CNRS-INSB UCA
CNRS-INSHS
lapsco
LAboratoire de Psychologie
Sociale et COgnitive

UMR 6024 UCA-CNRS
L'étude de la cognition depuis ses bases cérébrales jusqu'à sa régulation sous l'influence de l'environnement social

DERNIÈRES PUBLICATIONS
Troian-Adam J., Bonetto E., Varet F., Arciszewski T. & Dezecache G. (in press). Explaining social behaviour in response to death-related threats : The conspecific loss compensation mechanism. Evolutionary Behavioral Sciences.
Dezecache G., Frith C.D. & Deroy O. (2020). Pandemics and the great evolutionary mismatch. Current Biology, 30, R1-R3.
Ferrand, L., Ducrot, S., Chausse, P., Maïonchi-Pino, N., O’Connor, R. J., Parris, B. J., Perret, P., Riggs, K. J., & Augustinova, M. (2020). Stroop interference is a composite phenomenon : Evidence from distinct developmental trajectories of its components. Developmental Science. doi : 10.1111/desc.12899
ÉVÉNEMENTS
Soutenance HDR de Guillaume Vallet : Une approche incarnée et située du vieillissement cognitif

Mardi 01 septembre 2020. Soutenance d’Habilitation à Diriger des Recherches par Guillaume Vallet (LAPSCO, CNRS, UCA). A 14h30 à la Maison des Sciences de l’Homme, amphi 220.

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Accueil > Séminaires

07/12/2017 – Royce ANDERS

par Guillaume VALLET - publié le , mis à jour le

Advanced Signal Detection Theory for Social and Experimental Psychology : Empirical Cognitive Models for Performance and Questionnaire Data

Conférence

Date : 07 décembre 2017
Heure : 10h30 - 12h00
Lieu : Amphithéâtre Paul Collomp

Résumé de la conférence

Classical signal detection theory (such as signal and noise distribution paradigms) has come a long way over the previous 20 years. Particularly, this framework has been largely integrated into what I will refer to as empirical cognitive models. These models are used to learn more about the latent cognitive processes that underly observed performance from psychological experiments. These include high-performance models that can account for (or measure) human factors in the response process. Furthermore, developments in hierarchical Bayesian analysis has empowered these models to provide even stronger analyses than previously possible. In this seminar, I will review and demonstrate these concepts by going over two of my principal involvements in hierarchical Bayesian cognitive modelling to (1) social / anthropological applications and (2) experimental / psycholinguistic applications. The first of these approaches is excellent for learning more about the latent consensuses and subclusters from questionnnaire or knowledge-based studies. The second set of approaches is strong for learning more about performance (accuracy) and latency data. I may also discuss their implication in neuroscience studies.

Conférencier

Dr. Royce ANDERS
Université Aix-Marseille
CNRS
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