Individual differences in sensory integration predict differences in time perception and individual levels of schizotypy

To interact functionally with our environment, our perception must locate events in time, including discerning whether sensory events are simultaneous. The Temporal Binding Window (TBW; the time window within which two stimuli tend to be integrated into one event) has been shown to relate to individual differences in perception, including schizotypy, but the relationship with subjective estimates of duration is unclear. We compare individual TBWs with individual differences in the filled duration illusion, exploiting differences in perception between empty and filled durations (the latter typically being perceived as longer). Schizotypy has been related to both these measures and is included to explore a potential link between these tasks and enduring perceptual differences. Results suggest that individuals with a narrower TBW make longer estimates for empty durations and demonstrate less variability in both conditions. Exploratory analysis of schizotypy data suggests a relationship with the TBW but is inconclusive regarding time perception.     

A two-fold transformation model for human action recognition using decisive pose

Human action recognition in videos is a tough task due to the complex background, geometrical transformation and an enormous volume of data. Hence, to address these issues, an effective algorithm is developed, which can identify human action in videos using a single decisive pose. To achieve the task, a decisive pose is extracted using optical flow, and further, feature extraction is done via a two-fold transformation of wavelet. The two-fold transformation is done via Gabor Wavelet Transform (GWT) and Ridgelet Transform (RT). The GWT produces a feature vector by calculating first-order statistics values of different scale and orientations of an input pose, which have robustness against translation, scaling and rotation. The orientation-dependent shape characteristics of human action are computed using RT. The fusion of these features gives a robust unified algorithm. The effectiveness of the algorithm is measured on four publicly datasets i.e. KTH, Weizmann, Ballet Movement, and UT Interaction and accuracy reported on these datasets are 96.66%, 96%, 92.75% and 100%, respectively. The comparison of accuracies with similar state-of-the-arts shows superior performance.     

Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer-adaptive practice

We introduce a general response model that allows for several simple restrictions, resulting in other models such as the extended Rasch model. For the extended Rasch model, a dynamic Bayesian estimation procedure is provided, which is able to deal with data sets that change over time, and possibly include many missing values. To ensure comparability over time, a data augmentation method is used, which provides an augmented person-by-item data matrix and reproduces the sufficient statistics of the complete data matrix. Hence, longitudinal comparisons can be easily made based on simple summaries, such as proportion correct, sum score, etc. As an illustration of the method, an example is provided using data from a computer-adaptive practice mathematical environment.     

A noniterative method of joint correspondence analysis

Correspondence analysis leads to a graphical representation of the associations between categories of the row and column variables of a contingency table. Greenacre's (1988) formulation of joint correspondence analysis is a multivariate extension which finds the optimal joint display of contingency tables between all pairs of variables in a set. Greenacre presented a discrepancy function and an alternating least squares algorithm for its minimization. Boik (1996) presented an alternative algorithm, also of the alternating least squares type, for minimizing the same discrepancy function. In this paper, a noniterative procedure, not based on the minimization of any discrepancy function, is described.     

Sample size requirements for estimating pearson, kendall and spearman correlations

Interval estimates of the Pearson, Kendall tau-a and Spearman correlations are reviewed and an improved standard error for the Spearman correlation is proposed. The sample size required to yield a confidence interval having the desired width is examined. A two-stage approximation to the sample size requirement is shown to give accurate results.     

An estimate of the covariance between variables which are not jointly observed

Situations sometimes arise in which variables collected in a study are not jointly observed. This typically occurs because of study design. An example is an equating study where distinct groups of subjects are administered different sections of a test. In the normal maximum likelihood function to estimate the covariance matrix among all variables, elements corresponding to those that are not jointly observed are unidentified. If a factor analysis model holds for the variables, however, then all sections of the matrix can be accurately estimated, using the fact that the covariances are a function of the factor loadings. Standard errors of the estimated covariances can be obtained by the delta method. In addition to estimating the covariance matrix in this design, the method can be applied to other problems such as regression factor analysis. Two examples are presented to illustrate the method. This research was partially supported by NIMH grant MH5-4576     

Graphical regression models for polytomous variables

When modeling the relationship between two nominal categorical variables, it is often desirable to include covariates to understand how individuals differ in their response behavior. Typically, however, not all the relevant covariates are available, with the result that the measured variables cannot fully account for the associations between the nominal variables. Under the assumption that the observed and unobserved variables follow a homogeneous conditional Gaussian distribution, this paper proposesRC(M) regression models to decompose the residual associations between the polytomous variables. Based on Goodman's (1979, 1985)RC(M) association model, a distinctive feature ofRC(M) regression models is that they facilitate the joint estimation of effects due to manifest and omitted (continuous) variables without requiring numerical integration. TheRC(M) regression models are illustrated using data from the High School and Beyond study (Tatsuoka & Lohnes, 1988). This article was accepted for publication, when Willem J. Heiser was the Editor ofPsychometrika. This research was supported by grants from the National Science Foundation (#SBR96-17510 and #SBR94-09531) and the Bureau of Educational Research at the University of Illinois. We thank Jee-Seon Kim for comments and computational assistance.     

Crossover by Line Length and Spatial Location

It is well known that line length has a systematic influence on line bisection error in neglect. Most patients with neglect misbisect long lines on the same side of true center as their brain lesion but then cross over on short lines, misbisecting them on the opposite side (i.e., crossover by line length). What is less recognized is that the spatial location of lines relative to the viewer can similarly induce a crossover effect when one considers line bisection error scores that have been averaged across individual line lengths. Patients with right hemisphere injury and neglect classically make averaged line bisection errors that fall right of true center on lines located either at midline or to the left of the viewer; however, we observed that the averaged line bisection error can fall left of true center when lines are located to the right of the viewer (i.e., crossover by spatial location). We hypothesized that crossover by both line length and spatial location stem from systematic errors in magnitude estimation, i.e., perceived line length. We tested predictions based on this hypothesis by examining how the crossover effect by line length is altered by the spatial location of lines along a horizontal axis relative to the viewer. Participants included patients with unilateral lesions of the right and left cerebral hemispheres and age-appropriate normal subjects. All groups demonstrated a crossover effect by line length at the midline location but the effect was altered by placing lines to the right and left of the viewer. In particular, patients with right hemisphere injury and neglect crossed-over across a broader range of line lengths when the lines were located to the right of the viewer rather than at either midline or left of the viewer. It is proposed that mental representations of stimulus magnitude are altered in neglect, in addition to mental representations of space, and that traditional accounts of neglect can be enhanced by including the psychophysical concept of magnitude estimation.     

"Constructive" enumeration by chimpanzees (Pan troglodytes) on a computerized task

Two chimpanzees used a joystick to collect dots, one at a time, on a computer monitor (see video-clip in the electronic supplementary material), and then ended a trial when the number of dots collected was equal to the Arabic numeral presented for the trial. Both chimpanzees performed substantially and reliably above chance in collecting a quantity of dots equal to the target numeral, one chimpanzee for the numerals 1–7, and the second chimpanzee for the numerals 1–6. Errors that were made were seldom discrepant from the target by more than one dot quantity, and the perceptual process subitization was ruled out as an explanation for the performance. Additionally, analyses of trial duration data indicated that the chimpanzees were responding based on the numerosity of the constructed set rather than on the basis of temporal cues. The chimpanzees' decreasing performance with successively larger target numerals, however, appeared to be based on a continuous representation of magnitude rather than a discrete representation of number. Therefore, chimpanzee counting in this type of experimental task may be a process that represents magnitudes with scalar variability in that the memory for magnitudes associated with each numeral is imperfect and the variability of responses increases as a function of the numeral's value. Accepted after revision: 11 June 2001 Electronic Publication     

小脑与发展性阅读障碍

发展性阅读障碍是学龄儿童面临的学习问题之一。近年来,许多行为和神经生理学、影像学实验都发现,发展性阅读障碍的儿童有明显的运动功能失调,如平衡性差、身体灵敏度不够以及自动化水平低。Nicolson等人提出的小脑理论认为,阅读障碍者的小脑功能失调影响了书写及发音,导致语音及阅读能力不足,而且小脑与时间控制有关,阅读障碍者的时间估计能力有缺陷与他们的小脑功能失调有关。本文回顾了有关小脑理论的研究,并指出小脑的认知功能还有待进一步的研究。