Activities at the Laboratory of Computational Neuroscience focus on the following questions centered around temporal aspects of information processing in the brain.
- Models of spiking neurons
In contrast to most artificial neural networks, real neurons communicate with short pulses. How could the brain use pulse coding for information processing? What are the dynamical properties of networks of spiking neurons?
- Spike-timing dependent learning rules
Recent experiments show that the change of a synaptic weight from a neuron i to a neuron j depends on the relative timing of the pulses of neurons i and j. What are the computational consequences of such asymmetric learning rules?
- Spatial Representation and Models of the Hippocampus
Some animal brains contain a spatial representation of their environmont other’s don’t. What could be the use of spatial maps for navigation? How much can be achieved with pure reflexes without navigation? How can learning be incorporated in spatial representations?