Mathematical Neuroscience Lab, School of Maths, Trinity College Dublin, Ireland

We feel that by applying Network Theory to neuroscience that we can determine how information can pass through a network of neurons. In vivo data would only provide a partial network, so we could not examine the information flow properly. Therefore, we decided to simulate a network of neurons, so that we could have control over the input, and so that we could see how each neuron reacts with its neighbors.

We simulate our network of neurons using the Adaptive Exponential Integrate-and-Fire (aEIF) model

We determine, from the output data, which neurons have a strong influence on when other neurons spike using Incremental Mutual Information (IMI)

We feel that this could be a useful method for analyzing datasets of simultaneous neurons as such datasets get larger with advances in recording equipment.