Learn More
Multivariate pattern analysis (MVPA) is a relatively recent innovation in functional magnetic resonance imaging (fMRI) methods. MVPA is increasingly widely used, as it is apparently more effective than classical general linear model analysis (GLMA) for detecting response patterns or representations that are distributed at a fine spatial scale. However, we(More)
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. However, an often neglected fact is that learning to use working memory effectively is itself a difficult problem. The Gating(More)
The successor representation was introduced into reinforcement learning by Dayan ( 1993 ) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity of the successor representation has yet(More)
A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of " state classification " to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They focus on(More)
In this thesis, we investigate human decision making dynamics in a series of simple perceptual decision making tasks. The level of caution with which a human subject responds to stimuli is of central interest, since it influences the speed and accuracy of responses. We study the role of caution parameters in models of cognitive control processes. We first(More)
  • 1