Investigating Homelessness And Social Cognition

Introduction: The relationship between homelessness and brain injury is a growing area of interest in the literature. Several studies have used cognitive screening tools to ascertain the level of cognitive impairment present in this population and very few studies have used comprehensive neuropsychological batteries. Social cognition remains an underexplored area in homelessness, and it may serve as a causal and perpetuating factor. Better understanding the social cognitive needs of homeless individuals can help inform intervention strategies and preventative policies. Aims: The present study aims to use a comprehensive neuropsychological test battery including social cognition measures to explore the cognitive needs of a sample of homeless men. Methods: Eight residents of a homeless hostel took part in the study. Scores were analysed against normative data and exploratory non-parametric correlations revealed tentative relationships between cognitive domains. A case series analysis was also conducted for descriptive data exploration. Results: Individual and group-level exploratory analyses revealed several cognitive difficulties, including impairment in a mentalising task. No impairment was found in the domains of empathy and emotion recognition. Discussion: The findings add to the literature on cognitive impairments in homeless men and suggest the need for including social cognition measures in routine assessments. Implications for clinical practice and future research are discussed

Optical afterglow luminosities in the Swift epoch: confirming clustering and bimodality

We show that Gamma Ray Bursts (GRBs) of known redshift and rest frame optical extinction detected by the Swift satellite fully confirm earlier results concerning the distribution of the optical afterglow luminosity at 12 hours after trigger (rest frame time). This distribution is bimodal and relatively narrow, especially for the high luminosity branch. This is intriguing, given that Swift GRBs have, on average, a redshift larger than pre-Swift ones, and is unexpected in the common scenario explaining the GRB afterglow. We investigate if the observed distribution can be the result of selection effects affecting a unimodal parent luminosity distribution, and find that either the distribution is intrinsically bimodal, or most (60 per cent) of the bursts are absorbed by a substantial amount of grey dust. In both cases we suggest that most dark bursts should belong to the underluminous optical family.Comment: 5 pages 3 figures, minor revision, added reference, accepted for publication in MNRAS Letter

On a microcanonical relation between continuous and discrete spin models

A relation between a class of stationary points of the energy landscape of continuous spin models on a lattice and the configurations of a Ising model defined on the same lattice suggests an approximate expression for the microcanonical density of states. Based on this approximation we conjecture that if a O(n) model with ferromagnetic interactions on a lattice has a phase transition, its critical energy density is equal to that of the n = 1 case, i.e., a system of Ising spins with the same interactions. The conjecture holds true in the case of long-range interactions. For nearest-neighbor interactions, numerical results are consistent with the conjecture for n=2 and n=3 in three dimensions. For n=2 in two dimensions (XY model) the conjecture yields a prediction for the critical energy of the Berezinskij-Kosterlitz-Thouless transition, which would be equal to that of the two-dimensional Ising model. We discuss available numerical data in this respect.Comment: 5 pages, no figure

Kinetic theory for non-equilibrium stationary states in long-range interacting systems

We study long-range interacting systems perturbed by external stochastic forces. Unlike the case of short-range systems, where stochastic forces usually act locally on each particle, here we consider perturbations by external stochastic fields. The system reaches stationary states where external forces balance dissipation on average. These states do not respect detailed balance and support non-vanishing fluxes of conserved quantities. We generalize the kinetic theory of isolated long-range systems to describe the dynamics of this non-equilibrium problem. The kinetic equation that we obtain applies to plasmas, self-gravitating systems, and to a broad class of other systems. Our theoretical results hold for homogeneous states, but may also be generalized to apply to inhomogeneous states. We obtain an excellent agreement between our theoretical predictions and numerical simulations. We discuss possible applications to describe non-equilibrium phase transitions.Comment: 11 pages, 2 figures; v2: small changes, close to the published versio

A gravitational lensing explanation for the excess of strong Mg-II absorbers in GRB afterglow spectra

GRB afterglows offer a probe of the intergalactic medium out to high redshift which complements observations along more abundant quasar lines-of-sight. Although both quasars and GRB afterglows should provide a-priori random sight-lines through the intervening IGM, it has been observed that strong Mg-II absorbers are twice as likely to be found along sight-lines toward GRBs. Several proposals to reconcile this discrepancy have been put forward, but none has been found sufficient to explain the magnitude of the effect. In this paper we estimate the effect of gravitational lensing by galaxies and their surrounding mass distributions on the statistics of Mg-II absorption. We find that the multi-band magnification bias could be very strong in the spectroscopic GRB afterglow population and that gravitational lensing can explain the discrepancy in density of absorbers, for plausibly steep luminosity functions. The model makes the prediction that approximately 20%-60% of the spectroscopic afterglow sample (i.e. ~ 5-15 of 26 sources) would have been multiply imaged, and hence result in repeating bursts. We show that despite this large lensing fraction it is likely that none would yet have been identified by chance owing to the finite sky coverage of GRB searches. We predict that continued optical monitoring of the bright GRB afterglow locations in the months and years following the initial decay would lead to identification of lensed GRB afterglows. A confirmation of the lensing hypothesis would allow us to constrain the GRB luminosity function down to otherwise inaccessibly faint levels, with potential consequences for GRB models.Comment: 8 pages, 3 figures. Submitted to MNRAS

Spectral decomposition of starbursts and AGNs in 5-8 micron Spitzer IRS spectra of local ULIRGs

We present an analysis of the 5-8 micron Spitzer-IRS spectra of a sample of 68 local Ultraluminous Infrared Galaxies (ULIRGs). Our diagnostic technique allows a clear separation of the active galactic nucleus (AGN) and starburst (SB) components in the observed mid-IR emission, and a simple analytic model provides a quantitative estimate of the AGN/starburst contribution to the bolometric luminosity. We show that AGNs are ~30 times brighter at 6 micron than starbursts with the same bolometric luminosity, so that even faint AGNs can be detected. Star formation events are confirmed as the dominant power source for extreme infrared activity, since ~85% of ULIRG luminosity arises from the SB component. Nonetheless an AGN is present in the majority (46/68) of our sources.Comment: 5 Pages, 3 figures. MNRAS Letters, Accepte

Learning differential equation models from stochastic agent-based model simulations

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel, and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth-death-migration model commonly used to explore cell biology experiments and a susceptible-infected-recovered model of infectious disease spread

Cosmological Consequences of Nearly Conformal Dynamics at the TeV scale

Nearly conformal dynamics at the TeV scale as motivated by the hierarchy problem can be characterized by a stage of significant supercooling at the electroweak epoch. This has important cosmological consequences. In particular, a common assumption about the history of the universe is that the reheating temperature is high, at least high enough to assume that TeV-mass particles were once in thermal equilibrium. However, as we discuss in this paper, this assumption is not well justified in some models of strong dynamics at the TeV scale. We then need to reexamine how to achieve baryogenesis in these theories as well as reconsider how the dark matter abundance is inherited. We argue that baryonic and dark matter abundances can be explained naturally in these setups where reheating takes place by bubble collisions at the end of the strongly first-order phase transition characterizing conformal symmetry breaking, even if the reheating temperature is below the electroweak scale $\sim 100$ GeV. We also discuss inflation as well as gravity wave smoking gun signatures of this class of models.Comment: 22 pages, 7 figure

Coding Locations Relative to One or Many Landmarks in Childhood

Cognitive development studies how information processing in the brain changes over the course of development. A key part of this question is how information is represented and stored in memory. This study examined allocentric (world-based) spatial memory, an important cognitive tool for planning routes and interacting with the space around us. This is typically theorized to use multiple landmarks all at once whenever it operates. In contrast, here we show that allocentric spatial memory frequently operates over a limited spatial window, much less than the full proximal scene, for children between 3.5 and 8.5 years old. The use of multiple landmarks increases gradually with age. Participants were asked to point to a remembered target location after a change of view in immersive virtual reality. A k-fold cross-validation model-comparison selected a model where young children usually use the target location’s vector to the single nearest landmark and rarely take advantage of the vectors to other nearby landmarks. The comparison models, which attempt to explain the errors as generic forms of noise rather than encoding to a single spatial cue, did not capture the distribution of responses as well. Parameter fits of this new single- versus multi-cue model are also easily interpretable and related to other variables of interest in development (age, executive function). Based on this, we theorize that spatial memory in humans develops through three advancing levels (but not strict stages): most likely to encode locations egocentrically (relative to the self), then allocentrically (relative to the world) but using only one landmark, and finally, most likely to encode locations relative to multiple parts of the scene

Late development of cue integration is linked to sensory fusion in cortex

Adults optimize perceptual judgements by integrating different types of sensory information [ 1, 2 ]. This engages specialized neural circuits that fuse signals from the same [ 3–5 ] or different [ 6 ] modalities. Whereas young children can use sensory cues independently, adult-like precision gains from cue combination only emerge around ages 10 to 11 years [ 7–9 ]. Why does it take so long to make best use of sensory information? Existing data cannot distinguish whether this (1) reflects surprisingly late changes in sensory processing (sensory integration mechanisms in the brain are still developing) or (2) depends on post-perceptual changes (integration in sensory cortex is adult-like, but higher-level decision processes do not access the information) [ 10 ]. We tested visual depth cue integration in the developing brain to distinguish these possibilities. We presented children aged 6–12 years with displays depicting depth from binocular disparity and relative motion and made measurements using psychophysics, retinotopic mapping, and pattern classification fMRI. Older children (>10.5 years) showed clear evidence for sensory fusion in V3B, a visual area thought to integrate depth cues in the adult brain [ 3–5 ]. By contrast, in younger children (<10.5 years), there was no evidence for sensory fusion in any visual area. This significant age difference was paired with a shift in perceptual performance around ages 10 to 11 years and could not be explained by motion artifacts, visual attention, or signal quality differences. Thus, whereas many basic visual processes mature early in childhood [ 11, 12 ], the brain circuits that fuse cues take a very long time to develop