Predictive learning, prediction errors, and attention: evidence from event-related potentials and eye tracking

Prediction error (‘‘surprise’’) affects the rate of learning: We learn more rapidly about cues for which we initially make incorrect predictions than cues for which our initial predictions are correct. The current studies employ electrophysiological measures to reveal early attentional differentiation of events that differ in their previous involvement in errors of predictive judgment. Error-related events attract more attention, as evidenced by features of event-related scalp potentials previously implicated in selective visual attention (selection negativity, augmented anterior N1). The earliest differences detected occurred around 120 msec after stimulus onset, and distributed source localization (LORETA) indicated that the inferior temporal regions were one source of the earliest differences. In addition, stimuli associated with the production of prediction errors show higher dwell times in an eyetracking procedure. Our data support the view that early attentional processes play a role in human associative learning

Cluster Correlation in Mixed Models

We evaluate the dependence of the cluster correlation length r_c on the mean intercluster separation D_c, for three models with critical matter density, vanishing vacuum energy (Lambda = 0) and COBE normalized: a tilted CDM (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos yielding Omega_h = 0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of sigma_8 (and, henceforth, the observed cluster abundance) and are consistent with the observed abundance of Damped Lyman_alpha systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio sigma_8/sigma_25, yielding the spectral slope parameter Gamma, and nicely fit LCRS reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (side 360/h Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow to cover the same D_c interval inspected through APM and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit of cluster clustering data.Comment: 22 pages + 10 Postscript figures. Accepted for publication in Ap

Motion Planning from Demonstrations and Polynomial Optimization for Visual Servoing Applications

Vision feedback control techniques are desirable for a wide range of robotics applications due to their robustness to image noise and modeling errors. However in the case of a robot-mounted camera, they encounter difficulties when the camera traverses large displacements. This scenario necessitates continuous visual target feedback during the robot motion, while simultaneously considering the robot's self- and external-constraints. Herein, we propose to combine workspace (Cartesian space) path-planning with robot teach-by-demonstration to address the visibility constraint, joint limits and “whole arm” collision avoidance for vision-based control of a robot manipulator. User demonstration data generates safe regions for robot motion with respect to joint limits and potential “whole arm” collisions. Our algorithm uses these safe regions to generate new feasible trajectories under a visibility constraint that achieves the desired view of the target (e.g., a pre-grasping location) in new, undemonstrated locations. Experiments with a 7-DOF articulated arm validate the proposed method.published_or_final_versio

Evolution of the Cluster Mass and Correlation Functions in LCDM Cosmology

The evolution of the cluster mass function and the cluster correlation function from z = 0 to z = 3 are determined using 10^6 clusters obtained from high-resolution simulations of the current best-fit LCDM cosmology (\Omega_m = 0.27, \sigma_8 = 0.84, h = 0.7). The results provide predictions for comparisons with future observations of high redshift clusters. A comparison of the predicted mass function of low redshift clusters with observations from early Sloan Digital Sky Survey data, and the predicted abundance of massive distant clusters with observational results, favor a slightly larger amplitude of mass fluctuations (\sigma_8 = 0.9) and lower density parameter (\Omega_m = 0.2); these values are consistent within 1-\sigma with the current observational and model uncertainties. The cluster correlation function strength increases with redshift for a given mass limit; the clusters were more strongly correlated in the past, due to their increasing bias with redshift - the bias reaches b = 100 at z = 2 for M > 5 x 10^13 h^-1 M_sun. The richness-dependent cluster correlation function, represented by the correlation scale versus cluster mean separation relation, R0-d, is generally consistent with observations. This relation can be approximated as R_0 = 1.7 d^0.6 h^-1 Mpc for d = 20 - 60 h^-1 Mpc. The R0-d relation exhibits surprisingly little evolution with redshift for z < 2; this can provide a new test of the current LCDM model when compared with future observations of high redshift clusters.Comment: 20 pages, 9 figures, accepted for publication in Ap

The Clustering of Massive Halos

The clustering properties of dark matter halos are a firm prediction of modern theories of structure formation. We use two large volume, high-resolution N-body simulations to study how the correlation function of massive dark matter halos depends upon their mass and formation history. We find that halos with the lowest concentrations are presently more clustered than those of higher concentration, the size of the effect increasing with halo mass; this agrees with trends found in studies of lower mass halos. The clustering dependence on other characterizations of the full mass accretion history appears weaker than the effect with concentration. Using the integrated correlation function, marked correlation functions, and a power-law fit to the correlation function, we find evidence that halos which have recently undergone a major merger or a large mass gain have slightly enhanced clustering relative to a randomly chosen population with the same mass distribution.Comment: 10 pages, 8 figures; text improved, references and one figure added; accepted for publication in Ap

Evolution of the Cluster Correlation Function

We study the evolution of the cluster correlation function and its richness-dependence from z = 0 to z = 3 using large-scale cosmological simulations. A standard flat LCDM model with \Omega_m = 0.3 and, for comparison, a tilted \Omega_m = 1 model, TSCDM, are used. The evolutionary predictions are presented in a format suitable for direct comparisons with observations. We find that the cluster correlation strength increases with redshift: high redshift clusters are clustered more strongly (in comoving scale) than low redshift clusters of the same mass. The increased correlations with redshift, in spite of the decreasing mass correlation strength, is caused by the strong increase in cluster bias with redshift: clusters represent higher density peaks of the mass distribution as the redshift increases. The richness-dependent cluster correlation function, presented as the correlation-scale versus cluster mean separation relation, R_0 - d, is found to be, remarkably, independent of redshift to z <~ 2 for LCDM and z <~ 1 for TCDM (for a fixed correlation function slope and cluster mass within a fixed comoving radius). The non-evolving R_0 - d relation implies that both the comoving clustering scale and the cluster mean separation increase with redshift for the same mass clusters so that the R_0 - d relation remains essentially unchanged. The evolution of the R_0 - d relation from z ~ 0 to z ~ 3 provides an important new tool in cosmology; it can be used to break degeneracies that exist at z ~ 0 and provide precise determination of cosmological parameters.Comment: AASTeX, 15 pages, including 5 figures, accepted version for publication in ApJ, vol.603, March 200

Correlation length of X-ray brightest Abell clusters

We compute the cluster auto-correlation function $\xi_{cc}(r)$ of an X-ray flux limited sample of Abell clusters (XBACs, \cite{ebe}). For the total XBACs sample we find a power-law fit $\xi_{cc}=(r/r_0)^{\gamma}$ with $r_0=21.1$ Mpc h$^{-1}$and $\gamma =-1.9$ consistent with the results of $R \ge 1$ Abell clusters. We also analyze $\xi_{cc}(r)$ for subsamples defined by different X-ray luminosity thresholds where we find a weak tendency of larger values of $r_0$ with increasing X-ray luminosity although with a low statistical significance. In the different subsamples analyzed we find $21 < r_0 < 35$ Mpc h$^{-1}$ and $-1.9< \gamma < -1.6$. Our analysis suggests that cluster X-ray luminosities may be used for a reliable confrontation of cluster spatial distribution properties in models and observations.Comment: Accepted for publication in Astrophysical Journa

Spatial Correlation Function of X-ray Selected AGN

We present a detailed description of the first direct measurement of the spatial correlation function of X-ray selected AGN. This result is based on an X-ray flux-limited sample of 219 AGN discovered in the contiguous 80.7 deg^2 region of the ROSAT North Ecliptic Pole (NEP) Survey. Clustering is detected at the 4 sigma level at comoving scales in the interval r = 5-60 h^-1 Mpc. Fitting the data with a power law of slope gamma=1.8, we find a correlation length of r_0 = 7.4 (+1.8, -1.9) h^-1 Mpc (Omega_M=0.3, Omega_Lambda=0.7). The median redshift of the AGN contributing to the signal is z_xi=0.22. This clustering amplitude implies that X-ray selected AGN are spatially distributed in a manner similar to that of optically selected AGN. Furthermore, the ROSAT NEP determination establishes the local behavior of AGN clustering, a regime which is poorly sampled in general. Combined with high-redshift measures from optical studies, the ROSAT NEP results argue that the AGN correlation strength essentially does not evolve with redshift, at least out to z~2.2. In the local Universe, X-ray selected AGN appear to be unbiased relative to galaxies and the inferred X-ray bias parameter is near unity, b_X~1. Hence X-ray selected AGN closely trace the underlying mass distribution. The ROSAT NEP AGN catalog, presented here, features complete optical identifications and spectroscopic redshifts. The median redshift, X-ray flux, and X-ray luminosity are z=0.41, f_X=1.1*10^-13 cgs, and L_X=9.2*10^43 h_70^-2 cgs (0.5-2.0 keV), respectively. Unobscured, type 1 AGN are the dominant constituents (90%) of this soft X-ray selected sample of AGN.Comment: 17 pages, 8 figures, accepted for publication in ApJ, a version with high-resolution figures is available at http://www.eso.org/~cmullis/papers/Mullis_et_al_2004b.ps.gz, a machine-readable version of the ROSAT NEP AGN catalog is available at http://www.eso.org/~cmullis/research/nep-catalog.htm

Utterance Selection Model of Language Change

We present a mathematical formulation of a theory of language change. The theory is evolutionary in nature and has close analogies with theories of population genetics. The mathematical structure we construct similarly has correspondences with the Fisher-Wright model of population genetics, but there are significant differences. The continuous time formulation of the model is expressed in terms of a Fokker-Planck equation. This equation is exactly soluble in the case of a single speaker and can be investigated analytically in the case of multiple speakers who communicate equally with all other speakers and give their utterances equal weight. Whilst the stationary properties of this system have much in common with the single-speaker case, time-dependent properties are richer. In the particular case where linguistic forms can become extinct, we find that the presence of many speakers causes a two-stage relaxation, the first being a common marginal distribution that persists for a long time as a consequence of ultimate extinction being due to rare fluctuations.Comment: 21 pages, 17 figure

Relation between Skin Pharmacokinetics and Efficacy in AmBisome Treatment of Murine Cutaneous Leishmaniasis

AmBisome® (LAmB), a liposomal formulation of amphotericin B (AmB), is a second-line treatment for the parasitic skin disease cutaneous leishmaniasis (CL). Little is known about its tissue distribution and pharmacodynamics to inform clinical use in CL. Here, we compared the skin pharmacokinetics of LAmB with Fungizone® (DAmB), the deoxycholate form of AmB, in murine models of Leishmania major CL. Drug levels at the target site (the localized lesion) 48 hours after single intravenous (IV) dosing of the individual AmB formulations (1 mg/kg of body weight) were similar, but were 3-fold higher for LAmB than for DAmB on day 10 after multiple administrations (1 mg/kg on days 0, 2, 4, 6 and 8). After single and multiple dosing, intralesional concentrations were respectively 5- and 20-fold higher compared to those in the healthy control skin of the same infected mice. We then evaluated how drug levels in the lesion after LAmB treatment relate to therapeutic outcomes. After five administrations of the drug at 0, 6.25 or 12.5 mg/kg (IV), there was a clear correlation between dose level, intralesional AmB concentration and relative reduction in parasite load and lesion size (R2 values > 0.9). This study confirms the improved efficacy of the liposomal over the deoxycholate AmB formulation in experimental CL, which is related to higher intralesional drug accumulation