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New summaries and reviews of papers, articles, books etc.

1.) The Quantum Brain - Jeffrey Satinover - added 9 March 2010 (Under Protein&Coherence 2) - Useful discussion of quantum activity in protein

2.) The World in Your Head - Steven Lehar - added 1 March 2010 (under Neuroscience 4) - Argues against the concept of the brain as a conventional computer.

3.) Consciousness: Creeping up on the Hard Problem - Jeffrey Gray - added 17 February 2010 (under Mainstream 15) - Criticises functionalism from a mainstream point of view

4.) QUANTUM COHERENCE IN PROTEIN AT ROOM TEMPERATURE
Coherently wired light-harvesting in photosynthetic marine algae at ambient temperature - Elisabetta Collini, Cathy Wong, Krystyna Wilk, Paul Curmi, Paul Brumer & Gregory Scholes - added 8 February (under Protein&coherence 2) - Collini demonstrates quantum coherence in photosynthetic protein at room temperature undermining a key argument against quantum consciousness.

5.) Solving the binding problem: cellular adhesive molecules and their control of the cortical quantum entangled network - Danko Georgiev - added 27 January 2010 (under Danko Georgiev 2) - Proposal for quantum coherence extending between neurons via the synaptic cleft.

Other recent reviews:-
1.) A model of ionic wave propagation along microtubules - Satiric, M. et al - added 5 February 2010 (under Danko Georgiev ) 2.) Neuroligins and neurexins - Thomas Sudhof - added 22 January 2010 (under Danko Georgiev 2) 3.) Neurophysics of consciousness - John, E. - added 2 Feb 2010 (under General Articles 4) (4.) Consciousness not yet explained - Tallis, R. - added 23 Jan 2010 (under Philosophy 3) (5.) Molecular biology and biophysics of microtubules - Georgiev, D. et al - added 13 Jan 2010 (under Danko Georgiev 2) (6.) Why physicalism entails panpsychism - Strawson, G. - added 10 Jan 2010 (under Other Quantum 5) (7.) Dissipationless waves for information transfer in neurobiology - Georgiev, D. - added 6 Jan 2010 (under Danko Georgiev 2) (8.) Consciousness - Revonsuo, A. - added 2 Jan 2010 (under Mainstream 14) (9.) On the dynamic timescale of mind-brain interaction - Georgiev, D. - added 23 Dec 09 (under Danko Georgiev) (10.) Electric and magnetic fields inside neurons - Georgiev, D. - added 21 Dec 09 (under Danko Georgiev) (11.) Analysis of quantum decoherence in the brain - Georgiev, D. - added 15 Dec 09 (under Danko Georgiev) (12.) Mental causation: Libet & Soon - Batthyany, A. - Dec 09 (under Freewill 4).) (13.) Synaptic Self - Le Doux, J. - added 4 Dec 09 (under Neuroscience 3) (14.) Examination of quantum coherence in a photosynthetic system at physiological temperature - added 27 Nov 09 (under Protein&Coherence 2) (15.) Seeing Red - Humphery, N. - added 19 Nov 09 (under Mainstream 13) (16.) Brain Coherence and Entanglement in the 21st Century - added 12 Nov. 09 (under Protein&coherence 2) (17.) Falsification of Hameroff-Penrose model of consciousness - Georgiev, D. - added 5 Nov. 09 (under Other Quantum 4) (18.) Penrose's Godelian argument - Feferman, S. - added 3 Nov. 09 (under Penrose & Hameroff 8) (19.) Godel's First Incompleteness Theorem - added 30 Oct. 09 (under Penrose & Hameroff 8) (20.) The Illusion of Conscious Will - Wegner, D. - added 23 Oct. 09 (under Mainstream 12)

1.)

The Quantum Brain

Jeffrey Satinover

John Wiley & Sons (2001)

INTRODUCTION: This book is mainly of interest for its discussion of quantum features and particularly quantum tunnelling in protein, an area which more mainstream science popularisations are not often keen to discuss. Since Satinover wrote this book, the discovery of functional room-temperature, quantum coherence in photosynthetic protein has brought the importance of quantum activity in protein more to the fore. Apart from this discussion about protein, Satinover is mainly interested in developing the idea of quantum ramdomness driving chaos-based patterns of macroscopic neural processing. Although, he appears to derive a good part of his material from Penrose and Hameroff, he is more concerned with information processing than consciousness, and chooses to dismiss the Penrose/Hameroff consciousness theory without a proper discussion of the matter.

The researcher, John Hopfield, demonstrated that a type of neural net, now known as a Hopfield network, has an identical mathematical description to magnetic systems called spin glasses. These are magnetic substances that demonstrate collective behaviour, without the need for external orchestration. P. Satinover discusses a stable arrangement of magnets, in which opposite poles are holding the magnets apart. If the system is vigorously disturbed, this stable arrangement breaks down, but after a time, the system will settle into a new stable arrangement, to which it can always return after minor disturbances, although now there are more magnets than previously that are not aligned in parallel.

Ferromagnetic materials such as iron have many small areas or domains, in which electron spins (effectively magnetic charges) are aligned. But the domains have many different alignments, and these electrons are in a precarious position, where they can easily be flipped into a new alignment.

These ferromagnetic groups of neighbouring spins are mathematically similar to the excitatory (mainly glutamate) connections between neurons. However, in addition to spins that try to align in the same direction, there are antiferromagnetic systems that align in alternate directions, and these turn out to be mathematically similar to the inhibitory (mainly GABA) connections between neurons.

Materials that have ferromagnetic and antiferromagnetic domains mixed are referred to as spin glasses. This is a random mix of ferromagnetic and antiferromagnetic material, where adjacent electrons competing to align, or flip one another, are always on the edge of change, and are argued to resemble the analogous excitatory and inhibitory mix of neurons. A spin glass system has more than one 'best arrangement' and is similar to a brain, in that it can store new data without erasing existing material.

The brain and chaos: The brain is here regarded as a self-organising system that mathematically resembles the spin glass structure discussed above. However, it is pointed out that self-governing ensembles have a tendency towards chaos, meaning not actual disorder but deterministic chaos. The development of the system could in principle be described by an algorithm, but because this would require such a vast amount of information, the system is in practice unpredictable. The system does repeat patterns or behaviour, but they are similar, rather than exactly the same. It is suggested here that quantum randomness in areas of the brain might be amplified by chaos.

Microtubules: Satinover is interested in the possible involvement of microtubules in brain processing. The cytoskeleton, of which microtubules are the most important component, is considered to be uniquely suited to carry signals, because it spans the whole cell. The cytoskeleton used to be viewed, mainly as a support structure, but more recent studies (1&2) show that they are also signalling mechanisms. The self-organised activity of microtubules and associated proteins and filaments, is seen in recent visualisation studies, to control the mobility of cells and the configuration of dendrites, through which signals enter the cell. This structure is likened to the update rules governing interaction between neighbouring units which drives the evolution of so-called cellular automata from simplicity to complexity. Within the hexagonal tubulin grid that makes up the microtubule, each tubulin has six immediate neighbours, an arrangement of the same type as those conjectured by cellular automatons. The microtubule network as a whole is said to be harmonious and suitable for the transmission of vibrations. It is suggested that the neuron network of the brain is linked to the internal microtubule processing within neurons. The microtubule network is viewed as analagous to the Hopfield network and spin glass systems discussed above.

Quantum aspects of protein: The best section of this book is the discussion of the quantum aspects of protein, the basic building blocks of organic matter. A protein is a string of a hundred or more amino acid molecules. The amino acids are attached to one another by bridges called peptides, so that the protein is a macromolecule. Each amino acid has a unique shape, and a unique distribution of electric charge. For a protein to carry out its necessary functions within an organism, it must fold in a precise manner, at or very close to, the energy minima.

The problem with this system is that there can be trillions of similar ways for a protein to fold. Proteins can assume a very large number of conformational states, with a large number of energy minima. Despite this huge number of possible states, proteins can, within seconds, find the correct conformations and energy minima, which are also the most functional configurations.

There is, as yet, no clear indication as to how this is to be achieved. Random searching for a minimum energy conformation would take longer than the life of the universe to reach a solution. The position is not much better for supercomputers, where despite years of generous funding, it has proved impossible to calculate the minimum energy configuration for even a short chain of amino acids. This is known as the protein-folding problem. DNA encodes the primary structure of the protein, which is the sequence of the amino acids. At a secondary stage, the amino acid chains are formed into particular shapes, such as helices. At the tertiary stage, sections of helices and other shapes are brought together, and folded into a particular configuration of electric charges. It is this last stage of folding that constitutes the protein-folding problem. Satinover argues that the problem of protein folding is similar to the means, by which spin glasses reach alignment, with a huge number of axes, along which protein must flip.

Satinover explains that to achieve what they do proteins use quantum features. Some of the electrons in the protein are in a wave or superposed state, with the wave extending over a considerable distance through the protein. This is referred to as tunnelling, with the wave form of the electron able to penetrate into regions that the point-particle form of the electron cannot reach. This electron tunnelling can be exceptionally sensitive to minor couplings. In helical structures in particular, the influence of quantum tunnelling falls off only slowly with distance. The tunnelling of electrons triggers conformational changes in protein, and further to this, conformational changes in protein trigger yet more quantum tunnelling. Water is vital to living organisms, and it also exhibits tunnelling between molecules. The tunnelling process orders water into chiral (left and right-handed) clusters, which play an important role in protein folding. Tunnelling makes low-energy states more accessible within protein, and this probably proved to be an adaptive advantage, from an early stage in evolution. Studies by Peter Wolynes at the Centre of Biophysics and Computational Biology and also at the National Centre for Supercomputing Applications have simulated the tunnelling process in protein, showing that theories of spin glasses can be applied to the protein-folding problem, and also showing that tunnelling makes systems more efficient, particularly in the search for minimum energy levels. The advantage of quantum processing is that an electron can simultaneously search many routes for the most efficient route.

The existence of quantum tunnelling in protein raises the question of the vulnerability of quantum processes to decoherence. In general, the movement of molecules as a function of heat serves to disrupt quantum tunnelling. However, it is claimed that the opposite is true in the case of protein. Proteins also exhibit phonons that represent travelling, classical, mechanical coherence in protein. These are claimed to enhance tunnelling distance. This represents a mutually reinforcing relationship between classical, mechanical vibrations and quantum activity, so as to enhance short-lived coherences. Decoherence of superpositions may happen rapidly, but may collapse to just the right classical state, which also puts the protein into the right condition for the next burst of quantum coherence. Studies performed a number of years after Satinover's book look to have demonstrated just such a pattern of decline and resurgence in coherence, where quantum coherence has been demonstrated in photosynthetic proteins.

Tunnelling by hydrogen protons has been found to be essential for enzymatic action. Here again, there is an interaction between tunnelling protein conformation and more tunnelling, and here too, studies show that classical vibrations, rather than disrupting tunnelling, are actually required for tunnelling. Thus proteins, merely be absorbing heat from the environment, can initiate computational processing. Life here seems to use quantum effects to extract order from disorder. A study by Judith Klinman at Berkeley showed that hydrogen proton tunnelling in protons can occur at room temperature.

Subsequent to its discussion of quantum effects in protein, this book becomes less interesting. Ultimately, it is commited to 'the brain's a deterministic computer doctrine', albeit a computer driven by quantum randomness feeding into deterministic chaos. In essence the writer is concerned with quantum/chaotic information processing rather than consciousness.

Satinover appears to derive quite a lot from Penrose and Hameroff, but as is often the case, intellectual rigour goes out of the window, when discussing this theory. The whole theory appears to be dismissed solely on the basis of the Hameroff side of the theory, which is to do with implementation in the brain, rather than Penrose's original reasons for looking to quantum theory. Furthermore, if one is to argue against this theory on the basis of decoherence, as happens here, it is necessary to discuss the possibility of shielding of quantum processes, or the possible involvement in consciousness of the shorter lived coherences discussed by Satinover. This discussion is lacking in this book.

References:-
1.) Tuszynski, J. et al (1998) - Information processing and quantum computation in microtubules - Philosophical Transactions of the Royal Society 2.) Brown, J. & Tuszynski, J. (1997) - Dipole interactions in axonal microtubules as a mechanism of signal perception - Physical Review E 56, pp. 5834-40
3.) Wolynes, P. (1992) - Spin glass ideas and the protein folding problem - In: Spin Glasses and Biology, pp. 225-6 - Ed. Stein, D. - World Scientific Publishing
4.) Farid, R. et al (1993) - Electron transfer in proteins - Current Opinion in Structural Biology, 3, p.225
5.) Stuchebrukov, A. (1996) - Tunnelling currents in electron transfer reactions in proteins - Journal of Chemical Physics, 105, pp. 10819-10829
6.) Balabin, I. & Onuchic, J. (1998) - A new framework for electron transfer calculation - Journal of Physical Chemical B, 102, pp. 7497-7596
7.) Ogawa, M. et al (1993) - Distance dependence of intramolecular electron transfer rates across oligoprolines - Journal of Physical Chemistry, 97, pp. 11456-11463
8.) Balabin, I. & Onuchic, J. (1996) - Connection between simple models and quantum mechanical models for electron transfer tunnelling - Journal of Physical Chemistry, 100, pp. 11573-11580
9.) Basran, J., Sutcliffe, J. & Scrutton, N. (1999) - Enzymatic H-transfers requires vibration driven exteme tunnelling - Biochemistry, 38, pp. 3218-3222
10.) Wolynes, P. & Kuki, A. - Electron transfer paths in protein - National Center for Supercomputing Applications P. 11.) Bahnson, B. & Klinman, J. (1995) - Hydrogen Tunnelling in Enzymes Catalysis - Methods in Enzymology, 249, pp. 373-397

2.)

The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience

Steven Lehar, Schepens Eye Research Institute

Lawrence Erlbaum (2003)

INTRODUCTION: Lehar makes a good case against the computer/AI model of the brain, by highlighting the inability of computers to differentiate the edges needed to construct a model of the world, from the mass of less important input. He contrasts this with the ability of biological vision to deduce information from very flimsy inputs. The Gestalt methods suggested for achieving what the brain can do are not entirely convincing, as a means of sorting the mass of data input, and thus avoiding the combinatorial explosions implied by the requirements of visual perceptions. In this respect, a quantum computing approach might look to have a greater chance of success. Further to this, a weakness of the book is the lack of much attempt to relate what is proposed to the physical components and processing of the brain.

Lehar approaches consciousness from the angle of the relationship between visual image processing and artificial intelligence (AI). A computer has all the data relative to an image in the form of numerical data. However, turning this into usable information in AI/robotics has proved an intractable problem. Computers can detect features such as edges, but the problem is that they can detect too many of such features. Their edge detection includes details of texture, surface fragmentation and shadows, but fails to pick out those edges that are relevant for the outlines or volumes of an object. Further, there is no apparent algorithm to deal with occluded objects, where a small object obstructs the view of part of a larger object, but it can be deduced that the larger object continues behind the smaller object. This is taken to mean that the information of global significance for understanding the image is not available in the local edges.

Computers have problems with the spatial structure of visual scenes, and as a result difficulty in navigating in an environment of irregular forms, which, by contrast, present little problem for biological vision. Lehar points out that the retinal image is two-dimensional, but is perceived as three-dimensional, and that therefore the three-dimensional depth of the image must be the result of cortical processing. A basic function of visual perception is argued to be the transformation from a two-dimensional retinal image to a three-dimensional perception in the brain. Apart from inserting spatial structure into an initially two-dimensional image, the brain must also decompose this image into coherent objects with volume within the spatial structure. From this it is argued that the brain must operate a spatial algorithm, in order to produce this three-dimensional image. What computers have had difficulty in achieving is not receiving the visual data, but in developing the sort of processing that allows the brain to turn this data into a conscious image.

The literature relative to these problems concentrates on restricted domains, with separate algorithms for extracting shape from shading, for motion or for lines. However, the problem of dealing with shape of the conformation of objects that reflect light has remained largely unresolved. This divergence in relative performance is argued to show that the basis of biological and computer vision are very different from one another.

Conscious images: Lehar takes the view that the conscious image is assembled in the brain, in response to data from the external world. This is described as 'indirect realism,' in contrast to 'direct realism' or 'naive realism', in which it is believed that we perceive the external world as it actually is. The author thinks that discussions in neuroscience are often implicitly based on direct realism, but he argues that this view is based on false assumptions. The visual experience is at odds with scientific reality, because the subjective world is experienced, as if it were outside the brain, whereas visual processing occurs inside the brain. The causal chain of vision is one, in which the brain can only process material that has already been picked up by the sensory organs. Consciousness is therefore necessarily confined to the experience of internally constructed models. Lehar goes back to Kant, who distinguishes between the 'nouminal' world of light signals etc. and the phenomenal world of internal conscious perception. The 'nouminal' world is only perceived within the phenomenal world.

The author argues that the properties of subjective experience are inconsistent with the present neuroscientific thinking, based on the semi-independent sequential operation of billions of individual neurons. In contrast, our experience is mainly of stable and solid volumes, rather than billions of abstract features. The author accuses the neuroscientific community of evading this problem by assuming the 'naive realism' view, and ignoring subjective experience. This attitude is partly blamed on the mid-twentieth century advent of single-cell recording, which shifted the emphasis from assembly-wide features towards single-cell features. In the same period, the digital computer became a major part of technology, and was seen as an analogy of the brain. At this stage, AI researchers thought that they had the problem of vision solved, and that they could implement robotic vision without paying any attention to biological systems.

Famous Dalmatian: The author discusses the well-known picture of a Dalmatian dog against a speckled background. Much of the dog is missing, and some of the edges that are there are locally indistinguishable from the background. Much of the edge of the dog is missing and some of the edges that are there are locally indistinguishable from the background. The main point about this is that the local information does not allow the observer to distinguish the dog from the background, but when the picture is viewed as a whole, the dog is clearly distinguishable. Lehar argues that this indicates that perception is based on global brain activity, rather than the sequential processing of individual neurons. He claims that no algorithm has ever come close to handling the ambiguity of the Dalmatian dog picture. Furthermore, the picture is viewed as demonstrating, in exaggerated fashion, the principles that underlie biological visual processing. One argument tries to evade this conclusion, by suggesting that an image such as this is a special case that does not apply to normal visual processing. However, Lehar counters that studies that restrict the view of pictures to just a few edges show that humans cannot distinguish between edges that are important to the outline or form of objects, and edges that are just texture or shadows.

Kaniza triangle: Lehar discusses visual figures, such as the Kaniza triangle, where the mind automatically perceives a triangle, although all that is physically there on the printed paper is three black Pacman features. Thus, the observer perceives edges and a brighter white ground than the surrounding area, where neither exists on the paper. Again, this is argued to be a global processing of the image, rather than derived from the examination of individual edges.

Rubin vase/faces: The same is true of other well-known examples such as the Rubin face/vase illusion. A black figure on a page may be perceived, as either a vase or the profiles of two faces opposite one another. The brain jumps from one perception to the other, without ever offering a hybrid picture, and can as quickly reverse its perception. It is argued from this that visual recognition is not the result of feed-forward processing of a visual input leading to a perceptual output, as is often assumed in computer models of the brain, but instead involves a dynamic process that is not completely stable. P. Invariant perception: Lehar also discusses the problem of the invariance of our perception of objects, in that they can be recognised from different angles and in different lights, as the same objects, in a way that is not easily achievable by the analysis of individual edges. Conventional computing could only manage this by having a detector for each possible position, which could produce a combinatorial explosion or NP hard problem, where classical computing might only resolve the problem in a time that was longer than the life of the universe. There have been suggestions that local elements of the object are first recognised, and later put together, but this does not take into account instances, where what are actually different elements may form an image of the same object.

Visual agnosia: The distinction between being able to detect individual features, and gaining a practically useful model of the world can also be demonstrated from human pathology in the form of visual agnosia. There are two forms of this; in a condition known as apperceptive agnosia, the patient can see individual objects, but cannot integrate these features into a spatially coherent three-dimensional whole. The opposite condition is associative agnosia agnosia, where the patient perceives a coherent world, but cannot identify individual objects. This medical finding is argued to contradict the 'naive realism' claim that the brain is just seeing what is out in the world, in which case the whole spatial environment should be perceived.

Gestalt theory attempts to solve the problem of visual recognition by parallel processing, in which the solutions to each part of the visual recognition problem depend on one another, and thus constrain the possible solutions for one another, thus closing in on a single solution. Lehar also proposes the idea of 'harmonic resonance'. This involves resonance between different modules in the brain, with resonance ultimately being communicated to all the relevant systems in the brain. This is seen as a solution to the 'binding problem' or an explanation of the unity of different modalities in conscious experience. This of course relates to the EEG recordings of gamma frequency synchrony in the brain.

Conclusion: It is not clear that these Gestalt proposals involve sufficient processing capacity to overcome the likely combinatorial explosions/NP hard problems implied by perception. Lehar does relatively little to link his ideas to the physical components and processing of the brain. From the look of it, a quantum computing process would have more chance of bridging the gap between classical computing capacity and the requirements of visual perception as highlighted by Lehar.

3.)

Consciousness: Creeping up on the hard problem

Jeffrey Gray

Oxford University Press (2004)

INTRODUCTION: This book is worth reading for a number of interesting areas of discussion. It attempts to use aspects of synaesthesia to refute the still dominant functionalist theory of consciousness. It argues that intentionality or meaning arises from unconscious processing, and also that there is no true representation of the external world in the brain. Because of these last two points, it is argued that much of the philosophical baggage of consciousness studies can be left behind, and discussion of consciousness should be focused purely on qualia. Gray does not think we yet have an explanation for qualia. He takes the possibility of quantum consciousness, at least in the Penrose form more seriously than most mainstream investigators, although he argues that it contains no explanation for the selection of particular qualia. He sees conscious as being selected for by evolution, because it is causal, but causal in a sense that does not involve agency or freewill. Unconscious systems are claimed to respond to conscious perception, but only in the sense that our brains can respond to a sketch as a reminder, with the sketch having no agency of its own. This part of the discussion seems rather incomplete. Gray has relatively little to say about cognitive processing, the conscious emotional aspects of the brain, or the relationship between these two, which is known to be crucial in determining preferences for action and behaviour.

Gray stresses that conscious experience has no scientifically understood links with neuroscience or behavioural science. Without such links, there can be no understanding of the interaction of consciousness with the physical world. Neuroscience has built up a detailed knowledge of neurons, but this is viewed here as having made no contribution at all to explaining consciousness. Most neuroscience experimentation has not been aimed at understanding consciousness, but at understanding the movement of energy in the brain. Biology as such makes do with two systems, firstly the laws of physics and chemistry, and secondly feedback mechanisms that respond to a variable, which is being controlled. In fact, neuroscience has created a complete outline of brain processing without involving consciousness. There is nothing for consciousness to do within conventional neuroscience, and the existence of consciousness is something of an embarrassment to the theory. But Gray argues that while experimentation has shown much of what we perceive to be an illusion, we should hold onto the fact of conscious experience, for without conscious experience, it would be impossible to have an illusion in the first place. The unconscious mind is argued not to be capable of having an illusion, but only of making an error. In contrasts to an error, an illusion continues even when it is known to be an illusion. Thus knowing that a film is a series of frames does not prevent us from seeing it as continuous.

Refuting functionalism: Gray goes on to discuss functionalism, which he views as the dominant form of consciousness theory. According to functionalism, consciousness is the nature of certain complex systems, regardless of whether they are is made of neurons, silicon chips or some other material. The underlying tissues or machinery is irrelevant. Further to that, consciousness relates only to functions performed by the brain or other system, and does not arise as a result of anything that is non-functional. In looking at the qualia red and green, functionalism says that all that exists are responses, by which the individual's behaviour demonstrates the capacity to discriminate between red and green. For any discriminated difference in qualia, there must be a difference in function. It is also claimed that for every discriminated difference in function, there is a difference in qualia.

Gray claims to refute functionalism, on the basis of data from research into synaesthesia performed at the Institute of Psychiatry in London. In discussing this question further, Gray looks at synaesthesia, where modalities become mixed, as when numbers or sounds are experienced with colour. Extensive experimentation in recent years has demonstrated that synaesthesia is a real and observable brain state, and is most likely the consequence of abnormal projections into the V4 colour region of the visual cortex from other parts of the brain. Brain scanning studies showed that when words were spoken, in addition to the normal activity in the auditory cortex, the V4 colour vision area in the visual cortex became active, in a way which did not occur in normal subjects. There was no related activation in V1 or V2, the earlier stages of the visual pathway. The conclusion drawn from a whole series of experimentation was that the 'word-colour' type of synaesthete has an abnormal projection from the auditory cortex into the visual cortex causing the V4 colour area to produce consciousness of colour. However, there is no evidence that this colour sensation has any function. Thus, there is no relationship between the occurrence of the synaesthete's colour experiences and the linguistic function that triggers them. Gray argues that this phenomena refutes the functionalist theory's analysis of conscious experience.

Intentionality and the unconscious brain: Gray argues that a large proportion of the brain's activity is unconscious. Consciousness is commonly estimated to lag about 250 milliseconds behind an event being registered by the sense organs, but much action and behaviour takes place more rapidly than this. He also discusses the existence of separate systems for conscious and unconscious processing. This is the case in the visual system, where there is a ventral stream that underlies conscious perception, and a dorsal stream that underlies rapid but unconscious actions.

Conscious experience or more specifically the contents of consciousness are usually about something, and this is described as 'intentionality', whereas movements of energy in the brain are just themselves, and are not about anything. Intentionality is another aspect of the 'binding problem', as to how the different modalities, such as sight and hearing, are bound together into a single conscious experience. Gray points out that without binding, eating a banana could involve seeing yellow, feeling a surface and tasting something without the unifying awareness of a particular object known as a banana. Intentionality can also be referred to as meaning, the meaning of the yellow colour etc. is a banana. Without this binding, things would be just meaningless shapes, edges, colours etc. Consciousness appears to arise where modalities come together. This also involves the idea of categories that usually bridge two or more modalities, as with the example of the banana, as a particular category of object.

Gray sees the unconscious brain as containing subsystems that can be regarded as what he calls servomechanisms dedicated to controlling a particular variable, such as the distance between a hand and an object that is going to be grasped. These servomechanisms are often linked to actions. In contrast, conscious perception can be just about perception, such as looking at a sunset.

Despite this distinction, Gray argues that intentionality is based on unconscious processing. The processing in the visual cortex that underlies conscious perception is not itself conscious. Instead, the perception springs into consciousness fully-formed, including the intentionality of what the perception is, or is about. To prove this point, Gray use the example of pictures that can be either of two things, such a duck or a rabbit. They are never hybrid, but are always completely duck or completely rabbit. The perception of a duck or rabbit is argued to be constructed unconsciously up to the last moment. The actual process of binding, as in the binding problem, is also suggested to be an unconscious result of synchronous firing within and between brain regions. Gray's conclusion from this part of his discussion is that intentionality arises from the physical and chemical structure of the brain, but also that if intentionality can be constructed out of unconscious processing, it is unlikely to produce a solution to the 'hard problem' of how consciousness arises.

Representation: Gray goes on to discuss the question of the representation of the external world in the brain. First of all, he reminds us that the external world is nothing like what it appears like in conscious perception. The external world is bits of energy fluctuating in the vacuum, with none of the qualities of solidity, colour etc. attributed to the perceived world. But the author goes further than this. He dismisses what he calls the fall back position, which is to think that the perception of something, a cow for example, is a representation, in the sense of resembling the cow as it really exists. Gray argues that our only direct knowledge of the cow is a brain state. We have has no direct knowledge of the cow as it really is, and it is therefore meaningless to argue that the cow brain-state is a representation of the real cow.

Gray argues the conscious perceptions should be treated as signals. Signals have no need to resemble the thing about which they communicate. A whistle might warn thieves of the approach of a policeman, but a whistle is nothing like a policeman. Perceptual experiences are seen as signals, about what observers might expect about their environment. However, he stresses that these perceptual signals arise in the brain, and do not have any kind of external existence. This is not to say that we cannot deduce useful information about the real world from perception. Thus for example visual perception is a good guide to the reflectance of surfaces, which in turn often has survival value for an organism. Thus there is a 'fit' between the external world and the model constructed in the brain, otherwise we would not have much success in interacting with the world.

Gray also emphasises that conscious perception is not voluntary. Perceptions just pop into consciousness, and are argued here to come from unconscious processing. Furthermore, it is claimed that only a tiny proportion of the data that could potentially enter consciousness actually does. It is possible to distinguish between two types of unconscious processing. Firstly, processing that can never come into consciousness, and secondly processing which is potentially conscious but remains unconscious.

Philosophical Baggage: Gray's message is that we can dispense with much of the philosophical baggage of modern consciousness studies, as regards intentionality and representation, because these are either unconscious or non-existent. Given the reams that have been written on these subjects, and the meagre gains in our understanding of consciousness, many might be glad to dispense with this baggage train. Instead, Gray says we should concentrate on the qualia of subjective conscious experience, as the only aspect of the brain that involves consciousness.

Function of consciousness as comparator and late detector: Gray views the function of consciousness as a 'late error detector'. The brain is argued to be a 'comparator' system that predicts what should happen and detects departures from that prediction. It is suggested that consciousness is particularly concerned with novelty or error. It is also viewed as something that causes us to review past actions, and to learn from errors in these actions. Late error detection permits more successful adaption, if a similar situation emerges in the future. Gray looks at the question of pain. We remove our hands from a hot surface before consciously feeling the pain of touching it. The pain involves is argued to be a rehearsal of the action that led to it, and has the survival advantage of making a repetition of the damaging action less likely.

Gray accepts that there are many unconscious systems that detect errors, so this on its own does not produce a survival value for consciousness. However, he distinguishes consciousness as being multi-modal, and as directing us towards whatever is most novel within several modalities. The brain takes account of plans as to what to do next, plus memories of past regularities, in assessing what is likely to be the next stage of a particular process. These predictions are submitted to a comparator, but still at an unconscious stage. Only the unexpected outcomes, or feedback for the continuation of motor action enters consciousness. We are only conscious of things that change unexpectedly, or things that are particularly important at the moment.

Gray views the function of consciousness as the construction of relatively constant perceptions from ever-changing sensory inputs. The trick is the transmutation of the ever-changing into the constant. The survival value of consciousness is seen as the ability to take a second look, where actions or predictions have gone wrong. The actual detection of departure from prediction is argued to be at the unconscious level, and the perception of error then just jumps into consciousness.

The perceptual system is said to construct a relatively stable picture of the external world, against which unconscious processing by the comparator reports expectations, error and change. Experimental data suggests this is useful with navigation. A route once learnt can be re-used without trial and error on the basis of a few major land marks. Similarly in other circumstances such as physical actions, consciousness can act by providing information on key variables, which feed back into action.

Gray goes on to make the distinction between egocentric and allocentric views of the spatial world. The egocentric is concerned with action, and is centred on parts of the body. Conscious perception, however, uses an allocentric system where the relationship between objects is independent of the conscious observer. Damage to the inferior parietal lobule, as in Balint's syndrome, leads to errors in binding together the different features of a single object. This is related to the parietal's involvement with spatial perception, and is taken to suggest that binding requires that objects are attributed to a particular spatial location. Egocentric space is suggested to be unconscious in the parietal lobule, with a projection to the hippocampus, which supports conscious allocentric space.

Medium of display: Gray regards consciousness as a medium of display created by unconscious processing. The standard objection to this is that it creates an infinite regress because there has to be a conscious homunculus viewing the display in the Cartesian theatre, and then an homunculus within that homunculus and so on ad infinitum. However, Gray argues that the conscious display is used by unconscious systems, as in the example of unconscious aversion to a food associated with a gastric illness. Conscious perception is in this theory created by unconscious systems, and used by other unconscious systems to respond to late errors, unexpectedness or novelty.

Consciousness – causal but without agency: Gray likens the conscious perception to a sketch made of a particular scene that is retained for use as a record or reminder of the scene. In this way, the sketch is causal in the sense that it performs the function of recalling or assisting memories, but it is not directly active in the brain. In Gray's consciousness model, the conscious perception plays much the same role as the sketch in his analogy. Consciousness is causal, in the sense that downstream unconscious systems respond to it, mainly in the area of error correction. However, this conscious aspect of the brain has no agency or freewill with which to initiate or inhibit actions, anymore than the sketch on a piece of paper can initiate can initiate actions independently of our brain.

Incompleteness: I think that although there is much of interest in Gray's analysis of intentionality, representation and the unconscious, his analysis is nevertheless incomplete in important ways. In discussing the unconscious nature of rapid response actions, he adopts the conventional but superficial approach to the Libet experiments. When he describes how these showed that trivial (automatic pilot type) actions are initiated in the brain before the awareness of the decision to make the action, he appears to simply assume without further discussion that this must apply to more deliberative or strategic decisions that by their nature takes a longer time to reach a conclusion.

In line with this, he also makes no extended to attempt to discuss either cognitive activity or the impact of emotions, and more importantly the interaction between the prefrontal cognitive areas and the areas of the brain processing emotions. It might be possible to argue there are unconscious systems making the actual decisions in these areas of the brain, but if Gray did want to establish this point, he needed to discuss his model in terms of these systems, which have a central role in determining actions. In particular, he needed to pin down the role of our subjective experience of emotion in determining preferences and actions, if he wanted to justify the dominance of the unconscious in actual decision taking.

What are qualia: Gray poses the question, as to how the brain creates and inspects the display medium of conscious perception. In asking this question, he makes the assumption that consciousness is different from either behaviour or brain activity. He views this as a 'hard problem', in the sense of the term coined by the philosopher, David Chalmers. He considers that for all of biology, except for the question of consciousness, the laws of physics and chemistry, plus natural selection and the internal feedback mechanisms selected for by natural selection are sufficient explanation. He considers that consciousness has sufficient causal effects to justify it being selected for by evolution. The hard problem is seen as being the difficulty of locating consciousness qualia within physics.

Amongst researchers within mainstream neuroscience, Gray is unusual in not finding the idea of quantum states being relevant to neural activity as ridiculous. However, his discussion of the Penrose's version of the theory is not really complete, in that he concentrates entirely on Hameroff's propositions for quantum activity in the brain, rather than Penrose's original reason for looking to the quantum level in the first place. Penrose's suggestion was that a special form of quantum wave reduction was the only thing that could explain mathematical understanding, when it goes further than what can be determined by the axioms of any formal theorem. This might been seen to answer one of Gray's main objections to the theory, which is as to why particular wave function collapses should select for any one particular qualia. Gray also questions the temporal aspect of Hameroff's model, where the proposed 25 milliseconds to wave function collapse equates to the 40 Hz gamma synchrony, which is possibly the best known correlate of consciousness. Gray argues that this does not work very well because it takes at least ten times as long as this for a conscious perception to form. However, this does not seem an insuperable problem given that there is strong support for the idea of a connection between gamma synchrony and consciousness. This is the case even in conventional neuroscience, which suggests some physical link between synchrony and the time to conscious perception, whether at the classical or the quantum level. Gray's final word on the subject is that at least Penrose tries to explain qualia, which is seen as an advance on Dennett and functionalism, which essentially deny the data that we all have as to the existence of conscious experience or qualia, and which any valid theory of consciousness should attempt to explain rather than deny.

4.)

ROOM TEMPERATURE QUANTUM COHERENCE IN PROTEIN

Coherently wired light-harvesting in photosynthetic marine algae at ambient temperatures

Elisabetta Collini, Cathy Wong, Krystyna Wilk, Paul Curmi, Paul Brumer & Gregory Scholes

Universities of Toronto, New South Wales and Padua

Nature, 463, pp. 644-7, 4 February 2010 doi:10.1038/nature08811

INTRODUCTION: This low-key paper may in time come to be seen as one of the decisive studies of the 21st century. The paper shows that room temperature quantum coherence can occur in biological matter. In 2007, Engel et al had shown that coherence was possible in organic matter, but this was only demonstrated at very low temperatures, whereas the Collini study demonstrates similar activity at ambient temperature. The paper and related commentaries makes no mention of consciousness, although a relevance to quantum computing is suggested, which is a possible step towards discussing consciousness. The main plank of the arguments against quantum consciousness relates to the speed of decoherence in biological matter being too quick for coherence to be relevant to processing, particularly neural processing, in such matter. This argument looks to have been substantially undermined by the recent study.

Antenna proteins are an essential part of the photosyntetic process, which absorbs light and transmits the resulting excitation between molecules to a reaction centre. Recent research has concentrated on determining the mechanisms that support a very high level of efficiency in this energy transport. Light-harvesting antennas are comprised of eight pigment-molecules, with different pigments absorbing different frequencies of light. The route the energy takes across the molecule is important in terms of energy efficiency.

Studies have documented the fact that light-absorbing molecules in some photosynthetic proteins transfer energy according to quantum mechanical rather than classical laws even at ambient temperature. This contradicts the 20th century dogma that long-range quantum coherence would always decohere in the temperatures found found in biological systems.

This paper by Collini et al describes X-ray crystallography studies of two types of marine cryptophyte algae that have long-lasting excitation oscillations and correlations and anti-correlations, symptomatic of quantum coherence even at ambient temperature. Distant molecules within the photosynthetic protein are thought to be connected to quantum coherence, and to produce efficient light-harvesting as a result. The cryptophytes can photosynthesise in low-light conditions suggesting a particularly efficient transfer of energy within protein. According to the traditional theory, this would imply only small separation between chromophores, whereas the actual separation is unusually large.

In this study, performed at room temperature, the antenna protein received a laser pulse, which results in a coherent superposition in the protein. The experimental data of the study shows that the superposition persists for 400 femtoseconds and over a distance of 2.5 nanometres. Quantum coherence occurs in a complex mix of quantum interference between electronic resonances, and decoherence caused by interaction with the environment. The authors think that long-lived quantum coherence facilitates efficient energy transfer across protein units.

The authors remains uncertain, as to how quantum coherence can persist for hundreds of femtoseconds in biological matter. One suggestion is that the expected rate of decoherence is slowed by shared or correlated motions in the surrounding environment. Where light-harvesting chromophores are covalently bound to the protein backbone, it is suggested that this may strengthen correlated motions between the chromophores and the protein.

In the same issue of 'Nature' that published Collinis study, the 'News and Views' section of the journal also comments on her paper. It emphasises that this is the first study in which quantum coherence in photosynthetic proteins has been observed at room temperature. It comments on the remarkable efficiency of energy transfer, between the antennas that guide excitation energy from hundreds of light-absorbing pigment molecules towards the subsequent reaction centres that drive biochemical events. Collini is suggesting that quantum coherence could be a factor in this efficiency.

Earlier studies had observed coherent behaviour in green sulphur bacteria, but at very low temperatures. Collini et al observed quantum coherence in the antenna, and found that this persisted over 400 femtoseconds, in contrast to an expectation in traditional theory of only 100 femtoseconds. Coherence was observed between widely separated pigment molecules. This has also been observed in bacterial light-harvesting complexes. However, this was at very low temperatures, while the Collini study was at room temperature. Engel et al, who were responsible for some of the earlier studies, have speculated that quantum coherence allows antennas to search for the lowest energy state of the complex more efficiently, thus enhancing the energy transfer to the reaction centre. Coherence might help excitations to avoid local energy traps or minima, on their way to the reaction centre. Covalent binding to the protein backbone is speculated to make coherence longer lasting.

Perhaps the most surprising aspect of this latest paper on coherence in proteins is the speed with which news of the development has made its way to the level of more popular science, in the form of a useful full page summary by Kate McAlpine in the 'New Scientist'. She mentions that Gregory Engel, who was respnsible for the earlier low temperature studies of coherence in bacterial proteins, is enthusiastic about the Collini result. Engel and his group have also performed a study at 4 degrees centigrade, much above previous levels, although below the 21 degrees of the Collini study. Engel is also quoted as saying that this work could have implications for quantum computing, where a core problem has been to operate at the very low temperatures that are usually thought necessary to prevent quantum decoherence. The speed with which this work has been picked up and given prominence in a popular science magazine suggests a background change of attitude to coherence in protein. The vexed question of quantum consciousness is not mentioned, but the suggestion of activities within protein as a model for quantum computing is moving is in that direction.

5.)

Solving the binding problem: cellular adhesive molecules and their control of the cortical quantum entangled network

Danko Georgiev, Medical University of Varna

Cogprints: 2 May 2003

INTRODUCTION: The author proposes a model by which quantum coherence arises in the cytoskeleton, is transmitted to the synapse, and from there to neighbouring neurons via the neurexin-neuroligin complex in the synaptic cleft. This is suggested to bring a large group of neurons into quantum entanglement, and to provide a solution for the binding problem.

The article proposes a possible process to support quantum entanglement between neurons, based on neurexin and neuroligin. This involves the 20-30 nanometre wide synaptic cleft, which is filled with electron-dense material. The presynaptic side has an active zone containing vesicles of neurotransmitters. Apart from signalling processes, there is also an adhesive junction at the synapse formed by neurexins and neuroligins. These are brain specific molecules, which bind to one another, and are part of a family of molecules known as CAMS, which are often present at synapses. The author claims growing evidence for the role of CAMs in modulating both short and long lasting plasticity. Receptors required for longer term potentiation (LTP) may be linked to the modulation of the cell adhesion proteins. Adhesion proteins could modulate glutamate receptors, possibly by altering the width of the synaptic cleft, and the size of the pre and post synaptic active zones, and also by altering glial cell processing around the edge of the synapse. Neurexin and neuroligin appear well suited to link pre and postsynaptic signalling mechanisms. The C-termini of neuroligins are inside the postsynaptic neuron and bind to the PDZ, which is thought to act as a nexus for receptors and signalling molecules on the postsynaptic side. The C-termini of the neurexins binds to CASK another PDZ containing protein on the presynaptic side.

The author relates these structures to the proposal that the cytoskeleton is important to the processing of incoming information in the brain, and that macroscopic quantum coherence arises in the cytoskeleton. Beyond this, he is looking for a means by which coherence passes from one neuron to another. He has rejected the Hameroff proposal that this happens via gap junctions between dendrites.

There is a thickening of the cell membrane on both sides of the synapse. The postsynaptic density (PSD) has been proposed to be a protein lattice that organises receptors, ion channels and signalling molecules. The proteins in the lattice contain PDZ domains involving PSD-95 that can bind to many types of synaptic proteins, including receptors