- Leong, Yuan Chang [Browse]
- Senior thesis
- 90 pages
- Niv, Yael [Browse]
- Norman, Ken [Browse]
- Princeton University. Department of Psychology [Browse]
- Class year
- Restrictions note
- Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library.
- Summary note
- This thesis presents a framework to study the interaction between attention and learning.
The framework proposes that learning processes act on an attentionally-filtered representation of
the environment and that the attention filter is dynamically modulated by the outcomes of
ongoing learning. These assumptions were tested in a series of experiments in which participants
performed a multi-dimensional decision-making task with probabilistic rewards. Choice behavior
was analyzed using computational models. Some of these models incorporated information about
participants’ focus of attention, which was decoded on each trial by combining eye-tracking with
pattern classification of functional magnetic resonance imaging (fMRI) data. Model-based
analysis of behavior provided preliminary evidence that attention helps determine what we learn
about, but we also learn what to attend to.