Neural Networks
- 한국과학기술원
- 정용
페이스북
트위터
카카오톡
네이버밴드
링크복사
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- 주제분류
- 자연과학 >생물ㆍ화학ㆍ환경 >생명과학
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- 강의학기
- 2012년 2학기
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- 조회수
- 3,535
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This course will provide students with a current approaches of neural networks in biological perspectives. It will cover methodology for from macroscale network such as MRI or EEG to microscale network such as neuronal tracing or optical imaging; analysing methods such as graph theory and biological implications.
차시별 강의
| 1. | |
Introduction | Introduction:Why network? |  |
| 2. | |
Brain connectivity | How to investivage brain connectivity | |
| 3. | |
Brain Networks: Structure | Network measure and Architecture | |
| 4. | |
Brain Networks: and Dynamics | Brain conncetivity | |
| 5. | |
A Network Perspective on Neuroanatomy | Neuroanatomy and Network Science | |
| 6. | |
Mapping Cells, Circuits, and Systems | micro/macroscopic connectivity measure | |
| 7. | |
The Brains Small World | The brain’s Small World: Motifs, Modules, and Hubs | |
| 8. | |
Economy, Efficiency, and Evolution | Wiring minimization and the Evolution of Brain Connectivity | |
| 9. | |
Dynamic Patterns in Spontaneous Neural Activity | default mode network and functional network | |
| 10. | |
Dynamics:Stability and Diversity | Brain’s ability to self-organize and undergo transient state dynamics | |
| 11. | |
Neural Complexity | Measuring Complexity: Randomness and Organization | |
연관 자료
