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General Articles 1General Articles reviews and summarises articles of background relevance to quantum consciousness. General Articles 1 covers background articles related to neuroscience 1.) 23 Problems in Systems Neuroscience - Hemmen, L. & Sejnowski, T. 2.) Rhythms in the brain - Gyorky Busaki - Detailed discussion of brain oscillations including the gamma synchrony 3.) Putting the puzzle together - Newman, J. - Discusses differences between conscious and unconscious processes. 4.) Evidence supporting information processing in animals - Discusses inability of classical computing to cope with perception in the brain. 5.) Psychological Investigations of Unconscious Perception - Philip Merikle & Meredyth Daneman - Discusses conscious and unconscious perception 6.) Space, time & consciousness - Smythies, J. - Favours scientific representative theory 7.) The status of blindsight - Kentridge & Heywood 8.) Blindsight & qualia - Jason Holt 9.) i of the vortex - Llinas, R. - Discussion of self generating activity in the brain 10.) Nine Lifes - Gefter, A. 1.) 23 Problems in Systems Neuroscience (Comments on selected chapters) Eds. Leo von Hemmen & Terrence Sejnowski Oxford University Press (2006) Several of the chapters in this volume stress the importance of ongoing processes in the brain, relative to the more traditional emphasis on sensory input and subsequent motor response. The conventional picture viewed the brain as a passive receiver of sensory input, which is then processed to produce a motor response. In chapter 6 'What is Fed Back', Jean Bullier of Universite Paul Sabatier, Toulouse views the brain as a self-sustained process of internal information that occasionally samples the external world. In respect of this, Bullier emphasises a recent renewal of interest in the rhythm activity of the brain. It is stressed that the processing of internal inputs depends heavily on the state of the brain at the time of input. P In Chapter 9, Tal Kenet et al of the Weizmann Institute argues that ongoing dendritic activity in the brain should not be dismissed as noise, but that sensory input should be related to this. It is suggested that attempts to decipher the neural code will be incomplete without taking account of sub-threshold dendritic activity, which is often found to be synchronised across several millimetres of cortex. In Chapter 10 Bruno Olshausen of UC Berkeley and David Field of Cornell University take a pessimistic view of the current state of neuroscience. They query whether the previous decades of neuroscience have taken sufficient account of the non-linear qualities of neurons. They emphasise that cortical pyramidal neurons have elaborate dendritic trees and that modelling suggests that each branch of these trees could act as a non-linear sub-unit, so that any one neuron could compute many different combinations. The authors suggest that the earlier generation of experimenters may have chosen the wrong basis for experiments, and that even with V1, the basic area of the visual cortex, we may have only a flawed understanding. The authors go on to stress the problems involved in arriving at the right interpretation of an image. The low-level features, such as edges and contours, are ambigous in natural scenes. The nature of the scene has to be inferred from higher-level knowledge, but this itself depends on lower-level features. Some theorists argue that this depends on cortico-cortical feed back loops in order to disambiguate these levels in parallel. (Ullman, 1995) (Lewicke & Sejnowski, 1997). P In Chapter 17, Henning Scheich et al of the Leibnitz Institute argue that there is experimental evidence that the sensory cortex is not just a passive instrument for analysing stimuli, but rather the centre of active processes. In Chapter 19, Terrence Sejnowski of the Salk Institute also argues that we are not simply stimulus-repsonse machines, but instead suggests that many research proocols do not allow the flexibility that is a feature of the cortex to become apparent. He argues that experiments often impose an artificial distinction between sensory and motor systems. Other experiments suggest that, for instance, 'place' neurons in the hippocampus are driven as much by internal states as by external stimuli. Some studies suggest that oscillations in the cortex are related to attention and expectation in advance of actual stimuli (Fries et al, 2001). Studies on humans suggests that ongoing activities interact with sensory inputs (Makrieg et al, 2002). 2.) Rhythms of the Brain Gyorgy Buzsaki Buzsaki's book is disappointing in so much that it barely touches on the issue of consciousness, nor the possible involvement of the gamma synchrony. However, it is useful to the extent that few books discuss the existence of brain waves or oscillations in such detail. Much of the book concentrates on the oscillatory relationship between the pyramidal cells producing the excitatory neurotransmitter, glutamate, and the interneurons producing the inhibitory GABA neurotransmitter. These oscillations are related to the concept of self-organisation, which is itself fairly new in science. Biological systems are here viewed as complex, meaning not just complicated, but also involving non-linear relationships, and the amplifying or dampening of feed back loops. Neural systems that produce self-sustaining patterns of behaviour are called central pattern generators. Buszaki stresses that we are dealing with open complex systems far from equilibrium, sometimes called dissipative structures, which can progress themselves from disorganised to more organised. In this way, complicated protein structures can be built up by simple algorithmic steps in the variation of the four nucleic acids. Such systems can exchange energy, matter or entropy with the environment. This relates to non-linear dynamics and chaos theory. Buszaki stresses that brains should be understood in terms of interactions of the whole brain. Isolated bits of cortex in the laboratory fail to act spontaneously in the way that the brain does, and same problem is found in computer simulations of the brain. This appears to be a problem for Libet's idea of the 'mental field', which he suggests might be detected in experiments on isolated bits of cortex. Unexpected solutions emerge from non-linear equations, because the behaviour of a complex system cannot be predicted from its individual parts. Certain constituents of the whole gain dominance. This is described as an attractor or attractor property, and it decreases the degrees of freedom of the system. These systems could incorporate external influences into their future behaviour, and thus come to possess patterns for learning and growth. Excitatory & Inhibitory Influences P Thermodynamics as applied to closed systems and inanimate matter only possesses an excitatory interaction and uni-directional change, as a result of collisions with other particles or objects. Brains differ from such purely excitatory systems in containing both excitatory and inhibitory forces. This represents the difference between thermodynamic equilibrium systems destined to move towards greater and greater disorder, and the structure of the brain and biological tissue, which trends towards order. The latter derives its order from the balancing effect between the excitatory and inhibitory forces. Excitation by itself generates further excitation, moving the system involved only in the forward direction. But a ring of excitatory neurons can have inhibitory neurons in the same circuit. Such networks can self-organise complex properties. The presence of inhibition introduces hard to predict non-linear effects. In the brain, the relationship between pyramidal cells and interneurons governs cortical activity. All the main excitatory pathways have a matching group of interneurons. In physics, the balance of opposing forces, such as the forces of excitation and inhibition seen in the brain, often gives rise to rhythmic behaviour. Rhythms arise when positive and negative forces balance one another. The positive force drives the system away from a state, and the negative drives it back towards the original state. In the brain, the frequency of the oscillation depends on the duration of inhibition. Interneurons utilise GABA wherever they are located in the brain, and GABA is connected to the gamma synchrony, which arises in most brain structures. The gamma synchrony constrains axon potentials, so indirectly interneurons are seen as co-ordinating the timing of action potentials. Short oscillations in the gamma synchrony have been detected between distant sites processing different but related inputs. Resonance & Oscillation P Buzsacki sees resonance as a condition in which energy is fed into a system at the natural frequency of a system. The build up of energy in an object forces it to resonate. A sudden energy pulse can start the oscillation. An external force is supplied periodically at a frequency that matches the natural frequency of an object. Buzsaki views the neuron as a resonator-oscillator. The default state of cortical networks using glutamate and GABA is synchrony. Single neurons oscillate, because voltage-gated ion channels with opposite properties depolarise and hyperpolarise the membrane. Interneurons are the building blocks for network oscillators. Assemblies in the waking brain usually synchronise in the gamma range. The structure of the brain suggests an evolutionary preference for oscillation, which is the cheapest way of sustaining synchrony. 3.) Putting the Puzzle Together, towards a general theory of the neural correlates of consciousness James Newman Colorado Neurological Institute Journal of Consciousness Studies, 4, No. 2, 1997, pp. 100-21 Newmann suggests that orientation relative to the outer world, motor-sensory representation, and REM sleep converge on a core-conscious system called the extended reticular-thalamic activating system (ERTAS). The ERTAS has many projections with the cerebral cortex, and late 20th century research had increased knowledge of the connections between ERTAS and the major cognitive systems of the brain. It was noted as early as the mid 20th century that electrodes implanted into the thalamic system could alter the cortical EEG, either synchronising it, or desynchronising it. This area was associated with compulsion of attention and shifts in the reactivity of the nervous system. P The thalamus appears to be the region of the brain that drives alpha rhythms in the cortex. Stimulation of the diffuse thalamic nuclei at the 8-12Hz alpha frequency drives cortical waves, whereas higher frequency stimulation could abolish cortical waves. alpha frequency stimulation of the diffuse thalamic nuclei on one side produced the same frequency waves in the same nuclei of the opposite hemisphere. Later research suggests that the reticular nucleus is the main pacemaker for the alpha spindles, although the intralaminar cortex is also important for their distribution in the cortex. Other studies suggest that the intralaminar complex controls the so-called 40Hz oscillation found in both alert states and dreaming. Newman stresses that EEG rhythms have been unfashionable in neuroscience during much of the late 20th century. However, studies back to the 1940s demonstrate correlations between alpha and cognitive activities. Alpha is most prominent in the visual cortex. Alpha waves sweep periodically across the cortex and their speed depends on levels of arousal. It is suggested that alpha activity impacts on 40Hz gamma activity. Newman suggests that the ERTAS is central to the interplay of alpha and 40Hz. This oscillation is shown to travel from the front of the brain to the occipital lobe. Other studies suggest that this wave is involved in binding together the representations produced by different areas of the cortex. Thus spatially distributed neural actvities are bound in time. The succession of these bound moments could produce the stream of perceptions found in consciousness. Newman admits that the 40Hz synchrony idea does not deal with the problem of selectivity. We are only conscious of a tiny selection of the information in the brain, and somehow the rest has to be filtered out of consciousness. Newman thinks that the reticular nucleus is important in this respect. The nucleus is comprised of thin sheets of neurons on the left and right side of the thalamus. It projects mainly to the rest of the thalamus rather than the cortex. Nearly all the thalamocortical pathways pass through this area, which is in a good position for central control and representation of the information flow. The structure is seen as an array of tiny gates controlling the flow of neural information. Further experiments confirmed the role of the prefrontal in suppressing irrelevant stimuli and planning and monitoring goal orientated behaviour. At the same time, the posterior cortex is seen to stimulate selective attention. The thalamocortical circuit is thought to modulate which streams of information get attention. However, Newman does not think the modular approach to the brain is enough to deal with the problem of selecting information flows and also with the well-known binding problem of how unified consciousness is created. An article by J. Gray argues that the contents of consciousness are related to the limbic system, which surrounds the thalamus, and instantiates emotional processes. The prefrontal and the basal ganglia also have strong links to the limbic system. Parts of the frontal lobe, such as the cingulate, are seen as a kind of executive over the limbic, for working memory, inhibition of conditioned responses and goal directed attention. Gray points to the importance of understanding why there are differences between the conscious and unconscious and between the conscious present and the experience of memories. Things are more likely to be conscious if they vary to a significant degree from expectations. However, destruction of the limbic area does not oblate consciousness. The areas where this can happen are the reticular formation in the brain stem, the intralaminar complex in the thalamus and the parts of the cortex most strongly connected with this. 4.) Evidence supporting information processing in animals James A Donald, with references to David Deutch, T. Kanade and others The article starts by pointing out that animals can rapidly perceive objects, while classical computers cannot do this in polynomial time using any known algorithm (1-4). It goes on to say that that David Deutch (5) showed that quantum systems can solve problems that classical computers cannot solve in polynomial time. It admits, however, that Deutch did not claim that quantum computers could solve the problem of perception. Bialek (6-8) argued that perception is non-polynomial if tackled by an algorithm, but again he did not show that perception could be achieved by quantum computing either. Perception requires the brain to take in sensory data, and then find a category of object or event that could have given rise to that data. In this way, the brain can infer the nature of the external world. Animals do this very well, and simple animals appear to do it as well as more complex animals. In the past, this process was so much taken for granted, that it was only recognised as a problem when humans started to try programming perception into computers. However, the ease with which animals solve the problem of perception has sustained the belief that there must be an algorithm that can solve the problem quickly, but this has not been discovered. An algorithm that could achieve perception in polynomial time is called direct perception (DP) and works bottom up. However, these algorithms are not successful in constructing object descriptions (top level) from the immediate (bottom level) data. The writer quotes T. Kanade (4) as saying that this approach does not give unique solutions to perception problems. This claim is based on the polyhedral labelling problem. This is the problem of identifying contours within an image and labelling them as silhouette, concave surface, convex surface, groove or variation in surface radiation. Even with good quality local data, the bottom up approach to this problem does not yield a unique solution, and the approach is therefore insufficient for visual perception. Kanade found that it was necessary for the viewer to know what objects were likley to exist locally. Kanade performed an experiment in which he constructed an unlikely and unfamiliar object, and found that observers misperceived it even when it was right in front of them. It was apparent that light and shade were not by themselves sufficient for 3D perception. His conclusion was that we form hypothesises about objects, and to form a correct hypothesis, we need some knowledge of the object. Further to this, S. Ullman (9) and R.L. Gregory (10) provide examples where there is no local data or misleading local data, and the perception problem has to be solved from the top down. Gregory provided the well known example of the dalmatian dog against a spotted background, in which succesful perception of the image of the dog has to be based on a hypothesis rather than hard data. We find the same problem when a signal has to be extracted from background noise. The problem with a top-down algorithm for perception is that it has to search through an enormous number of possible matches. A classical computer would take far too long for the survival of an animal in its environment. As the problem involves numbers of objects moving at different speeds in different directions it becomes intractable for computers. But it is pointed out that animal brains solve this problem the whole time. The problem of robotics based on classical computers is that it has not been possible to move beyond systems that could only cope with a limited number of objects with few degrees of freedom. The complexity of the real world produces a combinatorial explosion, which swamps any classical computer. In the past it has been argued that it was not necessary to find an exact answer but just a good approximation, but when this approach was tried, the solutions were substantially wrong. The author argues that the failure of classical computing based on algorithms operating in polynomial time to explain the process of perception indicates that there must be a quantum mechanical process operating in the brain. (1) Tsotsos, J. (1987) IEEE computer society press, p. 346 (2) Kirousis, L & Papadimitriou, C. (1985) 26th annual symposium on the foundations of computer science, p. 175 (3) Kanade, T. (1980) Artficial Intelligence, 13, 279 (4) Kanade, T. (1981) Artficial Intelligence, 17, 409 (5) D. Deutch, Proceedings of the Royal Society (Lond) A400, (1985) 97 (6) Bialek, W (1986) Phys. Rev. Letters, 56, 996 (7) Bialek, W. & Sweitzer, A (1986) Phys Rev. Letters, 54, 725 (8) Bialek, W. (1987) Phys. Rev. Lett, 58, 741 (9) Ullman, S. (1980) Behaviour and brain sciences, 3, 373 (10) Gregory, R. The Intelligent Eye McGraw Hill Fröhlich, H. (1985) Physics Letters, 110A 480 Grimson, W (1990) Object recognition by computer MIT Press Jensen, R & Sanders, M. (1989) Phys Rev Lett, 63, 2771 Kendrick, K (1987) Science, 236 No. 4800, 448 (1990) New Scientist, 126 No. 1716, 62 5.) Psychological Investigations of Unconscious Perception Philip Merikle Dept. of Psychology, University of Waterloo Meredyth Daneman, Dept of Psychology, University of Toronto Journal of Consciousness Studies, 5, No 1, 1998, pp. 5-18 This paper discusses how it is possible to distinguish conscious and unconscious perception. These are shown to have qualitatively different effects. In a word experiment, subjects were shown words for 50 ms, which were not consciously perceived, and other words for 150 msecs, which were consciously perceived. After being shown these words, the subjects performed a memory test that demonstrated they were less successful with the words shown for 50 ms. A similar result was demonstrated with an experiment that involved naming a colour after, seeing a different colour either consciously or unconsciously. In the context of the debate about consciousness and in particular the ultra-reductionist ideas popularised by Daniel Dennett, the demonstration of the different effects of conscious and unconscious perception seems to undermine the argument that consciousness is simply brain processing, and has nothing of itself to add to unconscious brain processing. References:- Merikle, P. (1984) Towards a definition of awareness Bulletin of the Psychonomic Society, 22, pp. 449-50 Merikle, P. (1992) Perception without awareness American Psychologist, 47, pp. 792-5 Merikle, P. & Cheesman, J. (1987) Subliminal perception in Ed. Wallendorf, P. & Anderson, P. Advances in Consumer Research, Vol. XIV Association of Consumer Research Merikle, P. & Daneman, M. (1996) Memory for unconsciously perceived events Consciousness and Cognition, 5, pp. 525-41 Merikle, P. & Joordens, S. (1997) Measuring unconscious influences In Ed. Cohen, J. & Schooler, J. Scientific Approaches to Consciousness Erlbaum Merikle, P. et al (1995) Relative magnitude of unconscious influences Consciousness and Cognition, 4, pp. 422-39 Murphy, S. & Zajonc, R (1993) Affect, cognition and awareness Journal of Personality and Social Psychology, 64, pp. 723-39 Reingold, E. & Merikle, P. (1988) Perception without awareness Perception & Psychophysics, 44, pp. 563-75 Reingold, E. & Merikle, P. (1990) Study of unconscious processes Mind & Language, 5, pp. 9-28 6.) Space, Time and Consciousness John Smythies Journal of Consciousness Studies Vol 10 No 3 (2003) p. 47 The direct realist theory of perception states that we are directly aware of external physical objects. This was a view supported by many 20th century philosophers. Its main opponent was the scientific representative theory in which phenomenal objects and their space are creations of the central nervous system. The article claims that recent experiments, notably Smythies &Ramachandran (1998), (1) Ramachandran and Blakeslee (1998), (2) Kovacs et al (1996) (3) and Yarrow et al (2001) (4) resolve the controversy in favour of the scientific representative theory. Thus perception is the end result of a probability based computation. The previous direct realist theory held that the objects experienced only existed externally, but under scientific representative theory, they have to have their own phenomenal space. This is related to the fact that knowledge and experience of things are seen to be different in modern neuroscience. Thus in agnosia there is normal vision without knowledge about the objects seen, while in blindsight there is knowledge with consciousness. The same applies to awareness of the body, where phenomena such as phantom limbs demonstrate that the model of the body constructed by the brain may be different from the external reality. It is suggested that phenomenal space and physical space are different, they may be causally related but external to one another. (1) Smythies J. & Ramachandran V, An empirical refutation of the Direct Realist Theory of Perception Inquiry 40 pp 437-8 (2) Ramachandran & Blakeslee, Phantoms in the Brain (1998) (3) Kovacs et al, When the brain changes its mind Proceedings of the National Academy of Sciences USA 93 pp. 508-11 (4) Yarrow K. et al Illusory perceptions of space and time Nature 414 pp 302-5 7.) R. Kentridge & C. Heywood Dept. of Psychology, Durham University The Status of Blindsight Journal of Consciousness Studies, 6, No. 5, 1999 The term ‘blindsight’ was coined by Weiskrantz for the phenomenon in which subjects with some degree of damage to the primary visual cortex retain the ability to detect and discriminate visual stimuli, while denying any consciousness of the stimuli. The subjects particularly show ability to access information in a two-alternative forced-choice procedure, which is intended to exclude subjectivity as to what can and can’t be discriminated. The finding has important implications as to the nature of consciousness as something distinct from the non-conscious parts of the brain, and reductionists such as Daniel Dennett has come up with unconvincing attempts to circumvent its implications. It has implications for consciousness being something different from the mere reception of stimuli from the outside world. In discussions of blindsight, the conventional assumption has been that visual discrimination was preserved by using another non-conscious route that avoided the damaged visual cortex. Attempts have made to disprove this assumption, but the authors seek to defend the original view. The critics had suggested that blindsight was just a degraded version of normal vision, and that it was based on islands of functioning cortex within a damaged striate cortex, rather than a separate undamaged pathway. If this could be shown to be the case, it would appear to remove the threat to the mainstream reductionist stance on consciousness. The first argument may be that the subject is biased against reporting a visual stimuli. However, the two alternate forced-choice task, where the subject has no separate knowledge of the right answer gets round this particular objection (Azzopardi & Cowey, 1997)(1). Studies showed that in normal subjects, the same mechanisms subserved conscious reports and forced-choice discrimination, while in subjects with damaged cortex the mechanisms were different. A later study (Kentridge et al, 1999)(2) showed that there were differences between the good hemisphere of the brain and the damaged hemisphere in a blindsight subject used in the previous study by Azzopardi. A neuroimaging study by Stoerig et al (1998)(3) on a blindsight patient showed no response to visual stimuli in the damaged cortex but activity in the extrastriate cortex, which did not contain the normal pathway. They did not find elements of portions of surviving functional cortex in the striate. Fendrich et al, (1992)(4) did find such evidence, but it does not appear to have been enough to support extensive residual vision. The studies suggest to the authors that visual consciousness depends on an intact striate cortex, but detection and discrimination do not. Some studies do show that blindsighters have some degree of conscious awareness of movement or flickering from a stationary light source, but this does not disprove that the basic blindsight discrimination of stationary objects is suggested by recent studies to use a different pathway from conscious awareness. (1) Azzopardi, P & Cowey, A (1997) Is blindsight like normal near-threshold vision? Proceedings of the National Academy of Sciences USA, 94, pp. 14190-4 (2) Kentridge, R., Heywood, C. & Weiskrantz, L. (1999) Effects of temporal cueing on residual visual discrimination in blindsight Neurpphysiologia, 37, pp. 479-85 (3) Stoerig et al (1998) Magnetic resonance imaging of a blindsight patient Neuroreport, 9, pp. 21-5 (4) Fendrich et al, 1992 Residual vision in a scotoma: Implications for Blindisight Science, 258, pp. 1489-91 Block, N. (1995) On a confusion about a function of consciousness Behavioural and Brain Sciences, 18, pp. 227-87 Holt, J. (1999) The use of blindsight in debates about qualia Journal of Consciousness Studies, 6 (5), pp. 54-71 Marzi, C. (1999) Why is blindsight blind? Journal of Consciousness Studies, 6 (5), pp. 12-18 Pribram, K. (1999) Brain and the composition of conscious experience Journal of Consciousness Studies, 6, (5), pp. 12-18 Riddoch, G. (1917) Dissociation of visual perceptions Brain, 40, pp. 15-57 Sahraie, A. & Weiskrantz, L. (1997) Conscious and unconscious processing of visual signals Proceedings of the National Academy of Science USA, 94, pp. 9406-11 Stoerig, P. & Cowey, A. (1997) Blindsight in man and monkey Brain, 120, pp. 535-59 Weiskrantz, L. (1986) Blindsight: A case study and implications Oxford University Press Weiskrantz, L. (1997) Consciousness Lost and Found Oxford University Press Zeki & ffytche, D. (1998) The Riddoch syndrome Brain, 121, pp. 25-45 Sanders, M. & Weiskrantz, L. (1974) “Blindsight”: Vision in a field defect Nine Lives + One: Hello Kitty!8.) Jason Holt University of Manitoba Blindsight in debates about qualia Journal of Consciousness Studies, 6, No. 5, 1999 pp. 54-71 Holt’s paper is mainly interesting for its description of how blindsight might seem to a patient. Beyond this the piece gets diverted into a discussion of the various ways in which philosophers such as Dennett and others have tried to wriggle out of the implications of blindsight. The author asks us to imagine ourselves waking up in hospital and being told that we have suffered damage to the visual cortex. After this initial bad news, we are relieved to realise that we can see the hospital ward in a superficially normal way. However, on being asked by the doctor, you realise that you can’t see the door to your right, and the right hand side of your vision seems to have collapsed. Functionally, you can correct for this and see the door by moving your head, but you don’t have the normal width to your field of vision. However, when the doctor asks you to guess the nature of things that he places in the lost part of your field of vision, you are surprised by the frequency of correct guesses, despite having no conscious knowledge of what lies there. Holt remarks on the lack of use that has been made of the knowledge of blindsight, and this may be assumed to be connected to the persistent attempts to marginalise it. Blindsight is seen as relevant to the whole question of qualia. Qualia are often defined as the raw feel of experiences, with the redness of red being the classic example. Philosophers such as Dennett have tried to argued that qualia do not exist, but Holt sees blindsight as an argument in favour of the existence of qualia. Holt views blindsight as the dissociation of visual function from visual experience. Holt indicates that some philosophers have grossly exaggerated the abilities of blindsight patients as if the patients visual function was more or less intact. This is not the case. Patients have to be prompted in the first place, and they only obtain results that are better than chance, rather than the level of performance than would be expected from normal vision. Holt quotes Dretske(1) as saying that people with conscious experience of vision can do things that those without cannot, presumably such as knowing that the stimuli is there in the first place, without a second person prompting, and this is an obvious useful function of conscious vision. It might further be said that an organism that relied on others to warn it of external stimuli, such as the presence of a sabre tooth tiger, would be at a striking evolutionary disadvantage. Much of the middle part of the article is taken up with the discussion of a somewhat implausible thought experiment that seems to stem from Dennett. This is the idea of the ‘superblindsighter’, who is trained to such a degree that his visual function is as good as a person with normal. Then it is suggested that his/her experience would be the same. The objection is not the rather far-fetched nature of the experiment, but the fact that even it were to happen, it would make no difference whatsoever to the experience and implications of the normal blindsight. Holt returns to a more interesting question, which is the distinction between the threshold or limit of vision for people with normal sight and the unconscious visual knowledge available to blindsighters. The main distinction is that viewers at the threshold of vision can report on the poor quality of the viewing conditions and the process they are going through to determine what they are actually seeing. The blindsighters deny having any type of viewing conditions or visual information for them to discriminate, they merely make a guess. The normal viewers have undamaged visual cortex, and the state of their cortex correlates to their having a different experience from the blindsighters. In his final remarks, Holt notes that philosophers continue to try and read conscious activity into blindsight, presumably because of the adverse implications for reductionist views of consciousness, but the scientific record does not support this. (1) Dretske, F. (1995) Naturalising the Mind MIT Press Block, N. (1995) On a confusion about a function of consciousness Behavioural and Brain Sciences, 18, pp. 227-47 Carruthers, P. (1989) Brute Experience Journal of Philosophy, 86, pp. 258-69 Flanagan, O. (1992) Consciousness Reconsidered MIT Press Nagel, T. (1974) What is it like to be a bat? Philosophical Review, 83, pp. 435-50 Searle, J. (1983) Intentionality Cambridge University Press Stoerig, P. and Cowey, A. (1997) Blindsight in man and monkey Brain, 120, pp. 552-9 Weiskrantz, L. (1986) Blindsight: A case study and implications Clarendon Weiskrantz, L. (1997) Consciousness Lost and Found Oxford University Press Weiskrantz, L. Barbur, J. & Sahraie. A (1995) Parameters affecting conscious versus unconscious visual discrimination with damage to the visual cortex Proceedings of the National Academy of Science, 92, pp. 6122-6 9.) i of the vortex Llinas, R. New York School of Medicine MIT Press ISBN 0-262-12233-2 Llinas argues that much of the activity of the brain is intrinsic or self-generated, with sensory input seen as coming in on top of, and modulating, existing brain activity. The brain is suggested to be a closed system, with sensory input being more about specifying cognitive states than actual information. In this system, sensory cues are incorporated into on-going cognitive states. The more conventional image has been of a passive brain only performing when it receives sensory input. The author’s major emphasis is on the electrical oscillations in the brain. He describes how the electrical potential across cell membranes is subject to an intrinsic small oscillation. He likens this to gentle ripples on a pond. On occasion, much larger fluctuations arise. These are known as action potentials, and form the basis of communication between neurons. The intrinsic oscillation of a neuron can influence its responsiveness to incoming signals. Llinas regards electrical oscillation as the glue that allows the brain to organise itself. He stresses that simultaneity of neuronal activity is pervasive in the brain, and that this derives from neuronal oscillation. It is suggested that neurons that display rhythmic oscillation may entrain each. Neurons which oscillate in phase (with the peaks and troughs at the same time) can support simultaneity of operation. Llinas uses the example of cicadas that chirp in rhythmic unison because they have an internal clock, which is an intrinsic oscillator. Fluctuations within this rhythm constitute information that is available to individuals or cells remote from one another. Oscillation in phase so as to make scattered elements work together in amplified fashion is known as resonance. A group of neurons that resonate with each other may also resonate with another group that are in an area of the brain remote from them. However, not all neurons resonate at all times. Neurons are able to switch in and out of the oscillatory mode and this allows resonance to occur transiently among different group of neurons. Cells receiving new sensory information may start to resonate with other groups of neurons. Llinas’s own work has uncovered the existence of intrinsic neuronal oscillations and the ionic currents that generate them(1). This is related to membrane conductance, and it has been shown that neurons are capable of generating action potentials without the presence of external input(2). P Llinas argues that the brain is a closed rather than an open system. By an open system, he means one that is a reflex that merely receives, processes and outputs data, rather than contributing anything of its own(3). The closed-system hypothesis that Llinas favours argues for a mainly self-activating system generating its own intrinsic images. Sensory input only gains significance as a result of the pre-existing state of the brain. Llinas considers that our understanding of the external world arises from the juxtapositioning of internally generated images with the sensory properties of the external world. The internal images occur through intrinsic properties of the brain. Llinas develops this idea as an explanation of the process of dreaming. Dreams derive from intrinsic activity of neurons. In REM sleep, the brain is not receptive to sensory signals, but only to its intrinsic activity(4). Studies by Llinas himself(5) show that 40 Hz activity is present both in the awake condition and in REM sleep, but is greatly reduced during deep sleep, which is characterised by delta waves. In the waking state, auditory signals produced a change in the 40 Hz oscillation, but in REM sleep, there is no change in the oscillation. The significant thing is that in REM sleep the brain is so adjusted as to carry on with its intrinsic or internal activity, and to ignore sensory input. Interneurons are particularly important in Llinas’s view of the brain. An interneuron is defined as any neuron that does not communicate with the outside world, but only exchanges information with other neurons. The interneurons serve to distribute sensory input to various components of the brain. The interneurons are thus in a position to influence a large number of other neurons and in effect ‘steer with multiple reins’. A particularly sensory input may stimulate a relatively small number of cells, which may activate another small number of interneurons, which then go on to have widespread effects. Interneurons are found throughout the central nervous system and particularly in the thalamocortical areas. Llinas’s emphasis on the intrinsic or internal activity of the brain also leads to him being opposed to the tabula rasa view of the brain as a blank slate at birth ready to be entirely determined by subsequent conditioning. In support of his view, he quotes studies(6) in which newborn monkeys respond differently to lines of different orientation, although they had never previously seen lines. Llinas emphasises the importance of gap junctions in the operation of the brain. In addition to the synaptic connections between cells, which involve a neurotransmitter crossing a 20 wide nanometre gap, the gap junctions offer a quicker and more direct connection. Unlike the synapses that require a chemical signal, the gap junctions allow ions to move from one cell to the next, and this constitutes a form of signal transmission that is quicker than the synaptic kind. Moreover, cells that receive such an ion based signal may be activated to fire an action potential. This can result in rapid and synchronous firing of interconnected cells. This allows a group of neurons to fire synchronously, as a result of which other more distant groups may resonate with them in a synchronous signalling pattern. This rapid electric coupling produces simultaneity between many neurons or in Llinas’s words creates the ‘roar of the masses’ rather than a ‘voice in the wilderness.’ This is effectively Llinas’s solution to the binding problem. The synchronous activity of group of neurons at locations remote from one another in the brain combines information from disparate sources and modalities. Llinas suggests that the effect of resonance is to bind together the spatial related processing of different groups of neurons at the same time. He implies rather than says that this accounts for the ‘now’ or ‘present moment’ sensation that is so much a part of consciousness, but which conflicts with special relativity. Llinas points to the example of the electric shocks delivered by electric eels. The motor neurons involved in delivering the shock have axons of varying length depending on their distance from the point from which the shock is administered, arranged so that the charges are delivered simultaneously, without which they would be of little effect. In a similar way, activity in the central and peripheral parts of the human retina is almost synchronous when it subsequently arrives at the thalamus. We have to be specific about what Llinas appears to be trying to say here. He is not claiming that electrical oscillations are connected or correlated with qualia in some way but that they are the same thing as qualia. But this gives rise to the problem as to why it is only the electrical patterns in the brain, and only some of those that are conscious and have subjective experience. Elsewhere, he has given a good description of how the electric potential across the cell membrane works in principle in the same way as a battery, but Llinas does not presumably think that batteries are conscious. While brain activity is no doubt related to conscious, there is a requirement to show why these functions produce the property of consciousness or qualia not found elsewhere in the physical universe. Llinas could have attempted an explanation based on complexity or information processing. As far as he will go in this direction is to argue that the process of muscular movement is somewhat similar to the process of producing sensations in the brain. He is probably right in saying that the physical mechanisms are similar, but this does not really bring us any closer to why one class of these mechanisms is especially involved with subjective sensory experience. References:- 1.) Llinas, R. (1988) - Insight into the central nervous system function - Science, 242, pp. 1654-64 2.) Hutcheon, B. & Yarom, Y. (2000) - Intrinsic frequency preferences of neurons - Science, 242, pp. 1654-64 3.) Llinas, R. (1987) - Mindness - In: Mind Wave, Eds. Blackemore, C. & Greenfield, S. 4.) Llinas, R. & Pare, P. (1991) - Dreaming and wakefulness - Neuroscience, 44, pp. 521-35 5.) Llinas, R. & Ribary, U. (1993) - 40 Hz oscillation characteristics of dream states in humans - Pub. of the National Academy of Sciences, USA, 90, pp. 2078-81 6.) Hubel, D. & Wiesel, T. (1979) - Orientation columns in the striate cortex - Journal of Comparitive Neurology 7.) Eckhorn, R. et al (1989) - Coherent oscillations: A mechanism of feature linking in the cortex - Biol. Cybern, 60, pp. 121-30 8.) Gray, C. & Singer (1989) - Stimulus specific oscillations in orientation columns - Proceedings of the National Academy of Science, USA, 86, pp. 1698-1702 9.) Gray et al (1989) - Inter-columnar synchronisation - Nature, 338, pp. 334-7 10.) Llinas, R et al (1991) - Intrinsic oscillatory activity - Proceedings of the National Academy of Science, USA, 88, pp. 897 11.) Steriade, M. et al (1991) - 20-40 Hz oscillations in the thalamocortical system - Proceedings of the National Academy of Science, USA, 88, pp. 4396 12.) Whittington, M. et al (1995) - Synchronised oscillations in interneuron networks - Nature, 373 13.) Steriade, M. & Amzica, T. (1996) - Intracortical and corticothalamic coherency of fast oscillations - Proceedings of the National Academy of Science, USA, 93, pp. 2533-38 14.) Steriade, M. et al (1996) - Synchronicity of 30-40 Hz oscillations in the thalamocortical network - Journal of Neuroscience, 16, pp. 2788-2808 10.) New Scientist 12/05/07 Amanda Gefter Andrew Jordan of the University of Rochester has come up with a new take on the Schrödinger cat problem. Superposition is central to the problem. Experiments prove that superpositions do occur. But they are not apparent in the classical world, and there is a problem in deciding how and why things move from a superpositioned state to a single defined state. Jordan, working with Alexander Korotkov of the University of California claims that wave function collapse is not an instantaneous process. (Physical Review Letters, vol 97, p. 166805). Like other processes in nature it is claimed to take a finite time. In a UC experiment (Science, vol 32, p. 1498). The superposition is here shown to collapse in stages. A further experiment will involve a Schrödinger cat type situation with a loop of superconducting wire put into superposition. A measurement starts to push the loop towards one of two superpositioned states, equivalent to cat alive or cat dead. The level of energy can be adjusted so as to create the possibility that a qbit can tunnel through a barrier. If it fails to do this, it creates the possibility that the qbit it is at a low energy level. Repetition of this experiement could increase knowledge of the ‘cat’s’ state bit by bit always with the risk that it will tunnel through. If it does not the process is reversible. One feature of this experiment is that it could disprove a version of decoherence theory that claims that the wave function never collapses but that the information about it gets lost once a particle is entangled with the larger environment. This is because the so-called weak measurement indicated by the proposed experiment shows the particle being drawn towards one or other of the other definite conclusions. |
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