NEUR-3844: Computational Neuroscience and Neural Engineering
Description: Introduction to computational and systems neuroscience. Data analysis and signal processing techniques for neural data. Neural modeling to include mean field models, Hodgkin-Huxley models, integrate and fire models. Neural engineering and brain machine interface (BMI) applications.
Pathways: N/A
Course Hours: 3 credits
Sections Taught: 6
Average GPA: 3.24 (B+)
Strict A Rate (No A-) : 24.70%
Average Withdrawal Rate: 5.07%
| Sujith Vijayan | 2024 | 43.5% | 38.7% | 7.2% | 3.7% | 1.8% | 5.1% | 3.24 | 6 |