Colloques du Collège de France - Collège de France

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainTheme: Infancy, Development, and EducationWhy Is Conceptual Learning so Hard?Colloque - Véronique Izard : Why Is Conceptual Learning so Hard?Véronique IzardRésuméLearning concepts can be very difficult, especially in science and mathematics. For instance, children continue to struggle with fractions even after several years of formal instruction on the topic; and adults display persistent difficulties with algebra, biology or physics. Why these failures—and what happens during the long periods of time during which learners are struggling? While most theories of conceptual learning contend that learning proceeds gradually, little step by little step, I will present evidence showing that people experience sudden Eureka moments while learning mathematics. During these episodes, an insight suddenly breaks into consciousness, leading to a leap in understanding. These findings invite us to reconsider learning mechanisms in light of theories of conscious and unconscious processing.

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainTheme: Numerical and Mathematical DevelopmentIlluminating Fractions Learning: Neuronal Recycling of Non-Symbolic Ratios for Symbolic FractionsColloque - Edward Hubbard : Illuminating Fractions Learning: Neuronal Recycling of Non-Symbolic Ratios for Symbolic FractionsEdward HubbardRésuméWithin mathematics, fractions hold a special place. They present perennial difficulties to students, and yet, mastering fractions is a critical stepping stone towards algebra and higher-order mathematics. More than 20 years ago, Stanislas Dehaene suggested that fractions are difficult because they lack the intuitive perceptual foundation that permits us to readily comprehend whole numbers and instead may depend on formal and symbolic processes. Here, I will present research from my lab showing that fractions may indeed have a perceptual foundation, and that this perceptual foundation may be recycled to allow us to understand symbolic fractions. Behaviorally, we have shown that symbolic fractions do not need to be processed componentially and instead can be represented on a coherent mental number. We show that wholistic fraction comparisons (and translation to decimals) does not require time consuming computations, and that non-symbolic ratio perception in college students and American elementary school children predicts formal fractions skills. Using fMRI, we have further shown that non-symbolic ratio perception reliable recruits right parietal cortex, even before the onset of formal schooling, and these parietal systems become tuned to symbolic fractions after as little as two years of formal education. Despite this evidence that fractions do, indeed, have a perceptual foundation, they still present significant difficulties. I will close by arguing that fractions (and other domains) may be difficult not due to a lack of foundational systems, but rather, due to educational methods that fail to align with these perceptual foundations. Furthermore, I will argue that research in numerical cognition can (and should!) provide new pedagogical approaches that better align with the foundational systems we have discovered to help students better grasp higher-order mathematical concepts. 

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 1: Seeing and Decoding the MindThe Control of Sequence Working Memory in the Prefrontal CortexColloque - Liping Wang : The Control of Sequence Working Memory in the Prefrontal CortexLiping Wang

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 2: Training and Educating the BrainSeeing Syntax Everywhere: Syntactic Theory, Language Impairments, and the BrainColloque - Naama Friedmann : Seeing Syntax Everywhere: Syntactic Theory, Language Impairments, and the BrainNaama FriedmannRésuméA key notion in linguistics is that of syntactic movement. I will show that this notion and the further theoretical observations and generalizations regarding movement are useful in accounting for language impairments. I will describe syntactic impairments of various sources: acquired (following stroke, tumour, tumor resection), developmental, and neurodegenerative (progressive aphasia, Parkinson's Disease, Machado Joseph Ataxia), and show how useful a good syntactic theory is in assessing, describing, and treating these impairments. 

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 2: Training and Educating the BrainThe Neuronal Basis of Numerical Cognition in Humans and Nonhuman PrimatesColloque - Andreas Nieder : The Neuronal Basis of Numerical Cognition in Humans and Nonhuman PrimatesAndreas NiederInstitut de neurobiologie, département de biologie, université de Tübingen, AllemagneRésuméOur understanding of numbers, vital to our scientifically and technically advanced culture, has deep biological roots. Research across developmental psychology, anthropology, and animal cognition suggests that our ability to count symbolically arises from more primitive non-symbolic number representations. By studying single-neuron activity in associative brain areas of awake human patients and monkeys, we aim to uncover the physiological principles behind how numbers are represented in the brain. In both species, we've identified "number neurons" that encode set sizes regardless of how the stimuli are presented. These neurons play a crucial role in processing numerical information during goal-directed behavior. Moreover, investigating how numbers are processed in working memory offers insights into high-level cognitive control functions. Comparative research in numerical cognition is uniquely positioned to unravel the brain processes enabling humans to transition from nonsymbolic to symbolic representations, a hallmark of our species.

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 2: Training and Educating the BrainEducabilityColloque - Elizabeth Spelke : EducabilityElizabeth Spelke

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 2: Training and Educating the BrainIn Search of the Neural Code of LanguageColloque - Jean-Rémi King : In Search of the Neural Code of LanguageJean-Rémi KingRésuméHow does the brain transform words into meaning? By aligning insights from linguistics, neuroscience, and Large Language Models (LLMs), we observe that AI models and the human brain surprisingly converge on similar representational principles. Using neuroimaging and electrophysiology, we find that as LLMs improve at language tasks, their internal activations increasingly mirror cortical activity, and effectively enable us to decode meaning directly from these brain signals. Building on these results, we will outline a roadmap to uncover the neural code of language: (1) a benchmark dataset of brain recordings to build a "Rosetta Stone" across humans and models, (2) unique intracranial data from young children to characterize the computational principles of language development, and (3) a mathematical framework to understand the geometry of the neural representations of symbolic structures. Together, this research program moves us closer to deciphering how the human brain learns, represents and manipulates the structures of language.

Stanislas DehaeneChaire Psychologie cognitive expérimentaleAnnée 2025-2026Collège de FranceColloque : Seeing the Mind, Educating the BrainPart 1: Seeing and Decoding the MindExploring Consciousness at the Edge: Global Neuronal Workspace Framework & NeurologyColloque - Lionel Naccache : Exploring Consciousness at the Edge: Global Neuronal Workspace Framework & NeurologyLionel NaccacheRésuméAfter a brief synthetic introduction to the Global Neuronal Workspace (GNW) theoretical framework, I will show how the exploration of conscious state and conscious access in extreme neurological or physiological conditions can be mutually beneficial by: (i) improving medical and ethical care of patients, and (ii) enriching cognitive neuroscience of consciousness by testing key theoretical predictions in unusual situations. I will illustrate this bidirectional approach by focusing on Disorders of Consciousness (i.e.: vegetative states also coined unresponsive wakefulness syndrome, minimally conscious state and related conditions), but I will also address more briefly key recent findings in epilepsy, hemispherotomy and sleep.

Stanislas DehaenePsychologie cognitive expérimentaleCollège de FranceAnnée 2025-2026Colloque: Seeing the Mind, Educating the BrainPart 1: Seeing and Decoding the MindConscious Perception: The Propagation of Selection Signals through the Global Neuronal WorkspaceColloque - Pieter Roelfsema: Conscious Perception: The Propagation of Selection Signals through the Global Neuronal WorkspacePieter RoelfsemaNetherlands Institute for Neuroscience, Amsterdam & Institut de la Vision, ParisRésuméhe Global Neuronal Workspace (GNW) theory (Baars, 1988; Dehaene et al., 1998) proposes that information must be broadcast across widely distributed networks to enter conscious awareness. But what exactly is the information that is exchanged? I will argue that the GNW provides the substrate for the spread of selection signals and use this perspective to refine the distinction between access and phenomenal consciousness.Access consciousness corresponds to the information currently circulating within the GNW. In perception, this is the information selected by object-based attention, enabling a degree of representational flexibility that would otherwise not be attainable. In thought, access consciousness corresponds to the attended content of working memory, i.e. the items that can be actively transformed, combined, or used to retrieve associations. Phenomenal consciousness, by contrast, refers to the set of representations that are not yet part of the GNW, but that could be attended next because they are captured by the senses or because they are in an unattended memory form.I will illustrate these ideas in perception and memory. Perceptual experiments address the construction of coherent object representations through the spread of object-based attention, which at a neuronal level, corresponds to the spread of enhanced activity. In these studies, access consciousness aligns with object-based attention, and the GNW acts as the scaffold that allows selection signals to label all features of a perceptual object. This binding mechanism is incremental, time-consuming and explains why we consciously perceive unified, multi-feature objects.When considering memory, I will contrast iconic memory, supported by transient activity in early visual cortex, to working memory representations in higher areas that are maintained by persistent firing. Items in access awareness are attended within working memory and show stronger and more stable activity than non-attended items. I will show how the spread of selection signals among attended working memory items through the GNW supports conscious cognitive functions, such as resolving pronouns during reading and the retrieval of associations between concepts.Together, these findings suggest a revised view of the relationship between attention and consciousness, positioning the GNW as the orchestrator of distributed neuronal representations through the spread of attentional selection signals.

Stanislas DehaenePsychologie cognitive expérimentaleCollège de FranceAnnée 2025-2026Colloque: Seeing the Mind, Educating the BrainPart 1: Seeing and Decoding the MindIntuitive Physical Reasoning in the Human BrainColloque - Nancy Kanwisher: Intuitive Physical Reasoning in the Human BrainNancy KanwisherMITRésuméVisual scene understand requires much more than a list of the objects present in the scene and their locations. To understanding a scene, plan action on it, and predict what will happen next we must extract the relationships between objects (e.g., support and attachment), their physical properties (e.g., mass and material), and the forces acting upon them. One view is that we do this with the use of a "mental physics engine" that represents this information and runs forward simulations to predict what will happen next. Over the last several years we have been testing this idea with Josh Tenenbaum using fMRI. I will review evidence that certain brain regions in the parietal and frontal lobes (but not the ventral visual pathway) behave as expected if they implement a mental physics engine: they respond more strongly when deciding about physical than visual properties and when viewing physical versus social stimuli (Fischer et al, 2016), and they contain scenario-invariant information about object mass inferred from motion trajectories (Schwettmann et al, 2019), the stability of a configuration of objects (Pramod et al, 2022), and whether two objects are in contact with each other (Pramod et al 2025). Most tellingly, we can decode predicted collision events from perceived collision events, as expected if these brain regions run forward simulations of what will happen next. I will discuss the scope of engagement of this system by not just rigid "Things" but fluid "Stuff" (Paulun et al 2025), and (at least under some circumstances) by language. I will argue that these findings (as well as the poor performance of deep net models on many intuitive physical tasks) provide preliminary evidence for a physics engine in the human parietal and frontal cortex.