Neural Engineering
A Ph.D. Neural Engineering Program/Track has been recently established in the Bioengineering Department. The track is a modified BioE Ph.D graduate program.
Specifically, NroSci 2100 and 2101 (Molecular and Cellular Neurobiology I and II) and 2102 (System Neurobiology) are required for all the NE students. These two courses will fulfill the BioE life science requirement. Students without biology background will need to take remedial basic biology courses (eg. BioE 2510 and 2520) before taking these two more advanced courses.
At least 3 track courses are required. Track courses that are currently available are:
3 elective courses are required. Suggested elective courses:
From University of Pittsburgh
- BioE 2061 - Ergonomics &
Occupational Biomechanics
- BioE 2241 - Ethics in Biotechnology
- BioE 2703 - Rehabilitation Engineering
Design
- NroSci 3059 - Neuroplasticity in Sensory and Motor Systems
- MSNBIO 2135 - Historical Perspectives in Neuroscience
- MATH 3371 - Mathematical Neuroscience
- MATH 3375 - Introduction to Computational Neuroscience
- MATH 3370 - Computational Models of Neurobiological Dynamics
- INFSCI 2410 - Introduction to Parallel Distributed Processing
- EE 2236 - Electronic Design with Integrated Circuits
- EE 2372 - Pattern Recognition
- EE 2373 - Artificial Neural Networks
- EE 2521 - Analysis of Stochastic Processes
- EE 2523 - Digital Signal Processing
- EE 2595 - Special Topics: Signal Processing/Communications
- EE 2636 - Fuzzy Logic and Intelligent Control
- EE 2646 - Linear System Theory
- EE 2671 - Optimization Methods
- EE 3557 - Statistical Signal Processing
- EE 3647 - Optimal Stochastic Systems
- EE 3648 - Nonlinear Systems Theory
From Carnegie Mellon University:
- 03-315 : Introduction to MRI in Neuroscience
- 15-781 : Machine Learning
- 15-385/685 : Computer Vision
- 15-485/785 : Computational Perception and Scene Analysis
- 15-496/782 : Artificial Neural Networks
- 15-883 : Computational Models of Neural Systems
- 15-882 : Introduction to Artificial Neural Network
- 16-720 : Computer Vision
- 16-725 : Methods in Medical Image Analysis
- 85-713 : Human Information Processing-Artificial Intelligence
- 85-719/419 : Introduction to Parallel Distributed Processing
- 85-767/467 : Human Causal Reasoning
- 36-746 : Statistical Methods for Neuroscience
The following is an example of a curriculum for this track:
| Year 1, Fall |
| NroSci 2100 and 2101 Molecular and Cellular Neurobiology |
8 credits |
| Statistics |
3 credits |
| BioE Seminar |
1 credit |
| Total |
12 credits |
| Year 1, Spring |
| NroSci 2102 System Neurobiology |
6 credits |
| Math 1 |
3 credits |
| BioE Seminar |
1 credit |
| Total |
10 credits |
(PhD Preliminary Exam taken in summer after first two semesters
completed).
| Year 2, Fall |
| Elective 2 |
3 credits |
| Track Course 1 |
3 credits |
| Ethics |
3 credits |
| BioE Seminar |
1 credit |
| Total |
10 credits |
| Year 2, Spring |
| Elective 3 |
3 credits |
| Track Course 2 |
3 credits |
| BioE Seminar |
1 credit |
| Dissertation |
3 credits |
| Total |
10 credits |
| Year 3, Fall |
| Track Course 3 |
3 credits |
| Teaching Practicum 1 |
1 credit |
| Dissertation |
5 credits |
| BioE Seminar |
1 credit |
| Total |
10 credits |
| Year 3, Spring |
| Teaching Practicum 2 |
1 credit |
| Dissertation |
8 credits |
| BioE Seminar |
1 credit |
| Total |
10 credits |
Ultimately the students will fulfill the 3 track courses, 3 elective courses (suggested by the advisor), 2 teaching practicums, 8 credit BioE seminar and 28 research credits requirement.
For more information, please contact the Track Coordinators,
or
, or visit the Neural Engineering Program website.
