Does the Brain Function as a Quantum Phase Computer Using Phase Ternary Computation?

Here we provide evidence that the fundamental basis of nervous communication is derived from a pressure pulse/soliton capable of computation with sufficient temporal precision to overcome any processing errors. Signalling and computing within the nervous system are complex and different phenomena. Action potentials are plastic and this makes the action potential peak an inappropriate fixed point for neural computation, but the action potential threshold is suitable for this purpose. Furthermore, neural models timed by spiking neurons operate below the rate necessary to overcome processing error. Using retinal processing as our example, we demonstrate that the contemporary theory of nerve conduction based on cable theory is inappropriate to account for the short computational time necessary for the full functioning of the retina and by implication the rest of the brain. Moreover, cable theory cannot be instrumental in the propagation of the action potential because at the activation-threshold there is insufficient charge at the activation site for successive ion channels to be electrostatically opened. Deconstruction of the brain neural network suggests that it is a member of a group of Quantum phase computers of which the Turing machine is the simplest: the brain is another based upon phase ternary computation. However, attempts to use Turing based mechanisms cannot resolve the coding of the retina or the computation of intelligence, as the technology of Turing based computers is fundamentally different. We demonstrate that that coding in the brain neural network is quantum based, where the quanta have a temporal variable and a phase-base variable enabling phase ternary computation as previously demonstrated in the retina.

New plasmon-polariton model of the saltatory conduction

ABSTRACTWe propose a new model of the saltatory conduction in myelinated axons. This conduction of the action potential in myelinated axons does not agree with the conventional cable theory, though the latter has satisfactorily explained the electrosignaling in dendrites and in unmyelinated axons. By the development of the wave-type concept of ionic plasmon-polariton kinetics in axon cytosol we have achieved an agreement of the model with observed properties of the saltatory conduction. Some resulting consequences of the different electricity model in the white and the gray matter for nervous system organization have been also outlined.SIGNIFICANCEMost of axons in peripheral nervous system and in white matter of brain and spinal cord are myelinated with the action potential kinetics speed two orders greater than in dendrites and in unmyelinated axons. A decrease of the saltatory conduction velocity by only 10% ceases body functioning. Conventional cable theory, useful for dendrites and unmyelinated axon, does not explain the saltatory conduction (discrepancy between the speed assessed and the observed one is of one order of the magnitude). We propose a new nonlocal collective mechanism of ion density oscillations synchronized in the chain of myelinated segments of plasmon-polariton type, which is consistent with observations. This model explains the role of the myelin in other way than was previously thought.

A METHOD FOR STATIC ANALYSIS OF CABLE-STAYED STRUCTURES SUBJECTED TO IN-PLANE LOADS

Present cable theory which formulated from force balance equation of single cable under self-weight and forms a catenary shape of deflection, that is nonlinear; therefore to determine displacement, deformation and tension forces of the cable and cable-stayed structures we need to provide some additional assumptions of cables and use iteration calculation. This paper presents a new method for static analysis of cable-stayed structures subjected to in-plane loading. By combination of the Gaussian Extreme Principle method and virtual displacement principle, authors to formulate and solve nonlinear equation system of cable-stayed structures, which ensured forces balancing as well as continuity of displacements and deformations of structures. This method allows for simultaneous determination of displacement, deformation and internal forces of cable-stayed structures without any other additional hypothesis, which is different from present cable theory.

Neuronal coupling by endogenous electric fields: cable theory and applications to coincidence detector neurons in the auditory brain stem

The ongoing activity of neurons generates a spatially and time-varying field of extracellular voltage ( Ve). This Ve field reflects population-level neural activity, but does it modulate neural dynamics and the function of neural circuits? We provide a cable theory framework to study how a bundle of model neurons generates Ve and how this Ve feeds back and influences membrane potential ( Vm). We find that these “ephaptic interactions” are small but not negligible. The model neural population can generate Ve with millivolt-scale amplitude, and this Ve perturbs the Vm of “nearby” cables and effectively increases their electrotonic length. After using passive cable theory to systematically study ephaptic coupling, we explore a test case: the medial superior olive (MSO) in the auditory brain stem. The MSO is a possible locus of ephaptic interactions: sounds evoke large (millivolt scale) Ve in vivo in this nucleus. The Ve response is thought to be generated by MSO neurons that perform a known neuronal computation with submillisecond temporal precision (coincidence detection to encode sound source location). Using a biophysically based model of MSO neurons, we find millivolt-scale ephaptic interactions consistent with the passive cable theory results. These subtle membrane potential perturbations induce changes in spike initiation threshold, spike time synchrony, and time difference sensitivity. These results suggest that ephaptic coupling may influence MSO function.

Analytical Solution of a Tapering Cable Equation for Dendrites and Conformal Symmetry

Progress towards detailed characterization of structural and biophysical properties of dendrites emphasizes the importance of finding analytical solutions for more realistic dendrite models with circular cross-section and varying diameter. In this regard, we employ symmetry methods and the passive cable theory to deduce a generalized analytical solution for electric propagation in a family of tapering dendrites. In particular, we study the effect of such tapering geometries on the obtained electric voltage. Simulations using the deduced analytical solution indicate that for a subfamily of tapering profiles neural integration is better than in the stereotypical profile given by a cylinder.