How does the architecture of neural systems determine information processing?

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How does the architecture of neural systems determine information processing? The architecture is important to determine how neural systems process information. This holds at different length scales, e.g., at the synapse, the neuron, and the network of neurons. This project aims to reveal principles valid at different levels, by addressing the following topics: - Information processing in a synapse: Realistic modeling of receptor acti - vation in hippocampal excitatory synapses. Synaptic plasticity, long term potentiation and long term depression play an important role in learning and memory. Such adaptation of a synapse can reinforce or weaken the link between the pre- and post-synaptic neurons. We aim to consider a reconstructed real hippocampal synapse, and model synaptic transmission. We want to study the role of synaptic cleft size, number of neurotransmitters, density and location of receptors, neuro-transmitter uptake and the synapse-glia interaction. - Information processing in a neuron: Modeling spiking and back propagation of thalamo-cortical cell. The thalamus is the major gateway for the flow of information toward the crebral cortex and is a station where incoming signals can be blocked during sleep. The neurons in thalamus and in cortex display a rich variety of spiking patterns. We aim to model the generation of the action potential and its back propagation into the dendritic tree of a thalamo-cortical neuron. We want to study the factors influencing the spiking behaviour: the shape of the dendritic arbor, the distribution of synapses, the distribution of Calcium ion channels. - Information processing in a neural network: Binocular rivalry in visual perception. Perception plays a cardinal role in everything we do. Recent experiments allow to analyze the neural network dynamics underlying perception on mesoscopic spatio-temporal scales. This scale is involved in the development of smart brain-computer interfacing. We aim to model percept switches in binocular rivalry, study the location of onset of percept switches (nucleation), the growth of the nucleation zone, and its geometrical shape. By comparison with experiments we hope to learn about the connectivity structure of the neuron populations and its biophysical parameters.