Tracking the reconstruction of memories in the human brain
The PhD candidate will work on the ERC-funded project STREAM - The Spatio-Temporal Representational Architecture of Memory. This project, led by Dr Maria Wimber, aims to track how memories are reconstructed in the human brain. The project uses a combination of electrophysiological and neuroimaging methods, together with novel behavioural paradigms and state-of-the-art pattern analysis techniques. See the reerences below for our recent publications within this grant.
For this particular PhD project we are planning to combine EEG-MEG with the use of Deep Neural Networks (DNNs), in order to map exactly what features of a memory are reactivated when and where, and what mnemonic features are most relevant when recalling a past event.
The successful candidate should have a strong interest in long-term memory and how memories are represented in our brains. Programming (MATLAB or Python) and analytic thinking skills are essential. We will prioritize candidates who already have hands-on experience in analyzing electrophysiological data, or candidates who have computational modelling/neural network modelling background.
Please contact Dr Wimber directly via email ([Email Address Removed]) if you are interested in the PhD position.
The project is funded by the European Research Council (ERC) and includes full funding for a 3-year PhD, including salary and tuition fees.
Linde-Domingo J, Treder MS, Kerren C, Wimber M (2019). Evidence for a reversal of the neural information flow between object perception and object reconstruction from memory. Nature Communications 179, 10. https://doi.org/10.1101/300913.
Kerrén C, Linde-Domingo J, Hanslmayr S, Wimber M (2018). An optimal oscillatory phase for pattern reactivation during memory retrieval. Current Biology 28, 3383-92. https://doi.org/10.1016/j.cub.2018.08.065.
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