Topic: rule learning

Frequency tagging based on fast periodic visual stimulation (FPVS) provides a window into ongoing visual and cognitive processing and can be leveraged to measure rule learning and high-level categorization. In this talk, I will present data demonstrating highly proficient categorization as living and non-living in preschool children, and characterize the development of this ability during infancy. In addition to associating cognitive functions with development, an intriguing question is whether frequency tagging also captures enduring individual differences, e.g. in general cognitive abilities

Updating behavioral policies in novel environments or upon shifting action-outcome contingencies is essential for survival. A number of studies have identified the medial prefrontal cortex (mPFC) as a key player in cognitive flexibility, rule learning and uncertainty detection. Animals learning a new behavioral paradigm, or switching between rules, show abrupt changes in their performance, accompanied by sharp transitions in neuronal population dynamics. However, the precise mechanisms regulating behavioral flexibility remain unclear. Here we aim to extract the computational mechanisms behind

Humans’ ability to perceive and abstract relational structure is fundamental to our learning. It allows us to acquire knowledge all the way from linguistic grammar to spatial knowledge to social structures. How does a learner begin to perceive structure in the world? Why do we sometimes fail to see structural commonalities across events? To begin to answer these questions, I attempt to bridge two large, yet somewhat separate research traditions in understanding human’s structural abstraction: rule learning (Marcus et al., 1999) and analogical learning (Gentner, 1989). On the one hand, rule lea