သိစိတ္ဆိုတာ ဘာပါလိမ့္

သိစိတ္ဆိုတာ ဘာလဲ ။ က်ေနာ္တို႔ သိႀကတာက ၀တၳဳပစၥည္းတစ္ခုခုကိုပဲ ျဖစ္ျဖစ္ ၊ အေႀကာင္းအရာတစ္ခုခုကိုပဲ ျဖစ္ျဖစ္ အာရံုခံ အရာ ငါးပါးနဲ႔ ရင္ဆိုင္ေတြ႔ ၊ ထိခုိက္ျပီး ေပၚလာတဲ႔ အာရံုကို သိတယ္လို႔ သတ္မွတ္ႀကတယ္..။ အဲ႔ဒါကို သိလိုက္တယ္လို႔ ေခၚမယ္။ အနုစိတ္ေျပာရင္ ဗုဒၶဘာသာဘက္ကို သိပ္ေရာက္ေနမွာမို႔ ….လူဗိန္းအေတြးနဲ႔ပဲ စဥ္းစားျပီး ေရးပါမယ္။

က်ေနာ္တို႔ ဘာကို ဘယ္လို သိလိုက္ပါသလဲ။ သိတယ္ဆိုတာ ဘယ္ဟာကို ေခၚတာပါလဲ။ စကားလံုးေတြနဲ႔ မရွဳပ္ေထြးႀကပါစို႔နဲ႔ ။ေလာေလာဆယ္မွာေတာ့ အေနာက္တိုင္း သိပၸံ ပညာရွင္ ေတြ ထဲက အာရံုေႀကာပိုင္းအထူးျပဳ ပညာရွင္ေတြ အဲ႔ဒါကို ေတာ္ေတာ္ သိခ်င္ေနႀကပါတယ္။ သိစိတ္ကို ဘယ္လိုဆိုတာ သိခ်င္ေနတဲ႔သေဘာေပါ့ဗ်ာ။ အဲ႔အထဲမွာ ဒႆနိက သမားေေတြလည္း ထိပ္ဆံုးက ပါမယ္။ တကယ္ကလည္း ဒီအေႀကာင္းအရာဟာ ဒႆနိကနဲ႔ သိပၸံပညာရဲ ႔ အစဦးမွာကတည္းက ေပါက္ဖြားေနတဲ႔ ကိစၥေတြျဖစ္ပါတယ္။

ေလာေလာဆယ္မွာ မႀကာေသးမီက ( Tufts တကၠသိုလ္က ဒႆနိကပါေမာကၡ )Daniel Dennett က လူေတြရဲ႕ သိမွတ္မႈဟာ နွစ္ေပါင္း ႀကာရွည္ခက္ခဲေနတဲ႔၊ မေျဖရွင္းနိုင္ေသးတဲ႔ ကိစၥႀကီးတစ္ခု ျဖစ္တယ္လို႔ ဆိုပါတယ္။ လူသားေတြဟာ သူတို႔အတြက္ ခက္ခဲေနတဲ႔ ဒီသိစိတ္ဆိုတာႀကီးကိုပဲ အသံုးျပဳျပီး က်ေနာ္တို႔ သိခ်င္လွတဲ႔ စႀက၀ဠာသေဘာေတြ၊ အမႈန္ရူပေဗဒေတြ ၊ ေမာ္လီက်ဴးဇီ၀ဂမၼသေဘာေတြ၊ ဆင့္ကဲသီ၀ရီေတြ ေဖာ္ထုတ္လာမိႀကတာျဖစ္ပါတယ္။ ဒါေပမယ့္ သိစိတ္ ဆိုတာနဲ႔ ပတ္သက္ျပီးေတာ့ ခုထိမသိနိုင္ေလာက္ေအာင္ ရွိေနတုန္းပါပဲ…။ ကိုယ္ အသံုးခ်တဲ႔ လက္နက္ဟာ ဘာဆိုတာ မသိနိုင္ေသးေလာက္ေအာင္ က်ေနာ္တို႔အတြက္ခက္ခဲေနႀကတာပါလား ဆိုတဲ႔သေဘာနဲ႔ ေျပာသြားတာ ေတြ႕လိုက္မိပါတယ္။

အရာရာမွာ ေတာ္လွပါခ်ည္ရဲ႕ ဆိုတဲ႔ အသိသညာရွင္ႀကီးမ်ားနဲ႔ အတတ္ပညာရွင္ႀကီးမ်ားကို သိစိတ္နဲ႔ပတ္သက္လို႔ ေမးျမန္းမိရင္ …ဥာဏ္ႀကီးရွင္မ်ား လ်ာလိပ္ ကုန္ႀကတယ္။ ေတြေ၀ကုန္ ႀကတယ္။ ဒီသိစိတ္ဟာ ဘာေႀကာင့္မ်ား ဒီကေလာက္ နက္နဲေနရတာပါလဲ။

အေျခခံ သေဘာအားျဖင့္ေတာ့ သိစိတ္ဆိုတာ နိုးႀကားမႈနဲ႔ ဇီ၀ သတင္းအခ်က္အလက္ ကူးသြယ္ျခင္း လုပ္ရပ္တစ္မ်ိဳး ျဖစ္ပါတယ္။ ဆရာမ်ား ဆံုးျဖတ္ႀကတာက သိစိတ္ဟာ နိုးႀကားမႈ အေပၚ မွီခိုမေနဘူးလို႔ တြက္ဆႀကပါတယ္။ ဘယ္လိုပဲျဖစ္ေနပါေစ….သိျခင္းအစဥ္ဆိုတာ အာရံုေႀကာ ဆိုင္ရာ ျဖစ္စဥ္တစ္မ်ိဳးပဲ လို႔.. ရုပ္ဘက္ကေန ရပ္တည္ျပီး တိတိက်က်ေျပာႀကည့္ရေအာင္တဲ႔..။ သူတို႔ေျပာတာကို အဟုတ္လို႔လက္ခံရင္ ျပန္လွန္ေမးႀကည့္ခ်င္တာရွိပါတယ္။ အာရံုေႀကာေတြေပၚမွီခိုျပီးသိတယ္လို႔ သတ္မွတ္ရမယ့္ ဒီအဆိုမွာ ဟာကြက္ရွိပါတယ္။ အသိတစ္ခုဟာ မွန္ကန္မႈ ရွိေနမယ္ မရွိေနဘူးကို …သူတို႔စကားအရ.အာရံုေတြကို အားကိုးရေတာ့မယ္ဆုိေတာ့ ဒီအာရံုေတြမွာ အမွားအယြင္းရွိေနရင္ ဒီသိစိတ္အစဥ္ႀကီးေကာ မွားေနမလားဆိုတာ ေမးရပါမယ္။

လက္ေတြ႔မွာတင္ ကိစၥရပ္တစ္ခုအေပၚ အာရံုတပ္မိတာခ်င္း မတူညီတာေတြ က်ေနာ္တို႔ လူသားေတြႀကား ခဏခဏ ေတြ႔ေနရပါတယ္။ ဥပမာ – စားပြဲတစ္လံုးကို ျမင္တာေတာင္ က်ေနာ္ ျမင္တာနဲ႔ ခင္ဗ်ားျမင္တာမတူသလိုေပါ့ဗ်ာ။ ဒီဥပမာက ေသးပါေသးတယ္။ အျခားႀကီးႀကီးမားမား နိုင္ငံေရး၊ စီးပြားေရ စသျဖင့္ က်ေနာ္တို႔ ရုပ္၀ထၳဳအားျဖင့္ ခ်ျပလို႔မရတဲ႔ သိေနရမယ့္ ဟာ ေတြ မွာ …ဘယ္အာရံုခံနဲ႔ႀကည့္ျပီး အမွန္အမွား ခြဲျခားႀကမတဲ႔လဲ…။

အဲ႔ဒါက တစ္ပိုင္း။

အခု အဲ႔ဒါကို ေျဖရွင္းဖို႔ ဆရာမ်ားႀကိဳးစားႀကရာမွာ..ကေလးအေတြးနဲ႔ စတင္ႀကပါေတာ့တယ္။ ကေလးေတြ ဘယ္လိုေတြးမလဲ။ သိတယ္ဆိုတာ ေခါင္းထဲကလာတာ..။ ေခါင္းထဲက ဆိုေတာ့ ဦးေနွာက္ထဲကေပါ့ ။ က်ေနာ္တို႔ ဦးေနွာက္ရဲ႕ အတြင္းမွာ လ်ပ္စစ္ဓါတ္ေတြကူးလူးေနရာကေန..အသိ၊ သိစိတ္ျဖစ္လာမယ္လို႔ အနုမာန မွန္းဆ ႀကည့္လိုက္တယ္။ ခုိင္လံုတဲ႔ အေႀကာင္းျပခ်က္ မ်ိဳး ျဖစ္လာေစဖို႔ ႀကိဳးပမ္းႀကရာမွာ ..၂၀၀၉ ခုနွစ္၊ သခ်ၤာရူပေဗဒသမား Roger Penrose နဲ႔ အာရံုေႀကာသိပၸံပညာရွင္ Stuart Hamerhoff တို႔ ပူးေပါင္းစဥ္းစားထားတဲ႔ Quantum Mind Theory ဟာ ထင္ရွားပါတယ္။

အဲ႔ သီ၀ရီအေႀကာင္းကို ေရွ႕ပို႔စ္မွာေျပာဖုိ႔အတြက္ က်ေနာ္တို႔အခုအရင္ သိစိတ္ဆိုတာဘာပါလိမ့္လို႔ ( ခဏ ) ကိုယ့္ဘာသာကိုယ္ ေတြးႀကည္႔ႀကရေအာင္ဗ်ာ။

What is Consciousness?

Table of Contents
  1. The problem of consciousness
  2. Microtubules
  3. Pan-experiential philosophy meets modern physics
  4. Quantum computing and consciousness
  5. Roger Penrose’s ‘objective reduction’
  6. Are proteins qubits?
  7. Microtubule quantum automata – the ‘Orch OR’ model
  8. Orch OR, cognition and free will
  9. Consciousness and evolution
  10. Conclusions
  11. Acknowledgements/References
1. The Problem of Consciousness

Conventional explanations portray consciousness as an emergent property of classical computer-like activities in the brain’s neural networks. The prevailing views among scientists in this camp are that 1) patterns of neural network activities correlate with mental states, 2) synchronous network oscillations in thalamus and cerebral cortex temporally bind information, and 3) consciousness emerges as a novel property of computational complexity among neurons.
However, these approaches appear to fall short in fully explaining certain enigmatic features of consciousness, such as:

  • The nature of subjective experience, or ‘qualia’- our ‘inner life’ (Chalmers’ “hard problem”);
  • Binding of spatially distributed brain activities into unitary objects in vision, and a coherent sense of self, or ‘oneness’;
  • Transition from pre-conscious processes to consciousness itself;
  • Non-computability, or the notion that consciousness involves a factor which is neither random, nor algorithmic, and that consciousness cannot be simulated (Penrose, 1989, 1994, 1997);
  • Free will; and,
  • Subjective time flow.

Brain imaging technologies demonstrate anatomical location of activities which appear to correlate with consciousness, but which may not be directly responsible for consciousness.
Figure 1. PET scan image of brain showing visual and auditory recognition (from S Petersen, Neuroimaging Laboratory, Washington University, St. Louis. Also see J.A. Hobson “Consciousness,” Scientific American Library, 1999, p. 65).

Figure 2. Electrophysiological correlates of consciousness.
How do neural firings lead to thoughts and feelings? The conventional (a.k.a. functionalist, reductionist, materialist, physicalist, computationalist) approach argues that neurons and their chemical synapses are the fundamental units of information in the brain, and that conscious experience emerges when a critical level of complexity is reached in the brain’s neural networks.
The basic idea is that the mind is a computer functioning in the brain (brain = mind = computer). However in fitting the brain to a computational view, such explanations omit incompatible neurophysiological details:

  • Widespread apparent randomness at all levels of neural processes (is it really noise, or underlying levels of complexity?);
  • Glial cells (which account for some 80% of brain);
  • Dendritic-dendritic processing;
  • Electrotonic gap junctions;
  • Cytoplasmic/cytoskeletal activities; and,
  • Living state (the brain is alive!)

A further difficulty is the absence of testable hypotheses in emergence theory. No threshold or rationale is specified; rather, consciousness “just happens”.
Finally, the complexity of individual neurons and synapses is not accounted for in such arguments. Since many forms of motile single-celled organisms lacking neurons or synapses are able to swim, find food, learn, and multiply through the use of their internal cytoskeleton, can they be considered more advanced than neurons?

Figure 3. Single cell paramecium can swim and avoid obstacles using its cytoskeleton.
Are neurons merely simple switches?

2. Microtubules

Activities within cells ranging from single-celled organisms to the brain’s neurons are organized by a dynamic scaffolding called the cytoskeleton, whose major components are microtubules. Hollow, crystalline cylinders 25 nanometers in diameter, microtubules are comprised of hexagonal lattices of proteins, known as tubulin. Microtubules are essential to cell shape, function, movement, and division. In neurons microtubules self-assemble to extend axons and dendrites and form synaptic connections, then help to maintain and regulate synaptic activity responsible for learning and cognitive functions. Microtubules interact with membrane structures mechanically by linking proteins, chemically by ions and “second-messenger” signals, and electrically by voltage fields.

Figure 4. Schematic view of two neurons connected by chemical synapse. Axon terminal (above) releases neurotransmitter vesicles which bind receptors on post-synaptic dendritic spine. Within neurons are visible cytoskeletal structures microtubules (“MTs” – thicker tubes) as well as actin, synapsin and others which connect MTs to membranes. Also, MT-associated proteins (“MAPs”) interconnect MTs.

Figure 5. Immunoelectron micrograph of dendritic microtubules interconnected by MAPs. Some MTs have been sheared, revealing internal hollow core. The granular “corn-cob” surface of MTs is barely evident to close inspection. Scale bar, lower left: 100 nanometers. With permission from Hirokawa, 1991.

Figure 6. Crystallographic structure of microtubules.
While microtubules have traditionally been considered as purely structural elements, recent evidence has revealed that mechanical signaling and communication functions also exist:

  • MT “kinks” travel at 15 microns (2000 tubulin subunits) per second. Vernon and Woolley (1995) Experimental Cell Research 220(2)482-494
  • MTs vibrate (100-650 Hz) with nanometer displacement. Yagi, Kamimura, Kaniya (1994) Cell motility and the cytoskeleton 29:177-185
  • MTs optically “shimmer” when metabolically active. Hunt and Stebbings (1994), Cell motility and the cytoskeleton 17:69-78
  • Mechanical signals propogate through microtubules to cell nucleus; mechanism for MT regulation of gene expression. Maniotis, Chen and Ingber (1996) Proc. Natl. Acad. Sci. USA 94:849-854
  • Measured tubulin dipoles and MT conductivity suggest MTs are ferroelectric at physiological temperature (Tuszynski; Unger 1998)

Current models propose that tubulins within microtubules undergo coherent excitation, switching between two or more conformational states in nanoseconds. Dipole couplings among neighboring tubulins in the microtubule lattice form dynamical patterns, or “automata,” which evolve, interact and lead to the emergence of new patterns. Research indicates that microtubule automata computation could support classical information processing, transmission and learning within neurons.

Figure 7. Left: Microtubule (MT) structure: a hollow tube of 25 nanometers diameter, consisting of 13 columns of tubulin dimers arranged in a skewed hexagonal lattice (Penrose, 1994). Right (top): Each tubulin molecule may switch between two (or more) conformations, coupled to London forces in a hydrophobic pocket. Right (bottom): Each tubulin can also exist (it is proposed) in quantum superposition of both conformational states.

Figure 8. Microtubule automaton simulation (from Rasmussen et al., 1990). Eight nanosecond time steps of a segment of one microtubule are shown in “classical computing” mode in which conformational states of tubulins are determined by dipole-dipole coupling between each tubulin and its six (asymmetrical) lattice neighbors. Conformational states form patterns which move, evolve, interact and lead to emergence of new patterns.
Microtubule automata switching offers a potentially vast increase in the computational capacity of the brain. Conventional approaches focus on synaptic switching at the neural level which optimally yields about 1018 operations per second in human brains (~1011 neurons/brain with ~104 synapses/neuron, switching at ~103 sec-1). Microtubule automata switching can explain some 1027 operations per second (~1011 neurons with ~107 tubulins/neuron, switching at ~109-1). Indeed, the fact that all biological cells typically contain approximately 107 tubulins could account for the adaptive behaviors of single-celled organisms which have no nervous system or synapses. Rather than simple switches, neurons are complex computers. sec

3. Pan-experiential philosophy meets modern physics

Still, greater computational complexity and ultra-reductionism to the level of microtubule automata cannot address the enigmatic features of consciousness, in particular the nature of conscious experience. Something more is required. If functional approaches and emergence are incomplete, perhaps the raw components of mental processes (qualia) are fundamental properties of nature (like mass, spin or charge). This view has long been held by pan-psychists throughout the ages, for example Buddhists and Eastern philosophers claim a “universal mind.” Following the ancient Greeks, Spinoza argued in the 17th century that some form of consciousness existed in everything physical. The 19th century mathematician Leibniz proposed that the universe was composed of an infinite number of fundamental units, or “monads,” with each possessing a form of primitive psychological being. In the 20th century, Russell claimed that there was a common entity underlying both mental and physical processes, while Wheeler and Chalmers have maintained that there exists an experiential aspect to fundamental information.
Of particular interest is the work of the 20th century philosopher Alfred North Whitehead, whose pan-experiential view remains most consistent with modern physics. Whitehead argued that consciousness is a process of events occurring in a wide, basic field of proto-conscious experience. These events, or “occasions of experience,” may be comparable to quantum state reductions, or actual events in physical reality (Shimony, 1993). This suggests that consciousness may involve quantum state reductions (e.g. a form of quantum computation).
But what of Whitehead’s basic field of proto-conscious experience? In what medium are the “occasions of experience” (?quantum state reductions) occurring? Could proto-conscious qualia simply exist in the empty space of the universe?
What is empty space? Historically, empty space has been described as either an absolute void or a pattern of fundamental geometry. Democritus and the Michaelson-Morley results argued for “nothingness” while Aristotle (“plenum”) and Maxwell (“ether”) rejected the notion of emptiness in favor of “something” – a background pattern. Einstein weighed in on both sides of this debate, initially supporting the concept of a void with his theory of special relativity but then reversing himself in his theory of general relativity and its curved space and geometric distortions-the space-time metric. Could proto-conscious qualia be properties of the metric, fundamental space-time geometry?
What is fundamental space-time geometry? We know that at extremely small scales, space-time is not smooth, but quantized. Quantum electrodynamics and quantum field theory predict virtual particle/waves (or photons) that pop into and out of existence, creating quantum “foam” in their wake. The presence of virtual photons in space-time has been verified (Lamoreaux, 1997).

Figure 9. Quantum electodynamics (QED) predicts a foam of erupting and collapsing virtual particles which may be visualized as topographic distortions of the fabric of spacetime. Adapted from Thorne (1994) by Dave Cantrell.

Figure 10. A: The Casimir force of the quantum vacuum zero point fluctuation energy may be measured by placing two macroscopic surfaces separated by a tiny gap d1. As some virtual photons are excluded in the gap, the net “quantum foam” pressure forces the surfaces together. In Lamoreaux’s (1997) experiment, d1 was in the range of 0.6 to 6.0 microns (~1500 nanometers). B: George Hall (1996; 1997) has calculated the Casimir force on microtubules. As the force is proportional to d-4, and d2 for microtubules is 15 nanometers, the predicted Casimir force is 106 greater on microtubules (per equivalent surface area) than that measured by Lamoreaux. Hall calculates a range of Casimir force on microtubules (length dependent) from 0.5 to 20 atmospheres.
At the basic level, this granularity has been modeled by Roger Penrose as a dynamic web of quantum spins. These “spin networks” create an array of geometric volumes and configurations at the Planck scale (10-33 cm, 10-43 secs) which dynamically evolve and define space-time geometry.

Figure 11. A spin network. Introduced by Roger Penrose (1971) as a quantum mechanical description of the geometry of space, spin networks describe spectra of discrete Planck scale volumes and configurations (with permission, Rovelli and Smolin, 1995).
If spin networks are the fundamental level of space-time geometry, they could provide the basis for proto-conscious experience. In other words, particular configurations of quantum spin geometry would convey particular types of qualia, meaning and aesthetic values. A process at the Planck scale (e.g. quantum state reductions) could access and select configurations of experience.
For illustration, 4 dimensional space-time geometry is often portrayed as a 2 dimensional “space-time sheet.”

Figure 12. According to Einstein’s general relativity, mass is equivalent to curvature in spacetime geometry. Penrose applies this equivalence to the fundamental Planck scale. The motion of an object between two conformational states of a protein such as tubulin (top) is equivalent to two curvatures in spacetime geometry as represented as a two-dimensional spacetime sheet (bottom).

4. Quantum computing and consciousness

If proto-conscious information is embedded at the near-infinitesimal Planck scale, how could it be linked to biology? To begin, Penrose extends Einstein’s theory of general relativity (in which mass equates to curvature in space-time) down to the Planck scale. As a result, specific arrangements of mass are, in reality, specific configurations of space-time geometry. Events at the very small scale, however, are subject to the seemingly bizarre goings-on of quantum theory.
A century of experimental observation of quantum systems have shown that, at least at small scales, particles (mass) can exist in two or more states or locations simultaneously (quantum superposition). Penrose takes superposition (e.g. a mass in two places simultaneously) to be simultaneous space-time curvature in opposite directions – a separation, or bubble (“blister”) in underlying reality.

Figure 13. Mass superposition, e.g. a protein occupying two different conformational states simultaneously (top) is equivalent, according to Penrose, to simultaneous spacetime curvature in opposite directions – a separation, or bubble (“blister”) in fundamental spacetime geometry.

Figure 14. Spacetime superposition/separation bubble (bottom) will reduce, or collapse to one or the other spacetime curvatures (top).
Superposition and subsequent reduction, or collapse, to single, classical states may have profoundly important applications in technology, as well as toward the understanding of consciousness. In the 1980s Benioff, Feynman, Deutsch and other physicists proposed that states in a quantum system could interact (via entanglement) and enact computation while in quantum superposition of all possible states (“quantum computing”). Classical computing processes bits (or conformational states) as 1 or 0, quantum computations involve the processing of superpositioned “qubits” of both 1 and 0 (and other states) simultaneously.

Figure 15. Qubits useful in quantum computation may exist in two or more (“both”) states simultaneously prior to collapse, or reduction (left), and then in single, classical (“either, or”) states after reduction (right). Spin, quantum dots and photon polarization qubits have been proposed and/or demonstrated in prototype quantum computers, and tubulin proteins and spacetime geometry are proposed in the Orch OR model to perform as qubits also.
Quantum theory also tells us that two or more particles, if once together, will remain somehow connected (“entangled”), even when separated by great distances. Qubits can interact by quantum entanglement, so that quantum computing is able to achieve a nearly infinite parallel computational ability. Quantum computers, if they can be constructed, will be able to solve imprtant problems (e.g. factoring large numbers) with efficiency unattainable in classical computers (Shor, 1994).
Researchers have developed a “Figure of Merit” M for proposed quantum computing technologies (Modified from Barenco, 1996 & DiVincenzo, 1995). M is related to the number of elementary operations performed per qubit before the superposition/computation is disrupted by decoherence (or in the case of microtubules in the Orch OR proposal, before objective reduction terminates the superposition).

Technology telem
(sec)
Tdecoherence
(sec)
M (operations/qubit
pre-decoherence)
Mossbauer nucleus 10-19 10-10 109
Electrons GaAs 10-13 10-10 103
Electrons Au 10-14 10-8 106
Trapped ions 10-14 10-1 1013
Optical cavities 10-14 10-5 109
Electron spin 10-7 10-3 104
Electron quantum dots 10-6 10-3 103
Nuclear spin 10-3 104 107
Superconductor islands 10-9 103 106
Microtubule tubulins 10-9 10-1 108

Results, or solutions in quantum computing are obtained when, after a period of quantum superposition/computation, the qubits “collapse”, or reduce to classical bit states (“collapse of the wave function”). As quantum superposition may only occur in isolation from environment, collapse (reduction) may be induced by breaching isolation (this is what is envisioned in technological quantum computers – making a measurement). But what about quantum superpositions which remain isolated, for example Schrodinger’s mythical cat which is both dead and alive? This is the famous problem of collapse of the wave function, or quantum state reduction.

5. Roger Penrose’s ‘objective reduction’ OR

How or why do quantum superpositioned states which avoid environmental interactions become classical and definite in the macro-world? Many physicists now believe that some objective factor disturbs the superposition and causes it to collapse. Roger Penrose proposes that this factor is an intrinsic feature of space-time geometry itself – quantum gravity. According to Penrose’s interpretation of general relativity, quantum superposition (e.g. separation of mass from itself) is equivalent to separation in underlying space-time geometry-simultaneous space-time curvatures in opposite directions. Penrose argues that these separations in fundamental reality, (“bubbles, or blisters”) are unstable-even when isolated from the environment-and will reduce spontaneously (and non-computably) to specific states at a critical threshold of space-time separation (thereby avoiding the need for “multiple worlds”). This objective threshold is defined by the indeterminacy principle:
E = h/T
where E is the gravitational self-energy of the superposed mass separated from itself, h is Planck’s constant divided by 2pi, and T is the coherence time until collapse occurs. Thus, the size and energy of a system in superposition, or the degree of space-time separation, is inversely related to the time T until reduction. (E can be calculated from the superposed mass m and the separation distance a. See e.g. Hameroff and Penrose, 1996a.)
Assuming isolation, the following masses in superposition would collapse at the designated times, according to Penrose’s objective reduction:

Mass (m) Time (T)
Nucleon 107 years
Beryllium ion 106 years
Water Speck

10-5 cm radius Hours

10-4 cm radius 1/20 second

10-3 cm radius 10-3 seconds
Schrodinger’s cat (m=1kg, a=10 cm) 10-37 seconds

If quantum computation with objective reduction were occurring in the brain, enigmatic features of consciousness (see Section above – The Problem of Consciousness) could be explained:

  • By occurring as a self-organizing process in what is suggested to be a pan-experiential medium of fundamental spacetime geometry, objective reductions could account for the nature of subjective experience by accessing and selecting proto-conscious qualia.
  • By virtue of involvement of unitary (entangled) quantum states during pre-conscious quantum computation and the unity of quantum information selected in each objective reduction, the issue of binding may be resolved.
  • Regarding the transitions from pre-conscious processes to consciousness itself, the pre-conscious processes may equate to the quantum superposition/quantum computation phase, and consciousness itself to the actual (instantaneous) objective reduction events. Consciousness may then be seen as a sequence of discrete events (e.g. at 40 Hz).
  • As Penrose objective reductions are proposed to be non-computable (reflecting influences from space-time geometry which are neither random, nor algorithmic) conscious choices and understanding may be similarly non-computable.
  • Free will may be seen as a combination of deterministic pre-conscious processes acted on by a non-computable influence.
  • Subjective time flow derives from a sequence of irreversible quantum state reductions.

Could objective reduction be occurring in the brain? If so (from E = h/T) time T would be expected to coincide with known neurophysiological processes with time scales from tens to hundreds of milliseconds (e.g. 25 msec for coherent 40 Hz, 100 msec for alpha EEG, 500 msec for sensory threshold events such as Libet’s famous 1979 experiments). In what types of brain structures might quantum computation with objective reduction occur? For T in this range we can calculate (from E = h/T, and with E related to mass m as described in Hameroff and Penrose, 1996a) that superpositioned mass m in the nanogram range would be required for conscious events of 40 to 500 msec. What brain components in nanogram quantitites could support quantum computation and objective reduction? What is m?

6. Are proteins qubits?

Biological life is organized by proteins. By changing their conformational shape, proteins are able to perform a wide variety of functions, including muscle movement, molecular binding, enzyme catalysis, metabolism, and movement. Dynamical protein structure results from a “delicate balance among powerful countervailing forces” (Voet & Voet, 1995). The types of forces acting on proteins include charged interactions (such as covalent, ionic, electrostatic, and hydrogen bonds), hydrophobic interactions, and dipole interactions. The latter group, also known as van der Waals forces, encompasses three types of interactions:

  • permanent dipole – permanent dipole,
  • permanent dipole – induced dipole, and
  • induced dipole – induced dipole (London dispersion forces)

As charged interactions cancel out, hydrophobic and dipole – dipole forces are left to regulate protein structure. While induced dipole – induced dipole interactions, or London dispersion forces, are the weakest of the forces outlined above, they are also the most numerous and influential. Indeed, they may be critical to protein function. For example, anesthetics are able to bind in hydrophobic “pockets” of certain neural proteins and ablate consciousness by virtue of disrupting these London forces. London force attraction between any two atoms is usually less than a few kilojoules; however, since thousands occur in each protein, they add up to thousands of kilojoules per mole, and cause changes in conformational structure. As London forces are instrumental in protein folding (a problem intractable to conventional computational simulation), protein conformation and folding may be quantum computations.
Figure 16. A type of van der Waals force, the London dispersion force, is quantum mechanical and governs both protein conformation.

Figure 17. A. An anesthetic gas molecule (A) in a hydrophobic pocket of critical brain protein (receptors, channels, tubulin etc.) prevents normally occurring London forces, preventing protein conformational dynamics and superposition necessary for consciousness. B. A psychedelic hallucinogen (P) acts in hydrophobic pocket in critical brain protein to promote and sustain superposition, ‘expanding’ consciousness (see Figure 25).

Figure 18. A. Protein qubit. A protein such as tubulin can exist in two conformations determined by quantum London forces in hydrophobic pocket (top), or superposition of both conformations (bottom). B. The protein qubit corresponds to two alternative spacetime curvatures (top), and superposition/separation (bubble) of both curvatures (bottom).
If proteins are qubits, arrays or assemblies of proteins in some type of organelle or biomolecular structure could be a quantum computer. Ideal structures would be:

  • Abundant;
  • Capable of information processing and computation;
  • Functionally important (e.g., regulating synapses);
  • Self-organizing;
  • Tunable by input information (e.g., microtubule-associated protein orchestration);
  • Periodic and crystal-like in structure (e.g., dipole lattice);
  • Isolated (transiently) from environmental decoherence;
  • Conformationally coupled to quantum events (e.g., London forces);
  • Cylindrical wave-guide structure; and,
  • Plasma-like charge layer coating.

While various structures/organelles have been suggested (e.g., membrane proteins, clathrins, myelin, pre-synaptic grids, and calcium ions), the most logical candidates are microtubule automata.

Figure 19. The Penrose-Hameroff Orch OR model was hatched on a hike in the Grand Canyon following the Tucson I conference in April, 1994. From left: David Chalmers, Rhett Savage, Marie-Francoise Insinna, Seamus O’Morain, Stuart Hameroff, Roger Penrose, Vanessa Penrose, Jeff Tollaksen. Photo by Ezio Insinna.

7. Microtubule quantum automata – The ‘Orch OR’ model

The Penrose – Hameroff model of “orchestrated objective reduction” (Orch OR) proposes that:

  • Quantum superposition/computation occur in microtubule automata within brain neurons and glia.;
  • Tubulin subunits within microtubules act as qubits, switching between states on a nanosecond (10-9 sec) scale governed by quantum London forces in hydrophobic pockets;
  • Tubulin qubits interact computationally by nonlocal quantum entanglement according to the Schrodinger equation;


Figure 20. The basic idea in the Orch OR model is that each tubulin in a microtubule is a qubit.

Figure 21. Microtubule automaton sequence simulation in which classical computing (step 1) leads to emergence of quantum coherent superposition (steps 2-6) in certain (gray) tubulins due to pattern resonance. Step 6 (in coherence with other microtubule tubulins) meets critical threshold related to quantum gravity for self-collapse (Orch OR). Consciousness (Orch OR) occurs in the step 6 to 7 transition. Step 7 represents the eigenstate of mass distribution of the collapse which evolves by classical computing automata to regulate neural function. Quantum coherence begins to re-emerge in step 8.


  • pre-conscious processing which continues until the threshold for objective reduction (OR) is reached by E = h/T;
  • At that instant collapse, or OR occurs which is an actual event in fundamental space-time geometry. This event selects a particular configuration of Planck-scale experiential geometry, enacting a “moment of awareness,” “occasion of experience” or conscious event.


Figure 22. Schematic graph of proposed pre-conscious quantum superposition (number of tubulins) emerging versus time in microtubules. Area under curve connects superposed mass energy E with collapse time T in accordance with E=(h/T. E may be expressed as nt, the number of tubulins whose mass separation (and separation of underlying space time) for time T will self-collapse. For T = 25 msec (e.g. 40 Hz oscillations), nt = 2 x 1010 tubulins.

Figure 23. Schematic of quantum computation of three tubulins which begin (left) in initial classical states, then enter isolated quantum superposition in which all possible states coexist. After reduction, one particular classical outcome state is chosen (right).

Figure 24. Schematic quantum computation in spacetime curvature for three mass distributions (e.g. tubulin conformations in Figure 23) which begin (left) in initial classical states, then enter isolated quantum superposition in which all possible states coexist. After reduction, one particular classical outcome state is chosen (right).


  • A sequence of OR events (e.g. at 40 Hz) provides a forward flow of subjective time and “stream” of consciousness;


Figure 25. Quantum superposition/entanglement in microtubules for 5 states related to consciousness. Area under each curve equivalent in all cases. A. Normal 30 Hz experience: as in Figure 22. B. Anesthesia: anesthetics bind in hydrophobic pockets and prevent quantum delocalizability and coherent superposition. C. Heightened Experience: increased sensory experience input (for example) increases rate of emergence of quantum superposition. Orch OR threshold is reached faster, and Orch OR frequency increases. D. Altered State: even greater rate of emergence of quantum superposition due to sensory input and other factors promoting quantum state (e.g. meditation, psychedelic drug etc.). Predisposition to quantum state results in baseline shift and collapse so that conscious experience merges with normally sub-conscious quantum computing mode. E. Dreaming: prolonged sub-threshold quantum superposition time.


  • At the nanoscale each event determines new classical states of microtubule automata which regulate synaptic and other neural functions;
  • During the pre-conscious quantum superposition/computation phase, oscillations are “tuned” and “orchestrated” by microtubule-associated proteins (MAPs), providing a feedback loop between the biological system and the quantum state (hence Orch OR);
  • Quantum states in microtubules may link to those in microtubules in other neurons and glia by tunneling through gap junctions, permitting extension of the quantum state throughout significant volumes of the brain.


Figure 26. Schematic of proposed quantum superposition and entanglement in microtubules in three dendrites interconnected by tunneling through gap junctions. Within each neuronal dendrite, microtubule-associated-protein (MAP) attachments breach isolation and prevent quantum coherence; MAP attachment sites thus act as “nodes” which tune and orchestrate quantum oscillations and set possibilities and probabilities for collapse outcomes (orchestrated objective reduction: Orch OR). Gap junctions may enable quantum tunneling among dendrites resulting in macroscopic quantum states.


From E = h/T we can calculate the size and extension of Orch OR events which correlate with subjective or neurophysiological descriptions of conscious events.

Event T E
Buddhist “moment of awareness” 13 ms 4 x 1015 nucleons
(4 x 1010 tubulins/cell ~ 40,000 neurons)
“Coherent 40 Hz” oscillations” 25 ms 2 x 1015 nucleons
(2 x 1010 tubulins/cell ~ 20,000 neurons)
EEG alpha rhythm (8 to 12 Hz) 100 ms 5 x 1014 nucleons
(5 x 109 tubulins/cell ~ 5000 neurons)
Libet’s sensory threshold (1979) 500ms 1014 nucleons
(109 tubulins/cell ~ 1000 neurons)

But how could delicate quantum superposition/computation be isolated from environmental decoherence in the brain (generally considered to be a noisy thermal bath) while also communicating (input/output) with the environment? One possibility is that quantum superposition/computation occurs in an isolation phase which alternates with a communicative phase, for example at 40 Hz. One of the most primitive biological functions is the transition of cytoplasm between a liquid, solution (“sol”) phase, and a solid, gelatinous (“gel”) phase due to assembly and disassembly of the cytoskeletal protein actin. Actin sol-gel transitions can occur at 40 Hz or faster, and are known to be involved in neuronal synaptic release mechanisms.
Mechanisms for enabling microtubule quantum computation and avoiding decoherence long enough to reach threshold may include:

  • Sol-gel transitions;


Figure 27. Immunoelectron micrograph of cytoplasm showing microtubules (arrows), intermediate filaments (arrowheads) and actin microfilaments (mf). Dense gel of actin (lower left) completely obscures (?isolates) microtubules. Actin sol-gel transitions can occur at 40 Hz or faster. Scale bar (upper right): 500 nanometers. With permission from Svitkina et al, 1995.


  • Plasma phase sleeves (Sackett);


Figure 28. Dan Sackett at NIH recently described a plasma-like sleeve of charged ions surrounding microtubules at precisely optimal pH.


  • Quantum excitations/ordering of surrounding water (Jibu/Yasue/Hagan);
  • Hydrophobic pockets;
  • Hollow microtubule cores;
  • Laser-like pumping, including environment (Frohlich, Conrad).
  • Quantum error correcting codes

Another apparent obstacle to the Orch OR proposal is how the weak energy involved in the gravitational collapse can be influential. For a detailed description of this problem and potential solutions, see Hameroff, 1998c. One possibility is that the gravitational self-energy is delivered to the involved tubulins via London forces virtually instantaneously (e.g. within one Planck time) so that the power (energy/time) is significant – approximately one kilowatt per tubulin per Orch OR event.

8. Orch OR, cognition and free will

Quantum computation with objective reduction (Orch OR) is potentially applicable to cognitive activities. While classical neural-level computation can provide a partial explanation, the Orch OR model allows far greater information capacity, and addresses issues of conscious experience, binding, and non-computability consistent with free will. Functions like face recognition and volitional choice may require a series of conscious events arriving at intermediate solutions. For the purpose of illustration consider single Orch OR events in these two types of cognitive activities.
Imagine you briefly see a familiar woman’s face. Is she Amy, Betty, or Carol? Possibilities may superpose in a quantum computation. For example during 25 milliseconds of pre-conscious processing, quantum computation occurs with information (Amy, Betty, Carol) in the form of “qubits”3/4superposed states of microtubule tubulin subunits within groups of neurons. As threshold for objective reduction is reached, an instantaneous conscious event occurs. The superposed tubulin qubits reduce to definite states, becoming bits. Now, you recognize that she is Carol! (an immense number of possibilities could be superposed in a human brain’s 1019 tubulins).

Figure 29. Face recognition. A familiar face induces superposition (left) of three possible solutions (Amy, Betty, Carol) which “collapse” to the correct answer Carol (right). Volitional choice. Three possible dinner selections (shrimp, sushi, pasta) are considered in superposition (left), and collapse via Orch OR to choice of sushi (right).


In a volitional act possible choices may be superposed. Suppose for example you are selecting dinner from a menu. During pre-conscious processing, shrimp, sushi and pasta are superposed in a quantum computation. As threshold for objective reduction is reached, the quantum state reduces to a single classical state. A choice is made. You’ll have sushi!
How does the choice actually occur? In a conventional neural network scheme, the selection criteria can be described by a deterministic algorithm which precludes the possibility of free will. The non-computable influence in Orch OR may be useful in understanding free will.
The problem in understanding free will is that our actions seem neither totally deterministic nor random (probabilistic). What else is there in nature? As previously described, in OR (and Orch OR) the reduction outcomes are neither deterministic nor probabilistic, but involve a factor which is “non-computable.” The microtubule quantum superposition evolves linearly (analogous to a quantum computer) but is influenced at the instant of collapse by hidden non-local variables (quantum-mathematical logic inherent in fundamental spacetime geometry). The possible outcomes are limited, or probabilities set (“orchestrated”), by neurobiological feedback (in particular microtubule associated proteins, or MAPs). The precise outcome3/4our free will actions3/4are chosen by effects of the hidden logic on the quantum system poised at the edge of objective reduction.

Figure 30. Free will may be seen as the result of deterministic processes (behavior of trained robot windsurfer) acted on repeatedly by non-computable influences, here represented as a seemingly capricious wind.


Consider a sailboard analogy for free will. A sailor sets the sail in a certain way; the direction the board sails is determined by the action of the wind on the sail. Let’s pretend the sailor is a non-conscious robot zombie run by a quantum computer which is trained and programmed to sail. Setting and adjusting of the sail, sensing the wind and position, jibing and tacking (turning the board) are algorithmic and deterministic, and may be analogous to the pre-conscious, quantum computing phase of Orch OR. The direction and intensity of the wind (seemingly capricious, or unpredictable) may be considered analogous to Planck scale hidden non-local variables (e.g. “Platonic” quantum-mathematical logic inherent in space-time geometry). The choice, or outcome (the direction the boat sails, the point on shore it lands) depends on the deterministic sail settings acted on repeatedly by the apparently unpredictable wind. Our “free will” actions could be the net result of deterministic processes acted on by hidden quantum logic at each Orch OR event. This can explain why we generally do things in an orderly, deterministic fashion, but occasionally our actions or thoughts are surprising, even to ourselves.

9. Consciousness and evolution

When in the course of evolution did consciousness first appear? Are all living organisms conscious, or did consciousness emerge more recently, e.g. with language or toolmaking? Or did consciousness appear somewhere in between, and if so, when and why? The Orch OR model (unlike other models of consciousness) is able to make a prediction as to the onset of consciousness. Based on E = h/T we can ask, for example, is it feasible for single cell organisms such as paramecium (which exhibit complex behavior such as graceful swimming, mating and learning) to be conscious? Single cells including paramecium should contain approximately 1079 tubulins) would need to maintain quantum isolation for only 133 msec – not unreasonable. Such organisms (tiny worms and urchins) were prevalent at the beginning of the “Cambrian explosion,” a burst of evolution which occurred 540 million years ago. Did primitive consciousness (via Orch OR) accelerate evolution and precipitate the Cambrian explosion? tubulins, so T would be 50,000 msec, or nearly one minute. This seems unlikely. Larger organisms such as the nematode worm (e.g., C. elegans) with 300 neurons (3 x 10

Figure 31. A time-line of when consciousness could have arisen.

The Cambrian explosion was a burst of evolution 540 million years ago. Organisms present at the Cambrian onset included small worms and urchins. Did consciousness (Orch OR) cause the Cambrian explosion?

Figure 32. Organisms present at the early Cambrian explosion (e.g. tiny urchins, worms and suctorians) are the right size for primitive consciousness by Orch OR.

Figure 33. Actinosphaerium is a tiny urchin like those present at the early Cambrian explosion. Each has about one hundred rigid axonemes about 300 microns long, made up of a total of about 3 x 109 tubulins (with permission from L.E. Roth).

Figure 34. Cross-section of single axoneme of actinosphaerium – a double spiral array of interconnected microtubules. Scale bar: 500 nm (with permission from L.E. Roth).


Would consciousness be advantageous to survival (above and beyond intelligent, complex behavior)? It seems that, yes, consciousness would indeed be advantageous to survival, and hence capable of accelerating evolution. Non-computable behavior (unpredictability, intuitive actions) would be beneficial in predator-prey relations. Having conscious experience of taste would promote finding food; the experience of pain would promote avoiding predators. And the pleasurable qualia of sex would promote reproduction.
So “what is it like to be a worm?” Lacking our sensory apparatus, associative memory and complex nervous system such primitive consciousness would be a mere glimmer, a disjointed smudge of reality. But qualitatively, at a basic level, such primitive consciousness would be akin to ours.
What about future evolution? Will consciousness occur in computers? The advent of quantum computers opens the possibility, however as presently envisioned quantum computers will have insufficient mass in superposition (e.g. electrons) to reach threshold for objective reduction. Instead, superpositions will be disrupted by environmental decoherence. Conceivably, future generations of quantum computers could satisfy requirements for objective reduction and consciousness.

10. Conclusions
  • Brain processes relevant to consciousness extend downward within neurons to the level of cytoskeletal microtubules.
  • An explanation for conscious experience requires (in addition to neuroscience and psychology) a modern form of pan-protopsychism in which proto-conscious qualia are embedded in the basic level of reality, as described by modern physics.
  • Roger Penrose’s physics of objective reduction (OR) connects brain structures to fundamental reality, leading to the Penrose-Hameroff model of quantum computation with objective reduction in microtubules (orchestrated objective reduction: Orch OR).
  • The Orch OR model is consistent with known neurophysiological processes, generates testable predictions, and is the type of fundamental, multi-level, interdisciplinary theory which may account for the mind’s enigmatic features.
11. Acknowledgments & References

Some of the newer ideas expresssed here may not necessarily reflect Roger’s view. Thanks to Dave Cantrell for illustrations, and Carol Ebbecke for expert technical assistance. For a list of testable predictions of the Orch OR model, see Hameroff, 1998c or e.
References
Penrose, R. (1989) The Emperor’s New Mind, Oxford Press, Oxford, U.K
Penrose, R. (1994) Shadows of the Mind, Oxford Press, Oxford, U.K.
Penrose, R., Hameroff, S.R. (1995) What gaps? Reply to Grush and Churchland. Journal of Consciousness Studies 2(2):99-112.
Hameroff, S.R., and Penrose, R., (1996a) Orchestrated reduction of quantum coherence in brain microtubules: A model for consciousness. In: Toward a Science of Consciousness – The First Tucson Discussions and Debates, S.R. Hameroff, A. Kaszniak and A.C. Scott (eds.), MIT Press, Cambridge, MA.pp. 507-540. Also published in Mathematics and Computers in Simulation 40:453-480.
Hameroff, S.R., and Penrose, R. (1996b) Conscious events as orchestrated spacetime selections. Journal of Consciousness Studies 3(1):36-53.
Penrose, R. (1996) On gravity’s role in quantum state reduction. General relativity and gravitation. 28(5): 581-600
Penrose, R. (1997) On understanding understanding. International Studies in the Philosophy of Science 11(1):7-20.
Penrose R. (1998) The large, the small, and the human mind
Hameroff, S. (1998a) Did consciousness cause the Cambrian evolutionary explosion? In: Toward a Science of Consciousness II – The Second Tucson Discussions and Debates. Eds S Hameroff, A Kaszniak, A Scott. MIT Press, Cambridge MA pp 421-437
Hameroff, S. (1998b) “More neural than thou”: Reply to Churchland’s “Brainshy” in: Toward a Science of Consciousness II – The Second Tucson Discussions and Debates. Eds S Hameroff, A Kaszniak, A Scott. MIT Press, Cambridge MA pp 197-213
Hameroff, S. (1998c) Funda-mental geometry: The Penrose-Hameroff Orch OR model of consciousness. In: The geometric universe – Science, geometry and the work of Roger Penrose. Eds. S.A. Huggett, L.J. Mason, K.P. Tod, S.T. Tsou, and N.M.J. Woodhouse. Oxford Press, Oxford, U.K. pp 135-160
Hameroff, S. (1998d) “Funda-Mentality” – Is the conscious mind subtly connected to a basic level of the universe? Trends in Cognitive Science 2(4):119-127
Hameroff, S. (1998e) Quantum computation in microtubules? The Penrose-Hameroff ‘Orch OR’ model of consciousness. Philosophical Transactions of the Royal Society A (London)356:1869-1896
Hameroff, S. (1998f) Anesthesia, consciousness and hydrophobic pockets – A unitary quantum hypothesis of anesthetic action. Toxicology Letters 100/101-31-39.

Stuart Hameroff, M.D.
Department of Anesthesiology
Arizona Health Sciences Center

About zayya
Just Be. That's Enough! Shared words with Silence.

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