UC San Diego

The behaviors generated by neural circuits are constrained by the connectivity pattern among the neurons involved. Determining this connectivity pattern for circuits involving more than a handful of neurons becomes infeasible for physiological approaches that measure how the membrane potential of one neuron is affected by currents elicited in another. On the other hand, determining connectivity by anatomically discovering synapses is difficult due to the complicated and intertwining arbors that neurons possess. One approach to unravel this knotty problem is to image serial thin sections of neural tissue with an electron microscope. In this thesis, I describe the first application of large scale serial electron microscopy to the ganglion of the medicinal leech, Hirudo verbana. The leech ganglion is an ideal preparation for this experiment as it is compact enough in size that it is feasible to collect images spanning an entire ganglion. Here, I discuss results we collected from two image volumes of leech tissue. One spans a small region of adult ganglion neuropil, while the other includes an entire ganglion belonging to a juvenile leech. In these volumes, I reconstruct three-dimensional representations of neuronal arbors and locate the synapses between them. In Chapter 2, I show that we can differentiate neurons on the basis of where synaptic input and output sites are distributed throughout their arbors. In Chapter 3, I show that we can locate the synapses between pairs of neurons previously known to be connected, and that we can discover new synapses anatomically that are then recovered physiologically. Together, these results demonstrate the potential that this “connectomics” approach has when applied to the already physiologically accessible leech ganglion.