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Monday, May 15, 2023

Quantum mind

From Wikipedia, the free encyclopedia

The quantum mind or quantum consciousness is a group of hypotheses proposing that classical mechanics alone cannot explain consciousness, positing instead that quantum-mechanical phenomena, such as entanglement and superposition, may play an important part in the brain's function and could explain critical aspects of consciousness. These scientific hypotheses are as yet untested, and can overlap with quantum mysticism.

History

Eugene Wigner developed the idea that quantum mechanics has something to do with the workings of the mind. He proposed that the wave function collapses due to its interaction with consciousness. Freeman Dyson argued that "mind, as manifested by the capacity to make choices, is to some extent inherent in every electron".

Other contemporary physicists and philosophers considered these arguments unconvincing. Victor Stenger characterized quantum consciousness as a "myth" having "no scientific basis" that "should take its place along with gods, unicorns and dragons".

David Chalmers argues against quantum consciousness. He instead discusses how quantum mechanics may relate to dualistic consciousness. Chalmers is skeptical that any new physics can resolve the hard problem of consciousness. He argues that quantum theories of consciousness suffer from the same weakness as more conventional theories. Just as he argues that there is no particular reason why particular macroscopic physical features in the brain should give rise to consciousness, he also thinks that there is no particular reason why a particular quantum feature, such as the EM field in the brain, should give rise to consciousness either.

Approaches

Bohm

David Bohm viewed quantum theory and relativity as contradictory, which implied a more fundamental level in the universe. He claimed that both quantum theory and relativity pointed to this deeper theory, which he formulated as a quantum field theory. This more fundamental level was proposed to represent an undivided wholeness and an implicate order, from which arises the explicate order of the universe as we experience it.

Bohm's proposed order applies both to matter and consciousness. He suggested that it could explain the relationship between them. He saw mind and matter as projections into our explicate order from the underlying implicate order. Bohm claimed that when we look at matter, we see nothing that helps us to understand consciousness.

Bohm discussed the experience of listening to music. He believed that the feeling of movement and change that make up our experience of music derive from holding the immediate past and the present in the brain together. The musical notes from the past are transformations rather than memories. The notes that were implicated in the immediate past become explicate in the present. Bohm viewed this as consciousness emerging from the implicate order.

Bohm saw the movement, change or flow, and the coherence of experiences, such as listening to music, as a manifestation of the implicate order. He claimed to derive evidence for this from Jean Piaget's work on infants. He held these studies to show that young children learn about time and space because they have a "hard-wired" understanding of movement as part of the implicate order. He compared this hard-wiring to Chomsky's theory that grammar is hard-wired into human brains.

Bohm never proposed a specific means by which his proposal could be falsified, nor a neural mechanism through which his "implicate order" could emerge in a way relevant to consciousness. He later collaborated on Karl Pribram's holonomic brain theory as a model of quantum consciousness.

According to philosopher Paavo Pylkkänen, Bohm's suggestion "leads naturally to the assumption that the physical correlate of the logical thinking process is at the classically describable level of the brain, while the basic thinking process is at the quantum-theoretically describable level".

It was suggested by theoretical physicists David Bohm and Basil Hiley that mind and matter both emerge from an "implicate order". Bohm and Hiley's approach to mind and matter is supported by philosopher Paavo Pylkkänen. Pylkkänen underlines "unpredictable, uncontrollable, indivisible and non-logical" features of conscious thought and draws parallels to a philosophical movement some call "post-phenomenology", in particular to Pauli Pylkkö's notion of the "aconceptual experience", an unstructured, unarticulated and pre-logical experience.

Penrose and Hameroff

Theoretical physicist Roger Penrose and anaesthesiologist Stuart Hameroff collaborated to produce the theory known as "orchestrated objective reduction" (Orch-OR). Penrose and Hameroff initially developed their ideas separately and later collaborated to produce Orch-OR in the early 1990s. They reviewed and updated their theory in 2013.

Penrose's argument stemmed from Gödel's incompleteness theorems. In his first book on consciousness, The Emperor's New Mind (1989), he argued that while a formal system cannot prove its own consistency, Gödel's unprovable results are provable by human mathematicians. Penrose took this to mean that human mathematicians are not formal proof systems and not running a computable algorithm. According to Bringsjord and Xiao, this line of reasoning is based on fallacious equivocation on the meaning of computation. In the same book, Penrose wrote: "One might speculate, however, that somewhere deep in the brain, cells are to be found of single quantum sensitivity. If this proves to be the case, then quantum mechanics will be significantly involved in brain activity."

Penrose determined that wave function collapse was the only possible physical basis for a non-computable process. Dissatisfied with its randomness, he proposed a new form of wave function collapse that occurs in isolation and called it objective reduction. He suggested each quantum superposition has its own piece of spacetime curvature and that when these become separated by more than one Planck length, they become unstable and collapse. Penrose suggested that objective reduction represents neither randomness nor algorithmic processing but instead a non-computable influence in spacetime geometry from which mathematical understanding and, by later extension, consciousness derives.

Hameroff provided a hypothesis that microtubules would be suitable hosts for quantum behavior. Microtubules are composed of tubulin protein dimer subunits. The dimers each have hydrophobic pockets that are 8 nm apart and may contain delocalized π electrons. Tubulins have other smaller non-polar regions that contain π-electron-rich indole rings separated by about 2 nm. Hameroff proposed that these electrons are close enough to become entangled. He originally suggested that the tubulin-subunit electrons would form a Bose–Einstein condensate, but this was discredited. He then proposed a Frohlich condensate, a hypothetical coherent oscillation of dipolar molecules, but this too was experimentally discredited.

In other words, there is a missing link between physics and neuroscience. For instance, the proposed predominance of A-lattice microtubules, more suitable for information processing, was falsified by Kikkawa et al., who showed that all in vivo microtubules have a B lattice and a seam. The proposed existence of gap junctions between neurons and glial cells was also falsified. Orch-OR predicted that microtubule coherence reaches the synapses through dendritic lamellar bodies (DLBs), but De Zeeuw et al. proved this impossible by showing that DLBs are micrometers away from gap junctions.

In 2014, Hameroff and Penrose claimed that the discovery of quantum vibrations in microtubules by Anirban Bandyopadhyay of the National Institute for Materials Science in Japan in March 2013 corroborates Orch-OR theory. Experiments that showed that anaesthetic drugs reduce how long microtubules can sustain suspected quantum excitations appear to support the quantum theory of consciousness.

In April 2022, the results of two related experiments at the University of Alberta and Princeton University were announced at The Science of Consciousness conference, providing further evidence to support quantum processes operating within microtubules. In a study Hameroff was part of, Jack Tuszyński of the University of Alberta demonstrated that anesthetics hasten the duration of a process called delayed luminescence, in which microtubules and tubulins re-emit trapped light. Tuszyński suspects that the phenomenon has a quantum origin, with superradiance being investigated as one possibility. In the second experiment, Gregory D. Scholes and Aarat Kalra of Princeton University used lasers to excite molecules within tubulins, causing a prolonged excitation to diffuse through microtubules further than expected, which did not occur when repeated under anesthesia. However, diffusion results have to be interpreted carefully, since even classical diffusion can be very complex due to the wide range of length scales in the fluid filled extracellular space.

Also in 2022, a group of Italian researchers performed several experiments that falsified a related hypothesis by physicist Lajos Diósi.

Although these theories are stated in a scientific framework, it is difficult to separate them from scientists' personal opinions. The opinions are often based on intuition or subjective ideas about the nature of consciousness. For example, Penrose wrote:

[M]y own point of view asserts that you can't even simulate conscious activity. What's going on in conscious thinking is something you couldn't properly imitate at all by computer.... If something behaves as though it's conscious, do you say it is conscious? People argue endlessly about that. Some people would say, "Well, you've got to take the operational viewpoint; we don't know what consciousness is. How do you judge whether a person is conscious or not? Only by the way they act. You apply the same criterion to a computer or a computer-controlled robot." Other people would say, "No, you can't say it feels something merely because it behaves as though it feels something." My view is different from both those views. The robot wouldn't even behave convincingly as though it was conscious unless it really was—which I say it couldn't be, if it's entirely computationally controlled.

Penrose continues:

A lot of what the brain does you could do on a computer. I'm not saying that all the brain's action is completely different from what you do on a computer. I am claiming that the actions of consciousness are something different. I'm not saying that consciousness is beyond physics, either—although I'm saying that it's beyond the physics we know now.... My claim is that there has to be something in physics that we don't yet understand, which is very important, and which is of a noncomputational character. It's not specific to our brains; it's out there, in the physical world. But it usually plays a totally insignificant role. It would have to be in the bridge between quantum and classical levels of behavior—that is, where quantum measurement comes in.

In 2010, Lawrence Krauss was guarded in criticising Penrose's ideas. He said: "Roger Penrose has given lots of new-age crackpots ammunition... Many people are dubious that Penrose's suggestions are reasonable, because the brain is not an isolated quantum-mechanical system. To some extent it could be, because memories are stored at the molecular level, and at a molecular level quantum mechanics is significant."

Umezawa, Vitiello, Freeman

Hiroomi Umezawa and collaborators proposed a quantum field theory of memory storage. Giuseppe Vitiello and Walter Freeman proposed a dialog model of the mind. This dialog takes place between the classical and the quantum parts of the brain. Their quantum field theory models of brain dynamics are fundamentally different from the Penrose–Hameroff theory.

Quantum brain dynamics

In neuroscience, quantum brain dynamics (QBD) is a hypothesis to explain the function of the brain within the framework of quantum field theory.

As described by Harald Atmanspacher, "Since quantum theory is the most fundamental theory of matter that is currently available, it is a legitimate question to ask whether quantum theory can help us to understand consciousness."

The original motivation in the early 20th century for relating quantum theory to consciousness was essentially philosophical. It is fairly plausible that conscious free decisions (“free will”) are problematic in a perfectly deterministic world, so quantum randomness might indeed open up novel possibilities for free will. (On the other hand, randomness is problematic for goal-directed volition!)

Ricciardi and Umezawa proposed in 1967 a general theory of quanta of long-range coherent waves within and between brain cells, and showed a possible mechanism of memory storage and retrieval in terms of Nambu–Goldstone bosons. This was later fleshed out into a theory encompassing all biological cells and systems in the quantum biodynamics of Del Giudice and co-authors. Mari Jibu and Kunio Yasue later popularized these results and discussed the implications towards consciousness.

Umezawa emphasizes that macroscopic and microscopic ordered states are both of quantum origin according to quantum field theory and points out the shortcomings of classical neuronal models in describing them. In 1981, theoretical exploration of the Ising model in Cayley tree topologies and large neural networks yielded an exact solution on closed trees with arbitrary branching ratios greater than two, exhibiting an unusual phase transition in local-apex and long-range site-site correlations. This finding directly raises the possibility of multiple cooperative modes being present in ordering states long-range within neural networks and their constituents, with Barth cooperative effects of the closed tree Ising model (structurally and connectivity dependent, with critical point a function of branching ratio and site-to-site energies of interaction)  and Umezawa ordering of states (less structure dependent and with significantly greater degrees of freedom) independently or collectively guiding overall long-range macroscopic ordering often associated with higher cognitive functions in QBD.

Pribram

Karl Pribram's holonomic brain theory (quantum holography) invoked quantum mechanics to explain higher-order processing by the mind. He argued that his holonomic model solved the binding problem. Pribram collaborated with Bohm in his work on quantum approaches to mind and he provided evidence on how much of the processing in the brain was done in wholes. He proposed that ordered water at dendritic membrane surfaces might operate by structuring Bose–Einstein condensation supporting quantum dynamics.

Stapp

Henry Stapp proposed that quantum waves are reduced only when they interact with consciousness. He argues from the orthodox quantum mechanics of John von Neumannthat the quantum state collapses when the observer selects one among the alternative quantum possibilities as a basis for future action. The collapse, therefore, takes place in the expectation that the observer associated with the state. Stapp's work drew criticism from scientists such as David Bourget and Danko Georgiev. Georgievcriticized Stapp's model in two respects:

  • Stapp's mind does not have its own wavefunction or density matrix, but nevertheless can act upon the brain using projection operators. Such usage is not compatible with standard quantum mechanics because one can attach any number of ghostly minds to any point in space that act upon physical quantum systems with any projection operators. Stapp's model therefore negates "the prevailing principles of physics".
  • Stapp's claim that quantum Zeno effect is robust against environmental decoherence directly contradicts a basic theorem in quantum information theory: that acting with projection operators upon the density matrix of a quantum system can only increase the system's von Neumann entropy.

Stapp has responded to both of Georgiev's objections.

David Pearce

British philosopher David Pearce defends what he calls physicalistic idealism ("the non-materialist physicalist claim that reality is fundamentally experiential and that the natural world is exhaustively described by the equations of physics and their solutions") and has conjectured that unitary conscious minds are physical states of quantum coherence (neuronal superpositions). This conjecture is, according to Pearce, amenable to falsification, unlike most theories of consciousness, and Pearce has outlined an experimental protocol describing how the hypothesis could be tested using matter-wave interferometry to detect nonclassical interference patterns of neuronal superpositions at the onset of thermal decoherence. Pearce admits that his ideas are "highly speculative", "counterintuitive", and "incredible".

Catecholaminergic Neuron Electron Transport (CNET)

CNET is a hypothesized neural signaling mechanism in catecholaminergic neurons that would use quantum mechanical electron transport. The hypothesis is based in part on the observation by many independent researchers that electron tunneling occurs in ferritin, an iron storage protein that is prevalent in those neurons, at room temperature and ambient conditions. The hypothesized function of this mechanism is to assist in action selection, but the mechanism itself would be capable of integrating millions of cognitive and sensory neural signals using a physical mechanism associated with strong electron-electron interactions. Each tunneling event would involve a collapse of an electron wave function, but the collapse would be incidental to the physical effect created by strong electron-electron interactions.

CNET predicted a number of physical properties of these neurons that have been subsequently observed experimentally, such as electron tunneling in substantia nigra pars compacta (SNc) tissue and the presence of disordered arrays of ferritin in SNc tissue. The hypothesis also predicted that disordered ferritin arrays like those found in SNc tissue should be capable of supporting long-range electron transport and providing a switching or routing function, both of which have also been subsequently observed.

Another prediction of CNET was that the largest SNc neurons should mediate action selection.  This prediction was contrary to earlier proposals about the function of those neurons at that time, which were based on predictive reward dopamine signaling. A team led by Dr. Pascal Kaiser of Harvard Medical School subsequently demonstrated that those neurons do in fact code movement, consistent with the earlier predictions of CNET. While the CNET mechanism has not yet been directly observed, it may be possible to do so using quantum dot fluorophores tagged to ferritin or other methods for detecting electron tunneling.

CNET is applicable to a number of different consciousness models as a binding or action selection mechanism, such as Integrated Information Theory (IIT) and Sensorimotor Theory (SMT). It is noted that many existing models of consciousness fail to specifically address action selection or binding.  For example, O’Regan and Noë call binding a “pseudo problem,” but also state that “the fact that object attributes seem perceptually to be part of a single object does not require them to be ‘represented’ in any unified kind of way, for example, at a single location in the brain, or by a single process. They may be so represented, but there is no logical necessity for this.” Simply because there is no “logical necessity” for a physical phenomenon does not mean that it does not exist, or that once it is identified that it can be ignored.  Likewise, global workspace theory (GWT) models appear to treat dopamine as modulatory, based on the prior understanding of those neurons from predictive reward dopamine signaling research, but GWT models could be adapted to include modeling of moment-by-moment activity in the striatum to mediate action selection, as observed by Kaiser.  CNET is applicable to those neurons as a selection mechanism for that function, as otherwise that function could result in seizures from simultaneous actuation of competing sets of neurons. While CNET by itself is not a model of consciousness, it is able to integrate different models of consciousness through neural binding and action selection. However, a more complete understanding of how CNET might relate to consciousness would require a better understanding of strong electron-electron interactions in ferritin arrays, which implicates the many-body problem.

Experiments

In 2022, neuroscientists reported experimental MRI results that so far appear to imply nuclear proton spins of 'brain water' in the brains of human participants were entangled, suggesting brain functions that operate non-classically which may support quantum mechanisms being involved in consciousness as the signal pattern declined when human participants fell asleep. However, the results are far from unambiguous and if such brain functions indeed exist and are involved in conscious cognition, the extent and nature of their involvement in consciousness remains unknown.

Criticism

These hypotheses of the quantum mind remain hypothetical speculation, as Penrose and Pearce admit in their discussions. Until they make a prediction that is tested by experimentation, the hypotheses aren't based on empirical evidence. According to Krauss, "It is true that quantum mechanics is extremely strange, and on extremely small scales for short times, all sorts of weird things happen. And in fact, we can make weird quantum phenomena happen. But what quantum mechanics doesn't change about the universe is, if you want to change things, you still have to do something. You can't change the world by thinking about it."

The process of testing the hypotheses with experiments is fraught with conceptual/theoretical, practical, and ethical problems.

Conceptual problems

The idea that a quantum effect is necessary for consciousness to function is still in the realm of philosophy. Penrose proposes that it is necessary, but other theories of consciousness do not indicate that it is needed. For example, Daniel Dennett proposed a theory called multiple drafts model, which doesn't indicate that quantum effects are needed, in his 1991 book Consciousness Explained. A philosophical argument on either side isn't scientific proof, although philosophical analysis can indicate key differences in the types of models and show what type of experimental differences might be observed. But since there isn't a clear consensus among philosophers, there isn't conceptual support that a quantum mind theory is needed.

There are computers that are specifically designed to compute using quantum-mechanical effects. Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement. They are different from binary digital electronic computers based on transistors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits, which can be in superpositions of states. One of the greatest challenges is controlling or removing quantum decoherence. This usually means isolating the system from its environment, as interactions with the external world cause the system to decohere. Some quantum computers require their qubits to be cooled to 20 millikelvins in order to prevent significant decoherence. As a result, time-consuming tasks may render some quantum algorithms inoperable, as maintaining the state of qubits long enough eventually corrupts the superpositions. There aren't any obvious analogies between the functioning of quantum computers and the human brain. Some hypothetical models of quantum mind have proposed mechanisms for maintaining quantum coherence in the brain, but they have not been shown to operate.

Quantum entanglement is a physical phenomenon often invoked for quantum mind models. This effect occurs when pairs or groups of particles interact so that the quantum state of each particle cannot be described independently of the other(s), even when the particles are separated by a large distance. Instead, a quantum state has to be described for the whole system. Measurements of physical properties such as position, momentum, spin, and polarization, performed on entangled particles are found to be correlated. If one particle is measured, the same property of the other particle immediately adjusts to maintain the conservation of the physical phenomenon. According to the formalism of quantum theory, the effect of measurement happens instantly, no matter how far apart the particles are. It is not possible to use this effect to transmit classical information at faster-than-light speeds (see Faster-than-light § Quantum mechanics). Entanglement is broken when the entangled particles decohere through interaction with the environment—for example, when a measurement is made or the particles undergo random collisions or interactions. According to Pearce, "In neuronal networks, ion–ion scattering, ion–water collisions, and long-range Coulomb interactions from nearby ions all contribute to rapid decoherence times; but thermally induced decoherence is even harder experimentally to control than collisional decoherence." He anticipated that quantum effects would have to be measured in femtoseconds, a trillion times faster than the rate at which neurons function (milliseconds).

Another possible conceptual approach is to use quantum mechanics as an analogy to understand a different field of study like consciousness, without expecting that the laws of quantum physics will apply. An example of this approach is the idea of Schrödinger's cat. Erwin Schrödinger described how one could, in principle, create entanglement of a large-scale system by making it dependent on an elementary particle in a superposition. He proposed a scenario with a cat in a locked steel chamber, wherein the cat's survival depended on the state of a radioactive atom—whether it had decayed and emitted radiation. According to Schrödinger, the Copenhagen interpretation implies that the cat is both alive and dead until the state has been observed. Schrödinger did not wish to promote the idea of dead-and-alive cats as a serious possibility; he intended the example to illustrate the absurdity of the existing view of quantum mechanics. But since Schrödinger's time, physicists have given other interpretations of the mathematics of quantum mechanics, some of which regard the "alive and dead" cat superposition as quite real. Schrödinger's famous thought experiment poses the question, "when does a quantum system stop existing as a superposition of states and become one or the other?" In the same way, one can ask whether the act of making a decision is analogous to having a superposition of states of two decision outcomes, so that making a decision means "opening the box" to reduce the brain from a combination of states to one state. This analogy about decision-making uses a formalism derived from quantum mechanics, but doesn't indicate the actual mechanism by which the decision is made. In this way, the idea is similar to quantum cognition. This field clearly distinguishes itself from the quantum mind, as it is not reliant on the hypothesis that there is something micro-physical quantum-mechanical about the brain. Quantum cognition is based on the quantum-like paradigm, generalized quantum paradigm, or quantum structure paradigm that information processing by complex systems such as the brain can be mathematically described in the framework of quantum information and quantum probability theory. This model uses quantum mechanics only as an analogy, but doesn't propose that quantum mechanics is the physical mechanism by which it operates. For example, quantum cognition proposes that some decisions can be analyzed as if there is interference between two alternatives, but it is not a physical quantum interference effect.

Practical problems

Quantum mechanics is a mathematical model that can provide some extremely accurate numerical predictions. Richard Feynman called quantum electrodynamics, based on the quantum-mechanics formalism, "the jewel of physics" for its extremely accurate predictions of quantities like the anomalous magnetic moment of the electron and the Lamb shift of the energy levels of hydrogen. So it is not impossible that the model could provide an accurate prediction about consciousness that would confirm that a quantum effect is involved. If the mind depends on quantum mechanical effects, the true proof is to find an experiment that provides a calculation that can be compared to experimental measurement. It has to show a measurable difference between a classical computation result in a brain and one that involves quantum effects.

The main theoretical argument against the quantum-mind hypothesis is the assertion that quantum states in the brain would lose coherency before they reached a scale where they could be useful for neural processing. This supposition was elaborated by Max Tegmark. His calculations indicate that quantum systems in the brain decohere at sub-picosecond timescales. No response by a brain has shown computational results or reactions on this fast of a timescale. Typical reactions are on the order of milliseconds, trillions of times longer than sub-picosecond timescales.

Daniel Dennett uses an experimental result in support of his multiple drafts model of an optical illusion that happens on a time scale of less than a second or so. In this experiment, two different-colored lights, with an angular separation of a few degrees at the eye, are flashed in succession. If the interval between the flashes is less than a second or so, the first light that is flashed appears to move across to the position of the second light. Furthermore, the light seems to change color as it moves across the visual field. A green light will appear to turn red as it seems to move across to the position of a red light. Dennett asks how we could see the light change color before the second light is observed. Velmans argues that the cutaneous rabbit illusion, another illusion that happens in about a second, demonstrates that there is a delay while modelling occurs in the brain and that this delay was discovered by Libet. These slow illusions that happen at times of less than a second don't support a proposal that the brain functions on the picosecond time scale.

According to David Pearce, a demonstration of picosecond effects is "the fiendishly hard part – feasible in principle, but an experimental challenge still beyond the reach of contemporary molecular matter-wave interferometry. [...] The conjecture predicts that we'll discover the interference signature of sub-femtosecond macro-superpositions."

Penrose says:

The problem with trying to use quantum mechanics in the action of the brain is that if it were a matter of quantum nerve signals, these nerve signals would disturb the rest of the material in the brain, to the extent that the quantum coherence would get lost very quickly. You couldn't even attempt to build a quantum computer out of ordinary nerve signals, because they're just too big and in an environment that's too disorganized. Ordinary nerve signals have to be treated classically. But if you go down to the level of the microtubules, then there's an extremely good chance that you can get quantum-level activity inside them.

For my picture, I need this quantum-level activity in the microtubules; the activity has to be a large-scale thing that goes not just from one microtubule to the next but from one nerve cell to the next, across large areas of the brain. We need some kind of coherent activity of a quantum nature which is weakly coupled to the computational activity that Hameroff argues is taking place along the microtubules.

There are various avenues of attack. One is directly on the physics, on quantum theory, and there are certain experiments that people are beginning to perform, and various schemes for a modification of quantum mechanics. I don't think the experiments are sensitive enough yet to test many of these specific ideas. One could imagine experiments that might test these things, but they'd be very hard to perform.

A demonstration of a quantum effect in the brain has to explain this problem or explain why it is not relevant, or that the brain somehow circumvents the problem of the loss of quantum coherency at body temperature. As Penrose proposes, it may require a new type of physical theory.

Ethical problems

Quantum mind theories are often conflated with quantum woo, which is the justification of irrational beliefs by an obfuscatory reference to quantum physics. Buzzwords like "energy field", "probability wave", or "wave-particle duality" are used to magically turn thoughts into something tangible in order to directly affect the universe. Some have turned quantum woo into a career, such as Deepak Chopra, who often presents ill-defined concepts of quantum physics as proof for God, a "quantum soul" existing "apart from the body" and human "access to a field of infinite possibilities".

According to Lawrence Krauss, "You should be wary whenever you hear something like 'Quantum mechanics connects you with the universe' ... or 'quantum mechanics unifies you with everything else'. You can begin to be skeptical that the speaker is somehow trying to use quantum mechanics to argue fundamentally that you can change the world by thinking about it." A subjective feeling is not sufficient to make this determination. Humans don't have a reliable subjective feeling for how we do a lot of functions. According to Daniel Dennett, "On this topic, Everybody's an expert... but they think that they have a particular personal authority about the nature of their own conscious experiences that can trump any hypothesis they find unacceptable."

An ethically objectionable practice by proponents of quantum mind theories involves the practice of using quantum-mechanical terms in an effort to make the argument sound more impressive, even when they know that those terms are irrelevant. Dale DeBakcsy notes that "trendy parapsychologists, academic relativists, and even the Dalai Lama have all taken their turn at robbing modern physics of a few well-sounding phrases and stretching them far beyond their original scope in order to add scientific weight to various pet theories".

Misleading statements of this type have been given by, for example, Deepak Chopra. Chopra has commonly referred to topics such as quantum healing or quantum effects of consciousness. Seeing the human body as being undergirded by a "quantum-mechanical body" composed not of matter but of energy and information, he believes that "human aging is fluid and changeable; it can speed up, slow down, stop for a time, and even reverse itself", as determined by one's state of mind. Robert Carroll states that Chopra attempts to integrate Ayurveda with quantum mechanics to justify his teachings. Chopra argues that what he calls "quantum healing" cures any manner of ailments, including cancer, through effects that he claims are literally based on the same principles as quantum mechanics. This has led physicists to object to his use of the term quantum in reference to medical conditions and the human body. Chopra said: "I think quantum theory has a lot of things to say about the observer effect, about non-locality, about correlations. So I think there’s a school of physicists who believe that consciousness has to be equated, or at least brought into the equation, in understanding quantum mechanics." On the other hand, he also claims that "[quantum effects are] just a metaphor. Just like an electron or a photon is an indivisible unit of information and energy, a thought is an indivisible unit of consciousness." In his book Quantum Healing, Chopra stated the conclusion that quantum entanglement links everything in the Universe, and therefore it must create consciousness.

Chris Carter includes statements in his book Science and Psychic Phenomena of quotes from quantum physicists in support of psychic phenomena. In a review of the book, Benjamin Radford wrote that Carter used such references to "quantum physics, which he knows nothing about and which he (and people like Deepak Chopra) love to cite and reference because it sounds mysterious and paranormal.... Real, actual physicists I've spoken to break out laughing at this crap.... If Carter wishes to posit that quantum physics provides a plausible mechanism for psi, then it is his responsibility to show that, and he clearly fails to do so." Sharon Hill has studied amateur paranormal research groups, and these groups like to use "vague and confusing language: ghosts 'use energy', are made up of 'magnetic fields', or are associated with a 'quantum state'".

Critics of the quantum mind hypothesis do not deny that quantum effects are involved in computations in the brain. But as these effects are relevant only at very small scales, e.g. by determining the properties and structure of proteins and neurotransmitters, critics consider them irrelevant to consciousness emerging as a macroscopic phenomenon. As Daniel Dennett said, "quantum effects are there in your car, your watch, and your computer. But most things — most macroscopic objects — are, as it were, oblivious to quantum effects. They don't amplify them; they don't hinge on them."

Lawrence Krauss said: "We're also connected to the universe by gravity, and we're connected to the planets by gravity. But that doesn't mean that astrology is true.... Often, people who are trying to sell whatever it is they're trying to sell try to justify it on the basis of science. Everyone knows quantum mechanics is weird, so why not use that to justify it? ... I don't know how many times I've heard people say, 'Oh, I love quantum mechanics because I'm really into meditation, or I love the spiritual benefits that it brings me.' But quantum mechanics, for better or worse, doesn't bring any more spiritual benefits than gravity does."

Neural correlates of consciousness

From Wikipedia, the free encyclopedia
 
The Neuronal Correlates of Consciousness (NCC) constitute the smallest set of neural events and structures sufficient for a given conscious percept or explicit memory. This case involves synchronized action potentials in neocortical pyramidal neurons.

The neural correlates of consciousness (NCC) refer to the relationships between mental states and neural states and constitute the minimal set of neuronal events and mechanisms sufficient for a specific conscious percept. Neuroscientists use empirical approaches to discover neural correlates of subjective phenomena; that is, neural changes which necessarily and regularly correlate with a specific experience. The set should be minimal because, under the materialist assumption that the brain is sufficient to give rise to any given conscious experience, the question is which of its components are necessary to produce it.

Neurobiological approach to consciousness

A science of consciousness must explain the exact relationship between subjective mental states and brain states, the nature of the relationship between the conscious mind and the electro-chemical interactions in the body (mind–body problem). Progress in neuropsychology and neurophilosophy has come from focusing on the body rather than the mind. In this context the neuronal correlates of consciousness may be viewed as its causes, and consciousness may be thought of as a state-dependent property of an undefined complex, adaptive, and highly interconnected biological system.

Discovering and characterizing neural correlates does not offer a causal theory of consciousness that can explain how particular systems experience anything, the so-called hard problem of consciousness, but understanding the NCC may be a step toward a causal theory. Most neurobiologists propose that the variables giving rise to consciousness are to be found at the neuronal level, governed by classical physics. There are theories proposed of quantum consciousness based on quantum mechanics.

There is an apparent redundancy and parallelism in neural networks so, while activity in one group of neurons may correlate with a percept in one case, a different population may mediate a related percept if the former population is lost or inactivated. It may be that every phenomenal, subjective state has a neural correlate. Where the NCC can be induced artificially the subject will experience the associated percept, while perturbing or inactivating the region of correlation for a specific percept will affect the percept or cause it to disappear, giving a cause-effect relationship from the neural region to the nature of the percept.

There are some proposals that have been advanced over the years; What characterizes the NCC? What are the commonalities between the NCC for seeing and for hearing? Will the NCC involve all the pyramidal neurons in the cortex at any given point in time? Or only a subset of long-range projection cells in the frontal lobes that project to the sensory cortices in the back? Neurons that fire in a rhythmic manner? Neurons that fire in a synchronous manner?

The growing ability of neuroscientists to manipulate neurons using methods from molecular biology in combination with optical tools (e.g., Adamantidis et al. 2007) depends on the simultaneous development of appropriate behavioral assays and model organisms amenable to large-scale genomic analysis and manipulation. It is the combination of fine-grained neuronal analysis in animals with increasingly more sensitive psychophysical and brain imaging techniques in humans, complemented by the development of a robust theoretical predictive framework, that will hopefully lead to a rational understanding of consciousness, one of the central mysteries of life.

Level of arousal and content of consciousness

There are two common but distinct dimensions of the term consciousness, one involving arousal and states of consciousness and the other involving content of consciousness and conscious states. To be conscious of anything the brain must be in a relatively high state of arousal (sometimes called vigilance), whether in wakefulness or REM sleep, vividly experienced in dreams although usually not remembered. Brain arousal level fluctuates in a circadian rhythm but may be influenced by lack of sleep, drugs and alcohol, physical exertion, etc. Arousal can be measured behaviorally by the signal amplitude that triggers some criterion reaction (for instance, the sound level necessary to evoke an eye movement or a head turn toward the sound source). Clinicians use scoring systems such as the Glasgow Coma Scale to assess the level of arousal in patients.

High arousal states are associated with conscious states that have specific content, seeing, hearing, remembering, planning or fantasizing about something. Different levels or states of consciousness are associated with different kinds of conscious experiences. The "awake" state is quite different from the "dreaming" state (for instance, the latter has little or no self-reflection) and from the state of deep sleep. In all three cases the basic physiology of the brain is affected, as it also is in altered states of consciousness, for instance after taking drugs or during meditation when conscious perception and insight may be enhanced compared to the normal waking state.

Clinicians talk about impaired states of consciousness as in "the comatose state", "the persistent vegetative state" (PVS), and "the minimally conscious state" (MCS). Here, "state" refers to different "amounts" of external/physical consciousness, from a total absence in coma, persistent vegetative state and general anesthesia, to a fluctuating and limited form of conscious sensation in a minimally conscious state such as sleep walking or during a complex partial epileptic seizure.[10] The repertoire of conscious states or experiences accessible to a patient in a minimally conscious state is comparatively limited. In brain death there is no arousal, but it is unknown whether the subjectivity of experience has been interrupted, rather than its observable link with the organism. Functional neuroimaging have shown that parts of the cortex are still active in vegetative patients that are presumed to be unconscious; however, these areas appear to be functionally disconnected from associative cortical areas whose activity is needed for awareness.

The potential richness of conscious experience appears to increase from deep sleep to drowsiness to full wakefulness, as might be quantified using notions from complexity theory that incorporate both the dimensionality as well as the granularity of conscious experience to give an integrated-information-theoretical account of consciousness. As behavioral arousal increases so does the range and complexity of possible behavior. Yet in REM sleep there is a characteristic atonia, low motor arousal and the person is difficult to wake up, but there is still high metabolic and electric brain activity and vivid perception.

Many nuclei with distinct chemical signatures in the thalamus, midbrain and pons must function for a subject to be in a sufficient state of brain arousal to experience anything at all. These nuclei therefore belong to the enabling factors for consciousness. Conversely it is likely that the specific content of any particular conscious sensation is mediated by particular neurons in cortex and their associated satellite structures, including the amygdala, thalamus, claustrum and the basal ganglia.

The neuronal basis of perception

The possibility of precisely manipulating visual percepts in time and space has made vision a preferred modality in the quest for the NCC. Psychologists have perfected a number of techniques – masking, binocular rivalry, continuous flash suppression, motion induced blindness, change blindness, inattentional blindness – in which the seemingly simple and unambiguous relationship between a physical stimulus in the world and its associated percept in the privacy of the subject's mind is disrupted. In particular a stimulus can be perceptually suppressed for seconds or even minutes at a time: the image is projected into one of the observer's eyes but is invisible, not seen. In this manner the neural mechanisms that respond to the subjective percept rather than the physical stimulus can be isolated, permitting visual consciousness to be tracked in the brain. In a perceptual illusion, the physical stimulus remains fixed while the percept fluctuates. The best known example is the Necker cube whose 12 lines can be perceived in one of two different ways in depth.

The Necker Cube: The left line drawing can be perceived in one of two distinct depth configurations shown on the right. Without any other cue, the visual system flips back and forth between these two interpretations.

A perceptual illusion that can be precisely controlled is binocular rivalry. Here, a small image, e.g., a horizontal grating, is presented to the left eye, and another image, e.g., a vertical grating, is shown to the corresponding location in the right eye. In spite of the constant visual stimulus, observers consciously see the horizontal grating alternate every few seconds with the vertical one. The brain does not allow for the simultaneous perception of both images.

Logothetis and colleagues recorded a variety of visual cortical areas in awake macaque monkeys performing a binocular rivalry task. Macaque monkeys can be trained to report whether they see the left or the right image. The distribution of the switching times and the way in which changing the contrast in one eye affects these leaves little doubt that monkeys and humans experience the same basic phenomenon. In the primary visual cortex (V1) only a small fraction of cells weakly modulated their response as a function of the percept of the monkey while most cells responded to one or the other retinal stimulus with little regard to what the animal perceived at the time. But in a high-level cortical area such as the inferior temporal cortex along the ventral stream almost all neurons responded only to the perceptually dominant stimulus, so that a "face" cell only fired when the animal indicated that it saw the face and not the pattern presented to the other eye. This implies that NCC involve neurons active in the inferior temporal cortex: it is likely that specific reciprocal actions of neurons in the inferior temporal and parts of the prefrontal cortex are necessary.

A number of fMRI experiments that have exploited binocular rivalry and related illusions to identify the hemodynamic activity underlying visual consciousness in humans demonstrate quite conclusively that activity in the upper stages of the ventral pathway (e.g., the fusiform face area and the parahippocampal place area) as well as in early regions, including V1 and the lateral geniculate nucleus (LGN), follow the percept and not the retinal stimulus. Further, a number of fMRI and DTI experiments suggest V1 is necessary but not sufficient for visual consciousness.

In a related perceptual phenomenon, flash suppression, the percept associated with an image projected into one eye is suppressed by flashing another image into the other eye while the original image remains. Its methodological advantage over binocular rivalry is that the timing of the perceptual transition is determined by an external trigger rather than by an internal event. The majority of cells in the inferior temporal cortex and the superior temporal sulcus of monkeys trained to report their percept during flash suppression follow the animal's percept: when the cell's preferred stimulus is perceived, the cell responds. If the picture is still present on the retina but is perceptually suppressed, the cell falls silent, even though primary visual cortex neurons fire. Single-neuron recordings in the medial temporal lobe of epilepsy patients during flash suppression likewise demonstrate abolishment of response when the preferred stimulus is present but perceptually masked.

Global disorders of consciousness

Given the absence of any accepted criterion of the minimal neuronal correlates necessary for consciousness, the distinction between a persistently vegetative patient who shows regular sleep-wave transitions and may be able to move or smile, and a minimally conscious patient who can communicate (on occasion) in a meaningful manner (for instance, by differential eye movements) and who shows some signs of consciousness, is often difficult. In global anesthesia the patient should not experience psychological trauma but the level of arousal should be compatible with clinical exigencies.

Midline structures in the brainstem and thalamus necessary to regulate the level of brain arousal. Small, bilateral lesions in many of these nuclei cause a global loss of consciousness.

Blood-oxygen-level-dependent fMRI have demonstrated normal patterns of brain activity in a patient in a vegetative state following a severe traumatic brain injury when asked to imagine playing tennis or visiting rooms in his/her house. Differential brain imaging of patients with such global disturbances of consciousness (including akinetic mutism) reveal that dysfunction in a widespread cortical network including medial and lateral prefrontal and parietal associative areas is associated with a global loss of awareness. Impaired consciousness in epileptic seizures of the temporal lobe was likewise accompanied by a decrease in cerebral blood flow in frontal and parietal association cortex and an increase in midline structures such as the mediodorsal thalamus.

Relatively local bilateral injuries to midline (paramedian) subcortical structures can also cause a complete loss of awareness. These structures therefore enable and control brain arousal (as determined by metabolic or electrical activity) and are necessary neural correlates. One such example is the heterogeneous collection of more than two dozen nuclei on each side of the upper brainstem (pons, midbrain and in the posterior hypothalamus), collectively referred to as the reticular activating system (RAS). Their axons project widely throughout the brain. These nuclei – three-dimensional collections of neurons with their own cyto-architecture and neurochemical identity – release distinct neuromodulators such as acetylcholine, noradrenaline/norepinephrine, serotonin, histamine and orexin/hypocretin to control the excitability of the thalamus and forebrain, mediating alternation between wakefulness and sleep as well as general level of behavioral and brain arousal. After such trauma, however, eventually the excitability of the thalamus and forebrain can recover and consciousness can return. Another enabling factor for consciousness are the five or more intralaminar nuclei (ILN) of the thalamus. These receive input from many brainstem nuclei and project strongly, directly to the basal ganglia and, in a more distributed manner, into layer I of much of the neocortex. Comparatively small (1 cm3 or less) bilateral lesions in the thalamic ILN completely knock out all awareness.

Forward versus feedback projections

Many actions in response to sensory inputs are rapid, transient, stereotyped, and unconscious. They could be thought of as cortical reflexes and are characterized by rapid and somewhat stereotyped responses that can take the form of rather complex automated behavior as seen, e.g., in complex partial epileptic seizures. These automated responses, sometimes called zombie behaviors, could be contrasted by a slower, all-purpose conscious mode that deals more slowly with broader, less stereotyped aspects of the sensory inputs (or a reflection of these, as in imagery) and takes time to decide on appropriate thoughts and responses. Without such a consciousness mode, a vast number of different zombie modes would be required to react to unusual events.

A feature that distinguishes humans from most animals is that we are not born with an extensive repertoire of behavioral programs that would enable us to survive on our own ("physiological prematurity"). To compensate for this, we have an unmatched ability to learn, i.e., to consciously acquire such programs by imitation or exploration. Once consciously acquired and sufficiently exercised, these programs can become automated to the extent that their execution happens beyond the realms of our awareness. Take, as an example, the incredible fine motor skills exerted in playing a Beethoven piano sonata or the sensorimotor coordination required to ride a motorcycle along a curvy mountain road. Such complex behaviors are possible only because a sufficient number of the subprograms involved can be executed with minimal or even suspended conscious control. In fact, the conscious system may actually interfere somewhat with these automated programs.

From an evolutionary standpoint it clearly makes sense to have both automated behavioral programs that can be executed rapidly in a stereotyped and automated manner, and a slightly slower system that allows time for thinking and planning more complex behavior. This latter aspect may be one of the principal functions of consciousness. Other philosophers, however, have suggested that consciousness would not be necessary for any functional advantage in evolutionary processes. No one has given a causal explanation, they argue, of why it would not be possible for a functionally equivalent non-conscious organism (i.e., a philosophical zombie) to achieve the very same survival advantages as a conscious organism. If evolutionary processes are blind to the difference between function F being performed by conscious organism O and non-conscious organism O*, it is unclear what adaptive advantage consciousness could provide. As a result, an exaptive explanation of consciousness has gained favor with some theorists that posit consciousness did not evolve as an adaptation but was an exaptation arising as a consequence of other developments such as increases in brain size or cortical rearrangement. Consciousness in this sense has been compared to the blind spot in the retina where it is not an adaption of the retina, but instead just a by-product of the way the retinal axons were wired. Several scholars including Pinker, Chomsky, Edelman, and Luria have indicated the importance of the emergence of human language as an important regulative mechanism of learning and memory in the context of the development of higher-order consciousness.

It seems possible that visual zombie modes in the cortex mainly use the dorsal stream in the parietal region. However, parietal activity can affect consciousness by producing attentional effects on the ventral stream, at least under some circumstances. The conscious mode for vision depends largely on the early visual areas (beyond V1) and especially on the ventral stream.

Seemingly complex visual processing (such as detecting animals in natural, cluttered scenes) can be accomplished by the human cortex within 130–150 ms, far too brief for eye movements and conscious perception to occur. Furthermore, reflexes such as the oculovestibular reflex take place at even more rapid time-scales. It is quite plausible that such behaviors are mediated by a purely feed-forward moving wave of spiking activity that passes from the retina through V1, into V4, IT and prefrontal cortex, until it affects motorneurons in the spinal cord that control the finger press (as in a typical laboratory experiment). The hypothesis that the basic processing of information is feedforward is supported most directly by the short times (approx. 100 ms) required for a selective response to appear in IT cells.

Conversely, conscious perception is believed to require more sustained, reverberatory neural activity, most likely via global feedback from frontal regions of neocortex back to sensory cortical areas that builds up over time until it exceeds a critical threshold. At this point, the sustained neural activity rapidly propagates to parietal, prefrontal and anterior cingulate cortical regions, thalamus, claustrum and related structures that support short-term memory, multi-modality integration, planning, speech, and other processes intimately related to consciousness. Competition prevents more than one or a very small number of percepts to be simultaneously and actively represented. This is the core hypothesis of the global workspace theory of consciousness.

In brief, while rapid but transient neural activity in the thalamo-cortical system can mediate complex behavior without conscious sensation, it is surmised that consciousness requires sustained but well-organized neural activity dependent on long-range cortico-cortical feedback.

History

The neurobiologist Christfried Jakob (1866-1956) argued that the only conditions which must have neural correlates are direct sensations and reactions; these are called "intonations".

Neurophysiological studies in animals provided some insights on the neural correlates of conscious behavior. Vernon Mountcastle, in the early 1960s, set up to study this set of problems, which he termed "the Mind/Brain problem", by studying the neural basis of perception in the somatic sensory system. His labs at Johns Hopkins were among the first, along with Edward V.Evarts at NIH, to record neural activity from behaving monkeys. Struck with the elegance of SS Stevens approach of magnitude estimation, Mountcastle's group discovered three different modalities of somatic sensation shared one cognitive attribute: in all cases the firing rate of peripheral neurons was linearly related to the strength of the percept elicited. More recently, Ken H. Britten, William T. Newsome, and C. Daniel Salzman have shown that in area MT of monkeys, neurons respond with variability that suggests they are the basis of decision making about direction of motion. They first showed that neuronal rates are predictive of decisions using signal detection theory, and then that stimulation of these neurons could predictably bias the decision. Such studies were followed by Ranulfo Romo in the somatic sensory system, to confirm, using a different percept and brain area, that a small number of neurons in one brain area underlie perceptual decisions.

Other lab groups have followed Mountcastle's seminal work relating cognitive variables to neuronal activity with more complex cognitive tasks. Although monkeys cannot talk about their perceptions, behavioral tasks have been created in which animals made nonverbal reports, for example by producing hand movements. Many of these studies employ perceptual illusions as a way to dissociate sensations (i.e., the sensory information that the brain receives) from perceptions (i.e., how the consciousness interprets them). Neuronal patterns that represent perceptions rather than merely sensory input are interpreted as reflecting the neuronal correlate of consciousness.

Using such design, Nikos Logothetis and colleagues discovered perception-reflecting neurons in the temporal lobe. They created an experimental situation in which conflicting images were presented to different eyes (i.e., binocular rivalry). Under such conditions, human subjects report bistable percepts: they perceive alternatively one or the other image. Logothetis and colleagues trained the monkeys to report with their arm movements which image they perceived. Temporal lobe neurons in Logothetis experiments often reflected what the monkeys' perceived. Neurons with such properties were less frequently observed in the primary visual cortex that corresponds to relatively early stages of visual processing. Another set of experiments using binocular rivalry in humans showed that certain layers of the cortex can be excluded as candidates of the neural correlate of consciousness. Logothetis and colleagues switched the images between eyes during the percept of one of the images. Surprisingly the percept stayed stable. This means that the conscious percept stayed stable and at the same time the primary input to layer 4, which is the input layer, in the visual cortex changed. Therefore, layer 4 can not be a part of the neural correlate of consciousness. Mikhail Lebedev and their colleagues observed a similar phenomenon in monkey prefrontal cortex. In their experiments monkeys reported the perceived direction of visual stimulus movement (which could be an illusion) by making eye movements. Some prefrontal cortex neurons represented actual and some represented perceived displacements of the stimulus. Observation of perception related neurons in prefrontal cortex is consistent with the theory of Christof Koch and Francis Crick who postulated that neural correlate of consciousness resides in prefrontal cortex. Proponents of distributed neuronal processing may likely dispute the view that consciousness has a precise localization in the brain.

Francis Crick wrote a popular book, "The Astonishing Hypothesis", whose thesis is that the neural correlate for consciousness lies in our nerve cells and their associated molecules. Crick and his collaborator Christof Koch have sought to avoid philosophical debates that are associated with the study of consciousness, by emphasizing the search for "correlation" and not "causation".

There is much room for disagreement about the nature of this correlate (e.g., does it require synchronous spikes of neurons in different regions of the brain? Is the co-activation of frontal or parietal areas necessary?). The philosopher David Chalmers maintains that a neural correlate of consciousness, unlike other correlates such as for memory, will fail to offer a satisfactory explanation of the phenomenon; he calls this the hard problem of consciousness.

Cognitive model

From Wikipedia, the free encyclopedia

A cognitive model is an approximation of one or more cognitive processes in humans or other animals for the purposes of comprehension and prediction. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set of equations to software programs that interact with the same tools that humans use to complete tasks (e.g., computer mouse and keyboard). In terms of information processing, cognitive modeling is modeling of human perception, reasoning, memory and action.

Relationship to cognitive architectures

Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable. In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e.g., list learning), how two or more processes interact (e.g., visual search bsc1780 decision making), or making behavioral predictions for a specific task or tool (e.g., how instituting a new software package will affect productivity). Cognitive architectures tend to be focused on the structural properties of the modeled system, and help constrain the development of cognitive models within the architecture. Likewise, model development helps to inform limitations and shortcomings of the architecture. Some of the most popular architectures for cognitive modeling include ACT-R, Clarion, LIDA, and Soar.

History

Cognitive modeling historically developed within cognitive psychology/cognitive science (including human factors), and has received contributions from the fields of machine learning and artificial intelligence among others.

Box-and-arrow models

A number of key terms are used to describe the processes involved in the perception, storage, and production of speech. Typically, they are used by speech pathologists while treating a child patient. The input signal is the speech signal heard by the child, usually assumed to come from an adult speaker. The output signal is the utterance produced by the child. The unseen psychological events that occur between the arrival of an input signal and the production of speech are the focus of psycholinguistic models. Events that process the input signal are referred to as input processes, whereas events that process the production of speech are referred to as output processes. Some aspects of speech processing are thought to happen online—that is, they occur during the actual perception or production of speech and thus require a share of the attentional resources dedicated to the speech task. Other processes, thought to happen offline, take place as part of the child's background mental processing rather than during the time dedicated to the speech task. In this sense, online processing is sometimes defined as occurring in real-time, whereas offline processing is said to be time-free (Hewlett, 1990). In box-and-arrow psycholinguistic models, each hypothesized level of representation or processing can be represented in a diagram by a “box,” and the relationships between them by “arrows,” hence the name. Sometimes (as in the models of Smith, 1973, and Menn, 1978, described later in this paper) the arrows represent processes additional to those shown in boxes. Such models make explicit the hypothesized information- processing activities carried out in a particular cognitive function (such as language), in a manner analogous to computer flowcharts that depict the processes and decisions carried out by a computer program. Box-and-arrow models differ widely in the number of unseen psychological processes they describe and thus in the number of boxes they contain. Some have only one or two boxes between the input and output signals (e.g., Menn, 1978; Smith, 1973), whereas others have multiple boxes representing complex relationships between a number of different information-processing events (e.g., Hewlett, 1990; Hewlett, Gibbon, & Cohen- McKenzie, 1998; Stackhouse & Wells, 1997). The most important box, however, and the source of much ongoing debate, is that representing the underlying representation (or UR). In essence, an underlying representation captures information stored in a child's mind about a word he or she knows and uses. As the following description of several models will illustrate, the nature of this information and thus the type(s) of representation present in the child's knowledge base have captured the attention of researchers for some time. (Elise Baker et al. Psycholinguistic Models of Speech Development and Their Application to Clinical Practice. Journal of Speech, Language, and Hearing Research. June 2001. 44. p 685–702.)

Computational models

A computational model is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation. The system under study is often a complex nonlinear system for which simple, intuitive analytical solutions are not readily available. Rather than deriving a mathematical analytical solution to the problem, experimentation with the model is done by changing the parameters of the system in the computer, and studying the differences in the outcome of the experiments. Theories of operation of the model can be derived/deduced from these computational experiments. Examples of common computational models are weather forecasting models, earth simulator models, flight simulator models, molecular protein folding models, and neural network models.

Symbolic

A symbolic model is expressed in characters, usually non-numeric ones, that require translation before they can be used.

Subsymbolic

A cognitive model is subsymbolic if it is made by constituent entities that are not representations in their turn, e.g., pixels, sound images as perceived by the ear, signal samples; subsymbolic units in neural networks can be considered particular cases of this category.

Hybrid

Hybrid computers are computers that exhibit features of analog computers and digital computers. The digital component normally serves as the controller and provides logical operations, while the analog component normally serves as a solver of differential equations. See more details at hybrid intelligent system.

Dynamical systems

In the traditional computational approach, representations are viewed as static structures of discrete symbols. Cognition takes place by transforming static symbol structures in discrete, sequential steps. Sensory information is transformed into symbolic inputs, which produce symbolic outputs that get transformed into motor outputs. The entire system operates in an ongoing cycle.

What is missing from this traditional view is that human cognition happens continuously and in real time. Breaking down the processes into discrete time steps may not fully capture this behavior. An alternative approach is to define a system with (1) a state of the system at any given time, (2) a behavior, defined as the change over time in overall state, and (3) a state set or state space, representing the totality of overall states the system could be in. The system is distinguished by the fact that a change in any aspect of the system state depends on other aspects of the same or other system states.

A typical dynamical model is formalized by several differential equations that describe how the system's state changes over time. By doing so, the form of the space of possible trajectories and the internal and external forces that shape a specific trajectory that unfold over time, instead of the physical nature of the underlying mechanisms that manifest this dynamics, carry explanatory force. On this dynamical view, parametric inputs alter the system's intrinsic dynamics, rather than specifying an internal state that describes some external state of affairs.

Early dynamical systems

Associative memory

Early work in the application of dynamical systems to cognition can be found in the model of Hopfield networks. These networks were proposed as a model for associative memory. They represent the neural level of memory, modeling systems of around 30 neurons which can be in either an on or off state. By letting the network learn on its own, structure and computational properties naturally arise. Unlike previous models, “memories” can be formed and recalled by inputting a small portion of the entire memory. Time ordering of memories can also be encoded. The behavior of the system is modeled with vectors which can change values, representing different states of the system. This early model was a major step toward a dynamical systems view of human cognition, though many details had yet to be added and more phenomena accounted for.

Language acquisition

By taking into account the evolutionary development of the human nervous system and the similarity of the brain to other organs, Elman proposed that language and cognition should be treated as a dynamical system rather than a digital symbol processor. Neural networks of the type Elman implemented have come to be known as Elman networks. Instead of treating language as a collection of static lexical items and grammar rules that are learned and then used according to fixed rules, the dynamical systems view defines the lexicon as regions of state space within a dynamical system. Grammar is made up of attractors and repellers that constrain movement in the state space. This means that representations are sensitive to context, with mental representations viewed as trajectories through mental space instead of objects that are constructed and remain static. Elman networks were trained with simple sentences to represent grammar as a dynamical system. Once a basic grammar had been learned, the networks could then parse complex sentences by predicting which words would appear next according to the dynamical model.

Cognitive development

A classic developmental error has been investigated in the context of dynamical systems: The A-not-B error is proposed to be not a distinct error occurring at a specific age (8 to 10 months), but a feature of a dynamic learning process that is also present in older children. Children 2 years old were found to make an error similar to the A-not-B error when searching for toys hidden in a sandbox. After observing the toy being hidden in location A and repeatedly searching for it there, the 2-year-olds were shown a toy hidden in a new location B. When they looked for the toy, they searched in locations that were biased toward location A. This suggests that there is an ongoing representation of the toy's location that changes over time. The child's past behavior influences its model of locations of the sandbox, and so an account of behavior and learning must take into account how the system of the sandbox and the child's past actions is changing over time.

Locomotion

One proposed mechanism of a dynamical system comes from analysis of continuous-time recurrent neural networks (CTRNNs). By focusing on the output of the neural networks rather than their states and examining fully interconnected networks, three-neuron central pattern generator (CPG) can be used to represent systems such as leg movements during walking. This CPG contains three motor neurons to control the foot, backward swing, and forward swing effectors of the leg. Outputs of the network represent whether the foot is up or down and how much force is being applied to generate torque in the leg joint. One feature of this pattern is that neuron outputs are either off or on most of the time. Another feature is that the states are quasi-stable, meaning that they will eventually transition to other states. A simple pattern generator circuit like this is proposed to be a building block for a dynamical system. Sets of neurons that simultaneously transition from one quasi-stable state to another are defined as a dynamic module. These modules can in theory be combined to create larger circuits that comprise a complete dynamical system. However, the details of how this combination could occur are not fully worked out.

Modern dynamical systems

Behavioral dynamics

Modern formalizations of dynamical systems applied to the study of cognition vary. One such formalization, referred to as “behavioral dynamics”, treats the agent and the environment as a pair of coupled dynamical systems based on classical dynamical systems theory. In this formalization, the information from the environment informs the agent's behavior and the agent's actions modify the environment. In the specific case of perception-action cycles, the coupling of the environment and the agent is formalized by two functions. The first transforms the representation of the agents action into specific patterns of muscle activation that in turn produce forces in the environment. The second function transforms the information from the environment (i.e., patterns of stimulation at the agent's receptors that reflect the environment's current state) into a representation that is useful for controlling the agents actions. Other similar dynamical systems have been proposed (although not developed into a formal framework) in which the agent's nervous systems, the agent's body, and the environment are coupled together

Adaptive behaviors

Behavioral dynamics have been applied to locomotive behavior. Modeling locomotion with behavioral dynamics demonstrates that adaptive behaviors could arise from the interactions of an agent and the environment. According to this framework, adaptive behaviors can be captured by two levels of analysis. At the first level of perception and action, an agent and an environment can be conceptualized as a pair of dynamical systems coupled together by the forces the agent applies to the environment and by the structured information provided by the environment. Thus, behavioral dynamics emerge from the agent-environment interaction. At the second level of time evolution, behavior can be expressed as a dynamical system represented as a vector field. In this vector field, attractors reflect stable behavioral solutions, where as bifurcations reflect changes in behavior. In contrast to previous work on central pattern generators, this framework suggests that stable behavioral patterns are an emergent, self-organizing property of the agent-environment system rather than determined by the structure of either the agent or the environment.

Open dynamical systems

In an extension of classical dynamical systems theory, rather than coupling the environment's and the agent's dynamical systems to each other, an “open dynamical system” defines a “total system”, an “agent system”, and a mechanism to relate these two systems. The total system is a dynamical system that models an agent in an environment, whereas the agent system is a dynamical system that models an agent's intrinsic dynamics (i.e., the agent's dynamics in the absence of an environment). Importantly, the relation mechanism does not couple the two systems together, but rather continuously modifies the total system into the decoupled agent's total system. By distinguishing between total and agent systems, it is possible to investigate an agent's behavior when it is isolated from the environment and when it is embedded within an environment. This formalization can be seen as a generalization from the classical formalization, whereby the agent system can be viewed as the agent system in an open dynamical system, and the agent coupled to the environment and the environment can be viewed as the total system in an open dynamical system.

Embodied cognition

In the context of dynamical systems and embodied cognition, representations can be conceptualized as indicators or mediators. In the indicator view, internal states carry information about the existence of an object in the environment, where the state of a system during exposure to an object is the representation of that object. In the mediator view, internal states carry information about the environment which is used by the system in obtaining its goals. In this more complex account, the states of the system carries information that mediates between the information the agent takes in from the environment, and the force exerted on the environment by the agents behavior. The application of open dynamical systems have been discussed for four types of classical embodied cognition examples:

  1. Instances where the environment and agent must work together to achieve a goal, referred to as "intimacy". A classic example of intimacy is the behavior of simple agents working to achieve a goal (e.g., insects traversing the environment). The successful completion of the goal relies fully on the coupling of the agent to the environment.
  2. Instances where the use of external artifacts improves the performance of tasks relative to performance without these artifacts. The process is referred to as "offloading". A classic example of offloading is the behavior of Scrabble players; people are able to create more words when playing Scrabble if they have the tiles in front of them and are allowed to physically manipulate their arrangement. In this example, the Scrabble tiles allow the agent to offload working memory demands on to the tiles themselves.
  3. Instances where a functionally equivalent external artifact replaces functions that are normally performed internally by the agent, which is a special case of offloading. One famous example is that of human (specifically the agents Otto and Inga) navigation in a complex environment with or without assistance of an artifact.
  4. Instances where there is not a single agent. The individual agent is part of larger system that contains multiple agents and multiple artifacts. One famous example, formulated by Ed Hutchins in his book Cognition in the Wild, is that of navigating a naval ship.

The interpretations of these examples rely on the following logic: (1) the total system captures embodiment; (2) one or more agent systems capture the intrinsic dynamics of individual agents; (3) the complete behavior of an agent can be understood as a change to the agent's intrinsic dynamics in relation to its situation in the environment; and (4) the paths of an open dynamical system can be interpreted as representational processes. These embodied cognition examples show the importance of studying the emergent dynamics of an agent-environment systems, as well as the intrinsic dynamics of agent systems. Rather than being at odds with traditional cognitive science approaches, dynamical systems are a natural extension of these methods and should be studied in parallel rather than in competition.

Operator (computer programming)

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Operator_(computer_programmin...