POST-DOCTORAL RESEARCH FELLOW
Computational modelling of the neural mechanisms of spatial cognition
A post-doctoral research position in Neil Burgess’s
lab. at UCL is available for computational modelling of the
interactions between grid cells and place cells in coding spatial
location (see e.g. 1,2,3) and their role in human spatial
memory and imagery in combination with parietal cortex (see e.g.
4,5,6). Applicants should have experience of computational modelling
applied to neuroscience or cognition and of programming languages such
as MatLab. Experience of analysis or acquisition of
experimental data in neuroscience or psychology would be a bonus.
Neil’s lab. forms part of the UCL Institute of Cognitive Neuroscience (http://www.icn.ucl.ac.uk/), located close to the Gatsby Computational Neuroscience Unit (http://www.gatsby.ucl.ac.uk/)
The post is part of a European Union grant on
computational modelling of spatial cognition, with partners Fred Hamker
(T U Chemnitz), Patrick Cavanagh (U Paris Descartes), Pieter Menendorp
(Donders/Neijmegen) and Rufin Van Rullen (CNRS/U
Toulouse). It will start in March 2013, for 3 years, with starting
salary from around £30,000 pa, including London allowance. For more
information please send informal inquiries to:
n.burgess@ucl.ac.uk (he will be at SfN this year).
1. Burgess N, O’Keefe J (2011) Models of place and grid cell firing and theta rhythmicity.
Curr Opin. Neurobiol. 21: 734-744.
2. Barry C, Ginsberg LL, O’Keefe J, Burgess N (2012) Grid cell firing patterns signal environmental novelty by expansion.
P.N.A.S. In press.
3. Krupic J, Burgess N, O’Keefe J (2012) Neural Representations of Location Composed of Spatially-periodic Bands.
Science, 337: 853-857.
4. Doeller CF, Barry C, Burgess, N (2010) Evidence for grid cells in a human memory network.
Nature 463 657- 661.
5. Byrne P, Becker S, Burgess N (2007). Remembering
the past and imagining the future: a neural model of spatial memory and
imagery.
Psychological Review 114 340-375.
6. Tcheang L, Bülthoff H, Burgess N (2011) Visual
influence on path integration in darkness indicates a multimodal
representation of large-scale space.
P.N.A.S. 108: 1152-1157
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