Twin Cities campus
 
Twin Cities Campus

Neuroengineering Minor

Department of Biomedical Engineering
College of Science and Engineering
Link to a list of faculty for this program.
Contact Information
Graduate Minor in Neuroengineering, 7-105 Nils Hasselmo Hall, 312 Church Street S.E., Minneapolis, MN 55455 (612-624-8396; fax 612-626-6583)
  • Program Type: Graduate free-standing minor
  • Requirements for this program are current for Spring 2018
  • Length of program in credits (doctoral): 12
  • This program does not require summer semesters for timely completion.
The graduate minor in Neuroengineering (NE) is motivated by the notion that future breakthroughs in this rapidly-growing area of research will be made by engineers who understand the fundamental issues and principles of neuroscience that occur during neural interventions, and by neuroscientists who are truly competent in engineering concepts and tools. The minor trains doctoral students to develop the skills to revolutionize technologies for interfacing with the brain and to advance our understanding of the neuroscience processes that arise when we interface with and modulate the brain.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
Other requirements to be completed before admission:
Enrollment in the Neuroengineering Minor is open to all currently enrolled Ph.D. students in Biomedical Engineering, Electrical Engineering, Mechanical Engineering, and Neuroscience. Ph.D. students majoring in other programs may obtain approval from the Neuroengineering Director of Graduate Studies to participate in the minor program if they have the necessary science background to complete the coursework and are in good standing in their major program. Students must officially declare the minor before taking the Oral Preliminary Examination (OPE).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
Use of 4xxx courses towards program requirements is not permitted.
Coursework for the minor must total at least 12 credits and must be approved by the Neuroengineering Director of Graduate Studies (DGS) - see http://neuroengineering.umn.edu/faculty.html. For any course listed in multiple categories, students must choose which requirement that course will fulfill. A single course cannot be counted simultaneously toward multiple categories. Students may not use any of their minor courses to satisfy the core course requirements for their major program (i.e., a Neuroscience student cannot count NSCI 5101 as both a Neuroengineering Minor course and a core Neuroscience course).
Introduction Course
At least one introductory neural engineering/neuroscience course is required.
Take 1 or more course(s) from the following:
· BMEN 5411 - Neural Engineering (3.0 cr)
· NSCI 5101 - Introduction to Neuroscience for Graduate Students (3.0 cr)
· NSC 5561 - Systems Neuroscience (4.0 cr)
Neuroengineering Core Courses
Two courses designated as Neuroengineering Core must be completed. If NSC 8320 is used it must be Section 017 Neurostatistics; other sections of NSC 8320 do not satisfy this requirement. Only 3 credits of NSC 8320 may be applied to the minor.
Take 2 or more course(s) from the following:
· BMEN 5412 - Neuromodulation (3.0 cr)
· BMEN 5413 - Neural Decoding and Interfacing (3.0 cr)
· BMEN 8335 - Neuroengineering Practicum (3.0 cr)
· NSC 8320 - Readings in Neurobiology (1.0-4.0 cr)
Elective Course
One additional course from either an engineering or neuroscience discipline is required. If NSC 8320 is used it must be Section 017 Neurostatistics; other sections of NSC 8320 do not satisfy this requirement. Only 3 credits of NSC 8320 may be applied to the minor. Additional courses may be approved as electives by the Neuroengineering DGS.
Take 1 or more course(s) from the following:
· BMEN 5411 - Neural Engineering (3.0 cr)
· BMEN 5412 - Neuromodulation (3.0 cr)
· BMEN 5413 - Neural Decoding and Interfacing (3.0 cr)
· BMEN 8335 - Neuroengineering Practicum (3.0 cr)
· EE 5231 - Linear Systems and Optimal Control (3.0 cr)
· EE 5239 - Introduction to Nonlinear Optimization (3.0 cr)
· EE 5542 - Adaptive Digital Signal Processing (3.0 cr)
· ME 5281 - Analog and Digital Control (4.0 cr)
· ME 5286 - Robotics (4.0 cr)
· NSC 5202 - Theoretical Neuroscience: Systems and Information Processing (3.0 cr)
· NSC 8217 - Systems and Computational Neuroscience (2.0 cr)
· NSC 8320 - Readings in Neurobiology (1.0-4.0 cr)
Program Sub-plans
Students are required to complete one of the following sub-plans.
Students may not complete the program with more than one sub-plan.
Doctoral
 
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BMEN 5411 - Neural Engineering
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theoretical basis. Signal processing techniques. Modeling of nervous system, its response to stimulation. Electrode design, neural modeling, cochlear implants, deep brain stimulation. Prosthetic limbs, micturition control, prosthetic vision. Brain machine interface, seizure prediction, optical imaging of nervous system, place cell recordings in hippocampus. prereq: 3401 recommended
NSCI 5101 - Introduction to Neuroscience for Graduate Students
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Basic principles of cellular/molecular neurobiology and nervous system. A term paper supplements lectures. Multiple-choice exams. prereq: [BioC 3021 or BioC 4331], dept consent; intended for grad students outside neuroscience program who require comprehensive intro
NSC 5561 - Systems Neuroscience
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principles of organization of neural systems forming the basis for sensation/movement. Sensory-motor/neural-endocrine integration. Relationships between structure and function in nervous system. Team taught. Lecture, laboratory. prereq: NSc grad student or instr consent
BMEN 5412 - Neuromodulation
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Fundamentals of bioengineering approaches to modulate the nervous system, including bioelectricity, biomagnetism, and optogenetics. Computational modeling, design, and physiological mechanisms of neuromodulation technologies. Clinical exposure to managing neurological disorders with neuromodulation technology.
BMEN 5413 - Neural Decoding and Interfacing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Neural interface technologies currently in use in patients as well as the biophysical, neural coding, and hardware features relating to their implementation in humans. Practical and ethical considerations for implanting these devices into humans. prereq: 5411, [3201 or 3401 or equiv recommended]
BMEN 8335 - Neuroengineering Practicum
Credits: 3.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Spring
Topics/issues in neuroengineering. Ethics, professional conduct, conflicts, plagiarism, copyright, authorship, research design considerations, IRB, intellectual properties, review process, professional presentations, proposal writing. prereq: PhD student in BMEn, EE, ME, or NSci or instr consent
NSC 8320 - Readings in Neurobiology
Credits: 1.0 -4.0 [max 16.0]
Typically offered: Every Fall & Spring
Topics in neurobiology and neurophysiology.
BMEN 5411 - Neural Engineering
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theoretical basis. Signal processing techniques. Modeling of nervous system, its response to stimulation. Electrode design, neural modeling, cochlear implants, deep brain stimulation. Prosthetic limbs, micturition control, prosthetic vision. Brain machine interface, seizure prediction, optical imaging of nervous system, place cell recordings in hippocampus. prereq: 3401 recommended
BMEN 5412 - Neuromodulation
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Fundamentals of bioengineering approaches to modulate the nervous system, including bioelectricity, biomagnetism, and optogenetics. Computational modeling, design, and physiological mechanisms of neuromodulation technologies. Clinical exposure to managing neurological disorders with neuromodulation technology.
BMEN 5413 - Neural Decoding and Interfacing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Neural interface technologies currently in use in patients as well as the biophysical, neural coding, and hardware features relating to their implementation in humans. Practical and ethical considerations for implanting these devices into humans. prereq: 5411, [3201 or 3401 or equiv recommended]
BMEN 8335 - Neuroengineering Practicum
Credits: 3.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Spring
Topics/issues in neuroengineering. Ethics, professional conduct, conflicts, plagiarism, copyright, authorship, research design considerations, IRB, intellectual properties, review process, professional presentations, proposal writing. prereq: PhD student in BMEn, EE, ME, or NSci or instr consent
EE 5231 - Linear Systems and Optimal Control
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Properties and modeling of linear systems. Linear quadratic and linear-quadratic-Gaussian regulators. Maximum principle. prereq: [3015, CSE grad student] or instr consent
EE 5239 - Introduction to Nonlinear Optimization
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Nonlinear optimization. Analytical/computational methods. Constrained optimization methods. Convex analysis, Lagrangian relaxation, non-differentiable optimization, applications in integer programming. Optimality conditions, Lagrange multiplier theory, duality theory. Control, communications, management science applications. prereq: [3025, Math 2373, Math 2374, CSE grad student] or dept consent
EE 5542 - Adaptive Digital Signal Processing
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Design, application, and implementation of optimum/adaptive discrete-time FIR/IIR filters. Wiener, Kalman, and Least-Squares. Linear prediction. Lattice structure. LMS, RLS, and Levinson-Durbin algorithms. Channel equalization, system identification, biomedical/sensor array processing, spectrum estimation. Noise cancellation applications. prereq: [4541, 5531, CSE grad student] or dept consent
ME 5281 - Analog and Digital Control
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Continuous and discrete time feedback control systems. Frequency response, stability, poles and zeros; transient responses; Nyquist and Bode diagrams; root locus; lead-lag and PID compensators, Nicols-Ziegler design method. Digital implementation aliasing; computer-aided design and analysis of control system. prereq: 3281
ME 5286 - Robotics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Manipulator forward/inverse kinematics, homogeneous transformations, coordinate frames, Jacobian/velocity control, task primitives/programming, computational issues. Determining path trajectories. Reaction forces, manipulator dynamics/control. Vehicle kinematics, dynamics, and guidance. Lab project demonstrates concepts. prereq: [3281 or equiv], [upper div ME or AEM or CSci or grad student]
NSC 5202 - Theoretical Neuroscience: Systems and Information Processing
Credits: 3.0 [max 3.0]
Course Equivalencies: NSc 5202/Phsl 5202
Typically offered: Every Spring
Concepts of computational/theoretical neuroscience. Distributed representations and information theory. Methods for single-cell modeling, including compartmental/integrate-and-fire models. Learning rules, including supervised, unsupervised, and reinforcement learning models. Specific systems models from current theoretical neuroscience literature. Lecture/discussion. Readings from current scientific literature. prereq: [3101, 3102W] recommended
NSC 8217 - Systems and Computational Neuroscience
Credits: 2.0 [max 2.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Advanced seminar. prereq: 5561 or instr consent
NSC 8320 - Readings in Neurobiology
Credits: 1.0 -4.0 [max 16.0]
Typically offered: Every Fall & Spring
Topics in neurobiology and neurophysiology.