The Behavior Rating Inventory Of Executive Function - Self-Report Version (Brief-Sr) And The Delis-Kaplan Executive Function Sys

The assessment of executive functions is an area of study that has seen considerable development in recent years. Despite much research examining the validity of various measures of executive functions from both a direct and indirect format, little evidence exists in the extant literature evaluating the correspondence between these types of measures. The current study examined the extent of correspondence, comprising concurrent validity, between the Delis-Kaplan Executive Function System (D-KEFS) and the Behavior Rating Inventory of Executive Function ¿ Self-Report Version (BRIEF-SR). Participants included 30 undergraduate and high school students 18 years of age. Results indicated mixed evidence of concurrent validity between the two measures of executive functions. The findings obtained suggest both expected significant, negative correlation as well as lack of expected correlation between the measures. Suggestions for future research in the assessment of executive functions are discussed.

Understanding Neural Maps with Topographica

The biological function of neurons can often be understood only in the context of large, highly interconnected networks. These networks typically form two-dimensional topographic maps, such as the retinotopic maps in mammalian visual cortex. Computational simulations of these areas have led to valuable insights about how cortical topography develops and functions, but further progress has been hindered due to the lack of appropriate simulation tools. This paper introduces the freely available Topographica maplevel simulator, originally developed at the University of Texas at Austin and now maintained at the University of Edinburgh, UK. Topographica is designed to make large-scale, detailed models practical. The goal is to allow neuroscientists and computational scientists to work together to understand how topographic maps and their connections organize and operate. This understanding will be crucial for integrating experimental observations into a comprehensive theory of brain function.

Agency and ownership are independent components of 'sensing the self' in the auditory-verbal domain

'Sensing the self' relies on the ability to distinguish self-generated from external stimuli. It requires functioning mechanisms to establish feelings of agency and ownership. Agency is defined causally, where the subjects action is followed by an effect. Ownership is defined by the features of the effect, independent from the action. In our study, we manipulated these qualities separately. 13 right-handed healthy individuals performed the experiment while 76-channel EEG was recorded. Stimuli consisted of visually presented words, read aloud by the subject. The experiment consisted of six conditions: (a) subjects saw a word, read it aloud, heard it in their own voice; (b) like a, but the word was heard in an unfamiliar voice; (c) subject heard a word in his/her own voice without speaking; (d) like c, but the word was heard in an unfamiliar voice; (e) like a, but subjects heard the word with a delay; (f) subjects read without hearing. ERPs and difference maps were computed for all conditions. Effects were analysed topographically. The N100 (86-172 ms) displayed significant main effects of agency and ownership. The topographies of the two effects shared little common variance, suggesting independent effects. Later effects (174-400 ms) of agency and ownership were topographically similar, suggesting common mechanisms. Replicating earlier studies, significant N100 suppression was observed, with a topography resembling the agency effect. 'Sensing the self' appears to recruit from at least two very distinct processes: an agency assessment that represents causality and an ownership assessment that compares stimulus features with memory content.

Self-adaptive grids for noise mapping refinement

Noise maps are usually represented as contour or isolines maps describing the sound levels in a region. Using this kind of representation the user can easily find the noise level assigned to every location in the map. But the acoustic calculations behind the map are not performed for every single location on it; they are only performed in a grid of receivers. The results in this calculation grid are interpolated to draw the isolines or contours. Therefore, the resolution of the calculation grid and the way it was created (rectangular, triangulated, random…) have an effect on the resulting map. In this paper we describe a smart iterative procedure to optimize the quality of the map at a really low additional computational cost, using self-adaptive grids for the acoustic calculations. These self-adaptive grids add new receivers to the sampling grid in those locations where they are expected to be more useful, so that the performance at the output of the interpolator is enhanced. Self-adaptive sampling grids can be used for minimizing the overall error of the map (improving its quality), or for reducing calculation times, and can be also applied selectively to target areas or contour lines. This can be done by the user customizing the maximum number of iterations, the number of new receivers for each iteration, the target isolines, the target quality…

Antagonism of WT1 activity by protein self-association.

Germline loss-of-function mutations at the Wilms tumor (WT) suppressor locus WT1 are associated with a predisposition to WTs and mild genital system anomalies. In contrast, germ-line missense mutations within the WT1 gene encoding the DNA-binding domain often yield a more severe phenotype consisting of WT, sexual ambiguity, and renal nephropathy. In this report, we demonstrate that the products of mutant alleles that impair DNA recognition can antagonize WT1-mediated transcriptional repression. We demonstrate that WT1 can self-associate in vitro and in vivo and that the responsible domain maps to the amino-terminal region of the protein. Oligomers of full-length protein form less efficiently or produce less stable complexes than oligomers between truncated polypeptides and full-length protein. Our data suggest a molecular mechanism to explain how WT1 mutations may act in deregulating cellular proliferation and differentiation.

Aod1, the immunoregulatory locus controlling abrogation of tolerance in neonatal thymectomy-induced autoimmune ovarian dysgenesis, maps to mouse chromosome 16.

Mice thymectomized at three days of age (D3Tx) develop during adulthood a variety of organ-specific autoimmune diseases, including autoimmune ovarian dysgenesis (AOD). The phenotypic spectrum of AOD is characterized by the development of anti-ovarian autoantibodies, oophoritis, and atrophy. The D3Tx model of AOD is unique in that disease induction depends exclusively on perturbation of the normal developing immune system, is T-cell-mediated, and is strain specific. For example, D3Tx A/J mice are highly susceptible to AOD, whereas C57BL/6J mice are resistant. After D3Tx, self ovarian antigens, expressed at physiological levels, trigger an autoimmune response capable of eliciting disease. The D3Tx model provides, therefore, the opportunity to focus on the mechanisms of self-tolerance that are relevant to disease pathogenesis. Previous studies indicate that the principal mechanisms involved in AOD susceptibility are genetically controlled and govern developmental processes associated with the induction and maintenance of peripheral tolerance. We report here the mapping of the Aod1 locus to mouse chromosome 16 within a region encoding several loci of immunologic relevance, including scid, Igl1, VpreB, Igll, Igl1r, Mtv6 (Mls-3), Ly-7, Ifnar, and Ifgt.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

Weak and Semi Compatible Maps in Probabilistic Metric Space Using Implicit Relation

2000 Mathematics Subject Classification: 54H25, 47H10.

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).