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Frédéric Lavigne

PR  -  UCA

My research interests are in the areas of prediction and language comprehension. They focus on the dynamics of semantic and combinatory learning and processing in memory (experimental approach) and the underlying synaptic and neuronal mechanisms in the cerebral cortex (modeling approach).

CV

Frédéric Lavigne

Researcher/Professor in Cognitive Science.

Laboratoire BCL (Bases, corpus, Langage) - UMR 7320 CNRS - Université de Nice - Sophia Antipolis, France. Equipe Langage et Cognition

Research Background :

Post Doc positions:

  • Laboratoire de Neurophysiologie de la Perception et de l’Action - CNRS - Collège de France, Paris, France.
  • Laboratorium voor Experimentele Psychologie - Katholieke Universiteit, Leuven, Belgium.

Ph.D. in Cognitive Sciences: Laboratoire Language, Cognition, Ergonomie. CNRS - Ecole Normale Supérieure, Paris, France.

Advanced Master Degree in Cognitive Sciences: Université Pierre et Marie Curie and EHESS, Paris, France.

Master Degree in Neuroscience and Psychophysiology: Université Pierre et Marie Curie, Paris, France.

Latest publicationsHAL

pour l'idHal "frederic-lavigne" :

titre
Dynamic branching in a neural network model for probabilistic prediction of sequences
auteur
Elif Köksal Ersöz, Pascal Chossat, Martin Krupa, Frédéric Lavigne
article
Journal of Computational Neuroscience, 2022, 50 (4), pp.537-557. ⟨10.1007/s10827-022-00830-y⟩
annee_publi
2022
resume
An important function of the brain is to predict which stimulus is likely to occur based on the perceived cues. The present research studied the branching behavior of a computational network model of populations of excitatory and inhibitory neurons, both analytically and through simulations. Results show how synaptic efficacy, retroactive inhibition and short-term synaptic depression determine the dynamics of selection between different branches predicting sequences of stimuli of different probabilities. Further results show that changes in the probability of the different predictions depend on variations of neuronal gain. Such variations allow the network to optimize the probability of its predictions to changing probabilities of the sequences without changing synaptic efficacy.
typdoc
Journal articles
Accès au texte intégral et bibtex
https://inria.hal.science/hal-03532787/file/article_EPMF.pdf BibTex
titre
Differential use of Transitional Probabilities and Frequency in Statistical Learning of Pseudowords
auteur
Laura Lazartigues, Fabien Mathy, Frédéric Lavigne
article
International Conference on Interdisciplinary Advances in Statistical Learning, Jun 2022, San Sebastian, Spain
annee_publi
2022
resume
The ability to learn transitional probabilities (TPs) and frequency is central to language processing. Current evidence indicates that both frequency and transitional probability are involved in the memorization of sequences, but the questions of which prevails and why it would prevail in statistical learning remain unclear. The present study investigated the respective roles of transitional probability and frequency in statistical learning of pseudowords in two different tasks that focused on either prediction or recognition. The learning phase consisted of the repeated presentation of sixteen three-syllable pseudowords for which participants were asked to perform a target detection task on vowels (fully predictable based on TPs). The evolution of the rate of correct answer and response times during the learning phase was recorded. After the detection task, a two-alternative forced-choice task (2AFC) required participants to choose between a pseudoword and a lure. Results indicated a prevalence of TPs during the detection task, but a prevalence of frequency during the 2AFC task. Our findings suggests that TPs and frequency can be used flexibly depending on which process (learning or recognition) is more adapted to the task.
typdoc
Poster communications
Accès au texte intégral et bibtex
https://hal.science/hal-03688991/file/Lazartigues2022.pdf BibTex
titre
Statistical Learning of Second-Order Transitional Probabilities in Humans
auteur
Laura Lazartigues, Fabien Mathy, Frédéric Lavigne
article
62nd Virtual annual meeting of the Psychonomic Society, Nov 2021, Virtuel, United States
annee_publi
2021
resume
The order of stimuli within sequences and the transitional probabilities (TPs) these orders generate are central information in language acquisition, but less is known about how this type of information is extracted by general learning mechanisms. The present study focused on the statistical learning of second-order TPs (i.e., only the combination of two stimuli allowing to predict the third) of visual sequences. Eight three-item sequences exclusively governed by second-order TPs were presented. The response times were measured with oculometry. The task included a learning phase and a switch phase which reset the second-order TPs (e.g., the sequences ABC and BAF became respectively ABF and BAC). Results indicated a sole decrease of RTs between the second and the third stimulus and an increase of RTs during the switch phase that suggested the learnability of second-order TPs. We discuss this result in light of language acquisition.
typdoc
Poster communications
Accès au texte intégral et bibtex
https://hal.science/hal-03509457/file/Statistical%20Learning%20of%20Second-Order%20Transitional%20Probabilities%20in%20Humans.pdf BibTex
titre
Benefits and pitfalls of data compression in visual working memory
auteur
Laura Lazartigues, Frédéric Lavigne, Carlos Aguilar, Nelson Cowan, Fabien Mathy
article
Attention, Perception, and Psychophysics, 2021, ⟨10.3758/s13414-021-02333-x⟩
annee_publi
2021
resume
Data compression in memory is a cognitive process allowing participants to cope with complexity to reduce information load. However, previous studies have not yet considered the hypothesis that this process could also lead to over-simplifying information due to haphazard amplification of the compression process itself. For instance, we could expect that the over-regularized features of a visual scene could produce false recognition of patterns, not because of storage capacity limits but because of an errant compression process. To prompt memory compression in our participants, we used multielement visual displays for which the underlying information varied in compressibility. The compressibility of our material could vary depending on the number of common features between the multi-dimensional objects in the displays. We measured both accuracy and response times by probing memory representations with probes that we hypothesized could modify the participants’ representations. We confirm that more compressible information facilitates performance, but a more novel finding is that compression can produce both typical memory errors and lengthened response times. Our findings provide clearer evidence of the forms of compression that participants carry out.
typdoc
Journal articles
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BibTex
titre
Probabilities, Dependencies and Frequency Are Not All Equally Involved in Artificial Word Learning
auteur
Laura Lazartigues, Fabien Mathy, Frédéric Lavigne
article
2021 Virtual APS Convention, May 2021, Virtuel, France
annee_publi
2021
resume
The ability to learn transitional probabilities (TPs), adjacent and non-adjacent dependencies and frequency is central to language processing. Current evidence indicates that both frequency and transitional probability impact the memorization of sequences, but it is not sure yet which type of information prevails. Also, adjacent and non-adjacent pairs do not seem to be equally learnable based on statistical learning. These three factors however are not yet integrated into a unique model predicting learning, whereas they are all supposed to play a critical role in statistical learning. The present study thus investigated the concurrent roles of transitional probability, frequency and adjacency within a single task aiming at having participants learn artificial words. Participants were exposed to four conditions, with each condition consisting in four words (sequences of three syllables without meaning) governed by a specific rule. The first condition tested first order TP between adjacent elements, where the second syllable only allowed to predict the third. The second condition tested first order TP between non-adjacent elements, where the first syllable only allowed to predict the third. The next condition tested second order TP, where only the combination of the two first syllables allowed to predict the third. The last condition tested the effect of the frequency for a given second order TP, by presenting two words five times per block, a third word two times per block and the fourth word eight times per block. All words were presented randomly in each block of the experiment. Participants had to perform a target detection task on the vowels that corresponded to the last syllable of each word, and which were fully predictable from the rules that governed the conditions. Correct answer rates and response times (RTs) were recorded. Each participant completed five sessions of ten blocks (eighty trials per block), one session per day for five days. A transfer block at the end of the last session was added to test whether participants could adapt to a switch inverting the vowels (but maintaining the rest of the rules). The results showed that words were learned in all conditions with an increase of correct answer rates, a decrease of RTs during the learning phase, and a drop of performance during the switch phase. Results further indicated easier learning of first order TPs with higher correct responses and shorter RTs compared second order TPs. We also observed an advantage for adjacent dependencies over non-adjacent ones. Moreover, a low frequency caused lower correct answer rates and slower RTs and seemed to interfere with the learning of new words . Analysis of frequency and first order TPs in the condition where the effect of the frequency for a given second order TP was tested indicated a prevalence of TPs over frequency at the end of the learning process.
typdoc
Poster communications
Accès au texte intégral et bibtex
https://hal.science/hal-03509434/file/Transitional%20Probabilities%2C%20Dependencies%20and%20Frequency%20are%20Not%20All%20Equally%20involved%20in%20Artificial%20Word%20Learning.pdf BibTex
titre
Statistical learning of unbalanced exclusive-or temporal sequences in humans
auteur
Laura Lazartigues, Fabien Mathy, Frédéric Lavigne
article
PLoS ONE, 2021, 16 (2), pp.e0246826. ⟨10.1371/journal.pone.0246826⟩
annee_publi
2021
resume
A pervasive issue in statistical learning has been to determine the parameters of regularity extraction. Our hypothesis was that the extraction of transitional probabilities can prevail over frequency if the task involves prediction. Participants were exposed to four repeated sequences of three stimuli (XYZ) with each stimulus corresponding to the position of a red dot on a touch screen that participants were required to touch sequentially. The temporal and spatial structure of the positions corresponded to a serial version of the exclusive-or (XOR) that allowed testing of the respective effect of frequency and first- and second-order transitional probabilities. The XOR allowed the first-order transitional probability to vary while being not completely related to frequency and to vary while the second-order transitional probability was fixed (p(Z|X,Y) = 1). The findings show that first-order transitional probability prevails over frequency to predict the second stimulus from the first and that it also influences the prediction of the third item despite the presence of second-order transitional probability that could have offered a certain prediction of the third item. These results are particularly informative in light of statistical learning models.
typdoc
Journal articles
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BibTex
titre
Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability
auteur
Elif Köksal Ersöz, Carlos Aguilar Melchor, Pascal Chossat, Martin Krupa, Frédéric Lavigne
article
PLoS ONE, 2020, 15 (4), pp.1-28. ⟨10.1371/journal.pone.0231165⟩
annee_publi
2020
resume
In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions activation of regular or irregular sequences. The switch between the two types of activation occurs through the modulation of biological parameters, without altering the connectivity matrix. Some of the parameters included in our model are neuronal gain, strength of inhibition, synaptic depression and noise. We investigate how these parameters enable the existence of sequences and influence the type of sequences observed. In particular we show that synaptic depression and noise drive the transitions from one memory item to the next and neuronal gain controls the switching between regular and irregular (random) activation.
typdoc
Journal articles
Accès au texte intégral et bibtex
https://hal.science/hal-02879964/file/journal.pone.0231165.pdf BibTex
titre
Neuronal mechanisms for sequential activation of memory items: dynamics and reliability
auteur
Elif Köksal-Ersöz, Carlos Aguilar, Pascal Chossat, Martin Krupa, Frédéric Lavigne
article
2019
annee_publi
2019
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Preprints, Working Papers, ...
Accès au bibtex
https://arxiv.org/pdf/1904.12133 BibTex
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.
typdoc
Poster communications
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BibTex
titre
Statistical learning of adjacent and non-adjacent pairs in non-linguistic short sequences
auteur
Laura Lazartigues, Fabien Mathy, Arnaud R Rey, Joël R 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.
typdoc
Poster communications
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BibTex
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