BiS752 Neural Engineering
Synopsis
This course covers fundamental elements of neural interface technology: biophysical modeling of single neurons, quantitative approach of neural recording and stimulation, neural electrode interface, and neural signal processing (spike detection, spike sorting, neural data analysis). Due to the diversity of the field, students are guided to select their own field of interest (e.g. brain-computer interface, neural prostheses, neuromodulation techniques, artificial vision, artificial hearing, deep-brain stimulation, computational modeling, etc.) and write a mini-review by themselves. Quantitative approaches are based on differential equation models and electric circuit models.
Credit: 3 units
Prerequisite
This course requires undergraduate level neuroscience (BiS451 or 353), biophysics (BiS322), bioelectronics (BiS252), biomedical instrumentation (BiS350) or related courses. Students should be familiar with linear system theory and ordinary / partial differential equations.
* Matlab programming skill required to complete simulation problems in class
Grading:
Attendance, Final exam, Problem solving assignments
Weekly literature reading assignments
Term project (proposal, presentation, mini-review paper)
Textbook(s): Selected chapters from the following references
[1] R. Plonsey, R. C. Barr, Bioelectricity: A Quantitative Approach, Springer, 2007 (www.springerlink.com)
[2] J. Malmivuo & R. Plonsey, Biomagnetism (http://www.bem.fi/book/)
[3] Bin He Ed., Neural Engineering 2nd ed, Springer
[4] M. A. Nicolelis, Methods for Neural Ensemble Recordings, CRC Press
[5] Y, Nam (2021) State-of-the-Art Technology on MEAs for Interfacing Live Neurons. In: Thakor N.V. (eds) Handbook of Neuroengineering. Springer, Singapore.
Term Project: ‘Recent advances in Neural Engineering technology’
- Purpose: Review a specific field in neural engineering
- Choose some fields of interest by reading literature papers (weekly assignment)
- Project proposal/presentation/ mini-review paper
Lecture schedule:
Week 1: History of bioelectricity (Ref [2])
Week 2: Biophysics of bioelectric potentials (Ref[1])
Week 3: Action potential modeling (biophysics, mathematical model) (Ref[1])
Week 4: Compartmental modeling of neural system (impulse propagation) (Ref[1])
Week 5: Electrical stimulation (Ref[1])
Week 6: Electrical recording (extracellular fields) (Ref[1])
Week 7: Electrode-electrolyte interface (Ref[1])
Week 8: Midterm exam period
Week 9: Neural probe technology (Handout)
Week 10: Neural instrumentation technology (Ref [4])
Week 11: Spike detection / classification (Handout)
Week 12: Brain-computer interface technology (Ref [3])
Week 13: Brain-on-a-chip technology (Ref [5])
Week 14: Project presentation
Week 15: Project presentation
Week 16: Final exam / mini-review writing
Synopsis
This course covers fundamental elements of neural interface technology: biophysical modeling of single neurons, quantitative approach of neural recording and stimulation, neural electrode interface, and neural signal processing (spike detection, spike sorting, neural data analysis). Due to the diversity of the field, students are guided to select their own field of interest (e.g. brain-computer interface, neural prostheses, neuromodulation techniques, artificial vision, artificial hearing, deep-brain stimulation, computational modeling, etc.) and write a mini-review by themselves. Quantitative approaches are based on differential equation models and electric circuit models.
Credit: 3 units
Prerequisite
This course requires undergraduate level neuroscience (BiS451 or 353), biophysics (BiS322), bioelectronics (BiS252), biomedical instrumentation (BiS350) or related courses. Students should be familiar with linear system theory and ordinary / partial differential equations.
* Matlab programming skill required to complete simulation problems in class
Grading:
Attendance, Final exam, Problem solving assignments
Weekly literature reading assignments
Term project (proposal, presentation, mini-review paper)
Textbook(s): Selected chapters from the following references
[1] R. Plonsey, R. C. Barr, Bioelectricity: A Quantitative Approach, Springer, 2007 (www.springerlink.com)
[2] J. Malmivuo & R. Plonsey, Biomagnetism (http://www.bem.fi/book/)
[3] Bin He Ed., Neural Engineering 2nd ed, Springer
[4] M. A. Nicolelis, Methods for Neural Ensemble Recordings, CRC Press
[5] Y, Nam (2021) State-of-the-Art Technology on MEAs for Interfacing Live Neurons. In: Thakor N.V. (eds) Handbook of Neuroengineering. Springer, Singapore.
Term Project: ‘Recent advances in Neural Engineering technology’
- Purpose: Review a specific field in neural engineering
- Choose some fields of interest by reading literature papers (weekly assignment)
- Project proposal/presentation/ mini-review paper
Lecture schedule:
Week 1: History of bioelectricity (Ref [2])
Week 2: Biophysics of bioelectric potentials (Ref[1])
Week 3: Action potential modeling (biophysics, mathematical model) (Ref[1])
Week 4: Compartmental modeling of neural system (impulse propagation) (Ref[1])
Week 5: Electrical stimulation (Ref[1])
Week 6: Electrical recording (extracellular fields) (Ref[1])
Week 7: Electrode-electrolyte interface (Ref[1])
Week 8: Midterm exam period
Week 9: Neural probe technology (Handout)
Week 10: Neural instrumentation technology (Ref [4])
Week 11: Spike detection / classification (Handout)
Week 12: Brain-computer interface technology (Ref [3])
Week 13: Brain-on-a-chip technology (Ref [5])
Week 14: Project presentation
Week 15: Project presentation
Week 16: Final exam / mini-review writing
