Nonlinear brain dynamics and many-body field dynamics

We report measurements of the brain activity of subjects engaged in behavioral exchanges with their environments. We observe brain states which are characterized by coordinated oscillation of populations of neurons that are changing rapidly with the evolution of the meaningful relationship between the subject and its environment, established and maintained by active perception. Sequential spatial patterns of neural activity with high information content found in sensory cortices of trained animals between onsets of conditioned stimuli and conditioned responses resemble cinematographic frames. They are not readily amenable to description either with classical integrodifferential equations or with the matrix algebras of neural networks. Their modeling is provided by field theory from condensed matter physics.Comment: 8 pages, Invited talk presented at Fr\"ohlich Centenary International Symposium "Coherence and Electromagnetic Fields in Biological Systems", July 1-4, 2005, Prague, Czech Republi

The Nature of the Chemical Process. 1. Symmetry Evolution - Revised Information Theory, Similarity Principle and Ugly Symmetry

Three laws of information theory have been proposed. Labeling by introducing nonsymmetry and formatting by introducing symmetry are defined. The function L (L=lnw, w is the number of microstates, or the sum of entropy and information, L=S+I) of the universe is a constant (the first law of information theory). The entropy S of the universe tends toward a maximum (the second law law of information theory). For a perfect symmetric static structure, the information is zero and the static entropy is the maximum (the third law law of information theory). Based on the Gibbs inequality and the second law of the revised information theory we have proved the similarity principle (a continuous higher similarity-higher entropy relation after the rejection of the Gibbs paradox) and proved the Curie-Rosen symmetry principle (a higher symmetry-higher stability relation) as a special case of the similarity principle. Some examples in chemical physics have been given. Spontaneous processes of all kinds of molecular interaction, phase separation and phase transition, including symmetry breaking and the densest molecular packing and crystallization, are all driven by information minimization or symmetry maximization. The evolution of the universe in general and evolution of life in particular can be quantitatively considered as a series of symmetry breaking processes. The two empirical rules - similarity rule and complementarity rule - have been given a theoretical foundation. All kinds of periodicity in space and time are symmetries and contribute to the stability. Symmetry is beautiful because it renders stability. However, symmetry is in principle ugly because it is associated with information loss.Comment: 29 pages, 14 figure

Nonlinear brain dynamics as macroscopic manifestation of underlying many-body field dynamics

Neural activity patterns related to behavior occur at many scales in time and space from the atomic and molecular to the whole brain. Here we explore the feasibility of interpreting neurophysiological data in the context of many-body physics by using tools that physicists have devised to analyze comparable hierarchies in other fields of science. We focus on a mesoscopic level that offers a multi-step pathway between the microscopic functions of neurons and the macroscopic functions of brain systems revealed by hemodynamic imaging. We use electroencephalographic (EEG) records collected from high-density electrode arrays fixed on the epidural surfaces of primary sensory and limbic areas in rabbits and cats trained to discriminate conditioned stimuli (CS) in the various modalities. High temporal resolution of EEG signals with the Hilbert transform gives evidence for diverse intermittent spatial patterns of amplitude (AM) and phase modulations (PM) of carrier waves that repeatedly re-synchronize in the beta and gamma ranges at near zero time lags over long distances. The dominant mechanism for neural interactions by axodendritic synaptic transmission should impose distance-dependent delays on the EEG oscillations owing to finite propagation velocities. It does not. EEGs instead show evidence for anomalous dispersion: the existence in neural populations of a low velocity range of information and energy transfers, and a high velocity range of the spread of phase transitions. This distinction labels the phenomenon but does not explain it. In this report we explore the analysis of these phenomena using concepts of energy dissipation, the maintenance by cortex of multiple ground states corresponding to AM patterns, and the exclusive selection by spontaneous breakdown of symmetry (SBS) of single states in sequences.Comment: 31 page

Science is perception: what can our sense of smell tell us about ourselves and the world around us?

Human sensory processes are well understood: hearing, seeing, perhaps even tasting and touch—but we do not understand smell—the elusive sense. That is, for the others we know what stimuli causes what response, and why and how. These fundamental questions are not answered within the sphere of smell science; we do not know what it is about a molecule that … smells. I report, here, the status quo theories for olfaction, highlighting what we do not know, and explaining why dismissing the perception of the input as ‘too subjective’ acts as a roadblock not conducive to scientific inquiry. I outline the current and new theory that conjectures a mechanism for signal transduction based on quantum mechanical phenomena, dubbed the ‘swipe card’, which is perhaps controversial but feasible. I show that such lines of thinking may answer some questions, or at least pose the right questions. Most importantly, I draw links and comparisons as to how better understanding of how small (10’s of atoms) molecules can interact so specially with large (10 000’s of atoms) proteins in a way that is so integral to healthy living. Repercussions of this work are not just important in understanding a basic scientific tool used by us all, but often taken for granted, it is also a step closer to understanding generic mechanisms between drug and receptor, for example

Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments.\ud \ud \ud KEYWORDS: Emergence of Life and Human Consciousness;\ud Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. \ud \u

Clinical characterization of 66 patients with congenital retinal disease due to the deep-intronic c.2991+1655A>G mutation in CEP290

Purpose: To describe the phenotypic spectrum of retinal disease caused by the c.2991+1655A>G mutation in CEP290 and to compare disease severity between homozygous and compound heterozygous patients. Methods: Medical records were reviewed for best-corrected visual acuity (BCVA), age of onset, fundoscopy descriptions. Foveal outer nuclear layer (ONL) and ellipsoid zone (EZ) presence was assessed using spectral-domain optical coherence tomography (SD-OCT). Differences between compound heterozygous and homozygous patients were analyzed based on visual performance and visual development. Results: A total of 66 patients were included. The majority of patients had either light perception or no light perception. In the remaining group of 14 patients, median BCVA was 20/195 Snellen (0.99 LogMAR; range 0.12-1.90) for the right eye, and 20/148 Snellen (0.87 LogMAR; range 0.22-1.90) for the left. Homozygous patients tended to be more likely to develop light perception compared to more severely affected compound heterozygous patients (P = 0.080) and are more likely to improve from no light perception to light perception (P = 0.022) before the age of 6 years. OCT data were available in 12 patients, 11 of whom had retained foveal ONL and EZ integrity up to 48 years (median 23 years) of age. Conclusions: Homozygous patients seem less severely affected compared to their compound-heterozygous peers. Improvement of visual function may occur in the early years of life, suggesting a time window for therapeutic intervention up to the approximate age of 17 years. This period may be extended by an intact foveal ONL and EZ on OCT

The face, beauty, and symmetry: Perceiving asymmetry in beautiful faces

The relationship between bilateral facial symmetry and beauty remains to be clarified. Here, straight head-on photographs of “beautiful” faces from the collections of professional modeling agencies were selected. First, beauty ratings were obtained for these faces. Then, the authors created symmetrical left-left and right-right composites of the beautiful faces and asked a new group of subjects to choose the most attractive pair member. “Same” responses were allowed. No difference between the left-left and right-right composites was revealed but significant differences were obtained between “same” and the left-left or right-right. These results show that subjects detected asymmetry in beauty and suggest that very beautiful faces can be functionally asymmetrical