Information Processing in Data-driven Models of Neurons and Neural Networks
Our research involves the development and analysis of computational models in order to study synaptic plasticity,
associative memory and information processing in neuronal systems. We are currently involved in the following projects:
- Synaptic plasticity and pattern recognition in cerebellar Purkinje cells.
- Synaptic integration and neural coding in the deep cerebellar nuclei (in collaboration with Dieter Jaeger at Emory University and Chris de Zeeuw and Freek Hoebeek at Erasmus Medical Center Rotterdam).
- Information processing in data-driven models of cerebellar cortex (part of the ANR-BBSRC VESTICODE project in collaboration with UCL, the Ecole Normale Superieure and Institut Pasteur, Paris).
- The development of software to facilitate the construction and visualisation of realistic neuronal networks in 3D space (in collaboration with Padraig Gleeson and R. Angus Silver at UCL). [www.neuroconstruct.org]
- The generation of variable neuronal morphologies and their effect on information processing in single cells and networks.
- The evolution of spiking neural networks for the control of simulated agents (in collaboration with Borys Wrobel at the University of Poznan).
- The relation between connectivity and associative memory in models of cerebral cortex with different degrees of biological detail (in collaboration with Weiliang Chen at the Okinawa Institute of Science and Technology).
- Computational models of intracellular signalling networks.
- Determinants of gain control in cerebellar granule cells (in collaboration with Jason Rothman and R. Angus Silver at UCL).