Quantum-like model of processing of information in the brain based on classical electromagnetic field

We propose a model of quantum-like (QL) processing of mental information. This model is based on quantum information theory. However, in contrast to models of "quantum physical brain" reducing mental activity (at least at the highest level) to quantum physical phenomena in the brain, our model matches well with the basic neuronal paradigm of the cognitive science. QL information processing is based (surprisingly) on classical electromagnetic signals induced by joint activity of neurons. This novel approach to quantum information is based on representation of quantum mechanics as a version of classical signal theory which was recently elaborated by the author. The brain uses the QL representation (QLR) for working with abstract concepts; concrete images are described by classical information theory. Two processes, classical and QL, are performed parallely. Moreover, information is actively transmitted from one representation to another. A QL concept given in our model by a density operator can generate a variety of concrete images given by temporal realizations of the corresponding (Gaussian) random signal. This signal has the covariance operator coinciding with the density operator encoding the abstract concept under consideration. The presence of various temporal scales in the brain plays the crucial role in creation of QLR in the brain. Moreover, in our model electromagnetic noise produced by neurons is a source of superstrong QL correlations between processes in different spatial domains in the brain; the binding problem is solved on the QL level, but with the aid of the classical background fluctuations.     

Quantum-like model of cognitive decision making and information processing

In this paper we offer the quantum-like (QL) representation of the Shafir–Tversky statistical effect which is well known in cognitive psychology. We apply the so-called contextual approach. We consider the Shafir–Tversky effect to result from mixing statistical data obtained in incompatible contexts which are involved, e.g. in Prisoner’s Dilemma or in more general games in which the disjunction effect can be found. As a consequence, the law of total probability is violated for the experimental data obtained in experiments on cognitive psychology by Shafir and Tversky [Shafir, E., Tversky, A., 1992. Thinking through uncertainty: nonconsequential reasoning and choice. Cogn. Psychol. 24, 449–474] as well as Tversky and Shafir [Tversky, A., Shafir, E., 1992. The disjunction effect in choice under uncertainty. Psychol. Sci. 3, 305–309]. Moreover, we can find a numerical measure of contextual incompatibility (the so-called coefficient of interference) as well as represent contexts which are involved in Prisoner’s Dilemma (PD) by probability amplitudes—normalized vectors (“mental wave functions”). We remark that statistical data from Shafir and Tversky [Shafir, E., Tversky, A., 1992. Thinking through uncertainty: nonconsequential reasoning and choice. Cogn. Psychol. 24, 449–474] and Tversky and Shafir [Tversky, A., Shafir, E., 1992. The disjunction effect in choice under uncertainty. Psychol. Sci. 3, 305–309] experiments differ crucially from the point of view of mental interference. The second one exhibits the conventional trigonometric (cos?$\cos ?$-type) interference while the first one exhibits even the so-called hyperbolic (cosh?$\cosh ?$-type) interference. We discuss the QL processing of information by cognitive systems, especially, the QL decision making and both classical and QL rationality and ethics.     

Quantum-like formalism for cognitive measurements

We develop a quantum formalism (Hilbert space probabilistic calculus) for measurements performed over cognitive systems. In particular, this formalism is used for mathematical modelling of the functioning of consciousness as a self-measuring quantum-like system. By using this formalism, we could predict averages of cognitive observables. Reflecting the basic idea of neurophysiological and psychological studies on a hierarchic structure of cognitive processes, we use p-adic hierarchic trees as a mathematical model of a mental space. We also briefly discuss the general problem of the choice of an adequate mental geometry.     

Quantum-like interference effect in gene expression: glucose-lactose destructive interference

In this note we illustrate on a few examples of cells and proteins behavior that microscopic biological systems can exhibit a complex probabilistic behavior which cannot be described by classical probabilistic dynamics. These examples support authors conjecture that behavior of microscopic biological systems can be described by quantum-like models, i.e., models inspired by quantum-mechanics. At the same time we do not couple quantum-like behavior with quantum physical processes in bio-systems. We present arguments that such a behavior can be induced by information complexity of even smallest bio-systems, their adaptivity to context changes. Although our examples of the quantum-like behavior are rather simple (lactose-glucose interference in E. coli growth, interference effect for differentiation of tooth stem cell induced by the presence of mesenchymal cell, interference in behavior of PrP(C) and PrP(Sc) prions), these examples may stimulate the interest in systems biology to quantum-like models of adaptive dynamics and lead to more complex examples of nonclassical probabilistic behavior in molecular biology.     

Quantum-like behavior without quantum physics I

Recently there has been much interest in the possible quantum-like behavior of the human brain in such functions as cognition, the mental lexicon, memory, etc., producing a vast literature. These studies are both empirical and theoretical, the tenets of the theory in question being mainly, and apparently inevitably, those of quantum physics itself, for lack of other arenas in which quantum-like properties are presumed to obtain. However, attempts to explain this behavior on the basis of actual quantum physics going on at the atomic or molecular level within some element of brain or neuronal anatomy (other than the ordinary quantum physics that underlies everything), do not seem to survive much scrutiny. Moreover, it has been found empirically that the usual physics-like Hilbert space model seems not to apply in detail to human cognition in the large. In this paper we lay the groundwork for a theory that might explain the provenance of quantum-like behavior in complex systems whose internal structure is essentially hidden or inaccessible. The approach is via the logic obeyed by these systems which is similar to, but not identical with, the logic obeyed by actual quantum systems. The results reveal certain effects in such systems which, though quantum-like, are not identical to the kinds of quantum effects found in physics. These effects increase with the size of the system.     

Quantum-like model of brain's functioning: decision making from decoherence

We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in a complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices (representing mental states). This equilibrium state determines Alice's mixed (i.e., probabilistic) strategy. We use a master equation in which quantum physics describes the process of decoherence as the result of interaction with environment. Thus our model is a model of thinking through decoherence of the initially pure mental state. Decoherence is induced by the interaction with memory and the external mental environment. We study (numerically) the dynamics of quantum entropy of Alice's mental state in the process of decision making. We also consider classical entropy corresponding to Alice's choices. We introduce a measure of Alice's diffidence as the difference between classical and quantum entropies of Alice's mental state. We see that (at least in our model example) diffidence decreases (approaching zero) in the process of decision making. Finally, we discuss the problem of neuronal realization of quantum-like dynamics in the brain; especially roles played by lateral prefrontal cortex or/and orbitofrontal cortex.     

"Either-or" two-slit interference: stable coherent propagation of individual photons through separate slits

In quantum theory, nothing that is observable, be it physical, chemical, or biological, is separable from the observer. Furthermore, ". all possible knowledge concerning that object is given by its wave function" (Wigner, E. 1967. Symmetries and Reflections. Indiana University Press, Bloomington, IN), which can only describe probabilities of future events. In physical systems, quantum mechanical probabilistic events that are microscopic must, in turn, account for macroscopic events that are associated with a greater degree of certainty. In biological systems, probabilistic statistical mechanical events, such as secretion of microscopic synaptic vesicles, must account for macroscopic postsynaptic potentials; probabilistic single-channel events sum to produce a macroscopic ionic current across a cell membrane; and bleaching of rhodopsin molecules (responsible for quantal potential "bumps") produces a photoreceptor generator potential. Among physical systems, a paradigmatic example of how quantum theory applies to the observation of events concerns the interactions of particles (e.g., photons, electrons) with the two-slit apparatus to generate an interference pattern from a single common light source. For two-slit systems that use two independent laser sources with brief (<1 ms) intervals of mutual coherence (Paul, H. 1986. Rev. Modern Phys. 58:209-231), each photon has been considered to arise from both beams and has a probability amplitude to pass through each of the two slits. Here, a single laser source two-slit interference system was constructed so that each photon has a probability amplitude to pass through only one or the other, but not both slits. Furthermore, all photons passing through one slit could be distinguished from all photons passing through the other slit before their passage. This "either-or" system produced a stable interference pattern indistinguishable from the interference produced when both slits were accessible to each photon. Because this system excludes the interaction of one photon with both slits, phase correlation of photon movements derives from the "entanglement" of all photon wave functions due to their dependence on a common laser source. Because a laser source (as well as Young's original point source) will have stable time-averaged spatial coherence even at low intensities, the "either-or" two-slit interference can result from distinct individual photons passing one at a time through one or the other slit-rather than wave-like behavior of individual photons. In this manner, single, successive photons passing through separate slits will assemble over time in phase-correlated wave distributions that converge in regions of low and high probability.     

The philosophical "mind-body problem" and its relevance for the relationship between psychiatry and the neurosciences

Parallel to psychiatry, "philosophy of mind" investigates the relationship between mind (mental domain) and body/brain (physical domain). Unlike older forms of philosophy of mind, contemporary analytical philosophy is not exclusively based on introspection and conceptual analysis, but also draws upon the empirical methods and findings of the sciences. This article outlines the conceptual framework of the "mind-body problem" as formulated in contemporary analytical philosophy and argues that this philosophical debate has potentially far-reaching implications for psychiatry as a clinical-scientific discipline, especially for its own autonomy and its relationship to neurology/neuroscience. This point is illustrated by a conceptual analysis of the five principles formulated in Kandel's 1998 article "A New Intellectual Framework for Psychiatry." Kandel's position in the philosophical mind-body debate is ambiguous, ranging from reductive physicalism (psychophysical identity theory) to non-reductive physicalism (in which the mental "supervenes" on the physical) to epiphenomenalist dualism or even emergent dualism. We illustrate how these diverging interpretations result in radically different views on the identity of psychiatry and its relationship with the rapidly expanding domain of neurology/neuroscience.     

Quantum-like model of behavioral response computation using neural oscillators

In this paper we propose the use of neural interference as the origin of quantum-like effects in the brain. We do so by using a neural oscillator model consistent with neurophysiological data. The model used was shown elsewhere to reproduce well the predictions of behavioral stimulus-response theory. The quantum-like effects are brought about by the spreading activation of incompatible oscillators, leading to an interference-like effect mediated by inhibitory and excitatory synapses.     

Bio-computational model of object-recognition: quantum Hebbian processing with neurally shaped Gabor wavelets

Theoretical and simulational evidence, as well as experimental indications, are accumulating that quantum associative memory and imaging are possible. We compare these data with biological evidence, since we find them to a significant extent compatible. This paper presents a computationally implementable integrative model of appearance-based viewpoint-invariant recognition of objects. The neuro-quantum hybrid model incorporates neural processing up to V1 and quantum associative processing in V1, achieving together an object-recognition result in V2 and ITC. Results of our simulation of the central quantum-like parts of the bio-model, receiving neurally pre-processed inputs, are presented. This part contains our original simulated storage by multiple quantum interference of image-encoding Gabor wavelets done in a Hebbian way, especially using the Griniasty et al. pose-sequence learning rule.     

Extracting representations of cognition across neuroimaging studies improves brain decoding

Cognitive brain imaging is accumulating datasets about the neural substrate of many different mental processes. Yet, most studies are based on few subjects and have low statistical power. Analyzing data across studies could bring more statistical power; yet the current brain-imaging analytic framework cannot be used at scale as it requires casting all cognitive tasks in a unified theoretical framework. We introduce a new methodology to analyze brain responses across tasks without a joint model of the psychological processes. The method boosts statistical power in small studies with specific cognitive focus by analyzing them jointly with large studies that probe less focal mental processes. Our approach improves decoding performance for 80% of 35 widely-different functional-imaging studies. It finds commonalities across tasks in a data-driven way, via common brain representations that predict mental processes. These are brain networks tuned to psychological manipulations. They outline interpretable and plausible brain structures. The extracted networks have been made available; they can be readily reused in new neuro-imaging studies. We provide a multi-study decoding tool to adapt to new data.     

The neural correlates of problem states: testing FMRI predictions of a computational model of multitasking

Background

It has been shown that people can only maintain one problem state, or intermediate mental representation, at a time. When more than one problem state is required, for example in multitasking, performance decreases considerably. This effect has been explained in terms of a problem state bottleneck.

Methodology

In the current study we use the complimentary methodologies of computational cognitive modeling and neuroimaging to investigate the neural correlates of this problem state bottleneck. In particular, an existing computational cognitive model was used to generate a priori fMRI predictions for a multitasking experiment in which the problem state bottleneck plays a major role. Hemodynamic responses were predicted for five brain regions, corresponding to five cognitive resources in the model. Most importantly, we predicted the intraparietal sulcus to show a strong effect of the problem state manipulations.

Conclusions

Some of the predictions were confirmed by a subsequent fMRI experiment, while others were not matched by the data. The experiment supported the hypothesis that the problem state bottleneck is a plausible cause of the interference in the experiment and that it could be located in the intraparietal sulcus.     

A theoretical model of phase transitions in the human brain

An experiment using a multisensor SQUID (superconducting quantum interference device) array was performed by Kelso and colleagues (1992) which combined information from three different sources: perception, motor response, and brain signals. When an acoustic stimulus frequency is changed systematically, a spontaneous transition in coordination occurs at a critical frequency in both motor behavior and brain signals. Qualitatively analogous transitions are known for physical and biological systems such as changes in the coordination of human hand movements (Kelso 1981, 1984). In this paper we develop a theoretical model based on methods from the interdisciplinary field of synergetics (Haken 1983, 1987) and nonlinear oscillator theory that reproduces the main experimental features very well and suggests a formulation of a fundamental biophysical coupling. Received: 8 September 1993     

Nutritional modulation of cognitive function and mental health

The important role of diet in cardiometabolic health is generally well recognised; for mental health, it is not so well understood. However, lifestyle risk factors for poor physical health are the same risk factors for mental illness, including poor diet. This is reflected by the high level of poor physical health in people with mental illness. Mediterranean, whole food diets have been associated with reduced risk for chronic disease, but very little research has investigated their mental health benefits. We provide a model for the pathways by which food components provided by a Mediterranean-style diet can facilitate healthy brain function. We then review evidence for the role of selected nutrients/food components — antioxidants, omega-3 fatty acids and B vitamins — in the brain and, hence, modulation of cognitive function and mental health. Converging evidence indicates multiple pathways by which these nutrients can assist in brain function, drawing from studies investigating them in isolation. There is very little work done on synergistic actions of nutrients and whole diets, highlighting a need for human intervention studies investigating benefits of Mediterranean-style diets for mental, as well as cardiometabolic health.     

Cardiac cell: a biological laser?

We present a new concept of cardiac cells based on an analogy with lasers, practical implementations of quantum resonators. In this concept, each cardiac cell comprises a network of independent nodes, characterised by a set of discrete energy levels and certain transition probabilities between them. Interaction between the nodes is given by threshold-limited energy transfer, leading to quantum-like behaviour of the whole network. We propose that in cardiomyocytes, during each excitation-contraction coupling cycle, stochastic calcium release and the unitary properties of ionic channels constitute an analogue to laser active medium prone to "population inversion" and "spontaneous emission" phenomena. This medium, when powered by an incoming threshold-reaching voltage discharge in the form of an action potential, responds to the calcium influx through L-type calcium channels by stimulated emission of Ca2+ ions in a coherent, synchronised and amplified release process known as calcium-induced calcium release. In parallel, phosphorylation-stimulated molecular amplification in protein cascades adds tuneable features to the cells. In this framework, the heart can be viewed as a coherent network of synchronously firing cardiomyocytes behaving as pulsed laser-like amplifiers, coupled to pulse-generating pacemaker master-oscillators. The concept brings a new viewpoint on cardiac diseases as possible alterations of "cell lasing" properties.     

Thinking in circuits: toward neurobiological explanation in cognitive neuroscience

Cognitive theory has decomposed human mental abilities into cognitive (sub) systems, and cognitive neuroscience succeeded in disclosing a host of relationships between cognitive systems and specific structures of the human brain. However, an explanation of why specific functions are located in specific brain loci had still been missing, along with a neurobiological model that makes concrete the neuronal circuits that carry thoughts and meaning. Brain theory, in particular the Hebb-inspired neurocybernetic proposals by Braitenberg, now offers an avenue toward explaining brain–mind relationships and to spell out cognition in terms of neuron circuits in a neuromechanistic sense. Central to this endeavor is the theoretical construct of an elementary functional neuronal unit above the level of individual neurons and below that of whole brain areas and systems: the distributed neuronal assembly (DNA) or thought circuit (TC). It is shown that DNA/TC theory of cognition offers an integrated explanatory perspective on brain mechanisms of perception, action, language, attention, memory, decision and conceptual thought. We argue that DNAs carry all of these functions and that their inner structure (e.g., core and halo subcomponents), and their functional activation dynamics (e.g., ignition and reverberation processes) answer crucial localist questions, such as why memory and decisions draw on prefrontal areas although memory formation is normally driven by information in the senses and in the motor system. We suggest that the ability of building DNAs/TCs spread out over different cortical areas is the key mechanism for a range of specifically human sensorimotor, linguistic and conceptual capacities and that the cell assembly mechanism of overlap reduction is crucial for differentiating a vocabulary of actions, symbols and concepts.     

Toward an adequate mathematical model of mental space: Conscious/unconscious dynamics on m-adic trees

We try to perform geometrization of cognitive science and psychology by representing information states of cognitive systems by points of mental space given by a hierarchic m-adic tree. Associations are represented by balls and ideas by collections of balls. We consider dynamics of ideas based on lifting of dynamics of mental points. We apply our dynamical model for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1–3, we consider cognitive systems with increasing complexity of psychological behavior determined by structure of flows of associations and ideas.     

Classical and quantum dynamics on p-adic trees of ideas

We propose mathematical models of information processes of unconscious and conscious thinking (based on p-adic number representation of mental spaces). Unconscious thinking is described by classical cognitive mechanics (which generalizes Newton's mechanics). Conscious thinking is described by quantum cognitive mechanics (which generalizes the pilot wave model of quantum mechanics). The information state and motivation of a conscious cognitive system evolve under the action of classical information forces and a new quantum information force, namely, conscious force. Our model might provide mathematical foundations for some cognitive and psychological phenomena: collective conscious behavior, connection between physiological and mental processes in a biological organism, Freud's psychoanalysis, hypnotism, homeopathy. It may be used as the basis of a model of conscious evolution of life.     

Toward an adequate mathematical model of mental space: conscious/unconscious dynamics on m-adic trees

We try to perform geometrization of cognitive science and psychology by representing information states of cognitive systems by points of mental space given by a hierarchic m-adic tree. Associations are represented by balls and ideas by collections of balls. We consider dynamics of ideas based on lifting of dynamics of mental points. We apply our dynamical model for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1–3, we consider cognitive systems with increasing complexity of psychological behavior determined by structure of flows of associations and ideas.