BE Seminar Series: Synchronization is Robust in a Computational Model of Neuronal Network Dynamics and Injury

At the macroscale, synchronization between brain regions is believed to be important for memory and attention. Injury, including mild traumatic brain injury, can both increase and decrease synchronization as measured by functional MRI, but these changes are not well understood and are unknown at a smaller spatial scale. Here, we examined how injury affects the synchronization between two clusters of neurons. We used a computational network model consisting of excitatory and inhibitory neurons, derived from Izhikevich integrate-and-fire neurons. We connected two clusters of neurons with different intrinsic firing rates. In this architecture, two distinct clusters of neurons were directionally connected from one upstream cluster to one downstream cluster. The network remodeled according to the rules of spike-timing-dependent plasticity (STDP), resulting in highly synchronized activity between the clusters. We characterized structural subtypes within the network and subsequently explored the functional effects of damaging the network by removing neurons based on their subtype membership.