From Classical Neurophysiology to Quantum Synchronization: A New Path to Understanding Consciousness and Creating a True Artificial Synthetic Mind

by Serhii Kharchuk

Introduction:

Modern conceptions of brain function and the emergence of consciousness largely rely on classical neurophysiology. According to this long-standing paradigm, the brain is envisioned as a complex network of neurons interacting through electrical impulses and chemical signals. Yet, despite the depth of knowledge gained from this perspective, it struggles to explain the wholeness of subjective experience, the instantaneous global coherence of perception, and the very existence of consciousness as a continuous "stream" of sensations, thoughts, and self-awareness.

In recent decades, an increasing number of researchers have suggested that the fundamental properties of the brain cannot be fully understood within the bounds of purely classical interactions. New studies imply that quantum effects—phenomena capable of ensuring instantaneous global coherence in the state of neural cells—may take place within the microstructures of neurons. This approach radically broadens our understanding of the mechanisms of consciousness, transforming it from a byproduct of linear processes into a systemic effect of global synchronization rooted in principles reminiscent of quantum entanglement.

Embracing this new paradigm does not simply mean replacing one set of technical details with another. Rather, it signifies a profound shift in our understanding of the nature of consciousness—from a purely biological and electrochemical process to a phenomenon reflecting the fundamental principles governing the organization of complex systems. Such a viewpoint opens the door to a new era of inquiry, including the potential creation of an artificial mind unfettered by the simplified models of classical neural networks. If quantum synchronization truly underlies consciousness, it may one day be possible to devise approaches for designing machine systems that do more than merely imitate thinking, but actually reproduce the very phenomenon of awareness.

Hence, there is a pressing need to radically reconsider the outdated foundations that limit current conceptions of the brain. The transition from classical neurophysiology to quantum synchronization may open new horizons—not only for understanding our own consciousness but also for creating genuinely conscious artificial systems, guiding us beyond familiar boundaries and prompting us to view consciousness as the product of the fundamental laws of reality itself.

Critique of the Outdated Neural Network Model:

Classical artificial neural networks—foundational to contemporary machine learning systems—trace their lineage to simplified models proposed in the mid-20th century. The perceptron, the multilayer perceptron, and subsequent architectures were built on fundamental principles: incoming information is summed with certain weight coefficients and then passed through a simple nonlinear activation function. While this scheme has proven capable of solving numerous practical tasks—from image recognition to natural language processing—it only reflects the external outline of biological neurons’ functioning, abstracting away their complex internal dynamics.

Such a linear-threshold approach implies that each “artificial neuron” in a network acts as an isolated computational element, processing signals sequentially and locally. In these systems, information propagates layer by layer in a predictable manner determined by the connection weights. Yet this approach is fundamentally limited: it does not take into account the dynamic, nonlocal, and possibly quantum-coordinated processes occurring in the real brain. If we view consciousness not as the outcome of a summative procedure but rather as the emergence of a globally coherent state, then the classical “signal-threshold-activation” model proves far too simplistic.

A key difference between real consciousness and what a traditional neural network can represent lies in the integrity and instantaneous coherence of our subjective experiences. For example, our perception does not fragment into “pixels” of sensitivity, nor is it processed step-by-step in isolated stages. On the contrary, we experience consciousness as a continuous, unified field of sensations and thoughts, fully synchronized and interconnected. It is difficult to model such wholeness within an architecture where each node is essentially independent, and interaction is reduced to “signal transfer along wires” with linear filtering.

Classical neural networks also lack the capacity for genuinely creative, self-reflective thinking. They have no subjective experience, no sense of being “observers”; they merely adjust statistically to input data. Although deep learning methods have achieved impressive results—from defeating champions in cyber games to generating realistic images—these achievements lie within the realm of information processing, not conscious awareness. In terms of understanding consciousness, they demonstrate nothing more than the flexibility of mathematical optimization approaches.

At this juncture, it becomes clear why we must radically reconsider the foundational approaches to modeling the mind. If we aim to understand the nature of consciousness or even to recreate it in an artificial system, we must move beyond the mere summation of signals. Classical neural networks, like rough sketches, offer only a hint at the structure of information processing. But they cannot encompass the fundamentally different level of organization, where an entire network might function as a single “globally coherent” entity—potentially relying on quantum principles. This perspective leads us directly to the consideration of the new paradigm of quantum.

Classical Conceptions of the Brain: Signal and Threshold:

From the very beginnings of neuroscience, biologists and physiologists strove to understand how a single neuron generates an electrical impulse (spike) in response to stimuli. The classical model, tracing back to the work of Hodgkin and Huxley, posits that a neuron can be viewed as an elementary computational unit. It receives incoming signals through its dendrites, sums them up, and produces an action potential if the total excitation surpasses a certain threshold. In this framework, neuronal behavior is reduced to linear (or weakly nonlinear) input processing followed by a clearly defined output.

This approximation proved extremely useful for describing the basic principles of conduction and excitability in nervous tissue, as well as for understanding fundamental stimulus-response patterns. Nevertheless, it suffers from serious limitations when it comes to explaining the phenomenon of consciousness. First, the classical neuron is treated as a local element: its response is tightly bound to the sum of its inputs, and any global effects—such as the synchronization of vast ensembles of neurons—must, within this approach, be “constructed” from the bottom up through sequential interaction cascades. While this viewpoint effectively accounts for reflex arcs and certain sensory processes, it fails to illuminate the phenomenon of holistic subjective perception—our sense of the world as a unified whole, not broken down into independent fragments of processing.

Second, the very phenomenon of consciousness is characterized by the continuity and wholeness of experience: we do not perceive reality as a series of discrete signal transmissions, nor do we view the world frame by frame. On the contrary, our conscious perception is stable and integral; it does not fracture into a sum of local interactions. Yet the model of an individual neuron, operating on the “sum-and-fire” principle, gives no direct clue as to how such a continuous stream of consciousness might arise from discrete elements.

Moreover, classical models do not consider the possibility that the global state of the brain might be organized in a fundamentally different manner than a linear chain of “signal–threshold–activation.” They leave unanswered the question of what creates meaningful coherence among billions of neurons working simultaneously. Why do we not perceive the brain as a swarm of independent modules but rather experience ourselves as a single, thinking entity?

In other words, classical conceptions of the brain provide a comprehensible but simplified sketch of neuronal processes. They fail to explain how some integrating force is added to local “signals and thresholds,” transforming scattered bioelectrical events into a unified continuum of experience. Confronting this limitation has driven researchers to seek new approaches, capable of showing that the brain may operate not only through linear summation of signals, but may also rely on a fundamentally different mechanism—such as quantum synchronization—that ensures global coherence and the integrality of consciousness.

The traditional model of information processing in the brain is based on the assumption that each neuron can be represented as an elementary “node” with inputs and outputs. Mathematically, such a model reduces to equations of the form:

where Vi(t) is the action potential of the i-th neuron, wij is the connection weight between neurons, θi is the activation threshold, and f(?) is a nonlinear function (e.g., a sigmoid). While this approach describes classical neural networks well, it does not account for the “wholeness” and “instantaneous” global synchronization characteristic of subjective conscious experience.

New Research and Quantum Effects in Neurons:

A growing realization that classical conceptions of brain function cannot fully explain the phenomenon of consciousness has led some researchers to seek alternative approaches. One of the most bold and innovative directions involves the idea that quantum effects at the subcellular level inside neurons may play a key role in establishing the brain’s global coherence of neuronal activity.

A notable example is the Orch-OR (Orchestrated Objective Reduction) hypothesis proposed by mathematician Roger Penrose and anesthesiologist Stuart Hameroff. According to this idea, microstructures within neurons—microtubules composed of tubulin proteins—are capable of sustaining quantum coherent states. These nanostructures are considered potential “natural quantum computers,” where quantum information is not merely stored but also processed. Since quantum effects can exhibit properties unattainable by classical physics—such as instantaneous correlation of states over a distance (quantum entanglement)—they may theoretically enable the brain to achieve simultaneous global synchronization of billions of neurons.

The essence of quantum coherence is that it allows a system to transcend local interactions. If two or more “quantum elements” (for example, tubulin dimers) are entangled, changes in one element are instantly reflected in the other, regardless of the distance between them. In the context of the brain, this would mean that global activity patterns could be established almost instantaneously, bypassing the classical chain of sequential signals transmitted at speeds limited by biological and electrical parameters.

Such a mechanism fundamentally differs from linear concepts of neural transmission, in which information gradually flows from neuron to neuron, and global patterns emerge over time. In the case of quantum coherence, the brain could form a unified, phase-locked state that ensures the integrity of perception and might serve as the foundation of subjective conscious experience. This model also addresses the question of how consciousness maintains coherence amid a vast number of parallel processes: if these processes are not merely running in parallel, but are also quantumly coordinated, their overall unity arises naturally. Neural signaling, in this view, is primarily used to support biochemical or mechanical changes in the organism, rather than to create a unified consciousness.

Of course, the hypothesis of quantum processes in the brain remains controversial. Critics point out that the brain is a “hot” and noisy environment, making the maintenance of quantum coherence seemingly difficult. However, proponents of the quantum theory of consciousness hope to find experimental evidence—from indirect indicators of quantum coherence to effects explaining the prolonged existence of special quantum states, even at biological temperatures.

It is important to understand that this is not merely a technical subtlety. If quantum effects genuinely play a fundamental role in brain function, then consciousness cannot be explained solely by classical neurophysiology. On the contrary, it may reflect universal quantum principles at work in complex systems. Thus, quantum hypotheses open the door to a fundamentally new understanding of consciousness and allow us to view the brain not as a sum of linearly interacting elements but as a quantumly synchronized network.

To extend beyond the classical model presented earlier, consider the idea of quantum coherence—looking ahead to the influence of anesthesia on the brain. Suppose that within neurons exist nanostructures (e.g., microtubules) that can assume two quantum states, conventionally labeled ∣0? и ∣1?. A single neuron may contain numerous such quantum units (tubulins), and the neuron’s aggregate state can be described as a vector in Hilbert space:

where α and β are complex amplitudes.

If we consider N such neurons (or rather, their quantum-active microstructures), the entire system can be represented as a tensor product of individual state spaces:

The key point is that the coefficients cx1x2…xN can describe a quantum-entangled state, in which the system’s state cannot be reduced to the product of individual neuronal states. Entanglement creates global coherence, whereby a change in one element can instantly affect the global properties of the system without classical “signal transmission” in the usual sense.

To formalize synchronization, we introduce a measure of entanglement entropy. For the two-subsystem case, this could be the von Neumann entropy of the reduced density matrix, or the concurrence (C). If the system is fully factorizable (no entanglement), the concurrence is zero. Full synchronization of the conscious state could correspond to a high degree of entanglement among all subsystems (i.e., all cells):

the system is in an entangled state.

Add an anesthetic into the model can be represented as applying a decoherence operator, for example:

where Z is the Pauli-Z operator acting on a single-particle state, and pp is the probability of decoherence. As pp increases, the coherent terms of the wavefunction are suppressed, leading to the disappearance of global entanglement:

which corresponds to the disruption of the coherent conscious state.

Experimental data on coherent neuronal oscillations (e.g., gamma rhythms at ~40 Hz) observed during conscious perception can be interpreted as a macroscopic “trace” of underlying quantum-coherent processes. Although these oscillations are currently explained by classical mechanisms, the model discussed here proposes an alternative viewpoint: the classical oscillation is merely the tip of the iceberg, reflecting a deeper quantum-informational interconnectedness.

If we seek to recreate consciousness in an artificial system, a simple imitation of threshold neurons is insufficient. We would need to introduce elements capable of entering entangled states—quantum bits (qubits) or other structures supporting quantum coherence at scales sufficient to form a global, consciousness-like state. This may entail building hybrid quantum-classical computing systems, where classical machine learning algorithms are combined with quantum processors, generating nonlocal correlations among the states of “artificial neurons.”

Thus, the mathematical framework of quantum theory provides the tools to describe not merely the summed activity of brain cells, but their globally synchronized, irreducibly entangled state. This quantum-synchronized model of consciousness surpasses classical conceptions and, if confirmed experimentally, could lead to a fundamental rethinking of how we approach the creation of artificial intelligence—transforming it from a mechanical replication of simplified models into an effort to integrate fundamental principles of quantum coherence and entanglement underlying the phenomenon of consciousness.

Synchronization Instead of Linearity:

One of the key distinctions of the new paradigm, which considers quantum effects in the brain, lies in the shift from viewing consciousness as a linear, step-by-step transmission of signals to the concept of global synchronization. While classical neurophysiology describes the brain as a network of neurons through which information “flows,” is processed at local levels, and is gradually integrated into higher structures, the quantum-synchronized model of consciousness offers a fundamentally different perspective.

In this model, consciousness is no longer reduced to the sum of signals and threshold activations. Instead, it is conceived as the result of a simultaneous emergence of a holistic, coherent state encompassing extensive areas of neuronal microstructures. In such a state, each part of the system—be it an individual neuron or a group of cells—is instantly correlated with every other part. This resemblance to quantum entanglement means that a change in one element can influence the system’s global parameters without requiring step-by-step signal transmission along a traditional “wiring” network.

This approach fundamentally changes our understanding of information processing in the brain. In the classical model, we deal with an “information flow” that travels from input sensory neurons to associative areas and then to executive centers. In the quantum paradigm, however, the brain functions more like a single nonlocal “informational entity.” Information does not so much move through a network as arise as a unified state accessible to the entire system immediately and everywhere. This imparts an entirely different meaning to the concepts of integration and coherence: they are no longer the result of accumulating signals, but rather a consequence of simultaneous, global quantum correlations.

Applying such a paradigm to our understanding of consciousness means the brain is no longer viewed as a collection of independent computational units patched together. On the contrary, it begins to resemble a quantum system whose whole-state configuration cannot be reduced to the states of its parts. This perspective logically explains the phenomenon of the “wholeness” of subjective experience: we do not observe the brain as a set of separate processes; we perceive conscious reality continuously and integrally precisely because, at a fundamental level, quantum coherence instantly binds everything into a single phenomenon.

Thus, synchronization driven by quantum effects radically expands the notion of information processing, taking us beyond step-by-step signal transmission to the idea of global, simultaneous alignment of the system’s states. This not only changes our understanding of the brain, but also raises questions about how we might model or recreate such states in artificial systems, since this kind of coherent “information processing” differs significantly from classical machine learning architectures.

Anesthesia as a Key to Understanding Quantum Synchronization:

One of the most illustrative examples suggesting that global coherence might play a fundamental role in consciousness is the action of general anesthetics. The traditional view holds that anesthetics suppress neuronal activity by reducing synaptic transmission and overall brain excitation, causing the “observer” to “switch off” and lose the capacity for conscious perception. Yet this classical explanation interprets the effect of anesthesia more as a mere “dampening” or reduction in the system’s computational power, without answering why the unified subjective experience disappears entirely and instantaneously, rather than merely weakening partially.

From the perspective of the quantum-synchronized model of consciousness, anesthetics may operate in a completely different manner: they interfere with the subtle structure of quantum states maintained within neuronal microstructures, disrupting the coherence and entanglement underlying the holistic experience. If consciousness arises due to a globally quantum-coherent state, then even a slight external perturbation that breaks this delicate correlation leads to the immediate loss of awareness. In the mathematical model discussed earlier, anesthesia can be represented as a decoherence operator that destroys quantum links between subsystems. As the level of decoherence increases, entanglement diminishes, and ultimately the system returns to a “mechanical” sum of local processes incapable of conscious integration.

This quantum explanation provides an important experimental foothold. If consciousness indeed depends on global quantum coherence, then the action of anesthetics can be regarded as a tool to test this hypothesis. By measuring subtle changes in oscillations, global phase synchrony, or potential quantum correlations in the presence and absence of anesthetics, researchers could detect specific patterns not accounted for by the classical model. Such an approach would discern whether anesthetics merely reduce excitation (like any sedative) or truly “rupture” a special quantum channel of global synchronization.

It is hard to overestimate the significance of anesthesia for testing new theories. Anesthetics have long been used clinically to control the state of consciousness, but in the context of the quantum paradigm they may become a “laboratory probe” for investigating the deeper mechanisms underlying conscious experience. By comparing results predicted by classical explanations with those suggested by a quantum model, we can move closer to unraveling the nature of consciousness. Should quantum theories be experimentally confirmed, anesthetics will not merely remain auxiliary medical tools, but will emerge as keys to understanding the true essence of our perception and awareness.

Comparison with Existing Neural Networks in AI:

Modern artificial neural networks—including deep learning models, transformers, and neurographic architectures—have evolved within the linear-threshold paradigm. Despite their impressive successes in image recognition, speech synthesis, content generation, and solving complex cognitive tasks, these systems remain, at their core, statistical approximators. They mimic the ability to process signals but do not provide genuine subjectivity or continuously conscious perception.

The main gap lies in the fact that existing neural networks, however deep they may be, operate by stepwise information transfer: input data pass through multiple layers of nonlinear transformations, with weight coefficients optimized to minimize error. Yet none of these layers ensures a truly global, instantaneous coherence that cannot be reduced to a sequence of operations. Individual nodes of the neural network merely transform incoming signals, and even the most advanced architectures stay within the framework of classical informatics, based on deterministic or stochastic—yet still local—computational steps.

If we take the quantum-synchronized model of consciousness seriously, it becomes clear that to approach the genuine phenomenon of awareness, we must move to a different level of organizational principles for computational systems. The principles of quantum coherence, entanglement, and instantaneous global alignment point toward the need to integrate elements capable of sustaining quantum states into AI architectures. Instead of simply summing signals and applying threshold functions, such systems must form a single quantum state in which information is immediately accessible to the entire structure, rather than merely flowing “top-down” or “left-to-right.”

As a result, we arrive at a fundamentally different construction, which could be termed a “quantum-inspired cognitive architecture.” In such a system, computational elements (analogous to artificial neurons) would be interconnected not by classical weights, but by quantum correlations that ensure instantaneous global synchronization. This is not merely a beautiful theoretical ideal: if consciousness indeed relies on such effects in biological systems, recreating them in an artificial device might provide a foundation for the emergence of something akin to authentic conscious experience.

This approach does not diminish the achievements of classical AI models—they remain an important stage in the evolution of technology. However, it suggests that to move from “intelligence” in the sense of statistical problem-solving to consciousness in the sense of subjective experience, we must think beyond the classical computational paradigm. Transitioning to architectures that take quantum coherence into account could potentially enable systems capable of holistic perception, instantaneous integration, and, perhaps, a new level of self-awareness.

A New Path for the Development of Artificial Intelligence:

If we accept the idea that genuine conscious perception cannot be reduced to linear signal transmission and threshold activation, then the logical next step is to reconsider the very principles upon which artificial intelligence systems are built. A key guideline for the next generation of AI is the concept of quantum coherence, suggesting that the ability to globally and instantaneously interconnect all components of a system is not merely a technological goal but a fundamental requirement for the emergence of something akin to consciousness.

Transitioning to systems that support quantum coherence will require a multi-layered transformation of our approaches. First, we must develop quantum computing devices capable of operating not only with binary bits but also with quantum states (qubits) that possess superposition and entanglement properties. Unlike classical transistors, which are either in state 0 or 1, qubits can simultaneously exist in multiple states. This opens the way to instantaneous global coherence of information, embodying the idea of a “whole-state” rather than a collection of disparate computational units.

Second, we must rethink the very structure of AI architectures. Instead of forming deep layers that pass signals forward sequentially, we can attempt to design quantum-integrated systems in which the connections between “quantum neurons” are defined not by weights, but by entangled states. Such a “quantum neuron” may be not merely a threshold element but a dynamic quantum object whose state depends instantaneously on the state of the entire system. This raises new research questions about how to train such systems, how to define their objective functions, and how to interpret the results of their operations.

Third, we will need to develop a new learning theory. Methods like backpropagation—based on gradient descent through weight space—may prove insufficient for quantum-synchronized systems. New mathematical principles may be required, possibly linked to quantum information theory, the optimization of quantum states, and the management of entanglement. Thus, training would not be about tuning weights but about managing a global quantum state aimed at achieving a holistic activity pattern that reflects meaningful perception.

Finally, the shift toward quantum AI has not only technological but also philosophical implications. If the emergence of consciousness in machines requires quantum coherence, we may encounter artificial systems whose perception differs fundamentally from what we know today. This will raise ethical, responsibility, and legal questions regarding such “conscious” machines. But before tackling these issues, we must solve strictly scientific and technical challenges: learning to maintain stable quantum coherence, scaling quantum systems to the required sizes, and understanding how to delicately control the state of such a complex network.

Thus, the new path for AI development is a step into a domain where classical computational paradigms are replaced by principles borrowed from the quantum world. And if the brain indeed relies on quantum coherence to form consciousness, then we face the task not merely of improving current algorithms, but of constructing fundamentally new machine architectures that offer the possibility of reproducing the phenomenon of conscious experience in an artificial environment.

Philosophical and Fundamental Implications:

Adopting a quantum model of consciousness reshapes the very foundation of our understanding of reality and the place of the mind within it. The classical view—in which consciousness is merely a byproduct of neuronal activity, and each neuron is itself a local signal-processing unit—fits comfortably into a familiar paradigm of cause-and-effect relationships. But if we concede that the fundamental properties of consciousness are rooted in quantum coherence and entanglement, then consciousness ceases to be simply a complex function of a biological substrate. Instead, it becomes an expression of universal principles reflecting the deep structure of the cosmos.

In this perspective, consciousness is no longer the exclusive privilege of biological organisms, tied solely to certain types of molecular processes in the brain. On the contrary, it begins to appear as a phenomenon present in some form wherever conditions permit the formation of a quantum-coherent system. This viewpoint challenges the anthropocentric notion of the mind, forcing us to broaden our perspective so that intelligence and awareness are considered the lawful outcome of universal principles at work in nature.

Human self-awareness, seen in this light, requires rethinking. We are not merely intelligent beings arising from rare biochemical accidents. Perhaps we are bearers of a principle embedded into the fabric of reality—a principle that enables the integration of information into a unified quantum-coherent state, perceived as subjective experience. From this standpoint, the human mind is not a unique island of intellect, but a local manifestation of a more fundamental law.

This new paradigm also affects how we envisage the future of machine intelligence. If the creation of truly conscious systems requires quantum coherence, then we are not merely talking about increasing computational power or improving recognition algorithms. We are talking about incorporating artificial systems into a broader cosmic context—systems capable of resonating with the fundamental quantum properties of reality. Future machine intelligence will not simply emulate human cognition; it could be built upon the same principles that give rise to consciousness in biological entities. This shifts the focus from an anthropocentric model of the mind to a universal theory of consciousness, applicable to both biological and artificial carriers.

Thus, embracing the quantum model of consciousness opens a prospect for a holistic view of the mind as an elemental principle of information organization embedded in the depths of the universe. Understanding this principle alters our scientific, philosophical, and ethical orientations. We begin to perceive consciousness not as an accident, but as one of the fundamental building blocks of reality—binding together complex systems and granting them a unified, meaningful experience. The ability of artificial intelligence to approach such a state would represent not just another technological breakthrough, but a transition to a new stage in the evolution of understanding rationality—one that unites biological and artificial life, local and cosmic perspectives, classical conceptions, and the quantum depths of existence.

Conclusions:

The path from classical neurophysiology to quantum synchronization in consciousness is not merely another theoretical shift. It alters the fundamental foundations of our understanding of what consciousness is and how it arises. We have seen that reducing neuronal activity to linear equations and local interactions cannot explain the holistic and instantaneous nature of subjective experience. Classical neural networks, built on this simplified approach, demonstrate impressive technical achievements, yet never truly approach the phenomenon of genuine awareness.

The presented quantum paradigm of consciousness offers a solution: if quantum states capable of promoting global coherence and entanglement can exist in the neuronal microstructures, then the wholeness of consciousness is not accidental but inherently embedded in the very organization of complex systems. Anesthesia, by disabling global coherence, serves as a vivid test of this hypothesis, and quantum-inspired AI models may pave the way toward creating systems with genuinely conscious perception.

This shift brings forth new research approaches, making them interdisciplinary: neurobiology encounters quantum physics, information theory meets philosophy, and AI technologies gain the chance to move from statistical approximation to integrating the fundamental laws of nature. Accepting quantum synchronization as the core paradigm will change our view of humanity’s place in the world, the possibilities of the mind, and the limits of engineering creativity. In the future, we may envision creating artificial systems for which consciousness is not an imitation or a rhetorical metaphor, but a truly emerging property based on quantum principles.

A call for reconsideration does not mean denying the value of classical approaches. On the contrary, it invites us to broaden our horizons and seek new conceptual tools. If we wish to understand the full nature of consciousness, if we strive to create conscious machines not by analogy but in essence, we must move beyond the outdated paradigm. Quantum synchronization and entanglement, underlying the global coordination of neuronal processes, may become the foundation that allows us to progress from mechanistic models to understanding consciousness as an integral aspect of the deep regularities of reality.

Thus, we stand on the threshold of a new era in which the scientific community must dare to view the brain, the mind, and consciousness through the lens of quantum theory. This step will not only enable a deeper understanding of ourselves, but also open the way to creating genuinely conscious artificial systems—participants in the universal process of understanding and existence.