Synaptic Contact Localization in Three Dimensional Space Using a Center Distance Algorithm

Spatial distribution of synaptic inputs on the dendritic tree of a neuron can have significant influence on neuronal function. Consequently, accurate anatomical reconstructions of neuron morphology and synaptic localization are critical when modeling and predicting physiological responses of individual neurons. Historically, generation of three-dimensional (3D) neuronal reconstructions together with comprehensive mapping of synaptic inputs has been an extensive task requiring manual identification of putative synaptic contacts directly from tissue samples or digital images. Recent developments in neuronal tracing software applications have improved the speed and accuracy of 3D reconstructions, but localization of synaptic sites through the use of pre- and/or post-synaptic markers has remained largely a manual process. To address this, we developed an algorithm, based on 3D distance measurements between putative pre-synaptic terminals and the post-synaptic dendrite. The algorithm is implemented with custom Matlab routines, and its effectiveness evaluated through analysis of primary sensory afferent terminals on motor neurons