Welcome to the Computational and Cognitive Neuroscience (CCN) Summer School.

Designed to emphasize higher cognitive functions and their underlying neural circuit mechanisms, the course aims at training talented and highly motivated students and postdoctoral fellows from Asia and other countries in the world. Applicants with quantitative (including Physics, Mathematics, Engineering and Computer Science) or experimental background are welcomed. The lectures will introduce the basic concepts and methods, as well as cutting-edge research on higher brain functions such as decision-making, attention, learning and memory. Modeling will be taught at multiple levels, ranging from single neuron computation, microcircuits and large-scale systems, to normative theoretical approach. Python-based programming labs coordinated with the lectures will provide practical training in important computational methods.


  • Xiao-Jing Wang (New York University)
  • Zach Mainen (Champalimaud Neuroscience Program)
  • Si Wu (Beijing Normal University)
  • John D. Murray (Yale University)
  • Eric DeWitt (Champalimaud Neuroscience Program)

Course website