|
Contacts: Thierry Nieus, Michela Chiappalone (Post-docs); Valentina Pasquale, Matteo Garofalo (PhD students); Sergio Martinoia (Senior Collaborator).
Within this research line we investigate the computational capabilities of neuronal networks and we develop biophysical models to describe the experimentally observed neuronal responses.
Modelling activities along with recordings of both spontaneously active and electrically stimulated cultures are aimed at uncovering mechanisms of LTP/LTD at the network level, neural coding and pattern generation. The development of data analysis tools, either inspired by information theory or complex systems dynamics, allows to extract from electrophysiological recordings the functional connectivity of neuronal populations or to study network dynamics.
In addition realistic biophysical models are used to describe, for example, the neuronal responses observed at the single cell level. Detailed models of vesicle dynamic and of receptor dynamic are developed to understand how physiological inputs, e.g. input bursts, are processed by the synapses. Information theory allows to make predictions on how the processing occurs in different physiological contexts (e.g. after LTP induction) and thus to elucidate the nature of the neural code.
|
|
|
| Release of neurotransmitter is regulated by neuronal activity and it is stochastic. |
A bifurcation diagram shows that the injection of a fixed current cause a neuron-model to fire regularly. |
|
Projects