Neural Information Processing: between synchrony and chaos

The brain is characterized by performing many different processing tasks ranging from elaborate processes such as pattern recognition, memory or decision-making to more simple functionalities such as linear filtering in image processing. Understanding the mechanisms by which the brain is able to produce such a different range of cortical operations remains a fundamental problem in neuroscience. Some recent empirical and theoretical results support the notion that the brain is naturally poised between ordered and chaotic states. As the largest number of metastable states exists at a point near the transition, the brain therefore has access to a larger repertoire of behaviours. Consequently, it is of high interest to know which type of processing can be associated with both ordered and disordered states. Here we show an explanation of which processes are related to chaotic and synchronized states based on the study of in-silico implementation of biologically plausible neural systems. The measurements obtained reveal that synchronized cells (that can be understood as ordered states of the brain) are related to non-linear computations, while uncorrelated neural ensembles are excellent information transmission systems that are able to implement linear transformations (as the realization of convolution products) and to parallelize neural processes. From these results we propose a plausible meaning for Hebbian and non-Hebbian learning rules as those biophysical mechanisms by which the brain creates ordered or chaotic ensembles depending on the desired functionality. The measurements that we obtain from the hardware implementation of different neural systems endorse the fact that the brain is working with two different states, ordered and chaotic, with complementary functionalities that imply non-linear processing (synchronized states) and information transmission and convolution (chaotic states)

Semi-classical spin dynamics of the antiferromagnetic Heisenberg model on the kagome lattice

We investigate the dynamical properties of the classical antiferromagnetic Heisenberg model on the kagome lattice using a combination of Monte Carlo and molecular dynamics simulations. We find that frustration induces a distribution of timescales in the cooperative paramagnetic regime (i.e. far above the onset of coplanarity), as recently reported experimentally in deuterium jarosite. At lower temperature, when the coplanar correlations are well established, we show that the weath- ervane loop fluctuations control the system relaxation : the time distribution observed at higher temperatures splits into two distinct timescales associated with fluctuations in the plane and out of the plane of coplanarity. The temperature and wave vector dependences of these two components are qualitatively consistent with loops diffusing in the entropically dominated free energy landscape. Numerical results are discussed and compared with the $O(N)$ model and recent experiments for both classical and quantum realizations of the kagome magnets.Comment: 18 pages, 14 figure

Stochastic-Based Pattern Recognition Analysis

In this work we review the basic principles of stochastic logic and propose its application to probabilistic-based pattern-recognition analysis. The proposed technique is intrinsically a parallel comparison of input data to various pre-stored categories using Bayesian techniques. We design smart pulse-based stochastic-logic blocks to provide an efficient pattern recognition analysis. The proposed rchitecture is applied to a specific navigation problem. The resulting system is orders of magnitude faster than processor-based solutions

Global land use implications of biofuels: State of the art conference and workshop on modelling global land use implications in the environmental assessment of biofuels

Background, Aims and Scope On 4¿5 June 2007, an international conference was held in Copenhagen. It provided an interdisciplinary forum where economists and geographers met with LCA experts to discuss the challenges of modelling the ultimate land use changes caused by an increased demand for biofuels. Main Features The main feature of the conference was the cross-breeding of experience from the different approaches to land use modelling: The field of LCA could especially benefit from economic modelling in the identification of marginal crop production and the resulting expansion of the global agricultural area. Furthermore, the field of geography offers insights in the complexity behind new land cultivation and practical examples of where this is seen to occur on a regional scale. Results Results presented at the conference showed that the magnitude and location of land use changes caused by biofuels demand depend on where the demand arises. For instance, mandatory blending in the EU will increase land use both within and outside of Europe, especially in South America. A key learning for the LCA society was that the response to a change in demand for a given crop is not presented by a single crop supplier or a single country, but rather by responses from a variety of suppliers of several different crops in several countries. Discussion The intensification potential of current and future crop and biomass production was widely discussed. It was generally agreed that some parts of the third world hold large potentials for intensification, which are not realised due to a number of barriers resulting in so-called yield gaps. Conclusions Modelling the global land use implications of biofuels requires an interdisciplinary approach optimally integrating economic, geographical, biophysical, social and possibly other aspects in the modelling. This interdisciplinary approach is necessary but also difficult due to different perspectives and mindsets in the different disciplines. Recommendations and Perspectives The concept of a location dependent marginal land use composite should be introduced in LCA of biofuels and it should be acknowledged that the typical LCA assumption of linear substitution is not necessarily valid. Moreover, fertiliser restrictions/accessibility should be included in land use modelling and the relation between crop demand and intensification should be further explored. In addition, environmental impacts of land use intensification should be included in LCA, the powerful concept of land use curves should be further improved, and so should the modelling of diminishing returns in crop production

Estimating random transverse velocities in the fast solar wind from EISCAT Interplanetary Scintillation measurements

International audienceInterplanetary scintillation measurements can yield estimates of a large number of solar wind parameters, including bulk flow speed, variation in bulk velocity along the observing path through the solar wind and random variation in transverse velocity. This last parameter is of particular interest, as it can indicate the flux of low-frequency Alfvén waves, and the dissipation of these waves has been proposed as an acceleration mechanism for the fast solar wind. Analysis of IPS data is, however, a significantly unresolved problem and a variety of a priori assumptions must be made in interpreting the data. Furthermore, the results may be affected by the physical structure of the radio source and by variations in the solar wind along the scintillation ray path. We have used observations of simple point-like radio sources made with EISCAT between 1994 and 1998 to obtain estimates of random transverse velocity in the fast solar wind. The results obtained with various a priori assumptions made in the analysis are compared, and we hope thereby to be able to provide some indication of the reliability of our estimates of random transverse velocity and the variation of this parameter with distance from the Sun

Longitudinal and Transverse Zeeman Ladders in the Ising-Like Chain Antiferromagnet BaCo2V2O8

We explore the spin dynamics emerging from the N\'eel phase of the chain compound antiferromagnet BaCo2V2O8. Our inelastic neutron scattering study reveals unconventional discrete spin excitations, so called Zeeman ladders, understood in terms of spinon confinement, due to the interchain attractive linear potential. These excitations consist in two interlaced series of modes, respectively with transverse and longitudinal polarization. The latter have no classical counterpart and are related to the zero-point fluctuations that weaken the ordered moment in weakly coupled quantum chains. Our analysis reveals that BaCo2V2O8, with moderate Ising anisotropy and sizable interchain interactions, remarkably fulfills the conditions necessary for the observation of these longitudinal excitations.Comment: 5 pages, 4 figures, 2 additional pages of supplemental material with 2 figures; Journal ref. added; 1 page erratum added at the end with 1 figur

Effective interaction quenching in artificial kagom\'e spin chains

Achieving thermal equilibrium in two-dimensional lattices of interacting nanomagnets has been a key issue on the route to study exotic phases in artificial frustrated magnets. We revisit this issue in artificial one-dimensional kagom\'e spin chains. Imaging arrested micro-states generated by a field demagnetization protocol and analyzing their pairwise spin correlations in real space, we unveil a non-equilibrated physics. Remarkably, this physics can be reformulated into an at-equilibrium one by rewriting the associated spin Hamiltonian in such a way that one of the coupling constants is quenched. We ascribe this effective behavior to a kinetic hinderance during the demagnetization protocol, which induces the formation of local flux closure spin configurations that sometimes compete with the magnetostatic interaction.Comment: 8 pages, 5 figure

Berry phase of magnons in textured ferromagnets

We study the energy spectrum of magnons in a ferromagnet with topologically nontrivial magnetization profile. In the case of inhomogeneous magnetization corresponding to a metastable state of ferromagnet, the spin-wave equation of motion acquires a gauge potential leading to a Berry phase for the magnons propagating along a closed contour. The effect of magnetic anisotropy is crucial for the Berry phase: we show that the anisotropy suppresses its magnitude, which makes the Berry phase observable in some cases, similar to the Aharonov-Bohm effect for electrons. For example, it can be observed in the interference of spin waves propagating in mesoscopic rings. We discuss the effect of domain walls on the interference in ferromagnetic rings, and propose some experiments with a certain geometry of magnetization. We also show that the nonvanishing average topological field acts on the magnons like a uniform magnetic field on electrons. It leads to the quantization of the magnon spectrum in the topological field.Comment: 8 pages, 5 figure