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- School of Science
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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Social and Human Sciences
- Instructor(s)
- Kotani Yasunori
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- Day/Period(Room No.)
- Thr3-4(W9-607)
- Group
- -
- Course number
- SHS.D467
- Credits
- 1
- Academic year
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- 2024/4/4
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This class aims to understand methods to measure brain activity including fMRI, EEG, and NIRS. In addition, students also learn about analysis methods or softwaas well as statistical methods.
Student learning outcomes
Understanding mechanisms of EEG, fMRI, and NIRS.
Understanding analyses methods and software packages for EEG, fMRI, and NIRS
Understanding how to use a repeated-measures ANOVA for brain science.
Keywords
functional magnetic resonance imaging (fMRI)
electroencephalography (EEG)
near-infrared spectroscopy (NIRS)
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
This class will be managed through an active-learning system. Students will search the topic that was assigned, and share opinions and presentations with class members.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Guidance | Searching the topic that was assigned to yourself |
| Class 2 | electroencephalography (EEG) | Understanding mechanisms of EEG |
| Class 3 | functional magnetic resonance imaging (fMRI) | Understanding mechanisms of fMRI |
| Class 4 | near-infrared spectroscopy (NIRS) | Understanding mechanisms of NIRS |
| Class 5 | Setting experimental conditions and stimuli (e-prime) | Understanding how to set experimental conditions and stimuli |
| Class 6 | a repeated-measures ANOVA | Understanding the result of repeated-measures ANOVA |
| Class 7 | conclusion and review | review topics you learned |
Out-of-Class Study Time (Preparation and Review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
An Introduction to the Event-Related Potential Technique
Reference books, course materials, etc.
items will be distributed
Assessment criteria and methods
Presentation of your topic will be used as the estimation.
Related courses
- SHS.D466 ： Graduate Methodologies in Education, Welfare and Health S1A
Prerequisites (i.e., required knowledge, skills, courses, etc.)
This class is opened for students of the social and human sciences course
