Cédric Foucault

Pupil Dynamics Reflect Uncertainty-Driven Adjustments of Probability Learning

This study shows that pupil dynamics reflect uncertainty-driven adjustments in probability learning by tracking change point probability and prior uncertainty through phasic and tonic pupil responses.

A nonlinear code for event probability in the human brain

The paper identifies a nonlinear neural code for event probability in the human brain using fMRI, showing distinct tuning curves in prefrontal and parietal cortices.

Environmental dynamics shape human learning: change points versus random walks

This study shows humans adjust their learning to environmental dynamics, distinguishing between abrupt change points and gradual random walks.

Two determinants of dynamic adaptive learning for magnitudes and probabilities

This study investigates how humans dynamically adjust their learning rates for magnitudes and probabilities, identifying two distinct determinants for each type of learning.

Gated recurrence enables simple and accurate sequence prediction in stochastic, changing, and structured environments

The paper introduces a recurrent neural network architecture that enables accurate sequence prediction in stochastic and structured environments through gating, lateral connections, and recurrent weight training.