A Bio-Logical Theory of Animal Learning

This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical account for phenomena that are beyond the domain of existing models, such as extinction and the detection of novelty, from which “external inhibition” can be explained. Examples of the methods applied to make predictions are given using previously published results. The present theory proposes a new way to envision the minimal functions of the nervous system, and provides possible new insights into the way that brains ultimately create and use knowledge about the world

On-line relational SOM for dissimilarity data

International audienceIn some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilarities only. Several variants of the Self Organizing Map algorithm were introduced to generalize the original algorithm to this framework. Whereas median SOM is based on a rough representation of the prototypes, relational SOM allows representing these prototypes by a virtual combination of all elements in the data set. However, this latter approach suffers from two main drawbacks. First, its complexity can be large. Second, only a batch version of this algorithm has been studied so far and it often provides results having a bad topographic organization. In this article, an on-line version of relational SOM is described and justified. The algorithm is tested on several datasets, including categorical data and graphs, and compared with the batch version and with other SOM algorithms for non vector data

Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs

Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more efficiently if their functional nature is taken into account during the data analysis process. This is done by extending standard data analysis methods so that they can apply to functional inputs. A general way to achieve this goal is to compute projections of the functional data onto a finite dimensional sub-space of the functional space. The coordinates of the data on a basis of this sub-space provide standard vector representations of the functions. The obtained vectors can be processed by any standard method. In our previous work, this general approach has been used to define projection based Multilayer Perceptrons (MLPs) with functional inputs. We study in this paper important theoretical properties of the proposed model. We show in particular that MLPs with functional inputs are universal approximators: they can approximate to arbitrary accuracy any continuous mapping from a compact sub-space of a functional space to R. Moreover, we provide a consistency result that shows that any mapping from a functional space to R can be learned thanks to examples by a projection based MLP: the generalization mean square error of the MLP decreases to the smallest possible mean square error on the data when the number of examples goes to infinity

The historical vanishing of the Blazhko effect of RR Lyr from GEOS and Kepler surveys

RR Lyr is one of the most studied variable stars. Its light curve has been regularly monitored since the discovery of the periodic variability in 1899. Analysis of all observed maxima allows us to identify two primary pulsation states defined as pulsation over a long (P0 longer than 0.56684 d) and a short (P0 shorter than 0.56682 d) primary pulsation period. These states alternate with intervals of 13-16 yr, and are well defined after 1943. The 40.8 d periodical modulations of the amplitude and the period (i.e. Blazhko effect) were noticed in 1916. We provide homogeneous determinations of the Blazhko period in the different primary pulsation states. The Blazhko period does not follow the variations of P0 and suddenly diminished from 40.8 d to around 39.0 d in 1975. The monitoring of these periodicities deserved and deserves a continuous and intensive observational effort. For this purpose we have built dedicated, transportable and autonomous small instruments, Very Tiny Telescopes (VTTs), to observe the times of maximum brightness of RR Lyr. As immediate results the VTTs recorded the last change of P0 state in mid-2009 and extended the time coverage of the Kepler observations, thus recording a maximum O-C amplitude of the Blazhko effect at the end of 2008, followed by the historically smallest O-C amplitude in late 2013. This decrease is still ongoing and VTT instruments are ready to monitor the expected increase in the next few years.Comment: 10 pages, 6 figures. Accepted for publication in MNRAS. Contents of appendix B may be requested to first autho

Mastering the game of Go without human knowledge

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo’s own move selections and also the winner of AlphaGo’s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo

Resonant X-ray Scattering in Manganites - Study of Orbital Degree of Freedom -

Orbital degree of freedom of electrons and its interplay with spin, charge and lattice degrees of freedom are one of the central issues in colossal magnetoresistive manganites. The orbital degree of freedom has until recently remained hidden, since it does not couple directly to most of experimental probes. Development of synchrotron light sources has changed the situation; by the resonant x-ray scattering (RXS) technique the orbital ordering has successfully been observed . In this article, we review progress in the recent studies of RXS in manganites. We start with a detailed review of the RXS experiments applied to the orbital ordered manganites and other correlated electron systems. We derive the scattering cross section of RXS where the tensor character of the atomic scattering factor (ASF) with respect to the x-ray polarization is stressed. Microscopic mechanisms of the anisotropic tensor character of ASF is introduced and numerical results of ASF and the scattering intensity are presented. The azimuthal angle scan is a unique experimental method to identify RXS from the orbital degree of freedom. A theory of the azimuthal angle and polarization dependence of the RXS intensity is presented. The theoretical results show good agreement with the experiments in manganites. Apart from the microscopic description of ASF, a theoretical framework of RXS to relate directly to the 3d orbital is presented. The scattering cross section is represented by the correlation function of the pseudo-spin operator for the orbital degree of freedom. A theory is extended to the resonant inelastic x-ray scattering and methods to observe excitations of the orbital degree of freedom are proposed.Comment: 47 pages, 24 figures, submitted to Rep. Prog. Phy

The structural basis for SARM1 inhibition and activation under energetic stress

This is the author accepted manuscript. The final version is available on open access from eLife Sciences Publications via the DOI in this recordSARM1 an executor of axonal degeneration, displays NADase activity that depletes the key cellular metabolite, NAD+, in response to nerve injury. The basis of SARM1 inhibition, and its activation under stress conditions are still unknown. Here, we present cryo-EM maps of SARM1 at 2.9 and 2.7 Å resolution. These indicate that SARM1 homo-octamer avoids premature activation by assuming a packed conformation, with ordered inner and peripheral rings, that prevents dimerization and activation of the catalytic domains. This inactive conformation is stabilized by binding of SARM1's own substrate NAD+ in an allosteric location, away from the catalytic sites. This model was validated by mutagenesis of the allosteric site, which led to constitutively active SARM1. We propose that the reduction of cellular NAD+ concentration contributes to the disassembly of SARM1's peripheral ring, which allows formation of active NADase domain dimers, thereby further depleting NAD+ to cause an energetic catastrophe and cell death.IS

Follow-up observations at 16 and 33 GHz of extragalactic sources from WMAP 3-year data: I - Spectral properties

We present follow-up observations of 97 point sources from the Wilkinson Microwave Anisotropy Probe (WMAP) 3-year data, contained within the New Extragalactic WMAP Point Source (NEWPS) catalogue between declinations of -4 and +60 degrees; the sources form a flux-density-limited sample complete to 1.1 Jy (approximately 5 sigma) at 33 GHz. Our observations were made at 16 GHz using the Arcminute Microkelvin Imager (AMI) and at 33 GHz with the Very Small Array (VSA). 94 of the sources have reliable, simultaneous -- typically a few minutes apart -- observations with both telescopes. The spectra between 13.9 and 33.75 GHz are very different from those of bright sources at low frequency: 44 per cent have rising spectra (alpha < 0.0), where flux density is proportional to frequency^-alpha, and 93 per cent have spectra with alpha < 0.5; the median spectral index is 0.04. For the brighter sources, the agreement between VSA and WMAP 33-GHz flux densities averaged over sources is very good. However, for the fainter sources, the VSA tends to measure lower values for the flux densities than WMAP. We suggest that the main cause of this effect is Eddington bias arising from variability.Comment: 12 pages, 13 figures, submitted to MNRA