SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies
dc.contributor.author | Galindo, Sergio E. | |
dc.contributor.author | Toharia, Pablo | |
dc.contributor.author | Robles, Oscar D. | |
dc.contributor.author | Pastor, Luis | |
dc.date.accessioned | 2022-01-10T10:22:06Z | |
dc.date.available | 2022-01-10T10:22:06Z | |
dc.date.issued | 2021 | |
dc.description.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 article 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 the 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 the 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 a 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 is easily extendable to include functional data provided, for example, by any of the morphologically-detailed simulators available nowadays, such as Neuron and Arbor, for providing a deep insight into the circuits features prior to simulating it, in particular any analysis where it is important to combine morphology, network topology, and physiology. | es |
dc.description.sponsorship | The research leading to these results has received funding from the Spanish Ministry of Economy and Competitiveness under grants C080020-09 (Cajal Blue Brain Project, Spanish partner of the Blue Brain Project initiative from EPFL) and TIN2017-83132, and the Spanish Ministry of Science and Innovation under grants PID2020-113013RB-C21 and PID2020-113013RB-C22, as well as from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 785907 (Human Brain Project SGA2) and 945539 (Human Brain Project SGA3). | es |
dc.identifier.citation | Galindo SE, Toharia P, Robles OD and Pastor L (2021) SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies. Front. Neuroinform. 15:753997. doi: 10.3389/fninf.2021.753997 | es |
dc.identifier.doi | 10.3389/fninf.2021.753997 | es |
dc.identifier.issn | 1662-5196 | |
dc.identifier.uri | http://hdl.handle.net/10115/18508 | |
dc.language.iso | eng | es |
dc.publisher | Frontiers | es |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | scientific and data visualization in neuroscience | es |
dc.subject | joint neuron morphology and connectivity visualization | es |
dc.subject | neuron network connectivity visual analytics | es |
dc.subject | bioinformatics visualization | es |
dc.subject | visual analytics in neuroscience | es |
dc.title | SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies | es |
dc.type | info:eu-repo/semantics/article | es |
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