INTRODUCTION TO CUMPUTATIONAL NEUROSCIENCE
| Title | ΕΙΣΑΓΩΓΗ ΣΤΙΣ ΥΠΟΛΟΓΙΣΤΙΚΕΣ ΝΕΥΡΟΕΠΙΣΤΗΜΕΣ / INTRODUCTION TO CUMPUTATIONAL NEUROSCIENCE |
| Code | ΔΔ1318 |
| Interdepartmental Programme | PPS Advanced Computer and Communication Systems |
| Collaborating Schools | Electrical and Computer Engineering Medicine Music Studies Journalism and Mass Communications |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Dimitris Kugiumtzis |
| Common | No |
| Status | Active |
| Course ID | 600017415 |
Programme of Study: PPS Advanced Computer and Communication Systems
Registered students: 20
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| EUFYĪ KAI AUTONOMA SYSTĪMATA-METHODOLOGIES YPOLOGISTIKĪS NOĪMOSYNĪS KAI EFARMOGES | Compulsory Course | 2 | 1 | 5 |
| TECΗNOLOGIES DIADIKTYOU KAI DIADIKTYO TŌN PRAGMATŌN | Elective Courses | 2 | 1 | 5 |
| Academic Year | 2020 – 2021 |
| Class Period | Spring |
| Faculty Instructors | |
| Weekly Hours | 26 |
| Class ID | 600183816
|
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600183816
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=11767
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
- English (Instruction, Examination)
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work in teams
- Work in an interdisciplinary team
- Generate new research ideas
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 42 | ✓ | ✓ | ||
| Laboratory Work | 8 | ✓ | ✓ | ||
| Project | 24 | ✓ | ✓ | ✓ | |
| Written assigments | 8 | ✓ | ✓ | ||
| Total | 82 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Written Assignment (Summative)
- Performance / Staging (Summative)
Bibliography
Additional bibliography for study
1. Principles of Computational Modelling in Neuroscience, David Sterratt, Bruce Graham, Andrew Gillies,Bruce Graham, 2011
2. MATLAB for Neuroscientists - An Introduction to Scientific Computing in MATLAB, Wallisch et al, Elsevier, 2014
3. The Handbook of Brain Theory and Neural Networks, Second Edition, Arbib, MIT Press, 2002
4. Dynamical Systems in Neuroscience. Eugene M. Izhikevich MIT Press, 2007
5. Mathematical Foundations of Neuroscience, G. Bard Ermentrout, David H. Terman,Springer Science & Business Media, 2010
6. Niedermeyer's Electroencephalography: Basic Principles, Clinical Applications, and Related Fields (7 ed.), Edited by Donald L. Schomer and Fernando H. Lopes da Silva, Oxford University Press, 2017
7. Quantitative EEG analysis methods and clinical applications, Shanbao Tong and Nitish Vyomesh Thakor, Boston Artech House, 2009, www.electroneurodiagnostics.org/resources/EEG-Books/QuanitativeEEG.pdf
Last Update
20-11-2019
