Graduate Tracks

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:

• BioE 2540 - Neural Biomaterials and Tissue Engineering
• BioE 2580 Biomedical Applications of Signal Processing
• BioE 2600 - Neuroimaging
• BioE 2630 - Methods in Image Analysis
• BioE 2696/ECE 2695 - Control Theory in Neuroscience
• BioE 2707 - Anal. Adaptation Sensation & Comm. Impairment
• BioE 2709 - Rehabilitation Biomechanics
• BioE 2715- Microtechnologies in Neuroscience
• BioE 3528 - Time Frequency Signal Analysis
• NroSci 2011 - Functional Neuroanatomy
• NroSci 2012 - Neurophysiology
• EE 3650 - Optimal Control
• MSNBIO 2632 - Advanced Neurophysiology
• CMU 10-601 : Machine Learning

3 elective courses are required. Suggested elective courses:

From University of Pittsburgh

• BioE 2061 - Ergonomics & Occupational Biomechanics
• BioE 2241 - Ethics in Biotechnology
• BioE 2380 - Medical Imaging Systems
• BioE 2382 Medical Imaging Systems II
• BioE 2703 - Rehabilitation Engineering Design
• BioE 2810 - Biomaterials and Biocompatibility
• NroSci 3059 - Neuroplasticity in Sensory and Motor Systems
• MSNBIO 2005/NROSCI 2078-Biological Base of Neuropsychiatric Disorders
• 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.