Connectionists: Computational & Cognitive Neuroscience Summer School application open!

[Chengcheng Huang]

Applications are open for the 11th Computational and Cognitive Neuroscience
Summer School (CCNSS), which will be held from *June 26 to July 17, 2022*,
at *Suzhou, China*.


Online application: https://www.csh-asia.org/?content/1239

Application deadline: *April 30, 2022*


About CCNSS:

Designed to emphasize computational principles and neural circuit
mechanisms of higher cognitive functions, the course aims at training
talented and highly motivated students and postdoctoral fellows from Asia
and around the world. We welcome both applicants with quantitative
backgrounds (including Physics, Mathematics, Engineering and Computer
Science) and those with experimental backgrounds. 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 and microcircuits up to large-scale brain systems and
artificial intelligence and psychiatric disorders. Python-based programming
labs coordinated with the lectures will provide practical training in
important computational methods. More details can be found at the course
website https://www.ccnss.org.


Organizers:

Dora Angelaki, New York University

Christopher Honey,  Johns Hopkins University

Chengcheng Huang, University of Pittsburgh

Xiao-Jing Wang, New York University

Guangyu Robert Yang, Massachusetts Institute of Technology


Faculty:

Dani Bassett, University of Pennsylvania

Carlos Brody,  Princeton University

Bob Desimone, Massachusetts Institute of Technology

Angela Langdon, National Institute of Mental Health

Songting Li, Shanghai Jiao Tong University

Yunzhe Liu, Chinese Institute for Brain Research

Yuanyuan Mi, Chongqing University

Tirin Moore, Stanford University

Srdjan Ostojic, École normale supérieure

Anna Schapiro, University of Pennsylvania

Kim Stachenfeld,  DeepMind
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