131 research outputs found
Permutations of context-free, ET0L and indexed languages
© 2016 Discrete Mathematics and Theoretical Computer Science (DMTCS), Nancy, France. For a language L, we consider its cyclic closure, and more generally the language Ck(L), which consists of all words obtained by partitioning words from L into k factors and permuting them. We prove that the classes of ET0L and EDT0L languages are closed under the operators Ck. This both sharpens and generalises Brandstädt's result that if L is context-free then Ck(L) is context-sensitive and not context-free in general for k ≥ 3. We also show that the cyclic closure of an indexed language is indexed
Cerebral differences in explicit and implicit emotional processing - An fMRI study
The processing of emotional facial expression is a major part of social communication and understanding. In addition to explicit processing, facial expressions are also processed rapidly and automatically in the absence of explicit awareness. We investigated 12 healthy subjects by presenting them with an implicit and explicit emotional paradigm. The subjects reacted significantly faster in implicit than in explicit trials but did not differ in their error ratio. For the implicit condition increased signals were observed in particular in the thalami, the hippocampi, the frontal inferior gyri and the right middle temporal region. The analysis of the explicit condition showed increased blood-oxygen-level-dependent signals especially in the caudate nucleus, the cingulum and the right prefrontal cortex. The direct comparison of these 2 different processes revealed increased activity for explicit trials in the inferior, superior and middle frontal gyri, the middle cingulum and left parietal regions. Additional signal increases were detected in occipital regions, the cerebellum, and the right angular and lingual gyrus. Our data partially confirm the hypothesis of different neural substrates for the processing of implicit and explicit emotional stimuli. Copyright (c) 2007 S. Karger AG, Basel
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Pointing errors in non-metric virtual environments
There have been suggestions that human navigation may depend on representations that have no metric, Euclidean interpretation but that hypothesis remains contentious. An alternative is that observers build a consistent 3D representation of space. Using immersive virtual reality, we measured the ability of observers to point to targets in mazes that had zero, one or three ‘wormholes’ – regions where the maze changed in configuration (invisibly). In one model, we allowed the configuration of the maze to vary to best explain the pointing data; in a second model we also allowed the local reference frame to be rotated through 90, 180 or 270 degrees. The latter model outperformed the former in the wormhole conditions, inconsistent with a Euclidean cognitive map
The Global Genome Biodiversity Network (GGBN) Data Standard specification
© The Author(s) 2016. Published by Oxford University Press. Page 1 of 11 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. The article attached is the publisher's pdf
Natural Image Coding in V1: How Much Use is Orientation Selectivity?
Orientation selectivity is the most striking feature of simple cell coding in
V1 which has been shown to emerge from the reduction of higher-order
correlations in natural images in a large variety of statistical image models.
The most parsimonious one among these models is linear Independent Component
Analysis (ICA), whereas second-order decorrelation transformations such as
Principal Component Analysis (PCA) do not yield oriented filters. Because of
this finding it has been suggested that the emergence of orientation
selectivity may be explained by higher-order redundancy reduction. In order to
assess the tenability of this hypothesis, it is an important empirical question
how much more redundancies can be removed with ICA in comparison to PCA, or
other second-order decorrelation methods. This question has not yet been
settled, as over the last ten years contradicting results have been reported
ranging from less than five to more than hundred percent extra gain for ICA.
Here, we aim at resolving this conflict by presenting a very careful and
comprehensive analysis using three evaluation criteria related to redundancy
reduction: In addition to the multi-information and the average log-loss we
compute, for the first time, complete rate-distortion curves for ICA in
comparison with PCA. Without exception, we find that the advantage of the ICA
filters is surprisingly small. Furthermore, we show that a simple spherically
symmetric distribution with only two parameters can fit the data even better
than the probabilistic model underlying ICA. Since spherically symmetric models
are agnostic with respect to the specific filter shapes, we conlude that
orientation selectivity is unlikely to play a critical role for redundancy
reduction
Constrained Dynamic Tree Networks
We generalise Constrained Dynamic Pushdown Networks, introduced by Bouajjani\et al, to Constrained Dynamic Tree Networks.<br>In this model, we have trees of processes which may monitor their children.<br>We allow the processes to be defined by any computation model for which the alternating reachability problem is decidable.<br>We address the problem of symbolic reachability analysis for this model. More precisely, we consider the problem of computing an effective representation of their reachability<br>sets using finite state automata. <div>We show that backwards reachability sets starting from regular sets of configurations are always regular. </div><div>We provide an algorithm for computing backwards reachability sets using tree automata.<br><br></div
Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics
Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience
Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease
BACKGROUND:
Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes.
METHODS:
We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization.
RESULTS:
During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events.
CONCLUSIONS:
Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)
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