Next generation neural activity models: bridging the gap between mesoscopic and microscopic brain scales - Byrne, Aine (2017)
Neural mass and neural field models have been actively used since the 1970s to model the coarse grained activity of large populations of neurons and synapses. They have proven especially useful in understanding brain rhythms. However, although motivated by neurobiological considerations, they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. In this thesis we consider the θ-neuron model that has recently been shown to possess an exact mean-field description for smooth non-pulsatile interactions, and show that the inclusion of a more realistic synapse model leads to a mean-field model, that has many of the features of a neural mass model, coupled to a further dynamical equation that describes the evolution of network synchrony.