— Computational Neuroscience
Mathematical models and data analysis techniques used to describe computations performed by nervous systems. Lecture topics include single neuron biophysics, neural coding, network dynamics, memory, plasticity, and learning. Lab topics include programming mathematical models and data analysis techniques in MATLAB.
Topics
- single neuron biophysics
- neural coding
- network dynamics
- memory
- plasticity
- and learning
Topics explicitly listed in official catalogue description
Prerequisites & course information
Course Description: Mathematical models and data analysis techniques used to describe computations performed by nervous systems. Lecture topics include single neuron biophysics, neural coding, network dynamics, memory, plasticity, and learning. Lab topics include programming mathematical models and data analysis techniques in MATLAB. Learning Activities: Lecture 4 hour(s), Lecture/Lab 3 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE). Learning Activities: Lecture 4 hour(s), Lecture/Lab 3 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE).
Sources
- Course catalogue ↗2026-2027