 Hi, everyone. My name is Miri Hiayve. I'm a third year PhD candidate in Electrical and Computer Engineering Department at McMaster University. My research focuses on creating biophysically detailed neural network models for the bush cells of the cochlear nucleus. Cochlear nucleus is important in terms of being the first stage in the central auditory system where the sound signals enters the brain. Over here, useful information such as sound identification and localization gets extracted and began to propagate to the upper levels of the central auditory system via parallel pathways. There are two main types of cells that sends this information to the upper levels, T-cell cells and bush cells. Bush cells have the ability to preserve the fine timing information in the sound signals, which allows us to identify where the sound is actually coming from. To be able to understand the behavior of these cells, computational studies are as important as the experimental ones. In our research, we use detailed hydrogen-haxi type models for the ventral cochlear nucleus cells and create micro-surface out of them. These detailed models allow us to understand how the individual components such as excitation, inhibition, or the connection patterns affect the behavior of these cells. These days, we are investigating the effects of gap junctions and inhibition on the synchrony enhancement phenomena seen in the bush cells. For global or bush cells, which receives excitation from many auditory nerve fibers, this enhancement in the synchrony can be explained by coincidence detection mechanism. But for the spherical bush cells, which receives very few auditory nerve inputs, the mechanism behind the synchrony enhancement phenomena is still not clear. We believe developing a detailed model that can mimic the behavior of these cells can help us solve the spherical cell puzzle. Thank you so much.