INTERNATIONAL BURCH UNIVERSITY
Graduate Study - Faculty of Engineering and Natural Sciences
Genetics and Bioengineering PhD
2015-2016

SYLLABUS
Code Name Level Year Semester
GBE 614 Advanced Neuroengineering Graduate 1 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Area Elective 6 3 150 English

Instructor Assistant Coordinator
Almir Badnjević, Assist. Prof. Dr. Almir Badnjevic Almir Badnjević, Assist. Prof. Dr.
[email protected] [email protected] no email

This course is based upon the principle of reading reviews and discussions of contemporary and relevant topics by leading investigators in the field. This principles-and-applications approach to neural engineering is essential for all academicians, biomedical engineers, neuroscientists, neurophysiologists, and industry professionals wishing to take advantage of the latest and greatest in this emerging field. The course revolves around the principles of neural modeling and imaging as the next-generation application of neuroengineering for the 21st century.

COURSE OBJECTIVE
 Demonstrating the nerve cell and tissue.
 Giving an overview of the basic concepts of neurophysiology.
 Explaining neural modelling.
 Explaining neural tissue engineering.

COURSE CONTENT
Week
Topic
  1. Introduction to neurophysiology
  2. Brain computer interfaces
  3. Neurorobotics
  4. Decoding algorithms for brain-machine interfaces
  5. Neural modeling
  6. Neural modeling: Application
  7. Bidomain modeling of neural tissue
  8. MID-TERM EXAM WEEK
  9. Transcranial magnetic stimulation
  10. Managing neurological disorders using neuromodulation
  11. Functional magnetic resonance imaging
  12. Electrophysiological mapping and neuroimaging
  13. Exploring functional and casual connectivity in the brain
  14. Neural interfacing with the peripheral nervous system
  15. Neural tissue engineering

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Interactive Lectures
    • Presentation
    • Discussions and group work
    Description (%)
    Method Quantity Percentage (%)
    Midterm Exam(s)130
    Class Deliverables30
    Final Exam140
    Total: 100
    Learning outcomes
    • Illustrate nerve cells and tissues
    • Outline the basic concepts of neurophysiology
    • Have an integrated approach to the neural-machine interface
    • Conduct neural modeling
    • Divide the newest approaches to neuroengineering
    TEXTBOOK(S)

      ECTS (Allocated based on student) WORKLOAD
      Activities Quantity Duration (Hour) Total Work Load
      Lecture (14 weeks x Lecture hours per week)14342
      Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)14228
      Midterm Examination (1 week)122
      Final Examination(1 week)122
      Preparation for Midterm Examination11313
      Preparation for Final Examination11313
      Assignment / Homework/ Project12525
      Seminar / Presentation12525
      Total Workload: 150
      ECTS Credit (Total workload/25): 6