Working Memory, Strategies, and Reasoning Tasks

Author(s):  
Kenneth J Gilhooly
1995 ◽  
Vol 23 (6) ◽  
pp. 735-748 ◽  
Author(s):  
Desiree Budd ◽  
Paul Whitney ◽  
Kandi Jo Turley

2014 ◽  
Vol 43 (3) ◽  
pp. 389-396 ◽  
Author(s):  
Tyler L. Harrison ◽  
Zach Shipstead ◽  
Randall W. Engle

2020 ◽  
Vol 46 (2) ◽  
pp. 93-127 ◽  
Author(s):  
Johann Chevalère ◽  
Patrick Lemaire ◽  
Valérie Camos

2014 ◽  
Vol 5 (3) ◽  
pp. 22850 ◽  
Author(s):  
Bert Jonsson ◽  
Carola Wiklund-Hörnqvist ◽  
Mikaela Nyroos ◽  
Arne Börjesson

2009 ◽  
Vol 364 (1522) ◽  
pp. 1385-1391 ◽  
Author(s):  
Laurent Mottron ◽  
Michelle Dawson ◽  
Isabelle Soulières

According to the enhanced perceptual functioning (EPF) model, autistic perception is characterized by: enhanced low-level operations; locally oriented processing as a default setting; greater activation of perceptual areas during a range of visuospatial, language, working memory or reasoning tasks; autonomy towards higher processes; and superior involvement in intelligence. EPF has been useful in accounting for autistic relative peaks of ability in the visual and auditory modalities. However, the role played by atypical perceptual mechanisms in the emergence and character of savant abilities remains underdeveloped. We now propose that enhanced detection of patterns, including similarity within and among patterns, is one of the mechanisms responsible for operations on human codes, a type of material with which savants show particular facility. This mechanism would favour an orientation towards material possessing the highest level of internal structure, through the implicit detection of within- and between-code isomorphisms. A second mechanism, related to but exceeding the existing concept of redintegration, involves completion, or filling-in, of missing information in memorized or perceived units or structures. In the context of autistics' enhanced perception, the nature and extent of these two mechanisms, and their possible contribution to the creativity evident in savant performance, are explored.


2016 ◽  
Vol 26 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Susan Colmar ◽  
Nash Davis ◽  
Linda Sheldon

An exploratory applied study, using a set of attention and working memory strategies specifically developed for students and named Memory Mates, was completed with normally developing students attending a primary school. Students in one classroom received the intervention, while the other classroom functioned as a control group. The study was experimental, with quantitative measures. Additional qualitative data was collected to facilitate the ongoing development of Memory Mates. A working memory instrument was used to rank students initially, and as a post-intervention measure for children with low working memory, with some gains in working memory observed in the experimental classroom students. Data were collected on academic achievement in reading, spelling, and maths. Post-intervention data analysis of the impact of the Memory Mates intervention showed no differences between the experimental and control groups for standardised academic measures. Several reasons are postulated for the lack of significant quantifiable change, chiefly the short period of intervention.


2019 ◽  
Author(s):  
Andrea Alamia ◽  
Canhuang Luo ◽  
Matthew Ricci ◽  
Junkyung Kim ◽  
Thomas Serre ◽  
...  

AbstractThe development of deep convolutional networks (DCNs) has recently led to great successes in computer vision and have become de facto computational models of vision. However, a growing body of work suggests that they exhibit critical limitations beyond image categorization. Here, we study a fundamental limitation of DCNs for judging whether two items are the same or different (SD) compared to a baseline assessment of their spatial relationship (SR). We test the prediction that SD tasks recruit additional cortical mechanisms which underlie critical aspects of visual cognition that are not explained by current computational models. We thus recorded EEG signals from 14 participants engaged in the same tasks as the computational models. Importantly, the two tasks were matched in terms of difficulty by an adaptive psychometric procedure: yet, on top of a modulation of evoked potentials, our results revealed higher activity in the low beta (13-20Hz) band in the SD compared to the SR conditions, which we surmise as reflecting the crucial involvement of recurrent mechanisms sustaining working memory and attention.Author SummaryDespite the impressive progress of deep convolutional networks (DCNs) in object recognition, recent studies demonstrated that state-of-the-art vision algorithms encounter severe limitations when performing certain visual reasoning tasks: for instance, convolutional networks can easily solve problems involving spatial relations, but fail in identifying whether two items are identical or different (same-different task). This conclusion led us to test the hypothesis that different computational mechanisms are needed to successfully perform these tasks also in the visual system. First, we confirmed in our simulations that DCNs can successfully perform spatial relationship tasks but struggle with same-different ones. Then, we tested 14 participants on the same experimental design while recording their EEG signals. Remarkably, our results revealed a significant difference between the tasks in the occipital brain regions both in evoked potentials and in the oscillatory dynamics. Specifically, an increase of activity was found when performing the SD over the SR condition. We interpret these results as reflecting the fundamental involvement of recurrent mechanisms implementing cognitive functions such as working memory and attention.


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