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Found 4 papers, 2 papers with code
States as goal-directed concepts: an epistemic approach to state-representation learning
For example, when we are hungry, we tend to view objects in our environment according to whether or not they are edible (or tasty).
Explaining the effectiveness of fear extinction through latent-cause inference
Here, we propose a formal model to explain the effectiveness of gradual extinction in reducing spontaneous recovery and reinstatement effects, in contrast to the ineffectiveness of standard extinction and a gradual reverse control procedure.
A Bayesian method for reducing bias in neural representational similarity analysis
We show that this approach translates structured noise from estimated patterns into spurious bias structure in the resulting similarity matrix, which is especially severe when signal-to-noise ratio is low and experimental conditions cannot be fully randomized in a cognitive task.
Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement
Working memory is a central topic of cognitive neuroscience because it is critical for solving real world problems in which information from multiple temporally distant sources must be combined to generate appropriate behavior.
