SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies - Galindo, Sergio E.; Toharia, Pablo; Robles, Oscar D.; Pastor, Luis (Frontiers in Neuroinformatics, 2021)
Brain complexity has traditionally fomented the division of neuroscience into somehow separated compartments; the coexistence of the anatomical, physiological, and connectomics points of view is just a paradigmatic example of this situation. However, there are times when it is important to combine some of these standpoints for getting a global picture, like for fully analyzing the morphological and topological features of a specific neuronal circuit. Within this framework, this paper presents SynCoPa, a tool designed for bridging gaps among representations by providing techniques that allow combining detailed morphological neuron representations with the visualization of neuron interconnections at synapse level. SynCoPa has been conceived for the interactive exploration and analysis of the connectivity elements and paths of simple to medium complexity neuronal circuits at connectome level. This has been done by providing visual metaphors for synapses and interconnection paths, in combination with the representation of detailed neuron morphologies. SynCoPa could be helpful, for example, for establishing or confirming hypothesis about the spatial distributions of synapses, or for answering questions about the way neurons establish connections or the relationships between connectivity and morphological features. Last, SynCoPa could be used jointly with morphologically-detailed neuronal network simulators, such as Neuron and Arbor, for providing a deep insight into the circuits’ features prior to simulate it, in particularany analysis where it is important to combine morphology, network topology, and physiology.