AUTHOR=Galindo Sergio E. , Toharia Pablo , Robles Oscar D. , Pastor Luis 

TITLE=SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies

JOURNAL=Frontiers in Neuroinformatics

VOLUME=Volume 15 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2021.753997

DOI=10.3389/fninf.2021.753997

ISSN=1662-5196

ABSTRACT=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.