Every summer the Croucher Foundation funds short courses that aim to educate and inspire postgraduate students and early career researchers from Hong Kong an...
Computational neuroscience aspires at an understanding of the principles of brain functions at the circuit and system levels, the levels where cognitive phenomena – from learning and memory to motor behaviours – emerge. Thus, computational neuroscience is particularly relevant to elucidating complex disorders affecting higher-level brain functions, including Alzheimer’s disease and stroke. Unlocking the information content of neural signals is also critical for the development of brain-computer interfaces. Through this summer course, we aim to help fostering future leaders in the field in Hong Kong and broader Asia area.
In this summer course, local and international experts will deliver lectures on select topics. Considering that some students may not have a background in statistics and computer science, tutorials will be organised to help them acquire foundation knowledge. The tutorials will also serve as a platform for exchange of ideas and generation of novel collaborative possibilities.
In addition to providing students with a solid introduction to the fundamentals of the field, we will also ask our lecturers to discuss their latest research highlights. The advanced topics covered will be selected based on an emerging theme in the field, and for the 2019 course is “Beyond the Local Circuit”.
By the end of the course, our students will have their own answers to the following questions:
- What is computational neuroscience? In what ways is this discipline complementary to other ways of studying the Brain (such molecular and cellular approaches)?
- What are some current models of how sensory information or motor plans may be encoded by neural signals?
- How is computational neuroscience relevant to understanding nervous disorders – from Alzheimer’s diseases, stroke, to schizophrenia – and to devising novel treatment strategies for them?
- How may ideas in computational neuroscience be exploited to design brain-computer interfaces?
- What are the major open questions and key approaches for driving latest and upcoming breakthroughs in computational neuroscience?
Rosa Chan (CityU of HK)
Sage Chen (NYU)
Vincent Cheung (CUHK)
Yu Hu (HKUST)
Ko Ho Owen (CUHK)
Julie Semmelhack (HKUST)
Xiao-Jing Wang (NYU)
Quan Wen (USTC, China)
Sukbin Lim (NYU Shanghai)
Application Deadline: April 1st.
Please click here to apply.