| Professor | Teaching Assistants | |
| Name: | Michael Frank | Krishn Bera & Yu-Ang Cheng |
| Office: | Metcalf 335 | Metcalf 315 |
| Phone: | 863-6872 | |
| Email: |
| krishn_bera@brown.edu yuang_cheng@brown.edu |
| Office Hours: | 9-10am Tues or by apt | Labtime or by apt |
Text: O'Reilly, R. C., Munakata, Y., Frank, M. J., Hazy, T. E.,
and Contributors (2024). Computational Cognitive Neuroscience.
Wiki Book, 5th Edition. The url of the updated book is here.
Goals:
How does the brain secrete the mind? This course introduces you to
the field of computational cognitive neuroscience, which considers how
neural mechanisms inform the workings of the mind, and reciprocally,
how cognitive and computational constraints afford a richer
understanding of the problems these mechanisms evolved to solve. We
focus on simulations of cognitive and perceptual processes using
neural network models that bridge the gap between biology and
behavior. We first consider the basic biological and computational
properties of individual neurons and networks of neurons. We then
discuss learning (plasticity) mechanisms that allow networks of
neurons to be adaptive and which are required to perform any
reasonably complex task. We consider how different brain systems
(visual cortex, hippocampus, parietal cortex, frontal cortex, basal
ganglia) interact to solve difficult computational tradeoffs. We
examine a range of cognitive phenomena within this framework,
including visual object recognition, attention, various forms of
learning and memory, language and cognitive control. We will see how
damage to different aspects of biological networks can lead to
cognitive deficits akin to those observed in neurological
conditions. The class includes a lab component in which students get
hands on experience with graphical neural network software, allowing deeper, more intuitive
appreciation for how these systems work.
UPDATED Full Syllabus: PDF
Piazza: technical questions etc
Homework Projects: Here (will be updated during semester)