The brain learns proper actions. In this course, the computational modeling will be introduced.
This course provides the basic knowledge about Brain science, especially Motor control and learning algorithm are lectured.
By completing this course, students will be able to explain the methodology of computational neuroscience for motor control.
Motor control, Machine Learning, Brain science
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Each topic will be introduced with lecture note.
Course schedule | Required learning | |
---|---|---|
Class 1 | Computational neuroscience | Introduction of computational neural science |
Class 2 | trajectory planning and optimize function | Understand of trajectory planning and optimize function |
Class 3 | analysis of biological signals | Understand of analysis of biological signals |
Class 4 | modeling of biological system | Understand of modeling of biological system |
Class 5 | Learning and control of voluntary movement | Understand of learning and control of voluntary movement |
Class 6 | decoding of brain signals | Understand of decoding of brain signals |
Class 7 | Applications of brain science | Understand of Applications of brain science |
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.
original text will be used.
Principles of Neural Science, McGraw-Hill Professional
The above target is evaluated by final exam 60%, exercises 40%.
Without any requirements