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Can Transactions explain Conscious Intentional Will? The Central Enigma of Consciousness A state of the research report on the hard problem and quantum consciousness.

Principal areas in the human brain Redrawn from Scientific American. Although the brain does not display overt sexual polarization, there are a host of subtle differences from the cellular to the neurosystems level. The Enigmatic Three Pound Universe The brain is the gateway to the deepest enigma of modern science - subjective consciousness and the paradox of free will in a physical universe. It thus holds all the trump cards in the final frontier of scientific discovery, whose surface has only so far barely been scratched.

Although researchers in the reductionist paradigm of artificial intelligence and related areas have sought to see the brain as simply a glorified computer, there is little about the brain which in any way resembles the digital device we have invented to carry out our computational tasks.

For a start, the brain is a very bad computer. We have a memorizable digit span of only about seven figures and find even simple arithmetic calculations difficult without the aid of a pencil and paper. By contrast, we are able to remember whether or not almost a million different scenes are familiar or have been seen before, hinting at an almost unlimited 'environmental' memory capacity. This kind of contrast is reflected in everything we know about the anatomy and physiology of the brain.

Although the first nervous system to be studied, the giant axon potential of the squid, does have an apparently discrete response, it is in fact a pulse coded analogue signal which is being transferred, whose rate of discharge is proportional to the continuous depolarization at the cell body.

When we come to examine even the simplest nervous systems such as the ganglia of the sea slug aplysia we find that it is the 'silent' analogue cells with continuous potential changes which act as the organizing centres for behavior, with the pulse coded cells merely acting as long distance relays.

Similarly when we look at brain waves in the cortical electroencephalogram or EEG, we find so-called 'brain waves' such as the a, b, and g rhythms, which are not only continuous changes but broad spectrum vibrations more characteristic of chaos or edge of chaos dynamics, than the exact resonances of an ordered dynamical system.

In complete contrast to the essentially serial nature of the digital computer despite attempts to introduce some relatively trivial parallel architecture, the overweening paradigm for the central nervous system is 'parallel distributed processing'. Generally there are as little as 10 synapses between input and output despite there being between and neurons and around synapses in the cerebral cortex. Central nervous networks are also intrinsically fractal in architecture because of the many-to-many nature of connections arising from the tree structure of a neuron's dendrites and axons.

The combination of this many-to-many fractal architecture and the wavelike nature of neuronal transmissions is a key concept in Karl Pribram's description of the 'holographic brain' Pribram R Phase-locking can mark out populations of cells sharing a common 'experience' or process from other randomly related stimuli. This 'holographic' view is supported by much physiological evidence. Phase beats are the basis of the quantum uncertainty relationship p implying a potential connection.

The complementarity between continuous wave coherence and the discrete local information carried to a given neuron or synapse is deeply similar to wave-particle complementarity. Another important complementarity is provided by the reliance many neuronal connections make on non-linear processes and diverse chemical neurotransmitters to transduce information across the synaptic junction. Neurotransmitters come in a variety of types both excitatory and inhibitory of both temporary short-term effect and of potentially permanent effect in the long-term potentiation or LTP involved in memorization.

Despite the development of sophisticated techniques for visualizing brain activity such as those for speech left , and ingenious work tracing connectivity of activity between neurons in the cortex such as that establishing distinct parallel processing regions for colour and movement in vision right, Zeki R , no objective brain state is equivalent to a subjective conscious experience. The difficulty of bridging this abyss is called the hard problem in consciousness research Chalmers R If we consider what brains actually have to do to ensure our survival we can see at once why this might be the case.

Many problems which simulate environmental decision-making are computationally intractable. A good example is the traveling salesman problem - finding the shortest distance around n cities, which to be computed classically requires tracing every possible route which grows super-exponentially as n-1!

A gazelle standing at a forking in the paths to a water hole would become stranded and eaten by the tiger if it had to resort to classical computation. Moreover many of these problems are prisoners' dilemma problems in which the 'opponent' is forever changing their strategy, making computation historically out-of-date. The tiger may for example choose the safest looking path, or switch unpredictably. Finally there is no single answer to many of these decisions, most of which have many possible outcomes rather than one computational solution, which is why we have evolved to have free choice in the first place.

The way the brain appears to have evolved to solve this problem is to engage a kind of Darwinistic internal ecosystem of resonating excitations which are chaotic in time and enable holographic wave processing in 'space' across the cortex.

In a dynamic brain, phases of chaos are essential, both to provide the sensitivity on initial conditions of chaos which is essential to respond acutely sensitively to the outside world, and to provide the unpredictable, seemingly random, variation required to prevent the system getting caught in the rut of one overwhelming 'attractor' - the nemesis of all ordered systems.

The overall architecture of the mammalian brain consists of an overarching cortex acting as a modifier of resonant excitations ascending from mid-brain centres in the thalamus and deeper basal brain centres driving phases of alertness, sleep and dreaming. The cortex has a modular parallel architecture with sensory and cognitive processing for different modes occurring in parallel in distinct centres. For example upward of 24 centres have been identified for vision, handling colour and motion in separate parallel processing units.

These parallel differentiations extend to specific types of feature such as separate regions for recognition of different human faces and of human facial emotional expressions. Each of these modular regions is in turn organized into a series of columns on a scale of about 1mm which act as feature detectors for example of lines with a specific orientation.

Processing occurs in three to five distinct cellular layers comprising a mix of excitatory and inhibitory cells forming feedback loops enabling processing such as contrast enhancement.

Typical cortical structures centre are a combination of five-layers of neurons left , each composed into columnar modules about 1mm on the cortical surface. Such modules are sensitive to stimuli such as a line of a given orientation. Blob centres in layer II are also shown p Although specific sensory area have functional and anatomical specializations neural plasticity can enable changes of functional assignment indicating common principles throughout the cortex. Ocular dominance columns right for left or right eye illustrate functional columnar architecture.

Given only some 30, protein-producing structural genes in the human genome, there are far too few to genetically determine exact details of brain structure on a cell-to-cell basis in a hard-wired manner. The best specificity that can be managed consists of general rules of synaptic growth between specific cell types in different areas, which is what we see in cell migration and synaptic contact during development.

In the visual system, the developing retina first begins to manifest chaotic excitation. Only then does differentiation in the lateral geniculate become evident and in turn from its dynamical excitation the visual cortex becomes differentiated for pattern recognition. Thus while genes may be able to encode interconnections between specific excitatory and inhibitory cell types and to promote growth of axons between cell types in different regions, the central nervous system depends on dynamical excitation to establish the developed architecture of its connections.

Genetic determinism is thus a myth. Genes create developmental potentialities, which are shaped by excitation in both development and the environment. Nature thus utilizes nurture. This dynamical basis for development is reflected in cortical plasticity, where emerging changes in function can result in regions previously assigned to one function taking over another.

Examples are changes in binocular optical dominance when one or other eye is covered, through to the phenomenon of the phantom limb, where regions assigned to a removed limb become invaded by other functional areas, resulting in sensory confusion, and the illusion that the limb is still present, perhaps even painful. Changes also take place during higher learning such as becoming fluent in a new language.

These kinds of specialization and development are reflected in the modular organization of the cortex we see in positron emission tomography PET and functional magnetic resonance imaging fMRI studies of the language and perceptual areas of the cortex. The cerebral cortex is divided between front and rear broadly into motor and perception areas by the Sylvian fissure, which divides frontal regions and the motor cortex from the somatosensory touch and other sensory areas, including vision and hearing.

The broadly sensory 'input' and associated areas of the parietal and temporal cortices are complemented by frontal and pre-frontal areas which deal with 'output' in the form of action rather than perception and with forming anticipatory models of our strategic and living futures. These active roles of decision-making and 'working memory', which interact from pre-frontal cortical areas complement the largely sensory-processing of the temporal, parietal and occipital lobes with a space-time representation of our 'sense of future' and of our will or intent.

Another motif with undertones of sexual complementarity p is the fact that we possess two left and right hemispheres which are to all purposes separate cortices linked only by massive underlying parallel circuitry in the corpus callosum. Although much has been romanticized about our left and right brains in terms of the contrast between intuition and structured reasoning, and some people almost banish the sub-dominant hemisphere to inarticulate zombie-like status, there is abundant evidence for a degree of complementarity between foci in the two hemispheres, for example analytic language versus creative expression, linguistic versus musical perception, and holistic versus mechanical modes of thought.

Such lateralization has also been associated with the complementarity between different types of mathematical reasoning, the continuous ideas of topology p and calculus being associated with the right hemisphere, by contrast with the discrete operations of algebra p hypothetically assigned, like language to the left. The two key language areas, Broca's frontal area for verbal speech fluency and Wernicke's temporal area for semantic resolution are traditionally on the left.

However one should note that lateralization is more prominent in males and that females have generally greater facility with language, despite their language processing being less lateralized p As of a slew of reseach has emerged, which shows that handedness is not just confined to humans, but extends widely throughout the 'bilaterally-symmetric' animal kingdom spanning arthropods and vertebrates.

Vetrebrates from fish through birds to mammals are liable to hunt or forage with their right eyes and look for predators with their left, which allows brain areas in each cortex to become better adapted at serving each of these challenges. Prisoner's dilemma game theory simulations show that the safety in numbers when many members of a species adopt the same asymmetric strategy is offset to the best advantage of all players when there is a smaller subpopulation adopting the contralateral strategy thus confusing th epredator without becoming a primary target Southpaws: The cortex itself is relatively inert in electrodynamical terms and may actually form a complex boundary constraint on the activity of more active underlying areas such as the thalamus, which contains a number of centers with ordered projections to and from corresponding areas of the cortex.

Characteristic of the mammalian brain is also the peripheral 'limbic' system forming a loop around the periphery of the cortex, connecting primary frontal regions mediating integrated decision-making in action and the emotional centres of the cingulate cortex with the flight and fight centre of the amygdala, the long-term sequential memory of the hippocampus and basic bodily and sexual functions of the hypothalamus in great feedback loops whose dynamics are characteristic of changes in emotional mood and its influence on our outlook and strategic direction.

The limbic system lies at the core of mammalian emotionality from fear and anger to love and our capacity to transcend immediate genetic determinacies. The overall dynamical organization of the mammalian brain is also evident in the major ascending distributed pathways from the basal brain using specific neurotransmitters such as dopamine, noradrenaline and serotonin, which modify alertness and light and dreaming sleep see New Scientist 28 Jun 29 and are also modulated by psychedelics such as psilocin and mescaline.

These fan out from basal brain centres into wide areas of the cortex connecting into specific cortical layers where processing is taking place. The large pyramidal cells which coordinate output thus have several different types of neurotransmitter modulating their excitation, both in an excitatory and an inhibitory manner. Walter Freeman's model of chaos in sensory perception Skarda and Freeman R, Freeman R gives a good feeling for how dynamical chaos p could play a key role in sensory recognition, for example, when a rabbit sniffs the air for a strange smell.

The olfactory cortex enters high energy chaotic excitation forming a spatially correlated wave across the cortex, causing the cortex to travel through its space of possibilities without becoming stuck in any mode. As the sniff ends, the energy parameter reduces, carrying the dynamic down towards basins in the potential energy landscape.

If the smell is recognized the dynamic ends in an existing basin, a recognized smell, but if it is a new smell, a bifurcation eventually occurs to form a new basin a new symbol is created constituting the learning process. The same logic can be applied to cognition and problem solving in which the unresolved aspects of a problem undergo chaotic evolution until a bifurcation from chaos to order arrives at the solution in the form of a flash of insight - "eureka!

Freeman's model of olfaction is represented a by differing distributed excitations on the cortex. Eddington pointed out that the uncertainty of position of a vesicle is approximately the width of the membrane. Indicators of the use of chaos in neurodynamics come also from measurements of the fractal dimension p of a variety of brain states, from pathology through sleep to restful wakefulness. Recordings from single neurons, and from other cells such as the insulin-releasing cells of the pancreas confirm their capacity for chaotic excitation.

The organizers of neural systems are also frequently non-pulse coded 'silent' cells capable of continuous non-linear dynamics. Despite the approximate linearity of the axonal discharge rate with depolarization, virtually all aspects of synaptic transmission and excitation have non-linear characteristics capable of chaos and bifurcation.

For example the acetyl-choline ion channel has quadratic concentration dynamics, requiring two molecules to activate. Many cells have sigmoidal responses providing non-linear hyper-sensitivity and are tuned to this threshold. The electroencephalogram itself although nominally described as having brain rhythms such as alpha, beta, gamma and theta actually consists of broad band frequencies, rather than harmonic resonances, consistent with a ground-swell of chaotic excitation King R , R , R , R Broadly speaking neurodynamics is "edge of chaos" p in the time domain and parallel distributed in a coherent 'holographic' manner Pribram spatially.

While artificial neural nets invoke thermodynamic 'randomness' in annealing to ensure the system doesn't get caught in a sub-optimal local minimum, biological systems appear to exploit chaos to free up their dynamics to explore the 'phase space' of possibilities available, without becoming locked in a local energy valley which keeps it far from a global optimum.

Into this picture of global and cellular chaos comes another scale-linking property, the fractal p nature of neuronal architecture and brain processes and their capacity for self-organized criticality at a microscopic level. The many-to-many connectivity of synaptic connection, the tuning of responsiveness to an arbitrarily sensitive 'sigmoidal' threshold, and the fractal architecture of individual neurons combine with the sensitive dependence of chaotic dynamics p and self-organized criticality p of global dynamics to provide a rich conduit for instabilities at the level of the synaptic vesicle or ion channel to become amplified into a global change.

The above description of chaotic transitions in perception and cognition leads naturally to critical states in a situation of choice between conflicting outcomes and this is exactly where the global dynamic would become critically poised and thus sensitive to microscopic or even quantum instabilities.

Evidence for complex system coupling between the molecular and global levels. Stochastic activation of single ion channels in hippocampal cells a leads to activation of the cells c.

Activation of such individual cells can in turn lead to formation of global excitations as a result of stochastic resonance d. The brain is thus capable of supersenstivity to the instabilities of the quantum milieu Eccles R Chaotic excitability may be one of the founding features of eucaryote cells King R , R The Piezo-electric nature and high voltage gradient of the excitable membrane provides an excitable single cell with a generalized quantum sense organ.

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Can Transactions explain Conscious Intentional Will? The Central Enigma of Consciousness A state of the research report on the hard problem and quantum consciousness. Principal areas in the human brain Redrawn from Scientific American. Although the brain does not display overt sexual polarization, there are a host of subtle differences from the cellular to the neurosystems level.

The Enigmatic Three Pound Universe The brain is the gateway to the deepest enigma of modern science - subjective consciousness and the paradox of free will in a physical universe. It thus holds all the trump cards in the final frontier of scientific discovery, whose surface has only so far barely been scratched. Although researchers in the reductionist paradigm of artificial intelligence and related areas have sought to see the brain as simply a glorified computer, there is little about the brain which in any way resembles the digital device we have invented to carry out our computational tasks.

For a start, the brain is a very bad computer. We have a memorizable digit span of only about seven figures and find even simple arithmetic calculations difficult without the aid of a pencil and paper. By contrast, we are able to remember whether or not almost a million different scenes are familiar or have been seen before, hinting at an almost unlimited 'environmental' memory capacity.

This kind of contrast is reflected in everything we know about the anatomy and physiology of the brain. Although the first nervous system to be studied, the giant axon potential of the squid, does have an apparently discrete response, it is in fact a pulse coded analogue signal which is being transferred, whose rate of discharge is proportional to the continuous depolarization at the cell body. When we come to examine even the simplest nervous systems such as the ganglia of the sea slug aplysia we find that it is the 'silent' analogue cells with continuous potential changes which act as the organizing centres for behavior, with the pulse coded cells merely acting as long distance relays.

Similarly when we look at brain waves in the cortical electroencephalogram or EEG, we find so-called 'brain waves' such as the a, b, and g rhythms, which are not only continuous changes but broad spectrum vibrations more characteristic of chaos or edge of chaos dynamics, than the exact resonances of an ordered dynamical system. In complete contrast to the essentially serial nature of the digital computer despite attempts to introduce some relatively trivial parallel architecture, the overweening paradigm for the central nervous system is 'parallel distributed processing'.

Generally there are as little as 10 synapses between input and output despite there being between and neurons and around synapses in the cerebral cortex. Central nervous networks are also intrinsically fractal in architecture because of the many-to-many nature of connections arising from the tree structure of a neuron's dendrites and axons. The combination of this many-to-many fractal architecture and the wavelike nature of neuronal transmissions is a key concept in Karl Pribram's description of the 'holographic brain' Pribram R Phase-locking can mark out populations of cells sharing a common 'experience' or process from other randomly related stimuli.

This 'holographic' view is supported by much physiological evidence. Phase beats are the basis of the quantum uncertainty relationship p implying a potential connection.

The complementarity between continuous wave coherence and the discrete local information carried to a given neuron or synapse is deeply similar to wave-particle complementarity. Another important complementarity is provided by the reliance many neuronal connections make on non-linear processes and diverse chemical neurotransmitters to transduce information across the synaptic junction. Neurotransmitters come in a variety of types both excitatory and inhibitory of both temporary short-term effect and of potentially permanent effect in the long-term potentiation or LTP involved in memorization.

Despite the development of sophisticated techniques for visualizing brain activity such as those for speech left , and ingenious work tracing connectivity of activity between neurons in the cortex such as that establishing distinct parallel processing regions for colour and movement in vision right, Zeki R , no objective brain state is equivalent to a subjective conscious experience.

The difficulty of bridging this abyss is called the hard problem in consciousness research Chalmers R If we consider what brains actually have to do to ensure our survival we can see at once why this might be the case. Many problems which simulate environmental decision-making are computationally intractable. A good example is the traveling salesman problem - finding the shortest distance around n cities, which to be computed classically requires tracing every possible route which grows super-exponentially as n-1!

A gazelle standing at a forking in the paths to a water hole would become stranded and eaten by the tiger if it had to resort to classical computation. Moreover many of these problems are prisoners' dilemma problems in which the 'opponent' is forever changing their strategy, making computation historically out-of-date. The tiger may for example choose the safest looking path, or switch unpredictably.

Finally there is no single answer to many of these decisions, most of which have many possible outcomes rather than one computational solution, which is why we have evolved to have free choice in the first place. The way the brain appears to have evolved to solve this problem is to engage a kind of Darwinistic internal ecosystem of resonating excitations which are chaotic in time and enable holographic wave processing in 'space' across the cortex.

In a dynamic brain, phases of chaos are essential, both to provide the sensitivity on initial conditions of chaos which is essential to respond acutely sensitively to the outside world, and to provide the unpredictable, seemingly random, variation required to prevent the system getting caught in the rut of one overwhelming 'attractor' - the nemesis of all ordered systems.

The overall architecture of the mammalian brain consists of an overarching cortex acting as a modifier of resonant excitations ascending from mid-brain centres in the thalamus and deeper basal brain centres driving phases of alertness, sleep and dreaming. The cortex has a modular parallel architecture with sensory and cognitive processing for different modes occurring in parallel in distinct centres. For example upward of 24 centres have been identified for vision, handling colour and motion in separate parallel processing units.

These parallel differentiations extend to specific types of feature such as separate regions for recognition of different human faces and of human facial emotional expressions. Each of these modular regions is in turn organized into a series of columns on a scale of about 1mm which act as feature detectors for example of lines with a specific orientation.

Processing occurs in three to five distinct cellular layers comprising a mix of excitatory and inhibitory cells forming feedback loops enabling processing such as contrast enhancement. Typical cortical structures centre are a combination of five-layers of neurons left , each composed into columnar modules about 1mm on the cortical surface. Such modules are sensitive to stimuli such as a line of a given orientation.

Blob centres in layer II are also shown p Although specific sensory area have functional and anatomical specializations neural plasticity can enable changes of functional assignment indicating common principles throughout the cortex. Ocular dominance columns right for left or right eye illustrate functional columnar architecture. Given only some 30, protein-producing structural genes in the human genome, there are far too few to genetically determine exact details of brain structure on a cell-to-cell basis in a hard-wired manner.

The best specificity that can be managed consists of general rules of synaptic growth between specific cell types in different areas, which is what we see in cell migration and synaptic contact during development. In the visual system, the developing retina first begins to manifest chaotic excitation.

Only then does differentiation in the lateral geniculate become evident and in turn from its dynamical excitation the visual cortex becomes differentiated for pattern recognition. Thus while genes may be able to encode interconnections between specific excitatory and inhibitory cell types and to promote growth of axons between cell types in different regions, the central nervous system depends on dynamical excitation to establish the developed architecture of its connections.

Genetic determinism is thus a myth. Genes create developmental potentialities, which are shaped by excitation in both development and the environment. Nature thus utilizes nurture. This dynamical basis for development is reflected in cortical plasticity, where emerging changes in function can result in regions previously assigned to one function taking over another. Examples are changes in binocular optical dominance when one or other eye is covered, through to the phenomenon of the phantom limb, where regions assigned to a removed limb become invaded by other functional areas, resulting in sensory confusion, and the illusion that the limb is still present, perhaps even painful.

Changes also take place during higher learning such as becoming fluent in a new language. These kinds of specialization and development are reflected in the modular organization of the cortex we see in positron emission tomography PET and functional magnetic resonance imaging fMRI studies of the language and perceptual areas of the cortex.

The cerebral cortex is divided between front and rear broadly into motor and perception areas by the Sylvian fissure, which divides frontal regions and the motor cortex from the somatosensory touch and other sensory areas, including vision and hearing. The broadly sensory 'input' and associated areas of the parietal and temporal cortices are complemented by frontal and pre-frontal areas which deal with 'output' in the form of action rather than perception and with forming anticipatory models of our strategic and living futures.

These active roles of decision-making and 'working memory', which interact from pre-frontal cortical areas complement the largely sensory-processing of the temporal, parietal and occipital lobes with a space-time representation of our 'sense of future' and of our will or intent.

Another motif with undertones of sexual complementarity p is the fact that we possess two left and right hemispheres which are to all purposes separate cortices linked only by massive underlying parallel circuitry in the corpus callosum. Although much has been romanticized about our left and right brains in terms of the contrast between intuition and structured reasoning, and some people almost banish the sub-dominant hemisphere to inarticulate zombie-like status, there is abundant evidence for a degree of complementarity between foci in the two hemispheres, for example analytic language versus creative expression, linguistic versus musical perception, and holistic versus mechanical modes of thought.

Such lateralization has also been associated with the complementarity between different types of mathematical reasoning, the continuous ideas of topology p and calculus being associated with the right hemisphere, by contrast with the discrete operations of algebra p hypothetically assigned, like language to the left.

The two key language areas, Broca's frontal area for verbal speech fluency and Wernicke's temporal area for semantic resolution are traditionally on the left. However one should note that lateralization is more prominent in males and that females have generally greater facility with language, despite their language processing being less lateralized p As of a slew of reseach has emerged, which shows that handedness is not just confined to humans, but extends widely throughout the 'bilaterally-symmetric' animal kingdom spanning arthropods and vertebrates.

Vetrebrates from fish through birds to mammals are liable to hunt or forage with their right eyes and look for predators with their left, which allows brain areas in each cortex to become better adapted at serving each of these challenges. Prisoner's dilemma game theory simulations show that the safety in numbers when many members of a species adopt the same asymmetric strategy is offset to the best advantage of all players when there is a smaller subpopulation adopting the contralateral strategy thus confusing th epredator without becoming a primary target Southpaws: The cortex itself is relatively inert in electrodynamical terms and may actually form a complex boundary constraint on the activity of more active underlying areas such as the thalamus, which contains a number of centers with ordered projections to and from corresponding areas of the cortex.

Characteristic of the mammalian brain is also the peripheral 'limbic' system forming a loop around the periphery of the cortex, connecting primary frontal regions mediating integrated decision-making in action and the emotional centres of the cingulate cortex with the flight and fight centre of the amygdala, the long-term sequential memory of the hippocampus and basic bodily and sexual functions of the hypothalamus in great feedback loops whose dynamics are characteristic of changes in emotional mood and its influence on our outlook and strategic direction.

The limbic system lies at the core of mammalian emotionality from fear and anger to love and our capacity to transcend immediate genetic determinacies. The overall dynamical organization of the mammalian brain is also evident in the major ascending distributed pathways from the basal brain using specific neurotransmitters such as dopamine, noradrenaline and serotonin, which modify alertness and light and dreaming sleep see New Scientist 28 Jun 29 and are also modulated by psychedelics such as psilocin and mescaline.

These fan out from basal brain centres into wide areas of the cortex connecting into specific cortical layers where processing is taking place.

The large pyramidal cells which coordinate output thus have several different types of neurotransmitter modulating their excitation, both in an excitatory and an inhibitory manner. Walter Freeman's model of chaos in sensory perception Skarda and Freeman R, Freeman R gives a good feeling for how dynamical chaos p could play a key role in sensory recognition, for example, when a rabbit sniffs the air for a strange smell.

The olfactory cortex enters high energy chaotic excitation forming a spatially correlated wave across the cortex, causing the cortex to travel through its space of possibilities without becoming stuck in any mode. As the sniff ends, the energy parameter reduces, carrying the dynamic down towards basins in the potential energy landscape. If the smell is recognized the dynamic ends in an existing basin, a recognized smell, but if it is a new smell, a bifurcation eventually occurs to form a new basin a new symbol is created constituting the learning process.

The same logic can be applied to cognition and problem solving in which the unresolved aspects of a problem undergo chaotic evolution until a bifurcation from chaos to order arrives at the solution in the form of a flash of insight - "eureka! Freeman's model of olfaction is represented a by differing distributed excitations on the cortex. Eddington pointed out that the uncertainty of position of a vesicle is approximately the width of the membrane.

Indicators of the use of chaos in neurodynamics come also from measurements of the fractal dimension p of a variety of brain states, from pathology through sleep to restful wakefulness. Recordings from single neurons, and from other cells such as the insulin-releasing cells of the pancreas confirm their capacity for chaotic excitation.

The organizers of neural systems are also frequently non-pulse coded 'silent' cells capable of continuous non-linear dynamics. Despite the approximate linearity of the axonal discharge rate with depolarization, virtually all aspects of synaptic transmission and excitation have non-linear characteristics capable of chaos and bifurcation. For example the acetyl-choline ion channel has quadratic concentration dynamics, requiring two molecules to activate.

Many cells have sigmoidal responses providing non-linear hyper-sensitivity and are tuned to this threshold. The electroencephalogram itself although nominally described as having brain rhythms such as alpha, beta, gamma and theta actually consists of broad band frequencies, rather than harmonic resonances, consistent with a ground-swell of chaotic excitation King R , R , R , R Broadly speaking neurodynamics is "edge of chaos" p in the time domain and parallel distributed in a coherent 'holographic' manner Pribram spatially.

While artificial neural nets invoke thermodynamic 'randomness' in annealing to ensure the system doesn't get caught in a sub-optimal local minimum, biological systems appear to exploit chaos to free up their dynamics to explore the 'phase space' of possibilities available, without becoming locked in a local energy valley which keeps it far from a global optimum.

Into this picture of global and cellular chaos comes another scale-linking property, the fractal p nature of neuronal architecture and brain processes and their capacity for self-organized criticality at a microscopic level. The many-to-many connectivity of synaptic connection, the tuning of responsiveness to an arbitrarily sensitive 'sigmoidal' threshold, and the fractal architecture of individual neurons combine with the sensitive dependence of chaotic dynamics p and self-organized criticality p of global dynamics to provide a rich conduit for instabilities at the level of the synaptic vesicle or ion channel to become amplified into a global change.

The above description of chaotic transitions in perception and cognition leads naturally to critical states in a situation of choice between conflicting outcomes and this is exactly where the global dynamic would become critically poised and thus sensitive to microscopic or even quantum instabilities.

Evidence for complex system coupling between the molecular and global levels. Stochastic activation of single ion channels in hippocampal cells a leads to activation of the cells c. Activation of such individual cells can in turn lead to formation of global excitations as a result of stochastic resonance d. The brain is thus capable of supersenstivity to the instabilities of the quantum milieu Eccles R Chaotic excitability may be one of the founding features of eucaryote cells King R , R The Piezo-electric nature and high voltage gradient of the excitable membrane provides an excitable single cell with a generalized quantum sense organ.

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5 Comments

  1. In the visual system, the developing retina first begins to manifest chaotic excitation. This flood of estrogen is apparently quenched in females by binding to excess a-fetoprotein Kandell et.

  2. R , normal human participants imitated a finger movement and to perform the same movement after spatial or symbolic cues.

  3. Just 34 people - 17 men and 17 women - were exposed to the hormone lutocyclin in utero.

  4. Excitation could be perturbed mechanically and chemically through acoustic or molecular interaction, and electromagnetically through photon absorption and the perturbations of the fluctuating fields generated by the excitations themselves. Vetrebrates from fish through birds to mammals are liable to hunt or forage with their right eyes and look for predators with their left, which allows brain areas in each cortex to become better adapted at serving each of these challenges. However it is hard to eliminate cultural factors here.

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