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

The 7th CCN Summer School which will take place July 6-29, 2017, on the campus of NYU-Shanghai in Shanghai, China. Applications are closed for this edition. Please check this website for information on future editions which will be announced in the fall of 2017.

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)

2017 Lecturers:

  • Alex Pouget (University of Geneva)
  • Daphne Bavelier (University of Geneva)
  • Jeff Erlich (NYU Shanghai)
  • Matthew Botvinick (Google DeepMind)
  • Matthew Rushworth (University of Oxford)
  • Michael Breakspear (University of Queensland)
  • Michael Hausser (University College London)
  • Nikolaus Kriegeskorte (MRC Cognition and Brain Sciences Unit)
  • Robert Desimone (Massachusetts Institute of Technology)
  • Stefano Fusi (Columbia University)
  • Sukbin Lim (NYU Shanghai)
  • Surya Ganguli (Stanford University)
  • Timothy Behrens (University of Oxford)
  • Yann LeCun (New York University & Facebook AI Research)

Course website