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ViSimpl: Multi-View Visual Analysis of Brain Simulation Data

After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesosca...

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Detalles Bibliográficos
Autores principales: Galindo, Sergio E., Toharia, Pablo, Robles, Oscar D., Pastor, Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054003/
https://www.ncbi.nlm.nih.gov/pubmed/27774062
http://dx.doi.org/10.3389/fninf.2016.00044
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author Galindo, Sergio E.
Toharia, Pablo
Robles, Oscar D.
Pastor, Luis
author_facet Galindo, Sergio E.
Toharia, Pablo
Robles, Oscar D.
Pastor, Luis
author_sort Galindo, Sergio E.
collection PubMed
description After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures.
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spelling pubmed-50540032016-10-21 ViSimpl: Multi-View Visual Analysis of Brain Simulation Data Galindo, Sergio E. Toharia, Pablo Robles, Oscar D. Pastor, Luis Front Neuroinform Neuroscience After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures. Frontiers Media S.A. 2016-10-07 /pmc/articles/PMC5054003/ /pubmed/27774062 http://dx.doi.org/10.3389/fninf.2016.00044 Text en Copyright © 2016 Galindo, Toharia, Robles and Pastor. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Galindo, Sergio E.
Toharia, Pablo
Robles, Oscar D.
Pastor, Luis
ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title_full ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title_fullStr ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title_full_unstemmed ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title_short ViSimpl: Multi-View Visual Analysis of Brain Simulation Data
title_sort visimpl: multi-view visual analysis of brain simulation data
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054003/
https://www.ncbi.nlm.nih.gov/pubmed/27774062
http://dx.doi.org/10.3389/fninf.2016.00044
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