Towards a foundation model of human cognition

Most cognitive models are domain-specific, meaning that their scope is restricted to a single type of problem. The human mind, on the other hand, does not work like this -- it is a unified system whose processes are deeply intertwined. In this talk, I present our work on building domain-general computational models and using them to understand human cognition. I start by outlining how meta-learning can be used to construct cognitive models across various domains.

Feedback-based motor control can guide plasticity and drive rapid learning

Animals use afferent feedback to rapidly correct ongoing movements in the presence of a perturbation. Repeated exposure to a predictable perturbation leads to behavioural adaptation that counteracts its effects. Primary motor cortex (M1) is intimately involved in both processes, integrating inputs from various sensorimotor brain regions to update the motor output. Here, we investigate whether feedback-based motor control and motor adaptation may share a common implementation in M1 circuits.

Thanks to continuous technological advances, neuroscience is in perpetual motion

Chercheuse au Laboratoire de Neurosciences Cognitives et Computationnelles, Alex Cayco Gajic étudie la façon dont les réseaux neuronaux du cerveau contrôlent le comportement et apprennent de nouvelles tâches, en utilisant des méthodes mathématiques. Des recherches interdisciplinaires à la croisée des nouvelles technologies, qui l’ont amenée à rejoindre récemment le FENS-Kavli Network of Excellence, un prestigieux réseau européen de jeunes chercheurs et chercheuses en neurosciences. À cette occasion, Alex Cayco Gajic revient sur son parcours et ses récents travaux. 

Generalized Shape Metrics on Neural Representations

Understanding the operation of biological and artificial networks remains a difficult and important challenge. To identify general principles, researchers are increasingly interested in surveying large collections of networks that are trained on, or biologically adapted to, similar tasks. A standardized set of analysis tools is now needed to identify how network-level covariates -- such as architecture, anatomical brain region, and model organism -- impact neural representations (hidden layer activations).

The Brilliance Barrier: Stereotypes about Brilliance Are an Obstacle to Diversity in Science and Beyond

I propose that a field’s diversity is affected by what its members believe is required for success: Fields that value exceptional intellectual talent above all else may inadvertently obstruct the participation of women and (some) minority groups. The environment in these fields may be less welcoming to women and minority groups because of the cultural stereotypes that associate intellectual talent -- brilliance, genius, etc. -- with (white) men.

Subscribe to