Revealing Patterns of Inputs onto Relay Cells in the Visual Thalamus using Modeling Techniques and Association Rule Learning

The inner circuitry of the visual thalamus has been the subject of multiple decades of research using transmission electron microscopy (EM) to look at the synapses of different brain inputs onto relay cells which project to the visual cortex. However, many of these studies are limited in scope by the nature of their two-dimensional construction to fully understand the spatial organization of these inputs. Consequently, it has been challenging to quantitatively establish specific rules or patterns of inputs onto relay cells. I employed several techniques to do just that. I employed a 3D connectomics technique and collected axon terminal volumes from the visual thalamus of mice in order to model and characterize specific patterns of inputs based on association rule learning and network analysis. This additionally involved developing a means of randomly sampling axon terminals from a stack of EM images that can be applied to other datasets and using data simulation of model parameters to determine theoretical cutoff volumes between axon terminals. I uncovered specific rules between terminal inputs that can be used to characterize different sets of relay cell dendrites that possibly correlate to visual parallel pathways of other species. These results provide insight to the intrinsic circuitry of the visual thalamus of mice and relationships to other species.