Do Neuronal Microtubules Host Quantum Consciousness via Tubulin and EZ Water?
“The brain studying the brain. How trippy is that? Is consciousness emergent from, or fundamental to, the chaos of complex biology? Is it biology/chemistry/physics-based or, is it separate? And what are the roles of harmonic fields?”
Jessica Rose. Morning thoughts. April 8, 2025
Get comfortable. Grab a glass of wine. Or a bottle. This is a long one and it gets pretty technical. In this article I cover the human brain, microtubules, tubulin, artificial neural networks, cats, quantum biology, gel-like cytoplasm and ordered water layers, EZ water, the origins of consciousness from chemistry, the biochemistry of tubulin and consciousness as harmonic tuning – all for the love of consciousness.
A couple of definitions/comparisons for clarity
Biological human brain vs. artificial neural networks (ANNs): The human brain blends discrete neuronal action potentials with continuous dynamic processes, while ANNs, though theoretically continuous, operate discretely in practice – the former biological, the latter artificial. ANNs are inspired by the brain’s architecture and dynamics and excel at pattern recognition and learning primarily through brute computational force.
Classical vs. quantum computing: Unlike classical computing, which processes binary bits sequentially, quantum computing uses qubits that exist in multiple states simultaneously – enabling vastly different computational possibilities. Quantum computing leverages quantum phenomena like superposition and entanglement to process information in ways classical systems can’t, particularly for specific complex problems.
Prologue – stirring up the pot
Studying the brain and consciousness feels like being studied to me. The brain is an exceedingly complex biological squishy organ that produces our conscious experience. How, though? Does consciousness emerge simply from the brain’s neural computations, or is there something more elusive at play, perhaps tied to processes we don’t yet fully grasp? With the development of increasingly powerful ANNs, one must start to wonder if they too, might one day become conscious. Without knowing what consciousness is, how can we say one way or the other? If ANNs ever do get conscious, I’m betting tech like quantum computers, with their mind-bending power to crunch simultaneous computations, could be part of the puzzle.
Contemporary neuroscience predominantly views consciousness as an emergent property of the brain’s neural activity, supported by evidence linking subjective experience to specific neural correlates, such as synchronized oscillations in the cerebral cortex.¹ Yet, the precise nature of consciousness remains elusive, prompting speculation about whether it could transcend mere computation. This uncertainty complicates efforts to measure consciousness empirically, as its subjective essence resists objective quantification, a challenge often termed the ‘hard problem’ of consciousness.²For instance, while we can track energy expenditure in neural firing, no method distinguishes this from the qualitative experience of awareness, leaving open the question of its origins. Some philosophical perspectives, including panpsychism, propose that consciousness might be a fundamental feature of the universe, akin to mass or energy, existing independently and accessed by the brain rather than generated by it. Alternatively, a computational model likens consciousness to a software-like function, emerging from and dependent upon the brain’s hardware. Without a definitive understanding of its nature, both possibilities remain under active investigation, reflecting the profound complexity of this enduring mystery.
So, is consciousness an emergent property of neural computation or is it something else? In this article, I plan to dig into the Hameroff and Penrose’s Orchestrated objective reduction (Orch-OR) theory that posits that consciousness is a product of quantum processes inside neurons themselves, rather than being a product of neural connections. The connection between the human brain and quantum biology might lie in how quantum processes (like superposition or entanglement) could influence neural computation or consciousness at a microscopic level via microtubules and tubulin.
As I was writing this article, a paper was published that supports the idea that it is an emergent property of neural computation but not necessarily a universal model of consciousness. Fang et al. (April 4, 2025) demonstrate gating of conscious perception in visual awareness in specific locations in the brain in their latest work. Hameroff (I’ll introduce you to him soon) replied with a counterargument that I agree with:
Yes but thalamus can’t be necessary for all consciousness, as olfaction bypasses thalamus. And it’s not part of default mode network.
On the human brain
The human brain is the central organ of the nervous system working in tandem with our spinal cords to allow us to sense, speak and dance. It’s the command center for most of the activities of the body constantly processing, integrating and coordinating sensory information, translating sensing into action.
An average adult human brain is textured like tofu (apparently – I haven’t touched one yet) and weighs about 1.2–1.4 kg (2.6–3.1 pounds). The cerebrum is the largest part of the brain and the thing that most people imagine when they think of the brain, I would imagine. It includes the cerebral cortex (the outer layer) the outer layer of gray matter (about 2-4 mm thick) covering the cerebrum – the part that looks, brainy.
In addition to the cerebrum, we have the brain stem and the spinal cord. The brain stem is really important as the connector of the cerebrum and the spinal cord, and plays a vital role with regard to heart rate, respiration, consciousness, sleep/wake functioning and more. It’s really important in conduction, in other words. The spinal cord connects to the peripheral body allowing for movement.
The human brain comprises about 2% of the total body weight (not so heavy considering what it does!) and is made up of two hemispheres connected by the corpus callosum. The corpus callosum is like the information superhighway between the hemispheres of the brain and is the largest white matter structure in the human brain and consists of 200–300 million axonal projections (neural roads).
Each cerebral hemisphere consists of an inner core of white matter (I will get to this) and subcortical structures and an outer cerebral cortex, which is divided into four lobes: the frontal lobe (motor control, executive functions), parietal lobe (sensory processing, spatial awareness), temporal lobe (auditory processing, language comprehension, memory), and occipital lobe (visual processing).
There are a lot of non-moving parts in the human brain that comprise these lobes. The cerebellum shown in Figure 1b, almost seems like a little mini-brain protected by the mega-brain (cerebrum) and considering it runs more than half of the neurons in the brain³, it’s astounding that it only takes up about 10% of the volume. There’s the pineal gland, the posterior commissure, the body of fornix and all sorts of other squishy bits that make up this amazing organ.
Certain parts of the brain, including the cerebrum, brainstem, cerebellum, and spinal cord are covered by meninges that comprise 3 membranes and this is meant for protection, support (structure and vascular) and cushioning. The outermost membrane of the cerebral cortex is an important part of the blood–brain barrier. You can read about that here.
The human is made up of white matter and grey matter – so named partially because of the colouration (due to stains) when examining the brain from the inside as shown in Figure 1e. White matter is white because of myelination. Myelin’s high fat content reflects light, giving white matter its characteristic color in unstained sections. Myelin surrounds the nerve fibers (axons), and is found in almost all long nerve fibers, and acts as an electrical insulator. This is important because it allows messages to pass quickly from place to place in the brain acting as a conduit to grey matter within the central nervous system. This is also why demyelinating diseases are so bad: signal transmission can still occur, it’s just slower.
The cerebral cortex, composed of multiple layers of neurons, forms the bulk of the brain’s grey matter, consisting primarily of neuron cell bodies, dendrites, and unmyelinated axons, while the deeper subcortical white matter is predominantly made up of myelinated axons that connect various brain regions and extend to the spinal cord and periphery. The white matter of the brain makes up about half of the total brain volume.⁴
At the risk of making this piece a crash-course of the human brain instead of an exploration of the nature of consciousness, I would like to cut the intro part here. I wanted to hammer home the biology of the brain though and the places where certain functions take place.
There is no doubt that the human brain is an incredibly complex organ, both in its structure and function, but now I’d like to zoom in on neurons and microtubules (Figure 2 in green) and tubulin for the rest of this piece. Neurons and microtubules have a fascinating relationship wherein microtubules are the scaffold that support neuronal structure and function, and neurons are cells within the nervous system, (in the brain and spinal cord) that serve as conductors of electrical impulses. Neurons are excitable cells that generate electric signals known as action potentials, which travel across neural networks and communicate with each other via synapses using chemical neurotransmitters to transmit signals electrically. This interlacing combo of electrical and chemical processes underpins their critical role in the nervous system.
On microtubules and tubulin
Microtubules are hollow, cylindrical structures in cells built from tubulin proteins with ~25nm outer diameters (see Figure 3). Tubulin proteins are dimers (non-covalently paired molecules) of alpha- and beta-tubulin subunits that stack together by polymerization (chemical reaction to form polymer chains) to form protofilaments (13 per microtubule cross-section) that align laterally with a slight offset, forming a helical lattice around the hollow core to make up a hollow tube. Importantly, tubulin assembles head-to-tail when forming protofilaments and this gives microtubules an inherent polarity: a “+” end (where beta-tubulin is exposed, favoring growth) and a “-” end (where alpha-tubulin is exposed, less dynamic). This polarity drives directional processes like motor protein movement (kinesin toward the plus end, dyneintoward the minus) and microtubule organization in cells, including neurons, where it dictates transport along axons and dendrites.
Microtubule polarity arises primarily from the structural asymmetry of alpha-beta-tubulin dimers (which assemble head-to-tail) due to differences in their conformation and GTP-binding properties: alpha-tubulin binds GTP non-hydrolyzably and beta-tubulin binds GDP or GTP hydrolyzably. Charge distribution plays a supportive role by stabilizing these interactions through electrostatic forces. This polarity will become very important later on in this article.
Now here’s where it gets interesting.
Roger Penrose and Stuart Hameroff, have been exploring a theory called Orchestrated Objective Reduction (Orch-OR) in quantum biology, suggesting that microtubules act as quantum processors where consciousness emerges from quantum computations and not from purely computational processes. Unlike the idea that consciousness comes from regular neural connections, their theory proposes that microtubules in neurons facilitate quantum processes critical for consciousness. These processes rely on objective reduction (OR), a hypothesized mechanism where quantum superpositions – such as particles existing in multiple states simultaneously – collapse spontaneously due to gravitational effects in spacetime.
In Orch-OR, biologically orchestrated quantum states in microtubules enable coherent computations, with objective reduction (OR) collapses occurring at timescales that allow quantum effects to persist in microscopic structures – like tubulin proteins – while ensuring the brain’s macroscopic behavior remains classical and stable. OR, a hypothesized mechanism, proposes that quantum superpositions – multiple possible states – collapse spontaneously due to gravitational effects in spacetime, addressing the ‘measurement problem’ in quantum mechanics, by suggesting definite outcomes emerge objectively without requiring an observer. In applying OR, Orch-OR offers a speculative explanation for how quantum processes could underlie consciousness.
While some other theories assert that consciousness emerges as the complexity of the computations performed by cerebral neurons increases, Orch OR posits that consciousness is based on non-computable quantum processing performed by qubits formed collectively on cellular microtubules, a process significantly amplified in the neurons.⁵
They propose that tubulin’s conformational states could support quantum coherence, with electron movements in aromatic amino acids enabling superposition and entanglement. Think back to our heterodimer tubulin molecules make-up. Critics argue that biological systems are too ‘squishy’ for sustained quantum effects, yet there are studies that hint at quantum-like behaviors, such as vibrational resonance, in microtubules.
Now, the spiritual person in me really knows these guys are onto something. But so does the scientist. Let’s segue into ANNs because my brain don’t hurt enough yet.
On ANNs
There is a long history of the development of neural networks going all the way back to 1795 with Gauss’s exploration of the movement of planets using his groundbreaking work that led to the introduction of the Gaussian gravitational constant and the method of least squares, and the formulation of the fundamental principles of magnetism. Him and I share the belief that ‘the act of learning, not possession of knowledge, provides the greatest enjoyment’. Since his work involving least squares approximation, neural networks have come a long way.
With deep learning breakthroughs throughout the 1960s and 1970s, to include such advancements like backpropagation (involves the computation of the gradient of a loss function (with regard to minimization of loss) with respect to the weights of the network for a single input–output example), convolutional (computer ‘vision’) and recurrent (memory – the ‘P’ in ChatGPT stands for pre-training (self-supervised)) neural network development, through to Generative adversarial networks (GANs) (face-off between two neural networks) to recognize kitties, the use of multiple hidden layers in the neural network has helped us go from the image on the left in Figure to 4, to the one on the right in a little more than a decade. Astounding, isn’t it? I mean, the image on the right looks like a photograph, and if you read this article, you might start to wonder about what an image actually is and what, if anything, sets apart an image captured by a human and a computer.
And don’t forget, even though all of this is based on such an elegant model as linear regression, the evolution of the capabilities of [deep] neural networks is not linear. You can read more about this here at Skynet today. Eek. Here is another great article supplied to me by the great Dr. K that dives into the DARPA experience of artificial intelligence. Eek squared.
I would be remiss if I did not give a shout out to all the gamers out there because without them, I don’t think we’d be as far ahead as a we are today in all of this neural network development. I am not a gamer, but from the outside, I see them and their engagement to create strategies to ‘win’ in awesome graphical environments as a necessary driving force behind the ideas that led to the rapid evolution of these networks – particularly in the development of graphics hardware (GPUs, which are crucial for training neural networks) and in AI research for game-playing agents (e.g., DeepMind’s AlphaGo and AlphaStar).
It is absolutely clear that training data and hardware – which is of utmost importance in artificial neural network development – are the result of millions of hours of the hard work of playing games.
The incredible idea to pit neural networks off of each other to produce have GANs, stems more from game theory and machine learning concepts than direct gaming influence, but nonetheless, this idea is said to have come from Ian Goodfellow when he was hangin’ at the bar with his buds discussing how to improve generative models; kind of sounds like game playing to me. How very “A Beautiful Mind”. Isn’t it incredible how the answers to probably all of the most complex questions can be found in us and is commonly staring right at us as we live and breathe from the reflection in the bottom of a glass?
Back to neurons and microtubules.
So what did these geniuses over the years think to do in the ongoing development of these neural networks? What any genius would do: they tried to copy nature – the greatest genius of them all. More precisely, they tried (and keep trying) to mimic the neuron. Just so you know, the computery (artificial neural network) equivalent of a neuron is called a node (or perceptron).
Neurons fire via action potentials which are the consequence of the cumulative effect of graded potentials. Graded potentials are a localized, variable change in a cell’s membrane potential, proportional to stimulus strength, that decays over time and distance. It occurs in dendrites or soma and integrates signals to influence whether an action potential occurs. It’s distinct from action potentials due to its graded nature, lack of threshold, and short-range effect. When a neuron’s membrane potential reaches a threshold (typically around -55 mV), it fires an action potential. So action potentials themselves are pretty much either on or off. I say pretty much because of the process leading to firing with respect to rate and pattern of firing over time, varies. For example, a neuron might fire 10 times per second or 100 times per second, which adds a layer of complexity beyond a simple 0 or 1. Also, neurons aren’t ‘connected’ in a 1:1 way; a single neuron integrates thousands of inputs from other neurons.
You can think of these potentials like a sneeze: the graded potential is the buildup of tickles (like pollen or irritation in your nose and head), and the action potential is the sneeze itself – an all-or-none event that either happens or doesn’t. This is similar to a binary threshold unit in a neural network, which sums weighted inputs and fires a 0 or 1 based on a strict cutoff, like a sneeze triggered instantly if irritation crosses a line. But a neural network’s operation is like a chorus of sneezes, each sparked by varying tickles that blend, amplify, or dampen across many noses, creating a collective effect far beyond a single sneeze’s simple buildup.
Traditional computers use this binary system to compute by representing all data and instructions as combinations of 0s and 1s, which correspond to the off and on states of electrical signals in their circuits, processed through logic gates to perform calculations and operations. Understanding this is going to become important when I get into the quantum biology bit since quantum systems use qubits that can exist in superpositions (0, 1, or both simultaneously), enabling parallel processing and probabilistic outcomes for certain computations. More on that in a qubit. Hardy har har.
Here’s a gorgeous schematic diagram that describes how a typical human neuron is comparable to the binary system in its computing state.
As you can see from Figure 6, a neuron receives inputs via its dendrites where neurotransmitters from other neurons cause excitatory or inhibitory postsynaptic potentials (sneeze build-up); the inputs are processed, and an output signal is sent down the axon (myelinated in many cases), which can be interpreted as an ‘on’ state when the neuron fires (sneeze), while the overall output includes the synaptic transmission to the next neuron and the information encoded in the firing rate and pattern.
This is as opposed to in a neural network where an artificial neuron processes inputs through a weighted sum and applies an activation function, producing an output that may be binary (e.g., 0 or 1 with a step function) or continuous (e.g., a probability between 0 and 1 with a sigmoid), depending on the activation function used. Think of the weighted sum like a neuron deciding how much to listen to different signals from other neurons – each signal gets a weight based on its relevance, and the weighted sum determines the next step, though Orch-OR suggests quantum processes might add extra layers beyond this classical summing.
Both systems take inputs, process them, and produce an output. For a biological neuron, the output is the action potential (or lack thereof), and for a node (analogous to a biological neuron), the output is the result of the activation function. When the node’s output is binary, this mirrors the on/off nature of a neuron’s action potential.
Alright then, that’s enough about that. Let’s get back to biological neurons. What about these microtubules and tubulin? Since they play a structural role with regard to the conduction of action potentials, what else do they do? Is it possible that their component parts – namely the tubulin molecules – store information based on the direction of their polarity?
Microtubules found in neurons are called neuronal microtubules and differ slightly from microtubules with regard to their function and intracellular arrangement. I think by now everyone has seen the cute walking kinesin video on YouTube, right. If not here it is.
In the above video, the thing that the kinesin protein (aka: Mr. Kinesin) is walking on is a microtubule. Again, the microtubule is hollow, and made up of tubulin proteins as a dynamic (they can ‘grow’ and ‘shrink’ depending on the number of tubulin dimers), undivided polymer. As you can imagine more clearly now thanks to Mr. Kinesin, microtubules and the tubulin that makes them up are really important for transportation and infrastructure. Incidentally, because of the polarity direction of the microtubule, Mr. Kinesin can only walk from the “-” end to the “+” end. Better than Mr. Dynein’s fate: to only walk from the “+” to the “-” end. Poor Mr. Dynein.
In the following video made at Berkeley, you can visualize how tubulin dimers make up and break up microtubules.
Here’s another awesome video by Veritasium (below) that will help you visualize why microtubules are so important in the context of cell division and DNA replication. It’s so amazing. You’ll be able to visualize how the microtubules ‘grow’ by adding tubulin dimers at the interface of the chromatids (the kinetochore) to enable cell division.
Now that we understand a little more about microtubules and what they’re for, we can continue on to discuss how these things might ‘handle’ quantum biology via objective reduction.
Here’s one more little video interview snippet from an episode of Rogan and Sir Roger Penrose.
On quantum biology
Roger Penrose is a brilliant mathematician physicist, and has some amazing ideas about consciousness. Penrose says the cerebellum is unconscious. In addition to having more neurons than the rest of the brain as mentioned above, the cerebellum has more neurons than the cerebral cortex (about 69 billion compared to 16 billion), and the cerebrum has more total synaptic connections (around 150 trillion compared to the cerebellum’s 100 trillion) due to its complex, long-range connectivity. It’s not just about the number of neurons – it’s about the dynamic and perhaps chaotic behavior of the neurons in the brain as a whole. Penrose would likely surmise that microtubules are one of the best candidates with regard to consciousness.
The following PBS-produced video is a great summary of the meat of this argument behind the quantum brain idea. I wish I’d seen this before I started writing this; it’s a very good summary – complete with visuals – of most of the concepts I am covering in this article.
Penrose defers to anesthesiologist Stuart Hameroff – (he has also done some pretty incredible work in the realm of consciousness) on this subject matter, and raises the important point that one must examine what turns consciousness off – as is the case with the effects of anesthetics – in trying to answer questions about its nature.
How would microtubules work in quantum biology to enable consciousness?
Are microtubules molecular computers? Do individual tubulin molecules have the ability to store information based on their polarization direction? P.S. Watch this video to learn about wave function collapse – aka: objective collapse theories.
Penrose and Hameroff came up with a brilliant hypothesis: that tubulin dimers in microtubules can exist in a superposition of conformational states (e.g., one state might represent a slight shift in the dimer’s structure). How insanely logical and genius is that? We must not lose sight of the fact that in order for quantum effects to be meaningful, the superpositions must be maintained in a state of quantum coherence, meaning the quantum states don’t decohere (lose their quantum properties) due to interactions with the environment. This is a hard thing to imagine let alone achieve. But, do we? Penrose and Hemroff agree that microtubules might play a role in consciousness if a “good fraction of all of the microtubules in all the neurons in the brain need to be entangled to generate consciousness”. Hameroff suggests that microtubules are shielded from environmental noise (e.g., by a gel-like cytoplasm or water layers around them), allowing coherence to persist long enough for quantum computation to occur.
It’s worth noting that a paper was published last year (April 19, 2024) that demonstrated evidence that microtubules involve something called superradiance, and never mind what exactly that means (it pretty much just means really bright), just focus on the fact that it is a quantum effect. Think about that.
So do microtubules/tubulin molecules act as quantum computers within neurons? The lattice of tubulin dimers could act to process information through quantum interactions, such as quantum entanglement (where the states of multiple tubulin dimers become correlated) and quantum superposition. This would involve quantum computations happening on a timescale of milliseconds to seconds, involving billions of tubulin dimers across many microtubules in a single neuron, which is conceivable.
Thus the quantum states in microtubules are hypothesized to influence the neuron’s classical activity, such as the firing of action potentials. For example, the collective quantum state of microtubules might affect the neuron’s membrane potential or the release of neurotransmitters by altering the behavior of ion channels or synaptic vesicles. Hameroff has proposed that microtubules might interact with the neuron’s membrane through MAPs (microtubule-associated proteins – such as Tau proteins), which could link quantum events in microtubules to classical neuronal signaling.
If you don’t remember, Tau proteins are linked to Alzheimer’s disease and so I am also interested in the effects of the COVID shots on microtubules since there’s been an uptick in Alzheimer’s and degenerative diseases in general as seen in VAERS data. It’s an awful – but entirely plausible thought – to think that something in the COVID shots is messing with our quantum biology.
What is special about microtubules (besides the obvious)?
Penrose and Hameroff argue that microtubules are uniquely suited for quantum effects because of their nanoscale structure and potential for collective quantum behavior across many tubulin dimers. Their [crystal] lattice arrangement, size and scale, electrical properties (regions of positive and negative charge), and shielding from decoherence (gel-like cytoplasm or ordered water layers that shield them from environmental noise, allowing quantum coherence to persist for milliseconds to seconds, all contribute to the idea that these microtubules are quantum conduits.
The reduction part of the Penrose/Hameroff idea relates to microtubules whereby the objective collapse of quantum superpositions in microtubules’ tubulin dimers, driven by spacetime geometry, is proposed to produce discrete moments of conscious experience. Penrose and Hameroff estimate that these collapses occur at a frequency of about 40 Hz (matching the gamma frequency of brain waves often associated with conscious awareness), meaning consciousness is a series of such events. Foof. An example of a single conscious moment according to their theory would involve the collapse of superpositions across billions of tubulin dimers in thousands of neurons producing a unified experience like seeing a cat.
It’s kind of funny how Grok generated an image of 2 cats looking at each other. And one doesn’t have pupils.
The orchestrated part of the Penrose/Hameroff theory refers to the idea that biological processes in neurons including interactions with Tau proteins and other MAPs, synaptic inputs, or membrane potentials, orchestrate quantum events, ensuring they occur in a coordinated way across many microtubules and neurons.
On the gel-like cytoplasm and Ordered Water Layers- is it EZ water?
One of the things that I think warrants more attention in this discussion is the water component, and there’s no better to cite than Gerald Pollack for this. Gerald Pollack is a bioengineer at the University of Washington, is the founding Editor-in-Chief of the research journal WATER and Director of the Institute for Venture Science, and he studies water. More precisely, he studies the so-called fourth phase of water which has, you guessed it, gel-like properties.
Gerald Pollack has done amazing work for a very long time now on the subject matter of structured water. It goes something like this. Water molecules near biological structures like proteins or membranes can form structured layers due to hydrogen bonding and interactions with charged surfaces. Gerald’s work describes a form of water called exclusion zone (EZ) water, which forms near hydrophilic surfaces (like cell membranes or proteins) and has a more ordered, gel-like structure.
This structured water is more viscous and can exclude solutes, and some suggest it may play a role in cellular processes by organizing water molecules in a way that affects molecular interactions. Water acquires charge and becomes ordered when subjected to energetic inputs according to Gerald’s research. The water molecules link together to form hexagons to form a fourth phase of water as opposed to the known liquid, gas and solid water forms. According to his ideas, this fourth phase of water comprises most of the water in our cells and this has massive implications, including for Penrose and Hameroff’s hypothesis.
So is the water around microtubules more ordered than bulk water to function to reduce noise? I mean, without the shielding of microtubules from environmental noise via this water to prevent quantum decoherence (the loss of quantum states due to interactions with the environment), to allow quantum coherence to persist long enough for the proposed quantum processes to influence consciousness, would consciousness even be possible?
You should visit his site – there’s a nice video clip made by pro snowboarder, Travis Rice called The Fourth Phase.
Imagine for a second that Gerald is right, as I suspect he is. This explains so much with regard to biology in general – from blood pumping the heart to membrane potentials of cell walls. Imagine that the negative charge of EZ water could also influence how ions move; potentially affecting membrane potentials without needing as much energy as traditional models suggest. It’s like the cell gets a built-in battery from the water itself.
In membranes, this could mean the lipid bilayer isn’t just a passive barrier but an active player, with EZ water forming a layer that governs what gets in or out based on charge and structure rather than just size or solubility. It might even tie into why cells can maintain such precise electrical gradients – less about pumps working overtime and more about water’s inherent organization doing some of the heavy lifting.
If we weave EZ water into the context of neuronal microtubules, things get even more intriguing. Inside and around microtubules, water isn’t just a passive filler – it could be predominantly in this fourth phase, forming a negatively charged, ordered layer along the hydrophilic tubulin surfaces. Pollack’s work suggests EZ water excludes solutes and creates a proton-rich zone nearby, setting up a charge separation. In a neuron, this could mean microtubules aren’t just scaffolding but active electrical players. The negative charge of EZ water inside the tubes might act like a capacitor, storing and transmitting potentials along the neuron, complementing the membrane’s own gradients. This ties back into membrane potentials and charge – microtubules could be an internal booster, or even a parallel system.
Think about signal propagation. If EZ water lines the microtubules, their hollow cores might channel protons or ions, driven by this charge separation, almost like tiny bioelectric wires. This could speed up or fine-tune how neurons process signals, beyond what the axon’s action potential alone accounts for. It might also explain why microtubules are so abundant in dendrites and cell bodies, where integration of inputs happens – maybe they’re modulating local potentials via this water-based charge system.
Then there’s the transport angle. Microtubules ferry neurotransmitters and organelles using motor proteins like our cute little guys kinesin. If EZ water creates a slippery, charged interface, it could enhance efficiency – less friction, more electrostatic guidance. Pollack has demonstrated this in lab demonstrations with water near surfaces driving flow; scale that to a neuron, and it’s plausible.
Hameroff posits microtubules host quantum coherence. EZ water, being ordered and possibly shielding against decoherence, could stabilize those states. This hasn’t been proven yet, but this chick’s money is on it.
Microtubules functioning under the EZ water model could indeed be the bridge between biology and physics in neurons and indeed, unify the electrical and mechanical roles in the neuron. Think about it: charge dynamics, signal enhancement, and transport optimization – it’s all covered.
We should probably circle back to consciousness at this point.
Consciousness is a beast – subjective experience, self-awareness, the whole “what it’s like to be” thing. The Penrose-Hameroff Orch-OR idea says it’s quantum because classical systems, like a computer crunching 1s and 0s, can’t bridge the gap to qualia. They argue microtubules host quantum superpositions that collapse, tying physics to mind in a way classical mechanics can’t. It’s bold – Penrose even suggests that non-computable processes (quantum, maybe) are needed for human insight. If he’s right, consciousness might indeed need that quantum spark, and stuff like Pollack’s EZ water could be the glue keeping it coherent in the brain’s mess.
Brain biology is amazingly complex with trillions of neurons, synaptic plasticity, chaotic feedback loops, and emergent patterns that really do defy simple models. Think sync. My fireflies blinking at once, or a flock of birds: no bird computes the whole, yet the group moves as one. Consciousness could indeed be an emergent phenomenon from chaos, requiring no quantum magic. The brain has chemical gradients, electrical waves, and timing precision that rival any machine, all classical. Add in weirdness like mirror neurons or how psychedelics flip perception, and it’s plausible that sheer biological strangeness – amped up by evolution – gets us there. Quantum effects might juice it up (tunneling in synapses, say), but “needing them” feels like overkill when the system’s already so rich.
Considering that classical neural network models mimic cognition scarily well without a whiff of quantum, one might argue that since biology has proven it can do insane things with mundane parts (DNA’s a code, eyes are cameras, all from proteins and cells) without the need for quantum, why not consciousness too?
On the origins of consciousness from chemistry
“Nature wants us to to see things as they are.” Addy Pross
Is the whole world an illusion? Are bacteria aware? Addy Pross is a chemist and he has done remarkable work in his investgations of life itself. He penned the book “What Is Life? How Chemistry Becomes Biology”, which explores how chemistry can give rise to biology, and proposes that evolution is the biological expression of a deeper chemical principle. He would likely say that consciousness and cognition were around in the very early stages of evolution and that bacteria indeed are conscious, in order to persist. ‘Information flows and control systems are not one-way.’ Think about the fact that the central tenet of biology → DNA → mRNA → protein goes the other way too via reverse transcription.
Beyond thermodynamic states of matter, there are kinetic states of matter. Life itself, according to Addy Pross, is a replicating chemical system in a dynamic kinetic state. He says this kinetic state of matter flies in the face of the thermodynamics state of matter wherein the former holds that matter should be in a low energy state. Stability can mean low stability, but it can also mean persistent: unchanging over time and according to Pross, these do not need to overlap. You can have “stuff” that is unstable in “energy” terms, but stable in “time” terms and according to him, time stability is more fundamental in terms of kinetic and energetically stable systems than energy stability. So Pross argues that life is energetically unstable (it’s always fighting entropy with energy input, like ATP in cells) but temporally stable because it self-replicates faster than it degrades.
So how does this apply to our microtubules being consciousness-makers idea?
Pross argues that life operates in a kinetic state of matter, where temporal stability – persistence over time through replication – trumps energetic stability. Living systems are far-from-equilibrium, constantly using energy to maintain their structure and function. Microtubules in neurons fit this mold perfectly: they are dynamic structures, constantly assembling and disassembling, yet they persist as a network over time. They’re not in a low-energy state – they’re energetically active, with GTP molecules driving tubulin polymerization – but they achieve temporal stability through regulated cycles of growth and shrinkage. This aligns with Pross’s idea: microtubules are a system that is unstable in energy terms but stable in time, thanks to the cell’s machinery keeping them in a dynamic steady state.
Consciousness as a return to enable persistence…
Now, let’s bring in the consciousness angle, particularly through the lens of the Penrose and Hameroff’s Orch-OR theory aforementioned. They propose that microtubules in neurons aren’t just structural but computational, potentially hosting quantum superpositions that collapse to produce conscious moments. If we overlay Pross’s framework, microtubules could be seen as a microcosm of life’s kinetic state, but on a smaller scale within the neuron. Their dynamic nature – constantly cycling between growth and catastrophe – mirrors the far-from-equilibrium state Pross describes for life itself. This kinetic dance might be what allows microtubules to process information in a way that leads to consciousness.
Here’s where it gets interesting: Pross’s focus on replication as the driver of temporal stability doesn’t directly apply to microtubules (they don’t replicate like DNA), but the principle of persistence through dynamic activity does. Microtubules maintain their function through a balance of assembly, disassembly, and stabilization by proteins like MAPs, aforementioned. This dynamic stability could create the conditions for the quantum effects Hameroff talks about – like superpositions in tubulin dimers – by keeping the system in a high-energy, far-from-equilibrium state where quantum coherence might persist longer than expected. The brain’s warm, noisy environment should kill coherence fast, but a kinetically stable system might shield it, especially if EZ water (as we discussed) plays a role in structuring the environment around microtubules to reduce decoherence.
Now, let’s try to tie this to consciousness. If microtubules are indeed processing information via quantum effects, their kinetic state could be what enables this. The constant energy flow – GTP hydrolysis, ion movements, even EZ water’s charge effects – keeps them in a state where they can sustain the delicate quantum processes needed for Orch-OR’s “orchestrated” collapses. These collapses, in turn, might generate the subjective experience of consciousness. Pross suggests that life’s ability to exist in this kinetic state is what makes complexity possible; microtubules could be leveraging that same principle to enable the complexity of consciousness.
Let’s also loop in EZ water. If Pollack’s fourth phase of water lines microtubules, it could enhance their kinetic stability by providing a structured, charged environment that supports both classical and quantum processes. EZ water’s negative charge and proton gradients might act like a battery, driving the energy flows that keep microtubules in their far-from-equilibrium state. This could amplify their role as consciousness makers, whether through quantum effects or just by boosting their ability to integrate signals across the neuron.
So, Pross’s idea applies to microtubules by framing them as a dynamic, kinetically stable system within the larger kinetic state of the neuron. Their role in consciousness – whether quantum or classical – might depend on this state, allowing them to process information in ways that static, equilibrium systems couldn’t. It’s like they’re a miniature version of life’s trick: using energy to defy entropy and create something emergent, like awareness.
A closer look at the biochemistry of tubulin
One last thing about tubulin from a biochemical point of view. Tubulin polymerizes into microtubules: a process driven by GTP binding and hydrolysis. As demonstrated in the videos above, when GTP-bound beta-tubulin is added to a growing microtubule (at the plus end), the dimer assembles head-to-tail with other dimers, forming protofilaments – again: typically 13 of which align laterally into a hollow tube about 25 nm in diameter. GTP hydrolysis to GDP in beta-tubulin after incorporation destabilizes the structure, promoting dynamic instability: microtubules rapidly grow (rescue) when GTP-bound tubulin is abundant or shrink (catastrophe) when GDP-tubulin dominates, with rates of 1-10 μm/min in cells.
The alpha subunit binds GTP irreversibly (locked in place), while beta binds GTP reversibly, hydrolyzing it to GDP after incorporation. This GTP/GDP switch is the heart of tubulin’s ‘switch-like’ property. This switch is regulated by factors like Mg²⁺ ions, temperature, and MAPs (e.g., tau in neurons), which stabilize or destabilize the lattice. This is important to think about when contemplating coherent superposition. But what I am more interested in is getting down to the nitty gritty of the switch-like properties of the tubulin molecules with regard to structure and togetherness (quantum superpositions). In other words, how does the directional polarity “work”?
Tubulin dimers (alpha-beta pairs – 8 nm long) are inherently polarized because alpha-tubulin and beta-tubulin differ slightly in sequence and function, creating a molecular asymmetry. The inherent polarity doesn’t flip within a single dimer; it’s locked in from the moment the two subunits pair up in the cell’s cytoplasm. What does switch, and this is confusing, is the behavior of microtubules as a whole, driven by the collective state of many tubulin dimers.
Microtubules exhibit dynamic instability, where they grow (add GTP-bound dimers at the plus end) or shrink (lose GDP-bound dimers from the plus end), but this isn’t the individual dimers reversing polarity – it’s a change in the polymer’s length and stability. The GTP-to-GDP hydrolysis in beta-tubulin alters the dimer’s conformation (straight to curved), triggering growth or catastrophe, but the alpha-beta orientation within each dimer remains constant. Even when a microtubule depolymerizes, the released dimers retain their original polarity and can reassemble with the same plus-minus alignment.
If we go back to the PBS documentary about Penrose’s work and the superradiance study using tryptophan, it becomes clearer how the ordered arrangement could support quantum coherence, as the aligned dipoles (from tubulin’s charged regions or tryptophan’s electron clouds) might enhance collective effects like superradiance. The study’s focus on tryptophan (a fluorescent amino acid in tubulin) suggests that polarity contributes indirectly: the dimers’ consistent orientation in the microtubule lattice aligns these residues, potentially amplifying quantum interactions.
I highly recommend reading this article to find out more about microtubule dynamics. Below is a schematic from the amazing study described in the article where the authors used supercomputers to demonstrate a new behavior seen at microtubule tips.⁶ These guys claim this is awesome to make new drugs for Alzheimer’s, but I am thinking bigger: I think it has a lot to do with microtubule/tubulin involvement in quantum interactions.
Hameroff and Penrose suggest that tubulin dimers in microtubules exist in quantum superpositions, and their synchronized collapse – triggered by quantum gravity – generates conscious moments. This study’s findings could potentially inform their Orch-OR model by detailing how state transitions might contribute to network-wide dynamics.
On consciousness as harmonic tuning
Consciousness might be less like a random sneeze erupting from biological chaos and more like a melody harmonizing when the brain’s orchestra of sneezes coalesces into a unified rhythm. The brain’s got all these parts – neurons firing, chemicals sloshing, electrical impulses zipping around – and they’re not just noise. They sync up in patterns, like waves crashing in rhythm, a band locking into a groove, or my personal favorite: fireflies syncing up. These patterns show up as neural oscillations – think alpha, beta, gamma waves – measurable rhythms that shift with focus, sleep, or even meditation.
Tuned harmony could mean that consciousness isn’t just the chaos of complex biology or a simple pile-up of connections (like emergentism or Integrated Information Theory (IIT)). Instead, it could be what happens when these connections hit the right resonance. Imagine a guitar: pluck a string, and it’s just a twang – nothing special. But tune it, set it in a body that amplifies the vibration, and suddenly you’ve got music. The brain might be like that. With 86 billion neurons and trillions of synapses being the strings, consciousness might kick in when they vibrate in sync, forming a harmonic field.
This could tie into physics too. Some researchers – like those exploring electromagnetic field theories of consciousness – suggest the brain’s electrical activity generates fields that aren’t just by-products, but part of the awareness game. The Conscious Electromagnetic Information theory (CEMI) theory, for instance, posits that these fields integrate information across neurons, giving us that unified “I” feeling. Add harmonic resonance, and maybe it’s not any old field but a tuned one – like how our ghetto blaster picks up a clear signal when it’s dialed just right. Too much static (chaos), and you’re unconscious; perfect pitch, and you’re awake, aware: you.
Harmonic fields also might hint at something beyond biology. If consciousness needs this resonance, could it tap into some universal frequency? This idea is very speculative, but it’s not impossible, and as a scientist, it is my duty to explore all possibilities with humility. Studies on gamma waves (around 40 Hz) show they spike during focus and perception, and this hints at the idea that synchronized rhythms might indeed be the key to a conscious state.
The tuned harmony idea could be the brain acting like an instrument: chaos provides the raw material, complexity strings it together, but it’s the harmonic sweet spot – the resonant, synchronized fields – that makes consciousness sing.
One more thought: Bernardo Kastrup‘s (analytic idealism theory) idea of consciousness as the fundamental substrate of reality posits that mind, not matter, is the essence of existence and that matter does not create consciousness; it is consciousness that creates matter. Kastrup proposes that our physical reality is the outward appearance of our thoughts and emotions. He would say that the brain is the symptom of consciousness – much like a smile doesn’t cause happiness, the brain does not cause consciousness.
As I recently said at the Brownstone Retreat in Spain, I believe in magic and I also believe that in spite of the fact that emergent phenomena like consciousness could arise from chaos, I also believe that if quantum stuff was actually a part of this bare bones biology, it might better explain the unexplained. Like intuition. Memory. Quantum biology is real. We see examples of this with tunneling in enzymes and coherence in photosynthesis but applying it to consciousness, intuition, or memory is perhaps, remains to be seen.
Intuition is a real tricky thing to empirically define; it might just be fast, subconscious pattern-matching, chaos-driven; not quantum. Memory’s wild too – synaptic strengthening explains a lot classically, but some wonder if quantum coherence in microtubules (á la Orch-OR) could store or process more. Me? I don’t know yet.
I wanted this writing experience to be what I always aim for – a chance for both of us to learn – and I think I’ve succeeded. I haven’t resolved any major questions, but I’m fine with that. I’m excited by the testable research here: Could EZ water be the key to consciousness or how we ‘access’ it? I’m also happy that if these mechanisms hold, ANNs might never achieve consciousness through brute-force computing, at least. If neurons are also doing internal computations with microtubules, and “with a billion microtubules per neuron computing perhaps a million times faster than the neuron firing rate”⁷, then I would have to agree with PBS guy – we’re a long way away from AGI through this route. However, if there was a way that consciousness could be achieved, it would be via the fusion of ANNs (AIs) and quantum computers. And one last brain-poking question: What would happen if this happened?
I guess it all depends on what you believe is possible.
I would love feedback from your generous minds on this subject matter.
1
Koch, C. (2019). The Feeling of Life Itself: Why Consciousness Is Widespread but Can’t Be Computed. MIT Press
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Chalmers, D. J. (1995). Facing Up to the Problem of Consciousness. Journal of Consciousness Studies, 2(3), 200-219
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Azevedo, F.A.C., Carvalho, L.R.B., Grinberg, L.T., Farfel, J.M., Ferretti, R.E.L., Leite, R.E.P., Filho, W.J., Lent, R. and Herculano-Houzel, S. (2009), Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J. Comp. Neurol., 513: 532-541. https://doi.org/10.1002/cne.21974
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Jiangbo Wu et al, Data-driven equation-free dynamics applied to many-protein complexes: The microtubule tip relaxation, Biophysical Journal(2025). DOI: 10.1016/j.bpj.2025.01.009
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