Computational Neuroscience

Subject code


Course Number




M. Greene

Course Long Title

Computational Neuroscience


In this course, students examine formal models of brain function to determine how neurons give rise to thought. Examining real datasets, students explore how the brain encodes and represents information at cellular, network, and systems scales, and they discuss ideas about why the brain is organized as it is. Specific topics include spike statistics, reverse correlation and linear models of encoding, dimensionality reduction, cortical oscillations, neural networks, and algorithms for learning and memory. All assignments and most class work emphasizes computer programming in Python, though no programming background is assumed or expected. Prerequisite(s): NS/PY 160.

Modes of Inquiry

Quantitative and Formal Reasoning [QF], Scientific Reasoning [SR]

Writing Credit

No writing credit

GEC This Course Belongs To


Class Restriction

Exclude First Years

Offering Frequency

Normally offered every year