Modeling working memory: An interference model of complex span

This article introduces a new computational model for the complex-span task, the most popular task for studying working memory. SOB-CS is a two-layer neural network that associates distributed item representations with distributed, overlapping position markers. Memory capacity limits are explained by interference from a superposition of associations. Concurrent processing interferes with memory through involuntary encoding of distractors. Free time in-between distractors is used to remove irrelevant representations, thereby reducing interference. The model accounts for benchmark findings in four areas: (1) effects of processing pace, processing difficulty, and number of processing steps; (2) effects of serial position and error patterns; (3) effects of different kinds of item-distractor similarity; and (4) correlations between span tasks. The model makes several new predictions in these areas, which were confirmed experimentally

Retrospective judgments of confidence in a complex span task

International audienceAlthough the study of metamemory monitoring originated in predictions for simple span tasks, the study of metacognition for working memory (WM) has been somewhat neglected in comparison with long-term memory. We aimed to fill this gap by exploring the ability to self-assess WM operations. Thirty-four participants performed 16 series of complex span tasks and rated their confidence in a verbal recall paradigm. We manipulated the cognitive load based on the TBRS model in order to analyze the role of attentional resources on both WM and metacognitive evaluations. As expected, we found that recall is affected by cognitive load and we found standard serial position effects. Interestingly, metacognitive evaluations followed the same pattern, and measures of metacognitive sensitivity suggest that participants are able to make item-by-item retrospective judgments reflective of their performance. We discuss how these results contribute to our understanding of metacognitive access to newly-formed WM contents

A novel mutation L260P of the steroidogenic acute regulatory protein gene in three unrelated patients of Swiss ancestry with congenital lipoid adrenal hyperplasia

CONTEXT: Lipoid congenital adrenal hyperplasia (CAH) is the most severe form of CAH leading to impaired production of all adrenal and gonadal steroids. Mutations in the gene encoding steroidogenic acute regulatory protein (StAR) cause lipoid CAH. OBJECTIVE: We investigated three unrelated patients of Swiss ancestry who all carried novel mutations in the StAR gene. All three subjects were phenotypic females with absent Mullerian derivatives, 46,XY karyotype, and presented with adrenal failure. METHODS AND RESULTS: StAR gene analysis showed that one patient was homozygous and the other two were heterozygous for the novel missense mutation L260P. Of the heterozygote patients, one carried the novel missense mutation L157P and one had a novel frameshift mutation (629-630delCT) on the second allele. The functional ability of all three StAR mutations to promote pregnenolone production was severely attenuated in COS-1 cells transfected with the cholesterol side-chain cleavage system and mutant vs. wild-type StAR expression vectors. CONCLUSIONS: These cases highlight the importance of StAR-dependent steroidogenesis during fetal development and early infancy; expand the geographic distribution of this condition; and finally establish a new, prevalent StAR mutation (L260P) for the Swiss population

Faisabilite du soudage robotise laser YAG de forte puissance avec utilisation de fibre optique applique a l'assemblage de grands ensembles mecano-soudes

Available from INIST (FR), Document Supply Service, under shelf-number : AR 16333 (1); AR 16333 (2); AR 16333 (3); AR 16333 (4); AR 16333 (5) / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEMinistere de l'Enseignement Superieur et de la Recherche, 75 - Paris (France)FRFranc

Cognitive Load Theory and Time Considerations: Using the Time-Based Resource Sharing Model

International audienceFor a long time, Cognitive Load Theory has considered working memory models as tools to advance research on learning. It has used working memory capacity models, where working memory is viewed as being composed of a discrete number of slots (i.e., chunks) that can be kept active. However, recent results have shown that for a fixed quantity of information, the mere pace of information presentation can affect learning performance. Commonly used working memory models cannot explain such results. Here, we propose to use a new model in the field of Cognitive Load Theory, the Time-Based Resource Sharing model, which enables time to be taken into account when describing working memory solicitation. In two experiments, we tested hypotheses allowed by the model. Results showed that the Time-Based Resource Sharing model can assist the investigation of information presentation pace effects during learning, as long as prior knowledge is taken into account. Particularly, the results suggest a new interpretation of intrinsic and extrinsic load that could relate them to the time needed to process information