Motion in depth: adequate and inadequate simulation

We measured errors in estimating the absolute time to collision with a simulated approaching textured object. The texture elements were circular bright dots. When we matched the rate of angular expansion of the simulated object, the rate of expansion of the texture dots, and the rate of increase of dot separation, so as to accurately simulate an approaching object, errors were small underestimations that were independent of dot size (mean of 3.2%). When dot angular size was held constant during the simulated approach, errors were the same as when the simulation was accurate, provided that dot size was less than 2.2-4.4 min of arc. As dot size was progressively increased, errors changed to overestimations. For the largest dot size used (10.5 min of arc at time t = 0), time to collision was overestimated by up to 21%. A sufficiently large overestimation would mean that measures taken to avoid collision would be too late. We suggest that the relevance to everyday life of data on the perception of motion in depth and self-motion collected using constant-sized dot displays might be questionable if dot size exceeds 2.2-4.4 min of arc.     

Comment on “Visual layout modulates Fitts’s law: The importance of first and last positions”

Pratt, Adam, and Fischer (2007) investigated the effect of surrounding targets on the time it took to move to an individual target and found that the movement time to a central target was above the Fitts’s law line related to the first and last targets. They explained their results in terms of a “visuomotor hypothesis.” Here, an alternative explanation is given in terms of a previously validated model of the “available target width” that is determined by the size of the target and the width of the finger pad that is being used to hit the target.     

The detection of feigned disabilities: the effectiveness of the Personality Assessment Inventory in a traumatized inpatient sample

Research on feigned mental disorders indicates that severe psychopathology coupled with significant trauma histories often complicate feigning determinations, resulting in inaccuracies on otherwise effective measures. As part of malingering assessments, the Personality Assessment Inventory (PAI) is often used because of its excellent validation and the availability of three feigning indicators (Negative Impression, Malingering Index, and Rogers Discriminant Function), which have evidenced large effect sizes and clinically useful cut scores. The current study examined the effectiveness of the PAI in a traumatized inpatient sample using a between-subjects simulation design. Although Negative Impression appeared affected by trauma--especially in conjunction with dissociative symptoms--very positive results were found for Malingering Index and Rogers Discriminant Function. They remained relatively unelevated under honest conditions, despite posttraumatic stress disorder and extensive comorbidity. Using single-point cut scores provided moderately good classification of feigned and genuine PAI profiles. For purposes of classification, the authors operationally defined small indeterminate groups that were considered too close to classify (i.e., ±5T of the cut scores). With indeterminate cases removed, the overall classification rates improved modestly. However, the more important finding involved the error rates for the indeterminate group, which exceeded 50%. Directions for further research are discussed.     

Tools from evolutionary biology shed new light on the diversification of languages

Computational methods have revolutionized evolutionary biology. In this paper we explore the impact these methods are now having on our understanding of the forces that both affect the diversification of human languages and shape human cognition. We show how these methods can illuminate problems ranging from the nature of constraints on linguistic variation to the role that social processes play in determining the rate of linguistic change. Throughout the paper we argue that the cognitive sciences should move away from an idealized model of human cognition, to a more biologically realistic model where variation is central.