Narrow Results

Oscillatory phenomena in the brain activity and their synchronization are frequently studied using mathematical models and analytic tools derived from nonlinear dynamics. In many experimental situations, however, neural signals have a broadband character and if oscillatory activity is present, its dynamical origin is unknown. To cope with these problems, a framework for detecting nonlinear oscillatory activity in broadband time series is presented. First, a narrow-band oscillatory mode is extracted from a broadband background. Second, it is tested whether the extracted mode is significantly different from linearly filtered noise, modelled as a linear stochastic process possibly passed through a static nonlinear transformation. If a nonlinear oscillatory mode is positively detected, further analysis using nonlinear approaches such as the phase synchronization analysis can potentially bring new information. For linear processes, however, standard approaches such as the coherence analysis are more appropriate and provide sufficient description of underlying interactions with smaller computational effort. The method is illustrated in a numerical example and applied to analyze experimentally obtained human EEG time series from a sleeping subject.

The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly understood. Here, we have used a simple model of afferent excitatory neurons and interneurons with lateral inhibition, reproducing a network topology found in many brain areas from the cerebellum to cortical columns. When endowed with spike-timing dependent plasticity (STDP) at the excitatory input synapses and at the inhibitory interneuron–interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input patterns. The combination of plasticity in lateral inhibitory connections and homeostatic mechanisms in the inhibitory interneurons optimized mutual information (MI) transfer. The storage of multiple complex patterns in plastic interneuron networks could be critical for the generation of sparse representations of information in excitatory neuron populations falling under their control.

A new method, based on the original theory of conservation of sum of kinetic and potential energy defined for prices is proposed and applied on the Dow Jones Industrials Average (DJIA). The general trends averaged over months or years gave a roughly conserved total energy, with three different potential energies, i.e., positive definite quadratic, negative definite quadratic and linear potential energy for exponential rises (and falls), sinusoidal oscillations and parabolic trajectories, respectively. Corresponding expressions for force (impact) are also given.

Information coding by patterns of spike rates is incompatible with the experimental results on fast recognition of figures or scenes, which may be explained only on the basis of a one-spike-per-neuron computation. It had been suggested that coding may be achieved by means of the spikes arrival times. It is shown here that such a coding will be jammed up everytime a perceptive process extends over several spikes, unless the input integrator neurons are periodically reset.

This resetting may be responsible for the periodic burst firing and the oscillations of the local field potential which have been experimentally found in the cases of motion detection or of sustained attention. A presynchronisation process is required, for the initial coding and for scene fragmentation, and may be achieved by an electrical interneuronal coupling, which is shown to be both realistic and efficient. Information decoding may be implemented by neurons operating in a correlator mode, which is analysed.

We derive the relation between the amplitudes of short-baseline appearance and disappearance oscillations in $3+N_s$ neutrino mixing schemes which is the origin of the appearance–disappearance tension that is found from the analysis of the existing data in any $3+N_s$ neutrino mixing scheme. We illustrate the power of the relation to reveal the appearance–disappearance tension in the cases of $3+1$ and $3+2$ mixing using the results of global fits of short-baseline neutrino oscillation data.

The observed absence of the small-t oscillations in differential cross-section of the elastic scattering is considered as a consequence of the reflective scattering mode appearance at the highest energy of the LHC $\sqrt{s}=13$TeV.

This paper reviews the current status and the physics program of the OPERA experiment with the future CNGS long baseline neutrino beam from CERN to the Gran Sasso Laboratory. The expected background, the expected number of signal events at the atmospheric Δm² scale and the sensitivity for both ν_μ↔ν_τ and ν_μ↔ν_e oscillations are given.

Ultrahigh energy neutrinos can provide important information about the distant astronomical objects and the origin of the Universe. Precise knowledge about neutrino interactions and production rates is essential for estimating background, expected fluxes and detection probabilities. In this paper we review the applications of the high energy QCD to the calculations of the interaction cross-sections of the neutrinos. We also study the production of the ultrahigh energy neutrinos in the atmosphere due to the charm and beauty decays.

Among several interesting motivations for experimenting with orthopositronium (o-Ps) in vacuum the most exciting one is probably related to the search for the dark matter of a mirror-type. The mirror matter is predicted to exist if parity is an unbroken symmetry of the vacuum. The existence of the mirror matter, which in addition to gravity communicates with our world through photon-mirror photon mixing, would result in orthopositronium (o-Ps) to mirror orthopositronium (o-Ps') oscillations. The experimental signature of this effect is the invisible decay of o-Ps in vacuum.

We discuss an experiment to search for o-Ps→invisible decay in vacuum with a sensitivity in the branching ratio Br(o-Ps→invisible)≃10^-7, which is an order of magnitude better than the present limit on this decay mode from the Big Bang Nucleosynthesis. Details of the design are presented. The effect of various environments on o-Ps→o-Ps' oscillation probability is also discussed.

A new design of a high-efficiency pulsed slow positron beam for experiments with orthopositronium in vacuum is described. The new method is based on a RF waveform pulse applied to a double gap buncher system for adjusting the time-of-flight of positrons. Simulations show that compression of positrons emitted from the moderator during 300 ns into a pulse of 2 ns width is achievable. Preliminary results on the design and requirements for the pulsing system components are presented.

The MINERνA experiment at Fermilab will use a fully-active scintillator based fine grained neutrino detector and the high rate NuMI neutrino beam. MINERνA will measure low energy neutrino interaction properties and cross sections to a new level of precision. These measurements will be critical input to present and future accelerator-based neutrino oscillation experiments in this energy range.

Ab initio theoretical calculations of magnetic moments near the interfaces of 3d ferromagnetic transition metals were performed using the self-consistent interface Green's function technique based on linear-muffin-tin orbitals (LMTO) method within the tight-binding (TB) and atomic sphere approximation together with local-spin-density approximation. We have also made supercell spin-polarized (SP) band structure calculations of (1 0 0) Fe/Co interface in the framework of TB-LMTO method, in order to take into account structural deformations and estimate their influence on the magnetic moments near that interface. Our results for layer magnetic moments near Fe/Co, Fe/Ni and Ni/Co interfaces did not show any oscillating behavior, contrary to the recent findings for the magnetic moment profile near Fe/Co interface deduced from the perturbed angular correlation measurements of hyperfine fields. The reasons for this disagreement have been discussed and a comparison with earlier experimental and theoretical results was made.

The self-energy is received using the theory group and field techniques, based on the wave functions of the classes of point symmetry group and accounting for the two-particle system. It contains components responsible not only for relaxation processes but also for the oscillating ones, caused by a different degree of occupation of the class of point symmetry group by particles of the structure. Analyzing the character of energy oscillations depending on the degree of the class occupation, the mechanisms of diffusion, catalysis, chemical reactions and Le-Shatelje principle are described.

We investigate the dynamical behaviour of the genetic feedback loop present in the signalling network of the transcription factor NF-κB. This transcription factor is one of the most important regulators in mammalian cells, involved in a large number of cellular responses. We find that when the external stimulus is constant, the concentration of NF-κB inside the cell nucleus is either stationary or shows spiky oscillations. If the external stimulus is time dependent, the response can be more intricate. Here, we consider the response to pulsed and periodic stimuli. In the latter case the response can be chaotic with the NF-κB concentration converging to a strange attractor. The corresponding bifurcation diagram is also presented.

By developing a three-mode approximation, we derive dynamical equations governing a condensate in a symmetric three-well potential. Based on the dynamical equations, we numerically simulate the dynamical properties of a Bose–Einstein condensate in a symmetric three-well potential. It is shown that, for the zero-phase mode, atomic population in each well oscillates periodically with the amplitude dependent on the initial conditions, and there may exist a critical initial distribution. However, for the π-phase mode, it is possible for the system to exhibit a set of behaviors directly dependent on the ratio between the nonlinearity induced by the atom-atom interactions and the coupling of neighboring wells.

Oblique light propagation through a chiral photonic crystal (PC) layer with gradient parameters of modulation is considered. The problem is solved by Ambartsumian's layer addition modified method. It is shown that suppressing of diffraction oscillations near the photonic band gap (PBG) is possible at certain conditions. Thus, at certain conditions, the spectra for the finite PC layer is the same as that for the half space.

A deterministic model is introduced in terms of conservation principles to describe the (qualitative) price dynamics of a stock market. It is shown how the fundamentalist and chartist patterns of the trader behavior affect the price dynamics. The model can display complex oscillatory behavior with transient erratic oscillations, which resembles the behavior found in actual price dynamics. By means of numerical simulations, it is shown that the model can produce price time-series with statistics similar to that found in real financial data.

The present report describes the dynamic foundations of long-standing experimental work in the field of oscillatory dynamics in the human and animal brain. It aims to show the role of multiple oscillations in the integrative brain function, memory, and complex perception by a recently introduced conceptional framework: the super-synergy in the whole brain. Results of recent experiments related to the percept of the grandmother-face support our concept of super-synergy in the whole brain in order to explain manifestation of Gestalts and Memory-Stages. This report may also provide new research avenues in macrodynamics of the brain.

The general problem of brain mechanisms involved in perception can now be studied directly by means of new analysis–methods for the activity of large population of neurons. These methods range from indirect means of measuring changes in cerebral blood flow in local regions of the human cortex (functional magnetic resonance imaging, fMRI), or changes in the electrical activity of the human brain with EEG-recording with topological distributed macroelectrodes, to the use of chronically implanted multiple microelectrodes in primates. fMRI has the disadvantage of low temporal resolution and with multiple microelectrodes long distance measurements cannot yet be properly performed. Accordingly, recording of macro-activity (EEG/ERP or MEG) with a time resolution of millisecond-range is the most possibly adequate method to measure the dynamic properties of memory and the integrative brain function.

Since neuroscientists have come to the general conclusion that large numbers of different brain regions have to cooperate for any brain function, the analysis of relationships between different regions of the brain is becoming more and more important.

Before new progresses and importance of EEG studies research became clear, scientists working with macrodynamics of the brain had a long way to go, in order to elucidate brain functioning. In this tutorial report we explain in a narrative way the developments leading to the concept of Macrodynamics in search of an integrative brain function. Moreover, elements of a brain theory, which we call neurons-brain theory describing the dynamics of electrical activity in the whole brain, are introduced. The concept of superbinding in integrative brain function, which emerged from experimental data, is a consequence of this theory.

Current induced oscillations of a space clamped neuron action potential demonstrates a bifurcation scenario originally encapsulated by the four-dimensional Hodgkin–Huxley equations. These oscillations were subsequently described by the two-dimensional FitzHugh–Nagumo Equations in close agreement with the Hodgkin–Huxley theory. It is shown that the FitzHugh–Nagumo equations can to close approximation be reduced to a generalized van der Pol oscillator externally driven by the current. The current functions as an external constant force driving the action potential. As a consequence approximate analytic expressions are derived which predict the bifurcation scenario, the amplitudes of the oscillations and the oscillation periods in terms of the current and the physiological constants of the FitzHugh–Nagumo model. A second reduction permits explicit analytic solution and results in a spiking model which can be multiply coupled and extended to include the dynamics of phase locking, entrainment and chaos characteristic of time-dependent synaptic inputs.