Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia—the existence of a direct and an indirect pathway that compete against each other. This characteristic has important consequences in decision-making tasks, which are brought to light by Parkinson's disease as (...) well as genetic differences in dopamine receptors. This paper shows that a standard model of action selection in a cognitive architecture cannot replicate any of these findings, details an alternative solution that reconciles action selection in the architecture with the physiology of the basal ganglia, and extends the domain of application of cognitive architectures. The implication of this solution for other architectures and existing models are discussed. (shrink)

Objective: Clock variance is an important statistic in many clinical and developmental studies. Existing methods require a large number of trials for accurate clock variability assessment, which is problematic in studies using clinical or either young or aged participants. Furthermore, these existing methods often implicitly convolute clock and memory processes, making it difficult to disentangle whether the clock or memory system are driving the observed deviations. Here we assessed whether twenty repeated productions of a well-engrained interval (1 second), a task (...) that does not incorporate memory updating nor the processing of feedback, could provide an accurate assessment of clock variability. Method: Sixty-eight undergraduate students completed two tasks: a 1-second production task in which they were asked to produce a 1-second duration by ending a tone by a keypress, and a multi-duration reproduction task. Durations presented in the reproduction task were tones lasting 1.17, 1.4 and 1.68 seconds. No feedback was presented in either task, and the order of presentation was counterbalanced between participants. Results: The observed central tendency in the reproduction task was better explained by models including the measures of clock variability derived from the 1-second production task than by models without it. Three clock variability measures were calculated for each participant (standard deviation, root mean squared residuals (RMSR) from an estimated linear slope, and RMSR scaled by mean production duration). The model including the scaled RMSR was prefered over the alternative models, and no notable effects of the order of presentation were observed. These results suggest that (1) measures of variability should account for drift, (2) the presentation of another timing task before a 1-second production task did not influence the assessment of the clock variability, and (3) the observed variability adheres to the scalar property and predicts temporal performance, and is thus a usable index of clock variability. Conclusion: This study shows that just 20 repeated productions of 1 second provide a reliable index of clock variability. As administering this task is fast and easy, it could prove to be useful in a large variety of developmental and clinical populations. (shrink)

One of the goals of computerized tutoring systems is to optimize the learning of facts. Over a hundred years of declarative memory research have identified two robust effects that can improve such systems: the spacing and the testing effect. By making optimal use of both and adjusting the system to the individual learner using cognitive models based on declarative memory theories, such systems consistently outperform traditional methods. This adjustment process is driven by a continuously updated estimate of the rate of (...) forgetting for each item and learner on the basis of the learner's accuracy and response time. In this study, we investigated to what extent these estimates of individual rates of forgetting are stable over time and across different materials. We demonstrate that they are stable over time but not across materials. Even though most theories of human declarative memory assume a single underlying rate of forgetting, we show that, in practice, it makes sense to assume different materials are forgotten at different rates. If a computerized, adaptive fact-learning system allowed different rates of forgetting for different materials, it could adapt to individual learners more readily. (shrink)