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Laura Lazartigues

Doctorant -  UCA


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pour "Laura LAZARTIGUES" :

titre
Organization in Working Memory is Driven by the Compressibility of Information
auteur
Laura Lazartigues, Frédéric Lavigne, Carlos Aguilar, Fabien Mathy
article
60th Annual Meeting of the Psychonomic Society, Nov 2019, Montréal, Canada
annee_publi
2019
resume
Working memory (WM) is known to be limited in capacity, but mechanisms based on compression of information could contribute to the storage process. It has been shown that chunking governed by compression could be one of these mechanisms. The present study investigated how chunks can be formed using patterns to be discovered on the spot, that is, without these chunks being already formed in long-term memory. We predicted that a compact representation could leave room in WM at the expense of the quality. Our method was based on a compressibility metric that allowed prediction of memory errors linked to a lossy compression process. Our result showed that RTs and errors depended on compressibility, and those measures might be interpretable in terms of over-compressibility. We discuss the results to conclude that the present study offers a comprehension of WM capacity which cannot be accounted easily by shared-allocation models or discrete-slots models.
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Poster
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titre
Statistical learning of adjacent and non-adjacent pairs in non-linguistic short sequences
auteur
Laura Lazartigues, Fabien Mathy, Arnaud Rey, Joël Fagot, Frédéric Lavigne
article
21st Conference of the European Society for Cognitive Psychology (ESCOP), Sep 2019, Tenerife, Spain
annee_publi
2019
resume
The ability to learn adjacent and non-adjacent pairs is central in language processing. However, current evidence indicates that adjacent and non-adjacent pairs are not equally learnable. The present study investigated the role of transitional probabilities during the learning of adjacent and non-adjacent pairs appearing in non-linguistic short sequences. Participants were exposed to four sequences of three stimuli ABC repeated randomly during the experiment, with each stimulus corresponding to a given position of a dot on a touchscreen. In the first experiment the transition BC of the triplet ABC was predictable while the first transition AB was unpredictable. The second experiment required the learning of the fully predictable non-adjacent pair AC while the transitions AB and BC were unpredictable. The results showed that participants learned adjacent pairs and had greater difficulty to learn the non-adjacent pairs. These data provide additional constraints for modeling statistical learning mechanisms.
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Poster
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titre
Statistical learning of first and second order transitional probabilities
auteur
Laura Lazartigues, Fabien Mathy, Arnaud Rey, Joël Fagot, Frédéric Lavigne
article
Interdisciplinary Advances in Statistical Learning, Jun 2019, San Sebastian, Spain
annee_publi
2019
resume
The present study manipulates first and second order transitional probabilities during the statistical learning of short sequences. Participants were exposed to four sequences of three stimuli (ABC) repeated during the task, with each stimulus corresponding to the position of a red dot on a touchscreen. Participants were required to touch the dots as quickly as possible and response times were recorded between the first two stimuli (Transition Time 1 or TT1) and between the last two stimuli (TT2). In the first experiment the transition AB of a triplet ABC was fully predictable (p(B|A) = 1) while the second transition BC was unpredictable (p(C|B) = .5). The second experiment was a serial version of the exclusive-or (XOR), all first order transitional probabilities were equally unpredictable (p(B|A) = .5, p(C|B) = .5), while the combination of the first two stimuli fully predicted the last stimulus (p(C|AB) = 1). Results showed that participants were able to learn both type of transitional probabilities. The different evolution patterns of TT1 and TT2 and their implications in term of statistical learning mechanisms are discussed.
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Poster
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