A sequence of images, sounds, or words can be stored at several levels of detail, from
specific items and their timing to abstract structure. We propose a taxonomy of five distinct …

Research on confidence spreads across several sub-fields of psychology and neuroscience.
Here, we explore how a definition of confidence as Bayesian probability can unify these …

… (F(1,48) = 16.5, P < 0.001) with α + higher than α − . We also found a main effect of group (F(…
) and a significant interaction between group and learning rate type (F(1,48) = 7.8, P = 0.007)…

Learning in a stochastic environment consists of estimating a model from a limited amount
of noisy data, and is therefore inherently uncertain. However, many classical models reduce …

An outstanding challenge for consciousness research is to characterize the neural signature
of conscious access independently of any decisional processes. Here we present a model-…

The study of the brain’s representations of uncertainty is a central topic in neuroscience. Unlike
most quantities of which the neural representation is studied, uncertainty is a property of …

The brain constantly infers the causes of the inputs it receives and uses these inferences to
generate statistical expectations about future observations. Experimental evidence for these …

… The power at a given time t and frequency f 0 is given by the squared norm of the … In each
trial j, for each time point t and frequency f, the phase φ j ( t , f ) of the signal was estimated, …

Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning
algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically…

… These 20 models correspond to four possible combinations of the incentive effect: Ai,Sei,Sri
f g or Ai,Sei f g or Ai,Sri f g or Sei,Sri f g crossed with five possible combinations of the …