Research in Computational Neuroscience aims at developing detailed biophysical and abstract theoretical models of single cells, microcircuits and large neuronal networks in order to understand information processing and memory formation in the brain. Specifically, we built computational models and use them to investigate the biophysical and morphological mechanisms underlying learning and memory processes in various brain regions (hippocampus, prefrontal cortex, amygdala), paying particular attention to dendritic computations.
Computational modeling of the olfactory bulb network
The olfactory bulb is a neural network of the central nervous system and the first relay of odor information. Projection neurons of the olfactory bulb receive input from the olfactory receptor neurons and transmit it to other brain areas of the olfactory system. The olfactory bulb, however, is not just a relay station. The strict spatial organization and the large number of local interneurons indicate an important role in the processing of odor information.
The excitatory projections neurons comprise a highly diverse neuronal population regarding their morphology, their biophysical and their synaptic properties. They can however be categorized into two main distinct neuronal populations, namely the Mitral and Tufted cells. In this project we investigate the role of the two distinct populations in odor information processing. We use morphologically simplified biophysical models to simulate the two types of projection neurons, while we focus on their biophysical differences. Neurons are organised in a network incorporating the basic elements of the olfactory bulb. The aim of our project is to investigate stimulus coding mechanisms and to elucidate the reason why there are distinct populations of projection neurons.