Resumen de Information Processing Organization of a Biological Neural Network

S. Galella Toledo, Óscar Vilarroya Oliver, J. Garcia Ojalvo

• The aim of this study is to characterize how information is propagated within a biological neural network using the connectome of Caenorhabditis elegans as a model. In particular, reservoir computing is proposed as the architecture of the neural network of the organism. This architecture relies on a recurrent core of neurons that receives and encodes complex inputs in a high dimensional phase space. Encoding takes place by combining the incoming input signal with the existing state of the network, which depends on past inputs. In this study we used neuronal time series from C. elegans registered in conditions of oscillating temperature to assess the possibility of reservoir computing architecture in the nervous system of the nematode. This paradigm could help in the understanding of how a basic nervous system’s processing works, for further inferences in higher complex systems.