<description>&lt;p&gt;Stanislas Dehaene&lt;/p&gt;&lt;p&gt;Chaire Psychologie cognitive expérimentale&lt;/p&gt;&lt;p&gt;Année 2025-2026&lt;/p&gt;&lt;p&gt;Collège de France&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;Colloque : Seeing the Mind, Educating the Brain&lt;/p&gt;&lt;p&gt;Theme: Human Singularity&lt;/p&gt;&lt;p&gt;The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;Colloque - Valentin Wyart : The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;Valentin Wyart&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;Résumé&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;Quantitative modeling approaches are routinely used in cognitive science to make sense of behavior. Statistical models are designed to test *what* specific patterns are present in behavior, whereas cognitive computational models are developed to describe *how* specific behavioral patterns may emerge from latent cognitive processes. These two types of modeling approaches have successfully identified characteristic (and sometimes suboptimal) features of human learning and decision-making under uncertainty. In this talk, I will argue that cognitive computational models can be used to answer the distinct question of *why* these characteristic features are there. I will use recent studies that rely on different classes of models (low-dimensional algorithmic models, high-dimensional neural networks) to explain characteristic features of human cognition in terms of latent objectives and constraints.&lt;/p&gt;</description>

Psychologie cognitive expérimentale - Stanislas Dehaene

Collège de France

Colloque - Valentin Wyart : The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition

OCT 3, 202518 MIN
Psychologie cognitive expérimentale - Stanislas Dehaene

Colloque - Valentin Wyart : The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition

OCT 3, 202518 MIN

Description

<p>Stanislas Dehaene</p><p>Chaire Psychologie cognitive expérimentale</p><p>Année 2025-2026</p><p>Collège de France</p><p></p><p>Colloque : Seeing the Mind, Educating the Brain</p><p>Theme: Human Singularity</p><p>The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition</p><p></p><p>Colloque - Valentin Wyart : The What?, How? And Why? Of Behavior: Using Cognitive Computational Models to Answer Distinct Questions about Human Cognition</p><p></p><p>Valentin Wyart</p><p></p><p>Résumé</p><p></p><p>Quantitative modeling approaches are routinely used in cognitive science to make sense of behavior. Statistical models are designed to test *what* specific patterns are present in behavior, whereas cognitive computational models are developed to describe *how* specific behavioral patterns may emerge from latent cognitive processes. These two types of modeling approaches have successfully identified characteristic (and sometimes suboptimal) features of human learning and decision-making under uncertainty. In this talk, I will argue that cognitive computational models can be used to answer the distinct question of *why* these characteristic features are there. I will use recent studies that rely on different classes of models (low-dimensional algorithmic models, high-dimensional neural networks) to explain characteristic features of human cognition in terms of latent objectives and constraints.</p>