http://www.newscientist.com/article/mg21128321.500-quantum-life-the-weirdness-inside-us.html

Quantum life: The weirdness inside us

03 October 2011 by Michael Brooks
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Ideas from the stranger side of physics could explain some long-standing mysteries of biology

EVER felt a little incoherent? Or maybe you've been in two minds about something, or even in a bit of delicate state. Well, here's your excuse: perhaps you are in thrall to the strange rules of quantum mechanics.

We tend to think that the interaction between quantum physics and biology stops with Schrödinger's cat. Not that Erwin Schrödinger intended his unfortunate feline - suspended thanks to quantum rules in a simultaneous state of being both dead and alive - to be anything more than a metaphor. Indeed, when he wrote his 1944 book What is Life?, he speculated that living organisms would do everything they could to block out the fuzziness of quantum physics.

But is that the case? Might particles that occupy two states at once, that interact seemingly inexplicably over distances and exhibit other quantum misbehaviours actually make many essential life processes tick? Accept this notion, say its proponents, and we could exploit it to design better drugs, high-efficiency solar cells and super-fast quantum computers. There's something we need to understand before we do, though: how did the quantum get into biology in the first place?

On one level, you might think, we shouldn't be surprised that life has a quantum edge. After all, biology is based on chemistry, and chemistry is all about the doings of atomic electrons - and electrons are quantum-mechanical beasts at heart. That's true, says Jennifer Brookes, who researches biological quantum effects at Harvard University. "Of course everything is ultimately quantum because electron interactions are quantised."

On another level, it is gobsmacking. In theory, quantum states are delicate beasts, easily disturbed and destroyed by interaction with their surroundings. So far, physicists have managed to produce and manipulate them only in highly controlled environments at temperatures close to absolute zero, and then only for fractions of a second. Finding quantum effects in the big, wet and warm world of biology is like having to take them into account in a grand engineering project, says Brookes. "How useful is it to know what electrons are doing when you're trying to build an aeroplane?" she asks.

Might this received wisdom be wrong? Take smellMovie Camera, Brookes's area of interest. For decades, the line has been that a chemical's scent is determined by molecular shape. Olfactory receptors in the nose are like locks opened only with the right key; when that key docks, it triggers nerve signals that the brain interprets as a particular smell.

Is that plausible? We have around 400 differently shaped smell receptors, but can recognise around 100,000 smells, implying some nifty computation to combine signals from different receptors and process them into distinct smells. Then again, that's just the sort of thing our brains are good at. A more damning criticism is that some chemicals smell similar but look very different, while others have the same shape but smell different. The organic compound benzaldehyde, for example, comes in two almost identical molecular arrangements, vanillin and isovanillin, that have very distinctive smells.

There is an alternative explanation. Around 70 years ago, even before the lock-and-key mechanism was suggested, the distinguished British chemist Malcolm Dyson suggested that, just as the brain constructs colours from different vibrational frequencies of light radiation, it interprets the characteristic frequencies at which certain molecules vibrate as a catalogue of smells.

The idea languished in obscurity until 1996, when Luca Turin, a biophysicist then at University College London, proposed a mechanism that might make vibrational sensing work: electron tunnelling. This phenomenon results from the basic fuzziness of quantum mechanics, and is a staple of devices from microchips to microscopes. When an electron is confined in an atom, it does not have an exactly defined energy but has a spread of possible energies. That means there is a certain probability that it will simply burrow through the energy barrier that would normally prevent it escaping the atom.

Turin's idea is that when an odorous molecule lodges in the pocket of a receptor, an electron can burrow right through that molecule from one side to the other, unleashing a cascade of signals on the other side that the brain interprets as a smell. That can only happen if there is an exact match between the electron's quantised energy level and the odorant's natural vibrational frequency. "The electron can only move when all the conditions are met," Turin says. The advantage, though, is that it creates a smell without the need for an exact shape fit.

It was a controversial notion. In 2007 Brookes, then also working at University College London, and colleagues showed that the mechanism is physically plausible: the timescales are consistent with the speed with which the brain responds to smell, and the signals generated are large enough for the brain to process (Physical Review Letters, vol 98, p 038101). And in January this year Turin, now at the Alexander Fleming Biomedical Sciences Research Centre in Vari, Greece, and his colleagues delivered what looks like evidence for vibrational sensing. They showed that fruit flies can distinguish between two types of acetophenone, a common base for perfumes, when one contains normal hydrogen and the other contains heavier deuterium. Both forms have the same shape, but vibrate at different frequencies (Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.1012293108). That sensitivity can only mean electron tunnelling, says Andrew Horsfield of Imperial College London, a co-author on Brookes's paper: in classical models of electron flow the electron would not be sensitive to the vibrational frequency. "You can't explain it without the quantum aspect."

Smell is not the only thing that proponents of quantum biology think it might explain: there's also the mechanism that powers the entire animal kingdom. We all run on adenosine triphosphate, or ATP, a chemical made in cells' mitochondria by moving electrons through a chain of intermediate molecules. When we attempt to calculate how speedily this happens, we hit a problem. "In nature the process is much faster than it should be," says Vlatko Vedral, a quantum physicist at the University of Oxford.

Vedral thinks this is because it depends on the quality of "superposition" which allows the sort of quantum-mechanical wave that describes electrons to be in two places at once. He reckons quantum omnipresence might speed the electrons' passage through the reaction chain. "If you could show superposition is there and it's somehow also important for the electron flow, that would be very interesting," he says.

Vedral's first calculations support the idea, but he says it is too early to make any claims. It is hard to estimate all the parameters involved in electron transport, and it is possible that the classical calculations just used the wrong numbers. "And as yet we have no experimental proof," he says. Such proof might be quite close by - in how plants and some bacteria get their energy. It seems photosynthesis might be very much a quantum game.
Quantum marines

Direct evidence that this is so came in 2007, when a group led by Graham Fleming at the University of California, Berkeley, took a close look at photosynthesis in the green sulphur bacterium Chlorobium tepidum. They detected "beating" signals characteristic of quantum wave interference in the photosynthesising centres of bacteria cooled to 77 kelvin (Nature, vol 446, p 782). In January last year, a group led by Gregory Scholes of the University of Toronto, Canada, showed a similar effect at room temperature in light-harvesting proteins from two marine algae (Nature, vol 463, p 644).

This is a trick we might like to learn from. Although photosynthesis is not particularly efficient overall, the initial stage of converting incoming photons into the energy of electrons within a photosynthesising organism's light-gathering pigment molecules is extremely effective. When sunlight is weak, plants are able to translate more than 90 per cent of photons into an energy-carrying electron; in strong sunlight plants have to dump about half the energy to avoid overheating.

Scholes's explanation for this is that when sunlight hits electrons, they are kicked into a quantum superposition that allows them to be in two places at once. That effectively "wires" light-gathering molecules to the reaction centre where the photosynthesis takes place for a few hundred femtoseconds. During that time, an electron can, according to quantum rules, take all paths between the two places simultaneously. Probing the process more closely causes the superposition to collapse - and reveals the electron to have taken the path that lost it the least energy.

Might we take a leaf out of biology's book? Scholes thinks so. "Every year there are thousands of papers published on energy transfer," he says. "It sounds harsh but we haven't learned a thing apart from the obvious." A better understanding of what is going on might also help us on the way to building a quantum computer that exploits coherent states to do myriad calculations at once. Efforts to do so have so far been stymied by our inability to maintain the required coherence for long - even at temperatures close to absolute zero and in isolated experimental set-ups where disturbances from the outside world are minimised.

This remains the central conundrum for the physicists studying quantum aspects of biology. If we can't do these things in our isolated labs, how can a leaf in your less-than-isolated garden do it? If only the European robin could do more than warble chirpily. Perhaps then it could tell us - and explain its own apparent quantum superpowers, too (see "Bird's eye view").

At the moment we have little more than educated guesses. One is that it is simply a wonder of evolution. Scholes thinks that proteins around algae's light-harvesting equipment might have evolved structures that shield disturbances from the environment and so allow processes within to exploit the magic of quantum physics to give them a selective advantage. Vedral thinks something similar, although why and how nature would do this, he says, is "completely unclear".

Turin shrugs his shoulders, too. "Life's 4 billion years of nanoscale R&D will have engineered many miracles," he says. We should learn to accept what we see and try to mimic it, he says - and not just in solar cells and quantum computers. While what makes a drug effective or ineffective is far from clear, for instance, we do know that the operation of things like neurotransmitters in our brains depends on redox reactions, which are all to do with electron flow. If those flows occur in weirder ways than we have hitherto imagined, that could open up a new path to design drugs to treat some of our most pernicious ailments.

Others think nature is leading us up the garden path. Is photosynthesis, for example, really made more efficient by exploiting quantum interference and superposition effects? "I think the jury is still out on this question," says Robert Blankenship of Washington University in St Louis, Missouri. "I think it is possible that, depending on the details of the system, it could just as easily decrease the efficiency." Simon Benjamin, a colleague of Vedral's at the University of Oxford, wonders how we can really put long-lived quantum states to work if indeed they do pop up in natural systems. "It's certainly too early to be making dramatic claims," he says.

All those stepping gingerly around this new field agree that caution is needed - yet there is a palpable sense of excitement. Max Planck first discovered quantum theory more than a century ago because of odd observations that could be explained in no other way. That led to the laser and the semiconductor and all the technological revolutions they have seeded. Quantum biology is at that early stage of inexplicable observations. Turin for one believes something big is emerging. "I can't help thinking we are seeing just a small part of a far, far bigger iceberg," he says.
Bird's eye view

Another instance of quantum effects in biology might be in how birds sense Earth's magnetic field (New Scientist, 27 November 2010, p 42). In 2004, Thorsten Ritz of the University of California, Irvine, showed how magnetic disturbances that would only show up on systems that could detect transitions between particular quantum-mechanical atomic spin states could disrupt the compass of the European robin, Erithacus rubecula.

Ritz suggested that birds come equipped with a sensor system containing spin states that flip in response to changes in Earth's magnetic field, producing signals that the bird's brain in some way detects. But how?

The first proposal was that some apparatus in the eye initiates a chemical response. But this would require a constant, fast flipping of spins to keep chemical information flowing, whereas the birds seemed to maintain delicate spin states for extraordinarily long times of up to 100 microseconds.

According to the late Marshall Stoneham of University College London and his colleagues, the problem might be overcome if the birds used something similar to a human visual peculiarity that detects light polarisation. Known as Haidinger's brush, this superimposes a faint, yellow bow-tie shape on our visual field, and is thought to result from the way blue light-absorbing lutein molecules are arranged in concentric circles within our eye. Stare at a blank piece of paper and a polarising filter or a blank document on a laptop screen and you can see it for yourself.

Stoneham calculated that a magnetic field could produce a similar distortion in a bird's visual field, the orientation of which would change with a change in magnetic field. Crucially, that would occur only if quantum states lasted long enough to affect many of the bird's light sensing molecules at the same time. Birds might see the result, Stoneham suggested, in a kind of a head-up display of the kind that is embedded in the windscreens of some luxury cars (arxiv.org/abs/1003.2628).

Michael Brooks is a consultant for New Scientist. His latest book is Free Radicals: The secret anarchy of science (Profile, 2011)

http://blogs.scientificamerican.com/observations/2011/09/15/time-on-the-brain-how-you-are-always-living-in-the-past-and-other-quirks-of-perception/


Time on the Brain: How You Are Always Living In the Past, and Other Quirks of Perception
By George Musser | September 15, 2011 | Comments10


I always knew we humans have a rather tenuous grip on the concept of time, but I never realized quite how tenuous it was until a couple of weeks ago, when I attended a conference on the nature of time organized by the Foundational Questions Institute. This meeting, even more than FQXi’s previous efforts, was a mashup of different disciplines: fundamental physics, philosophy, neuroscience, complexity theory. Crossing academic disciplines may be overrated, as physicist-blogger Sabine Hossenfelder has pointed out, but it sure is fun. Like Sabine, I spend my days thinking about planets, dark matter, black holes—they have become mundane to me. But brains—now there’s something exotic. So I sat rapt during the neuroscientists’ talks as they described how our minds perceive the past, present, and future. “Perceive” maybe isn’t strong enough a word: our minds construct the past, present, and future, and sometimes get it badly wrong.

Neuroscientist Kathleen McDermott of Washington University began by quoting famous memory researcher Endel Tulving​, who called our ability to remember the past and to anticipate the future “mental time travel.” You don’t use the phrase “time travel” lightly in front of a group of physicists for whom the concept is not a convenient metaphor but a very real possibility. But when you hear about how our minds glide through time—and how our memory provides a link not only to the past but also to the future—you see Tulving’s point.

McDermott outlined the case of Patient K.C., who has even worse amnesia than the better-known H.M. on whom the film Memento was based. K.C. developed both retrograde and anterograde amnesia from a motorcycle crash in 1981. (The literature doesn’t say whether he was wearing a helmet, but let this be a lesson.) He can’t remember anything that happened more than a few minutes ago. He retains facts and skills, but can’t remember actually doing anything or being anywhere.

Tellingly, not only can he not recall the past, he can’t envision the future. When researchers ask him to picture himself somewhere he might go, he says that all he sees is “a big blankness.” Another patient McDermott has worked with can explain the future in the abstract, but says he can’t imagine himself in it.

To investigate the perception of past and future in people without brain injuries, McDermott did fMRI brain scans of 21 college students, asking them to recall a specific incident in their past and then envision themselves in a specific future scenario. Subjectively, the two feel very different. Yet the scans showed the same patterns of activity. Areas scattered all over the brain lit up; our temporal perception is distributed. As a control, McDermott also asked the students to remember events involving Bill Clinton​ (presumably, ones they were not personally involved in), and the patterns were very different. In a follow-up study, McDermott asked 27 students to anticipate an event in both a familiar and an unfamiliar place. The brain scan for the familiar one resembled the one for the act of remembering; the unfamiliar one was the odd man out.

The bottom line is that memory is essential to constructing scenarios for ourselves in the future. Anecdotal evidence backs this up. Our ability to project forward and to recollect the past both develop around age 5, and people who are good at remembering also report having vivid thoughts about the future.

McDermott’s colleague Henry Roediger studies metacognition—thinking about thinking. We express varying degrees of confidence in our memories. How we do this is clearly an issue for the court system. The N.J. Supreme Court recently tightened standards on the consideration of eyewitness testimony, citing the risk of false positives. Roediger pointed out that false negatives get less attention, but are equally bad. The worst eyewitnesses are full of passionate intensity, and the best lack all conviction. In both cases, innocent people can be sent to death row while the guilty walk.

Cognitive psychologists find that confidence sometimes correlates with accuracy, sometimes not. Roediger gave volunteers a memory word test. They had to study a list of words; afterwards, they were presented with a series of words and had to indicate whether each had been on the original list. They also had to say how confident they felt about their answer.

Whenever I hear about such tests, I brace myself for bad news. But Roediger said people actually did pretty well, and their confidence scores tracked the accuracy of their recall. Their blind spots were predictable. They systematically messed up, both in recall accuracy and self-assessment, when presented words that weren’t on the list but were synonyms of ones that were. The findings match what happens with eyewitnesses. We get things broadly right, but are easily confused by similar situations and faces.

It’s not that our memory is a glitchy wetware version of computer flash memory; it’s that the computer metaphor just doesn’t apply. Roediger said we store only bits and pieces of what happened—a smattering of impressions we weave together into feels like a seamless narrative. When we retrieve a memory, we also rewrite it, so that the time next we go to remember it, we don’t retrieve the original memory but the last one we recollected. So, each time we tell a story, we embellish it, while remaining genuinely convinced of the veracity of our memories.

So go easy on your friend who caught the 150-pound catfish. He wasn’t consciously lying, which is why he spoke with conviction, but that still doesn’t mean you should swallow his tale. To confuse is human; to accept we confuse, divine.

Speaking of fish, as neuroscientist Malcolm MacIver of Northwestern once put it to me, electric fish are the fruit flies of neuroscience—model organisms for studying how we sense the world. MacIver told the FQXi conference about his astoundingly comprehensive, leave-no-stone-unturned study of a species of Amazonian electric fish, using everything from supercomputer fluid simulations to an working model of the fish (captured in this video) and even an art installation.

The fish generates an electric field of about 1 millivolt per centimeter at a frequency that ranges from 50 to 2000 hertz. Water fleas, its prey, give themselves away by disrupting the field. (You can build a proximity sensor based on this concept. I use one to control the lights in my study.) What gets ichthyologists flapping is that, when this fish is out hunting, it doesn’t swim straight ahead, but at a 30-degree angle to the axis of its body—a seemingly cuckoo behavior that nearly triples the water drag force.

But MacIver demonstrated that the orientation also increases the effective volume of water sensed by the electric field. The fish strikes a balance between mechanical and sensory efficiency. Generalizing this insight, he distinguished between two distinct volumes around an organism: its sensory volume (the region it can scan for prey) and its motor volume (the region it can directly reach). For this fish and most other aquatic animals, the two are comparable in size—there’d be no point in looking out any farther. A fish’s reach does not exceed its grasp.

For land animals, though, things are quite different: their sensory volume is much bigger than their motor volume, since light travels much farther in air than in seawater. So when our ancestors crawled out of the sea, they gained the opportunity to plan their behavior in advance. No longer restricted to reacting to immediate stimuli, they had time to take in the scene and deliberate before moving. Animals that could arbitrage the difference in sensory and motor volumes gained an evolutionary advantage.

MacIver speculated that this set the stage for the evolution of consciousness. After all, what is consciousness, but the ability to make plans and gain some advantage over our environment, rather than lurching from crisis to crisis? Psychologist Bruce Bridgeman proposed this view of consciousness in the early 1990s. MacIver elaborated in a post on his blog, Science Not Fiction, earlier this year.

The fun thing about neuroscience is that you can do the experiments on yourself. David Eagleman of the Baylor College of Medicine proceeded to treat us as his test subjects. By means of several visual illusions, he demonstrated that we are all living in the past: Our consciousness lags 80 milliseconds behind actual events. “When you think an event occurs it has already happened,” Eagleman said.

In one of these illusions, the flash-lag effect, a light flashes when an object moves past it, but we don’t see the two as coincident; there appears to be a slight offset between them. By varying the parameters of the experiment, Eagleman showed that this occurs because the brain tries to reconstruct events retroactively and occasionally gets it wrong. The reason, he suggested, is that our brains seek to create a cohesive picture of the world from stimuli that arrive at a range of times. If you touch your toe and nose at the same time, you feel them at the same time, even though the signal from your nose reaches your brain first. You hear and see a hand clap at the same time, even though auditory processing is faster than visual processing. Our brains also paper over gaps in information, such as eyeblinks. “Your consciousness goes through all the trouble to synchronize things,” Eagleman said. But that means the slowest signal sets the pace.

The cost of hiding the logistical details of perception is that we are always a beat behind. The brain must strike a balance. Cognitive psychologist Alex Holcombe at Sydney has some clever demonstrations showing that certain forms of motion perception take a second or longer to register, and our brains clearly can’t wait that long. Our view of the world takes shape as we watch it.

The 80-millisecond rule plays all sorts of perceptual tricks on us. As long as a hand-clapper is less than 30 meters away, you hear and see the clap happen together. But beyond this distance, the sound arrives more than 80 milliseconds later than the light, and the brain no longer matches sight and sound. What is weird is that the transition is abrupt: by taking a single step away from you, the hand-clapper goes from in sync to out of sync. Similarly, as long as a TV or film soundtrack is synchronized within 80 milliseconds, you won’t notice any lag, but if the delay gets any longer, the two abruptly and maddeningly become disjointed. Events that take place faster than 80 milliseconds fly under the radar of consciousness. A batter swings at a ball before being aware that the pitcher has even throw it.

The cohesiveness of consciousness is essential to our judgments about cause and effect—and, therefore, to our sense of self. In one particularly sneaky experiment, Eagleman and his team asked volunteers to press a button to make a light blink—with a slight delay. After 10 or so presses, people cottoned onto the delay and began to see the blink happen as soon as they pressed the button. Then the experimenters reduced the delay, and people reported that the blink happened before they pressed the button.

Eagleman conjectured that such causal reversals would explain schizophrenia. All of us have an internal monologue, which we safely attribute to ourselves; if we didn’t, we might think of it as an external voice. So Eagleman has begun to run the same button-blink experiment on people diagnosed with schizophrenia. He reported that changing the delay time did not cause them to change their assessment of cause and effect. “They just don’t adjust,” Eagleman said. “They don’t see the illusion. They’re temporally inflexible.” He ventured: “Maybe schizophrenia is fundamentally a disorder of time perception.” If so, it suggests new therapies to cajole the brains of schizophrenic patients into recalibrating their sense of timing.

In the experiment for which Eagleman is best known, he sought to find out why time passes more slowly when we’re scared. Does something really happen in the brain—for instance, the time resolution of perception speeds up—or do we just think it does, in hindsight? After brainstorming scare tactics that probably wouldn’t have passed muster with a university ethics committee, he hit upon asking volunteers to take one of those Freefall or Demon Drop rides you find in amusement parks. They wore a special watch whose digits counted up too quickly for people to register them under normal conditions—thinking that, if perception really did speed up, people would be able to read the digits.

Alas, they couldn’t. Although they consistently reported that the ride took about a third longer than it really did, this must have been a trick of memory; their hyperacuity was a mirage.

Our memory becomes distorted because our brains react more strongly to novelty than to repetition. Eagleman investigated this effect by asking volunteers to estimate the duration of flashes of light; those flashes that were the first in a series, or broke an established pattern, seemed to last longer. This feature of consciousness, like the 80-millisecond rule, explain so much about our daily experience. When we’re sitting through a boring event, it seems to take forever. But when we look back on it, it went by in a flash. Conversely, when you’re doing something exciting, time seems to race by, but when you look back on it, it stretched out. In the first case, there was little to remember, so your brain collapsed the feeling of duration. In the second, there was so much to remember, so the event seemed to expand. Time flies when you’re having fun, but crawls when you recollect in tranquility.

I suspect that this inverse relation in our perception of time also explains how our experiences shift as we age. When you’re a kid, you wake up and say to yourself: “I’ve got a whole day ahead of me. How will I possibly fill it all?” But when you’re an adult, it’s more like: “I’ve got a day ahead of me. How will I possibly get it all done?” And don’t get me started on how people swear that the first year of their baby’s life went by so fast. (A second child is usually enough to disabuse them.)

You can probably tell from my lengthy description of Eagleman’s talk that it seemed to zip by at the time. The physicists in attendance found it one of the highlights of the conference. Not only was it engrossing in its own right, it had some professional interest for them. All theories of physics begin with sense-data. As Eagleman said, “We build our physics on top of our intuitions.”

We also build our physics on a recognition of the limits of perception. The whole point of theories such as relativity is to separate objective features of the world from artifacts of our perspective. One of the most important books of the past two decades on the physics and philosophy of time, Huw Price’s Time’s Arrow and Archimedes’ Point, argues that concepts of cause and effect derive from our experience as agents in the world and may not be a fundamental feature of reality.

Time plays a variety of roles in physics, from defining causal sequences to giving a direction to the unfolding of the universe. How many of these roles are rooted in the contingent ways our brains perceive time? How might an alien being, who perceives time in a radically different way, formulate physics?

......

http://thecuriousbrain.com/?p=24083

from neurons to self

by Rodolfo R. Llinas



This essay arose out of a set of talks given at The University of St. Andrews
in Scotland, where Professor Glen Cottrell had graciously invited
me to give the American Alumni Lectures in 1989. Little did I know then
that St. Andrews would be back in my life, when, in 1998, my son Alexander
obtained his Ph.D. there during a break in his medical studies at
New York University.
The generation of this essay owes much to Michael Kistler, to whom I
dictated much of this manuscript, so giving me a leg up into getting the
material into a form that I could work with. Dr. Jean Jacoby helped with
the editing. My son Rafael, presently a junior staff neurologist at Harvard’s
Beth Israel Hospital, took the time to read and criticize this effort,
as did my wife, Dr. Gillian Kimber, from her perspective as a philosopher
of mind. I would also like to thank a special friend, Dr. Antonio
Fernandez de Molina, and my colleague Dr. Kerry Walton for special
comments and additions.
This book presents a personal view of neuroscience aimed toward a
general audience, as well as toward students and those of my colleagues
who might enjoy an attempt at synthesis. This general view is offered
from the perspective of a single-cell physiologist interested in neuronal
integration and synaptic transmission. Such a position is privileged,
because it lies between the realms of the molecular and the systemic, as
they relate to brain function.
Single large neurons have physical dimensions observable at low optimal
magnification, that of a tenth of a millimeter. That is big enough to
be dissected by hand with pins, using a good magnifying glass (Deiters
1856). Moving just two orders of magnitude down to the micrometer
level, which requires a good microscope, one is at the scale of synaptic
transmission. One may observe synapses at the union between nerve and
muscle, for example. Two orders of magnitude further down, at tens of
nanometers, with the aid of electron microscopy, we find the realm of single
ion channels and of signal transduction and molecular biology.
If, on the other hand we wish to roam orders of magnitude above the
physiology of single cells, we find at two orders of magnitude above, and
in the centimeter realm, the world of systems that is the scale of pennies,
buttons, and fingernails. At a further two orders of magnitude up, we
come to meters and to the world of motricity and cognition that characterizes
human beings. That is, we arrive at the realm of chairs and telephones
and other objects that one can hold in one’s hand or under one’s
arm.
Most neuroscientists feel that two orders of magnitude above and below
one’s central focus is “horizon enough,” and that anyone attempting
four orders above and below is reckless. However, there are some who
attempt such a dangerous dynamic range. They probably know that the
risk of failure is the price of synthesis, without which there are only fields
of dismembered parts.


...

http://www.dictionaryofobscuresorrows.com/

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reading starts below this line





karmapol

n. the imaginary committee of elders that keeps a running log of your mistakes, steadily building their case that you’re secretly a fraud, a coward, a doofus and a douche, and who would’ve successfully revoked your good fortune years ago had they not been hampered by bitter squabblings over grammar and spelling.

Posted 1 day ago
by jkcreative
330 notes

ecidivism

n. the habit of closing a browser tab to go do something else, only to absentmindedly return to the website you just left, which is your brain’s way of stress-testing your attention span under a synthetic and highly experimental blend of ones and zeroes, mostly zeroes.

Posted 1 week ago
by jkcreative
352 notes

antematter

n. the dream versions of things in your life, which appear totally foreign but are still somehow yours—your anteschool, your antefriends, your antehome—all part of a parallel world whose gravitational pull raises your life’s emotional stakes, increasing the chances you’ll end up betting everything you have.

Posted 1 month ago
by jkcreative
682 notes
Brianne Farley

flashover

n. the moment a conversation becomes real and alive, which occurs when a spark of trust shorts out the delicate circuits you keep insulated under layers of irony, momentarily grounding the static emotional charge you’ve built up through decades of friction with the world.

Posted 2 months ago
by jkcreative
1,021 notes

aoyaoia

n. a musical flavor found in electric guitar solos that compels you to snarl, squint and bend your spine like a longbow being drawn back to fire a warning shot to your distant ancestors, so they may know that your domestication will not go unavenged.

Posted 3 months ago
by jkcreative
416 notes

wytai

acronym [“when you think about it”] a feature of modern society that suddenly strikes you as absurd and grotesque—from zoos and milk-drinking to organ transplants, life insurance and fiction—part of the faint background noise of absurdity that reverberates from the moment our ancestors first crawled out of the slime but could not for the life of them remember what they got up to do.

Posted 4 months ago
by jkcreative
483 notes

aimonomia

n. fear that learning the name of something—a bird, a constellation, an attractive stranger—will somehow ruin it, transforming a lucky discovery into a conceptual husk pinned in a glass case, which leaves one less mystery to flutter around your head, trying to get in.

The sad, sad demise of Greenpeace
by Wilson da Silva

GREENPEACE WAS ONCE a friend of science, helping bring attention to important but ignored environmental research. These days, it’s a ratbag rabble of intellectual cowards intent on peddling an agenda, whatever the scientific evidence.

 http://www.cosmosmagazine.com/blog/4523/the-sad-sad-demise-greenpeace 

Jack A. Tuszynski (Ed.)

"THE EMERGING PHYSICS OF CONSCIOUSNESS"


Contents


1 The Path Ahead
Jack A. Tuszynski, Nancy Woolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Definition and Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Definition of Consciousness
and the Classical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Quantum Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.3 Quantum Processing
by Microtubules and Neurocognition . . . . . . . . . . . . . . . . . . 8
1.2 Overview of the Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3 New and Notable Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.3.1 An Electromagnetic Fingerprint
of Transport Along Microtubules . . . . . . . . . . . . . . . . . . . . . 17
1.3.2 Extrapolations to Mesoscopic and Macroscopic Levels . . . 22
1.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2 Consciousness and Quantum Physics: Empirical Research
on the Subjective Reduction of the Statevector
Dick J. Bierman, Stephen Whitmarsh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.1.1 The Measurement Problem . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.1.2 Objective Reduction and Consciousness . . . . . . . . . . . . . . . 29
2.1.3 Previous Empirical Work on Subjective Reduction . . . . . . 30
2.1.4 Current Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.2 Experimental Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3 Experimental Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3.1 Subjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3.2 Physiological Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3.3 Further Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.4 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.5 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.7 Further Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3 Microtubules in the Cerebral Cortex:
Role in Memory and Consciousness
Nancy J. Woolf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.1.1 General Features of the Brain . . . . . . . . . . . . . . . . . . . . . . . . 49
3.1.2 Neuronal Assemblies: Patterns of Connection . . . . . . . . . . 51
3.1.3 Neurons, Synapses and Neurotransmitter Molecules . . . . . 52
3.2 Functions of Microtubules and MAPs . . . . . . . . . . . . . . . . . . . . . . . . 56
3.2.1 Transport along Microtubules . . . . . . . . . . . . . . . . . . . . . . . . 57
3.2.2 Signal Transduction and Anchoring
of Signal-Transduction Molecules . . . . . . . . . . . . . . . . . . . . . 57
3.3 Learning and Memory: Neuroplasticity vs. Stability . . . . . . . . . . . . 65
3.3.1 Synaptic Change: Hebb’s Rule Revisited . . . . . . . . . . . . . . 66
3.3.2 Microtubules and MAPs in Dendrites
Play a Critical Role in Memory . . . . . . . . . . . . . . . . . . . . . . 70
3.3.3 Microtubules Influence Synaptic Efficacy . . . . . . . . . . . . . . 77
3.4 Consciousness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.4.1 Attention: The Spotlight of Consciousness . . . . . . . . . . . . . 78
3.4.2 Waking, Sleeping and Dreaming:
Different Levels of Consciousness . . . . . . . . . . . . . . . . . . . . . 80
3.4.3 Mental Force to Think and Act . . . . . . . . . . . . . . . . . . . . . . 81
3.4.4 Consciousness, Memory and Microtubules . . . . . . . . . . . . . 83
3.5 Microtubules and Quantum Entanglement:
A Possible Basis for Memory and Consciousness . . . . . . . . . . . . . . . 85
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4 Towards Experimental Tests of Quantum Effects
in Cytoskeletal Proteins
Andreas Mershin, Hugo Sanabria, John H. Miller, Dharmakeerthna
Nawarathna, Efthimios M.C. Skoulakis, Nikolaos E. Mavromatos,
Alexadre A. Kolomenskii, Hans A. Schuessler, Richard F. Luduena,
Dimitri V. Nanopoulos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.1.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.1.2 Tubulin and Microtubules . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.1.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.2 QED Model of Tubulin and its Implications. . . . . . . . . . . . . . . . . . . 102
4.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.2.2 Quantum Coherence in Biological Matter? . . . . . . . . . . . . . 105
4.2.3 Implications for Cell Function. . . . . . . . . . . . . . . . . . . . . . . . 115
4.2.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
4.3 Tau Accumulation in Drosophila Mushroom Body Neurons
Results in Memory Impairment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
4.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
4.3.2 Drosophila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
4.3.3 Genetic Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
4.3.4 Conditioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
4.3.5 Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
4.3.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.3.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
4.3.8 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
4.4 Refractometry, Surface Plasmon Resonance, and Dielectric
Spectroscopy of Tubulin and Microtubules . . . . . . . . . . . . . . . . . . . . 136
4.4.1 Theory of Dielectrics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
4.4.2 Optics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
4.4.3 Surface Plasmon Resonance (SPR) . . . . . . . . . . . . . . . . . . . 145
4.4.4 Dielectric Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
4.5 Emerging Directions of Experimental Tests
of the Quantum Consciousness Idea. . . . . . . . . . . . . . . . . . . . . . . . . . 159
4.5.1 Entanglement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
4.5.2 Molecular Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
4.5.3 Proposed Further Research . . . . . . . . . . . . . . . . . . . . . . . . . . 160
4.6 Unification of Concepts and Conclusions . . . . . . . . . . . . . . . . . . . . . 163
4.6.1 Putting It All Together . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
4.6.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
5 Physicalism, Chaos and Reductionism
Alwyn Scott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
5.2 Quantum and Classical Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
5.3 What Are Classical Nonlinear Phenomena? . . . . . . . . . . . . . . . . . . . 173
5.4 The Biological and Cognitive Hierarchies . . . . . . . . . . . . . . . . . . . . . 174
5.5 Reductionism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
5.6 Objections to Reductionism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
5.6.1 Constructionism versus Reductionism . . . . . . . . . . . . . . . . . 179
5.6.2 Immense Numbers of Possibilities . . . . . . . . . . . . . . . . . . . . 180
5.6.3 Sensitive Dependence on Initial Conditions . . . . . . . . . . . . 181
5.6.4 The Nature of Causality . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
5.6.5 Nonlinear Causality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
5.6.6 The Nature of Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
5.6.7 Downward Causation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
5.6.8 Open Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
5.6.9 Closed Causal Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
5.7 Concluding Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
6 Consciousness, Neurobiology and Quantum Mechanics:
The Case for a Connection
Stuart Hameroff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
6.1 Introduction: The Problems of Consciousness . . . . . . . . . . . . . . . . . 193
6.2 Time and Consciousness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
6.2.1 Is Consciousness Continuous
or a Sequence of Discrete Events? . . . . . . . . . . . . . . . . . . . . 197
6.2.2 The Timing of Conscious Experience . . . . . . . . . . . . . . . . . 198
6.2.3 Taking Backward Time Referral Seriously . . . . . . . . . . . . . 202
6.3 The Neural Correlate of Consciousness . . . . . . . . . . . . . . . . . . . . . . . 206
6.3.1 Functional Organization of the Brain . . . . . . . . . . . . . . . . . 206
6.3.2 Cerebral Cortex and Neuronal Assemblies . . . . . . . . . . . . . 208
6.3.3 Axons and Dendrites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
6.3.4 Neural Synchrony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
6.3.5 Gap-Junction Assemblies – “Hyperneurons” . . . . . . . . . . . 215
6.3.6 The Next NCC Frontier –
Neuronal Interiors and the Cytoskeleton. . . . . . . . . . . . . . . 216
6.4 The Neuronal Cytoskeleton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
6.4.1 Microtubules and Networks inside Neurons . . . . . . . . . . . . 217
6.4.2 Microtubule Automata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
6.4.3 Protein Conformational Dynamics –
Nature’s Bits and Qubits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
6.4.4 Anesthesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
6.5 Quantum Information Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
6.5.1 Quantum Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
6.5.2 Quantum Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
6.5.3 Quantum Computing with Penrose OR . . . . . . . . . . . . . . . 229
6.6 The Quantum Unconscious . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
6.7 Quantum Computation in Microtubules – The Orch OR Model . . 232
6.7.1 Specifics of Orch OR. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
6.7.2 Decoherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
6.7.3 Testability and Falsifiability . . . . . . . . . . . . . . . . . . . . . . . . . 236
6.8 Applications of Orch OR to Consciousness and Cognition . . . . . . . 236
6.8.1 Visual Consciousness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
6.8.2 Volition and Free-Will . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
6.8.3 Quantum Associative Memory . . . . . . . . . . . . . . . . . . . . . . . 239
6.8.4 The Hard Problem of Conscious Experience . . . . . . . . . . . 239
6.8.5 What is Consciousness? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
6.8.6 Consciousness and Evolution. . . . . . . . . . . . . . . . . . . . . . . . . 241
6.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
7 Life, Catalysis and Excitable Media:
A Dynamic Systems Approach to Metabolism and Cognition
Christopher James Davia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
7.1 Life and Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
7.2 Life and Catalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260
7.3 Catalysis, Traveling Waves and Excitable Media . . . . . . . . . . . . . . . 271
7.4 The Brain as an Excitable Medium . . . . . . . . . . . . . . . . . . . . . . . . . . 274
7.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
8 The Dendritic Cytoskeleton as a Computational Device:
An Hypothesis
Avner Priel, Jack A. Tuszynski, Horacion F. Cantiello. . . . . . . . . . . . . . . 293
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
8.1.1 Neurobiological Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 293
8.1.2 Neuro computational Introduction . . . . . . . . . . . . . . . . . . . . 297
8.1.3 Dendritic Channel Function . . . . . . . . . . . . . . . . . . . . . . . . . 299
8.1.4 Actin–Microtubule Cytoskeletal Connections . . . . . . . . . . . 299
8.2 C-Termini in Microtubules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301
8.2.1 Potential Configurations of Microtubular C-Termini . . . . 303
8.2.2 Dynamic Model of the C-Termini . . . . . . . . . . . . . . . . . . . . . 305
8.2.3 Ionic Wave Propagation along MAP2 . . . . . . . . . . . . . . . . . 306
8.3 Ion Waves along Actin Filaments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
8.3.1 Ionic Condensation along the Actin Filament . . . . . . . . . . 308
8.3.2 Electrical Modeling of Actin . . . . . . . . . . . . . . . . . . . . . . . . . 309
8.3.3 Implications of Actin Filament’s Electrical Activity . . . . . 312
8.4 Dendritic Cytoskeleton Computation – Vision of Integration . . . . 313
8.4.1 MTN Control of Synaptic Plasticity,
Modulation, and Integration . . . . . . . . . . . . . . . . . . . . . . . . . 318
8.5 Final Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
9 Recurrent Quantum Neural Network and its Applications
Laxmidhar Behera, Indrani Kar, Avshalom C. Elitzur . . . . . . . . . . . . . . . . 327
9.1 Intelligence – Still Ill-Understood . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
9.2 Intelligent Filtering – Denoising of Complex Signals . . . . . . . . . . . . 328
9.2.1 RQNN Architecture used for Stochastic-Filtering . . . . . . . 329
9.2.2 Integration of the Schr¨odinger Wave Equation . . . . . . . . . 331
9.2.3 Simulation Results I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
9.3 A Comprehensive Quantum Model of Intelligent Behavior . . . . . . 337
9.4 RQNN-based Eye-Tracking Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 338
9.4.1 A Theoretical Quantum Brain Model . . . . . . . . . . . . . . . . . 338
9.4.2 An Eye–Tracking Model using RQNN
with Nonlinear Modulation of Potential Field . . . . . . . . . . 339
9.4.3 Simulation Results II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342
9.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348
10 Microtubules as a Quantum Hopfield Network
Elizabeth C. Behrman, K. Gaddam, J.E. Steck, S.R. Skinner . . . . . . . . . 351
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
10.2 Microtubulin Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
10.3 Hopfield Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354
10.4 Quantum Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355
10.5 Quantum Hopfield Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358
10.6 QHN as Information Propagator for a Microtubules Architecture 360
10.7 Conclusions and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369
11 Consciousness and Quantum Brain Dynamics
Gordon Globus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
11.1 Deconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
11.2 Quantum Brain Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
11.3 Hermitean Dual-Mode Quantum Brain Dynamics . . . . . . . . . . . . . . 375
11.4 Non-Hermitean Dual-Mode Quantum Brain Dynamics . . . . . . . . . 376
11.5 Application to Mathematics: The Riemann Hypothesis . . . . . . . . . 377
11.6 Monadological Implications of Non-Hermitean Dual-Mode QBD . 381
11.7 Comment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384
12 The CEMI Field Theory:
Seven Clues to the Nature of Consciousness
Johnjoe McFadden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
12.1 Why Do we Need a Theory of Consciousness? . . . . . . . . . . . . . . . . . 387
12.2 Field Theories of Consciousness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
12.3 The Brain’s Electromagnetic Field . . . . . . . . . . . . . . . . . . . . . . . . . . . 394
12.4 The Influence of the Brain’s Electromagnetic Field
on Neural Firing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
12.5 The CEMI Field Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396
12.6 Why don’t External Fields Influence our Minds? . . . . . . . . . . . . . . 397
12.7 Does the CEMI Field Theory Account for the Seven Clues
to the Nature of Consciousness? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398
12.8 A Last Word, Concerning Quantum Theories of Consciousness . . 401
12.9 Conclusions and the Way Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . 404
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404
13 Quantum Cosmology
and the Hard Problem of the Conscious Brain
Chris King . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407
13.1 Subject–Object Complementarity and the Hard Problem . . . . . . . 407
13.2 Wave–Particle Complementarity, Uncertainty
and Quantum Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410
13.3 Two-Timing Nature of Special Relativity . . . . . . . . . . . . . . . . . . . . . 415
13.4 Reality and Virtuality:
Quantum Fields and Seething Uncertainty . . . . . . . . . . . . . . . . . . . . 416
13.5 The Spooky Nature of Quantum Entanglement . . . . . . . . . . . . . . . . 417
13.6 Quantum Match-Making:
Transactional Supercausality and Reality . . . . . . . . . . . . . . . . . . . . . 420
13.7 Exploring the “Three Pound Universe” . . . . . . . . . . . . . . . . . . . . . . . 423
13.8 Chaos and Fractal Dynamics as a Source
of Sensitivity, Unpredictability and Uncertainty . . . . . . . . . . . . . . . 428
13.9 Classical and Quantum Computation, Anticipation and Survival . 430
13.10 The Cosmic Primality of Membrane Excitation. . . . . . . . . . . . . . . . 433
13.11 Chaotic Excitability and Quantum Sensitivity
as a Founding Eucaryote Characteristic . . . . . . . . . . . . . . . . . . . . . . 437
13.12 Models of the Global-Molecular-Quantum Interface . . . . . . . . . . . . 440
13.13 Quantum Mind and Transactional Supercausality . . . . . . . . . . . . . 442
13.14 Complementarity and the Sexuality of Quantum Entanglement . . 448
13.15 The Hard Problem: Subjective Experience, Intentional Will
and Quantum Mind Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
13.16 Consciousness and Neurocosmology . . . . . . . . . . . . . . . . . . . . . . . . . . 451
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454
14 Consciousness and Logic
in a Quantum Computing Universe
Paola Zizzi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457
14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 458
14.2 The “Big Wow” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
14.3 How the “Big Wow” Drove Human Minds . . . . . . . . . . . . . . . . . . . . 461
14.3.1 Entanglement with the Environment . . . . . . . . . . . . . . . . . . 463
14.3.2 Holography and Cellular Automata . . . . . . . . . . . . . . . . . . . 463
14.4 Consciousness and Tubulins/Qubits . . . . . . . . . . . . . . . . . . . . . . . . . . 464
14.5 Consciousness Arises in the “Bits Era” . . . . . . . . . . . . . . . . . . . . . . . 465
14.5.1 The Boolean Observer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465
14.5.2 The Analogy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466
14.6 The Double Logic of the Observer Inside a Quantum Universe . . 467
14.7 IT from Qubit: The Whole Universe as a Quantum Computer . . . 468
14.8 Quantum Minds and Black – Hole Quantum Computers
in a Quantum Game . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
14.9 Qualia and Quantum Space-Time . . . . . . . . . . . . . . . . . . . . . . . . . . . 470
14.10 Mathematical Intuition and the Logic of the Internal Observer . . 473
14.11 The Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
14.11.1 The Self and the Mirror Measurement . . . . . . . . . . . . . . . . 475
14.11.2 Nonself . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476
14.11.3 The Universal Self: The Universe and the Mirror . . . . . . . 476
14.11.4 The Universal Self: The Mathematical Truth . . . . . . . . . . . 477
14.12 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477



1 The Path Ahead
Jack A. Tuszynski and Nancy Woolf
Summary. This chapter provides an introduction to the rest of the book, which
has a multidisciplinary approach to the physics of consciousness. We summarize
the various contributions and present our own point of view, which is that there
are some deficiencies in defining higher-order consciousness in strict terms of classic
physics. We favor a proposal that considers some aspects of quantum-mechanical
operations among molecules involved with neurotransmission and mechanical transport
of synaptic proteins. In our view, the wiring of the brain is not as complex,
and certainly not as integrated, as commonly assumed. Instead, the wiring pattern
redundantly obeys a few general principles focused on high resolution rather than
crossmodal integration. Basing cognitive functions, such as higher-order consciousness,
solely on electrophysiological responses in neural networks thus wired may not
suffice. On the other hand, coherent quantum computing, executed by tubulins, the
protein subunits of microtubules, may exert en masse influences over the transport
of many receptor and scaffolding proteins to various activated synapses, thereby
accounting for the unity of conscious experience. We discuss the potential problems
of quantum computing, such as decoherence, and also present counterarguments,
as well as recent empirical results consistent with the notion that quantum computing
in the interiors of neurons, in particular, within the interiors of dendrites
may indeed be possible.