A cautionary note on the use of probability values to evaluate interobserver agreement

Proposed methods of assessing the statistical significance of interobserver agreements provide erroneous probability values when conducted on serially correlated data. Investigators who wish to evaluate interobserver agreements by means of statistical significance can do so by limiting the analysis to every k(th) interval of data, or by using Markovian techniques which accommodate serial correlations.     

Sport Skill–Specific Expertise Biases Sensory Integration for Spatial Referencing and Postural Control

The authors asked how sport expertise modulates visual field dependence and sensory reweighting for controlling posture. Experienced soccer athletes, ballet dancers, and nonathletes performed (a) a Rod and Frame test and (b) a 100-s bipedal stance task during which vision and proprioception were successively or concurrently disrupted in 20-s blocks. Postural adaptation was assessed in the mean center of pressure displacement, root mean square of center of pressure velocity and ankle muscles integrated electromyography activity. Soccer athletes were more field dependent than were nonathletes. During standing, dancers were more destabilized by vibration and required more time to reweigh sensory information compared with the other 2 groups. These findings reveal a sport skill–specific bias in the reweighing of sensory inputs for spatial orientation and postural control.     

大学新生时间管理倾向、手机依赖与无聊倾向的关系：一项交叉滞后研究

在3个月的时间内对425名大学新生进行3次追踪测量，以考察时间管理倾向、手机依赖与无聊倾向之间的因果顺序和发展变化趋势。结果发现：（1）大学新生的无聊倾向与时间管理倾向呈同时性和继时性的负相关，并与手机依赖水平呈同时性和继时性的正相关。（2）T1和T2的无聊倾向分别正向预测T2和T3的手机依赖，并分别负向预测T2和T3的时间管理倾向；T1的时间管理倾向负向预测T2的无聊倾向；T2的手机依赖正向预测T3的无聊倾向。结论：无聊倾向分别与手机依赖、时间管理倾向之间存在相互预测关系。     

The relative sensitivities of same-different and identification judgment models to perceptual dependence

Probabilistic models of same-different and identification judgments are compared (within each paradigm) with regard to their sensitivity to perceptual dependence or the degree to which the underlying psychological dimensions are correlated. Three same-different judgment models are compared. One is a step function or decision bound model and the other two are probabilistic variants of a similarity model proposed by Shepard. Three types of identification models are compared: decision bound models, a probabilistic multidimensional scaling model, and probabilistic models based on the Shepard-Luce choice rule. The decision bound models were found to be most sensitive to perceptual dependence, especially when there is considerable distributional overlap. The same-different model based on the city-block metric and an exponential decay similarity function, and the corresponding identification model were found to be particularly insensitive to perceptual dependence. These results suggest that if a Shepard-type similarity function accurately describes behavior, then under typical experimental conditions it should be difficult to see the effects of perceptual dependence. This result provides strong support for a perceptualindependence assumption when using these models. These theoretical results may also play an important role in studying different decision rules employed at different stages of identification training.We thank Robert Melara, Jerome Busemeyer and three anonymous reviewers for comments on an earlier draft of this paper.     

Revisionary Dispositionalism and Practical Reason

This paper examines the metaphysically modest view that attributionsof normative reasons can be made true in the absence of a responseindependent normative reality. The paper despairs in finding asatisfactory account of normative reasons in metaphysically modestterms.     

Conditional Direction Dependence Analysis: Evaluating the Causal Direction of Effects in Linear Models with Interaction Terms

Abstract

Direction dependence analysis (DDA) makes use of higher than second moment information of variables (x and y) to detect potential confounding and to probe the causal direction of linear variable relations (i.e., whether x?→?y or y?→?x better approximates the underlying causal mechanism). The “true” predictor is assumed to be a continuous nonnormal exogenous variable. Existing methods compatible with DDA, however, are of limited use when the relation of a focal predictor and an outcome is affected by a moderator. This study presents a conditional direction dependence analysis (CDDA) framework which enables researchers to evaluate the causal direction of conditional regression effects. Monte–Carlo simulations were used to evaluate two different moderation scenarios: Study 1 evaluates the performance of CDDA tests when a moderator affects the strength of the causal effect x?→?y. Study 2 evaluates cases in which the causal direction itself (x?→?y vs y?→?x) depends on moderator values. Study 3 evaluates the robustness of DDA tests in the presence of functional model misspecifications. Results suggest that significance tests compatible with CDDA are suitable in both moderation scenarios, i.e., CDDA allows one to discern regions of a moderator in which the causal direction is uniquely identifiable. An empirical example is provided to illustrate the approach.     

Brain tumor detection using fusion of hand crafted and deep learning features

The perilous disease in the worldwide now a days is brain tumor. Tumor affects the brain by damaging healthy tissues or intensifying intra cranial pressure. Hence, rapid growth in tumor cells may lead to death. Therefore, early brain tumor diagnosis is a more momentous task that can save patient from adverse effects. In the proposed work, the Grab cut method is applied for accurate segmentation of actual lesion symptoms while Transfer learning model visual geometry group (VGG-19) is fine-tuned to acquire the features which are then concatenated with hand crafted (shape and texture) features through serial based method. These features are optimized through entropy for accurate and fast classification and fused vector is supplied to classifiers. The presented model is tested on top medical image computing and computer-assisted intervention (MICCAI) challenge databases including multimodal brain tumor segmentation (BRATS) 2015, 2016, and 2017 respectively. The testing results with dice similarity coefficient (DSC) achieve 0.99 on BRATS 2015, 1.00 on BRATS 2015 and 0.99 on BRATS 2017 respectively.     

Compulsive exercise or exercise dependence? Clarifying conceptualizations of exercise in the context of eating disorder pathology

ObjectiveMaladaptive exercise relates to eating disorder (ED) pathology and impairment in clinical and non-clinical populations. At present, two different conceptualizations of maladaptive exercise are often studied in relation to ED pathology: compulsive exercise and exercise dependence. Compulsive exercise functions to avoid negative affect (e.g., guilt and anxiety) associated with not exercising, whereas exercise dependence is associated with tolerance to exercise benefits and avoidance of exercise withdrawal. At present, clinicians and researchers struggle to determine the most appropriate term for describing problematic exercise in individuals with ED pathology. This study aimed to directly compare these conceptualizations of maladaptive exercise in relation to severity of ED pathology.DesignThis study examined cross-sectional data.MethodUndergraduate participants (N = 235, 78% female) with elevated ED pathology completed the Eating Disorder Examination Questionnaire (EDE-Q), Compulsive Exercise Test (CET), and Exercise Dependence Scale (EDS). Multiple linear regression analyses evaluated associations between EDE-Q and CET and EDS scores and dominance analysis determined which qualities of exercise were uniquely associated with EDE-Q scores.ResultsResults suggest that compulsive qualities of exercise, including exercise to control shape and weight and to avoid negative affect are more strongly associated with severity of ED pathology than qualities of exercise dependence.ConclusionsClinicians and researchers working with ED populations can benefit from prioritizing assessments that capture compulsive qualities of exercise. Additionally, these results suggest that interventions that effectively target other compulsive behaviors (e.g., exposure and response prevention) may be promising treatment options for problematic exercise in the context of EDs.     

Non-invasive estimation of local field potentials for neuroprosthesis control

Recent experiments have shown the possibility of using the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or non-invasive, depending on how the brain signals are recorded. In principle, invasive approaches will provide a more natural and flexible control of neuroprostheses, but their use in humans is debatable given the inherent medical risks. Non-invasive approaches mainly use scalp electroencephalogram (EEG) signals and their main disadvantage is that these signals represent the noisy spatiotemporal overlapping of activity arising from very diverse brain regions, i.e., a single scalp electrode picks up and mixes the temporal activity of myriads of neurons at very different brain areas. In order to combine the benefits of both approaches, we propose to rely on the non-invasive estimation of local field potentials (LFP) in the whole human brain from the scalp measured EEG data using a recently developed inverse solution (ELECTRA) to the EEG inverse problem. The goal of a linear inverse procedure is to de-convolve or un-mix the scalp signals attributing to each brain area its own temporal activity. To illustrate the advantage of this approach we compare, using an identical set of spectral features, classification of rapid voluntary finger self-tapping with left and right hands based on scalp EEG and non-invasively estimated LFP on two subjects using a different number of electrodes.