Biosignal Analysis- Neuroinformatics
| Title | Ανάλυση Βιοσημάτων- Νευροπληροφορική / Biosignal Analysis- Neuroinformatics |
| Code | DMCI104 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter |
| Coordinator | Nikolaos Laskaris |
| Common | Yes |
| Status | Active |
| Course ID | 600016141 |
Programme of Study: PMS PSĪFIAKA MESA - YPOLOGISTIKĪ NOĪMOSYNĪ (2018 éōs sīmera) PF
Registered students: 12
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses belonging to the selected specialization | 1 | 1 | 7.5 |
| Academic Year | 2020 – 2021 |
| Class Period | Winter |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600177051
|
Course Type 2016-2020
- Scientific Area
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/1/600177051
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=8137
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Good knowledge of signal processing techniques and basics of pattern analysis and computational intelligence
Learning Outcomes
Cognitive: To familiarize with digital techniques of processing, analyzing and handling the information in biosignals and get introduced to their modern applications in contemporary digitalized life.
Skills: Computational Techniques for analyzing biosignals and neuroscientific data.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Work autonomously
- Work in teams
- Work in an interdisciplinary team
- Generate new research ideas
- Be critical and self-critical
Course Content (Syllabus)
Biosignals (recoding, digital processing, analysis, modelling, inspection and automated monitoring). Basic principles of Electrophysiology. Elements from Neurophysiology and Cognitive Neuroscience. NeuroInformatics : contemporary neuroimaging techniques and the extraction-management-scrutiny of information from the experimental data. Introduction to computational neuroscience and the neural modelling of various brain processes and mental faculties. The Brain as a complex system.
Keywords
biosignal analysis, neuroinformatics
Educational Material Types
- Notes
- Slide presentations
- Multimedia
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
Description
software demos related to the analysis of particular types of biosignals
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 30 | ✓ | |||
| Laboratory Work | 45 | ✓ | |||
| Reading Assigment | 60 | ||||
| Project | 90 | ✓ | |||
| Total | 225 |
Student Assessment
Description
The final mark reflects the performance in written exams (30%),
oral presentation of a recent paper(30%) and implementation of a project (40%)
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Performance / Staging (Summative)
- Report (Summative)
Bibliography
Additional bibliography for study
1. U. Windhorst & H. Johansson. Modern Techniques in Neuroscience Research. Springer (ed.).1999
2. M.Cohen. Analyzing Neural Time Series Data: Theory and Practice (MIT Press).2014
3. A Fornito, A. Zalesky, E Bullmore. Fundamentals of Brain Network Analysis. (Academic Press).2016
& Selected articles from the recent literature.
Last Update
05-10-2020
