coherence is related to consciousness in a fundamental way.
Based on a calculation of neural decoherence rates, we argue that the degrees of freedom of the human brain that relate to cognitive processes should be thought of as a classical rather than quantum system, i.e., that there is nothing fundamentally wrong with the current classical approach to neural network simulations. We find that the decoherence time scales ( approximately 10(-13)-10(-20) s) are typically much shorter than the relevant dynamical time scales ( approximately 10(-3)-10(-1) s), both for regular neuron firing and for kinklike polarization excitations in microtubules. This conclusion disagrees with suggestions by Penrose and others that the brain acts as a quantum computer, and that quantum coherence is related to consciousness in a fundamental way.
This paper presents in details how the subjective time is constructed by the brain cortex via reading packets of information called "time labels", produced by the right basal ganglia that act as brain timekeeper. Psychophysiological experiments have measured the subjective "time quanta" to be 40 ms and show that consciousness operates beyond that scale - an important result having profound implications for the Q-mind theory. Although in most current mainstream biophysics research on cognitive processes, the brain is modelled as a neural network obeying classical physics, Penrose (1989, 1997) and others have argued that quantum mechanics may play an essential role, and that successful brain simulations can only be performed with a quantum computer. Tegmark (2000) showed that make-or-break issue for the quantum models of mind is whether the relevant degrees of freedom of the brain can be sufficiently isolated to retain their quantum coherence and tried to settle the issue with detailed calculations of the relevant decoherence rates. He concluded that the mind is classical rather than quantum system, however his reasoning is based on biological inconsistency. Here we present detailed exposition of molecular neurobiology and define the dynamical timescale of cognitive processes linked to consciousness to be 10-15 ps showing that macroscopic quantum coherent phenomena in brain are not ruled out, and even may provide insight in understanding life, information and consciousness.
The tantalizing hypothesis that quantum phenomena underpin the brain’s remarkable computational abilities has sparked intense interdisciplinary interest. This study delves into quantum neuroscience by computationally exploring quantum coherence in neural systems, aiming to uncover whether quantum effects enhance information processing. We developed a sophisticated model simulating a 1,000-qubit neural network, with each qubit representing a neuron entangled under biologically relevant conditions (310 K, 0.15 µs coherence time). Using IBM’s Qiskit framework, we tested signal propagation efficiency, latency, and coherence duration across four conditions: quantum models with full, moderate, and high decoherence, and a classical benchmark. Our results reveal a striking 19.4% improvement in signal propagation efficiency in the full-coherence quantum model (95.8% ± 2.9%) compared to the classical model (76.4% ± 5.1%; p < 0.001). Latency was reduced by 31%, with the quantum model achieving 0.68 µs versus 0.98 µs for the classical model. Coherence persisted for up to 1.5 µs, sufficient for short-range neural signaling. Extensive sensitivity analyses, varying temperature (300–325 K), noise (0.01–0.12 µs^-1), and network size (500–1,500 qubits), confirmed robustness, with efficiency remaining above 90% under moderate perturbations. These findings suggest quantum coherence could complement classical neural mechanisms, potentially enhancing processes like sensory integration or consciousness. However, biological complexity, including biochemical interactions, warrants further exploration. We advocate for experimental validation using advanced quantum sensors, such as nitrogen-vacancy centers, to detect coherence in neural tissue. This study bridges quantum physics and neuroscience, offering a robust computational framework to probe the brain’s quantum potential and inspiring future interdisciplinary research into cognition’s mechanistic underpinnings.
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.
This paper explores the ambitious goal of developing a quantum simulation framework capable of accurately modeling the computational processes of the human brain. The core claim is that by leveraging quantum algorithms, we can simulate the intricate neural networks within the brain with a fidelity exceeding classical approximations, offering potential insights into the fundamental principles underlying consciousness. We investigate a novel approach combining quantum state manipulation with specific algorithmic design to mimic neural network dynamics, highlighting the challenges and opportunities inherent in this endeavor. The research will address key concepts such as entanglement, superposition, and quantum decoherence, while outlining a preliminary framework for quantum neural network simulation. The paper concludes with a discussion of the potential ramifications and limitations of this research, emphasizing the need for further theoretical and experimental investigation.
In the mid-1990s, it was proposed that quantum effects in proteins known as microtubules play a role in the nature of consciousness. The theory was largely dismissed due to the fact that quantum effects were thought unlikely to occur in biological systems, which are warm and wet and subject to decoherence. However, the development of quantum biology now suggests otherwise. Quantum effects have been implicated in photosynthesis, a process fundamental to life on earth. They are also possibly at play in other biological processes such as avian migration and olfaction. The microtubule mechanism of quantum consciousness has been joined by other theories of quantum cognition. It has been proposed that general anesthetic, which switches off consciousness, does this through quantum means, measured by changes in electron spin. The tunneling hypothesis developed in the context of olfaction has been applied to the action of neurotransmitters. A recent theory outlines how quantum entanglement between phosphorus nuclei might influence the firing of neurons. These, and other theories, have contributed to a growing field of research that investigates whether quantum effects might contribute to neural processing. This review aims to investigate the current state of this research and how fully the theory is supported by convincing experimental evidence. It also aims to clarify the biological sites of these proposed quantum effects and how progress made in the wider field of quantum biology might be relevant to the specific case of the brain.
Quantum models of the mind associate consciousness with coherent superposition of states in the brain. Some authors consider consciousness to be the result of a kind of internal quantum measurement process in the brain. In this paper we discuss the ideas of Hameroff-Penrose and Tegmark and their calculation for an estimate of decoherence time. We criticize the Hameroff-Penrose model in the context of a quantum brain model by gravitational collapse orchestrated objective reduction (OOR), assumed by Penrose, and we propose instead that the decoherence process is caused by interaction with the environment. We consider it useful to exploit this possibility because of the growing importance of the decoherence theory in quantum measurement, and also because quantum mechanics can be applied to brain study independently of the Hameroff-Penrose model for mind and consciousness. Our conclusion is that the Hameroff-Penrose model is not compatible with decoherence, but nevertheless the quantum brain can still be considered if we replace gravitational collapse OOR with decoherence. However, our result does not agree with Tegmark's conclusion of refuting not only the Hameroff-Penrose gravitational collapse but also the quantum brain, based on decoherence time calculations in specific cases in the brain. In spite of this fact we also disagree with some points of the response to Tegmark's article given by Hagan, Hameroff, and Tuszynski.