A computerized test of speed of language comprehension unconfounded by literacy

A computerised version of the Silly Sentences task developed for use with children (Baddeley et al, 1995) is found to be equivalent to the pencil-and-paper version from the SCOLP Test (Baddeley et al, 1992) with UK undergraduates, and is usable by a sample of young UK children. Because the sentences are presented aloud instead of being written, the computerised test is not affected by literacy skills. Translated into Kiswahili, the task was used in Tanzanian schools, despite the absence of an electricity supply and a very different cultural background. The decision latencies had a test-retest reliability of 0.69 over 5 months, and were independent of age and baseline decision speed. The task appears appropriate for longitudinal studies, including those in developing countries. Given its simplicity and the correlations with the original SCOLP version of the task, it may also be useful in studies on literate adults

Residuals and goodness-of-fit tests for stationary marked Gibbs point processes

The inspection of residuals is a fundamental step to investigate the quality of adjustment of a parametric model to data. For spatial point processes, the concept of residuals has been recently proposed by Baddeley et al. (2005) as an empirical counterpart of the {\it Campbell equilibrium} equation for marked Gibbs point processes. The present paper focuses on stationary marked Gibbs point processes and deals with asymptotic properties of residuals for such processes. In particular, the consistency and the asymptotic normality are obtained for a wide class of residuals including the classical ones (raw residuals, inverse residuals, Pearson residuals). Based on these asymptotic results, we define goodness-of-fit tests with Type-I error theoretically controlled. One of these tests constitutes an extension of the quadrat counting test widely used to test the null hypothesis of a homogeneous Poisson point process

Social Influence and Individual Difference in Experimental Juries

In a jury decision-making, individuals must compromise in order to reach a group consensus. If individuals compromise for non-rational reasons, such as a preference for conformity or due to erroneous information, then the final decision of the group may be biased. This paper presents original experimental data which shows that groups do have a significant tendency to compromise in jury-like settings. Econometric evidence also shows that features of groups, including the generosity of the group overall, will dictate the extent of compromise. The data also reveal that individual traits such as gender and capacity for empathy are associated with the extent of compromise in a jury-type setting. The implications are that interactions between individual and group characteristics limit the objectivity of decision-making

An architecturally constrained model of random number generation and its application to modeling the effect of generation rate

Random number generation (RNG) is a complex cognitive task for human subjects, requiring deliberative control to avoid production of habitual, stereotyped sequences. Under various manipulations (e.g., speeded responding, transcranial magnetic stimulation, or neurological damage) the performance of human subjects deteriorates, as reflected in a number of qualitatively distinct, dissociable biases. For example, the intrusion of stereotyped behavior (e.g., counting) increases at faster rates of generation. Theoretical accounts of the task postulate that it requires the integrated operation of multiple, computationally heterogeneous cognitive control (“executive”) processes. We present a computational model of RNG, within the framework of a novel, neuropsychologically-inspired cognitive architecture, ESPro. Manipulating the rate of sequence generation in the model reproduced a number of key effects observed in empirical studies, including increasing sequence stereotypy at faster rates. Within the model, this was due to time limitations on the interaction of supervisory control processes, namely, task setting, proposal of responses, monitoring, and response inhibition. The model thus supports the fractionation of executive function into multiple, computationally heterogeneous processes

Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models

We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a "pseudo-score" test derived from Besag's pseudo-likelihood, and to a class of diagnostics based on point process residuals. The results lend theoretical support to the established practice of using functional summary statistics, such as Ripley's $K$-function, when testing for complete spatial randomness; and they provide new tools such as the compensator of the $K$-function for testing other fitted models. The results also support localization methods such as the scan statistic and smoothed residual plots. Software for computing the diagnostics is provided.Comment: Published in at http://dx.doi.org/10.1214/11-STS367 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Generalization of color by chickens: experimental observations and a Bayesian model

Sensory generalization influences animals' responses to novel stimuli. Because color forms a perceptual continuum, it is a good subject for studying generalization. Moreover, because different causes of variation in spectral signals, such as pigmentation, gloss, and illumination, have differing behavioral significance, it may be beneficial to have adaptable generalization. We report on generalization by poultry chicks following differential training to rewarded (T+) and unrewarded (T−) colors, in particular on the phenomenon of peak shift, which leads to subjects preferring stimuli displaced away from T−. The first three experiments test effects of learning either a fine or a coarse discrimination. In experiments 1 and 2, peak shift occurs, but contrary to some predictions, the shift is smaller after the animal learned a fine discrimination than after it learned a coarse discrimination. Experiment 3 finds a similar effect for generalization on a color axis orthogonal to that separating T+ from T−. Experiment 4 shows that generalization is rapidly modified by experience. These results imply that the scale of a “perceptual ruler” is set by experience. We show that the observations are consistent with generalization following principles of Bayesian inference, which forms a powerful framework for understanding this type of behavior