Cognitive Neuroscience Robotics – Part A
Cognitive Neuroscience Robotics is an interdisciplinary area for development of new information and robot technology systems based on understanding higher functions of the human brain, with the integration of cognitive science, neuroscience, and robotics.
This course introduces Cognitive Neuroscience Robotics with two approaches: the synthetic and the analytic approach. The synthetic approach means an engineering approach to understand human cognitive functions synthetically, trying to understand human cognitive functions by replicating them as artificial systems and putting them into social environments. Specifically, it develops artificial systems such as robots based on findings in neuroscience and physiology, and investigates how they could acquire intelligent behaviors through interaction with others and the environment.
On the other hand, human cognitive activities are investigated analytically. They are supported by higher functions of the brain and have been examined by psychological experiments or brain imaging. With the analytic approach, psychologists, cognitive scientists, and medical doctors are pursuing an understanding of the mechanism of the mind and its biological basis, with the help of engineering and philosophy.
This program will help students make a basis for interdisciplinary research by providing opportunities to understand what is undertaken in other disciplines and how to collaborate and exchange ideas with people from other disciplines. We expect many motivated students to apply.
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- Virtual Classroom
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Course delivery details
This course is offered through Osaka University, a partner institute of EdX.
3-4 hours per week
- Verified Track -$49
- Audit Track - Free
Certification / Credits
What you'll learn
- Basic issues in cognitive neuroscience robotics
- Recent development and findings in robotics based on cognitive and brain sciences
- Ideas and methods in various disciplines relevant to cognitive neuroscience robotics and how they relate to each other
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