The attentional cost of amplitude and directional requirements when pointing to targets

The aim of this study was to investigate the comparative cost of accuracy constraints in direction or amplitude for movement regulation. The attentional cost is operationally defined as the amount of disturbance created in a secondary task by the simultaneous execution of a pointing task in direction or amplitude. The cost is expressed in terms of modifications in response to a secondary task, consisting of a foot-pedal release in response to an auditory stimulus (probe). The probe was introduced during the programming portion or the first, middle, or last portion of the pointing movement. The independent variables were the requirements of the task: direction or amplitude, and the moments of occurrence of the probe. Subjects were submitted to eight experimental conditions: (1) simple foot reaction time to a buzzer; (2) single directional task; (3) single amplitude task; (4) dual directional task (i.e. directional task with probe); (5) dual amplitude task (i.e. amplitude task with probe); (6) retest of foot simple reaction time; (7) retest of single directional task; and (8) retest of single amplitude task. Regulation in direction was more attention-demanding than regulation in distance in terms of programming. During pointing in amplitude, probe RT increased monotonically from start to end of movement execution, whereas directional pointing did not lead to any significant probe RT changes. These results emphasize the specific attentional loads for directional and amplitude pointing tasks, hence the involvement of different central nervous system mechanisms for the programming and regulation of the directional and amplitude parameters of pointing movements.     

Individual prediction of dyslexia by single versus multiple deficit models

The overall goals of this study were to test single versus multiple cognitive deficit models of dyslexia (reading disability) at the level of individual cases and to determine the clinical utility of these models for prediction and diagnosis of dyslexia. To accomplish these goals, we tested five cognitive models of dyslexia--two single-deficit models, two multiple-deficit models, and one hybrid model--in two large population-based samples, one cross-sectional (Colorado Learning Disability Research Center) and one longitudinal (International longitudinal Twin Study). The cognitive deficits included in these cognitive models were in phonological awareness, language skill, and processing speed and/or naming speed. To determine whether an individual case fit one of these models, we used two methods: 1) the presence or absence of the predicted cognitive deficits, and 2) whether the individual's level of reading skill best fit the regression equation with the relevant cognitive predictors (i.e., whether their reading skill was proportional to those cognitive predictors.) We found that roughly equal proportions of cases met both tests of model fit for the multiple deficit models (30-36%) and single deficit models (24-28%); hence, the hybrid model provided the best overall fit to the data. The remaining roughly 40% of cases in each sample lacked the deficit or deficits that corresponded with their best-fitting regression model. We discuss the clinical implications of these results for both diagnosis of school-age children and preschool prediction of children at risk for dyslexia.