The CAJAL Advanced Neuroscience Training Programme : Computational Neuroscience

External Event - 12th Aug to 1st Sep 2018

Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modelling the brain, and also for designing and interpreting experiments. Mathematical modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements.

The course teaches the central ideas, methods, and practices of modern computational neuroscience through a combination of lectures and hands-on project work. During the course’s mornings, distinguished international faculty deliver lectures on topics across the entire breadth of experimental and computational neuroscience. For the remainder of the time, students work on research projects in teams of 2 to 3 people under close supervision of expert tutors and faculty. Research projects are proposed by faculty before the course, and include the modeling of neurons, neural systems, and behaviour, the analysis of state-of-the-art neural data (behavioural data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories to explain experimental observations.

This course is designed for graduate students and postdoctoral fellows from a variety of disciplines, including neuroscience, physics, electrical engineering, computer science, mathematics and psychology. Students are expected to have a keen interest and basic background in neurobiology, a solid foundation in mathematics, as well as some computing experience. A four-day pre-school in mathematics and programming is offered for students that want to catch up on their math and programming skills. 

Course directors : 

• Jakob Macke, Research Center Caesar, Germany
• Christian Machens, Champalimaud research, Portugal
• Joe Paton, Champalimaud research, Portugal

Speakers : 

• Matthias Bethge, University of Tübingen, Germany
• Kevin Briggman, Research Center Caesar, Germany
• Megan Carey, Champalimaud Research, Portugal
• Claudia Clopath, Imperial College London, UK
• Sophie Denève, École Normale Supérieure, France
• Rainer Engelken, Columbia University, USA
• Julijana Gjorgjieva, MPI Brain Research, Germany
• Pedro J. Gonçalves, Research Center Caeser, Associate of Max Planck Society, Germany
• Michael Häusser, University College London, UK
• Andreas Herz, Bernstein Center for Computational Neuroscience, Germany
• Simon Laughlin, University of Cambridge, UK
• Gilles Laurent, MPI Brain Research, Germany
• Máté Lengyel, University of Cambridge, UK
• Jennifer Linden, UCL Ear Institute, UK
• Elliot Ludvig, University of Warwick, UK
• Anthony Movshon, New York University, USA
• Maneesh Sahani, Gatsby Computational Neuroscience Unit, UCL, UK
• Cristina Savin, New York University, USA
• Jeffrey Taube, Darthmouth College, USA
• Eero Simoncelli, New York University, USA
• Tim Vogels, University of Oxford, UK
• Byron Yu, Carnegie Mellon University, USA

For further information please visit https://www.fens.org/Training/CAJAL-programme/CAJAL-courses-2018/CCCN-2018/