Visual Exploratory Analysis for Multiple T-Maze Studies

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dc.contributor.authorBechtold, Fabriziaen_US
dc.contributor.authorSplechtna, Raineren_US
dc.contributor.authorMatkovic, Kresimiren_US
dc.contributor.editorPuig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pauen_US
dc.date.accessioned2018-09-19T15:20:04Z
dc.date.available2018-09-19T15:20:04Z
dc.date.issued2018
dc.description.abstractEvaluation of spatial learning and memory in rodents is commonly carried out using different maze settings such as the Multiple T-Maze. State-of-the-art analysis is primarily based on statistics of quantitative measures stemming from animal trajectories in a maze, e.g. path length or correct decisions made. Currently trajectories themselves are analyzed and evaluated one at a time and comparison of multiple trajectories is a tedious task. The resulting findings may not fully answer complex questions that behavioral researchers encounter as well, e.g., why do animals behave in a certain way or can atypical behaviour be detected? This paper describes an innovative approach on how exploratory analysis for Multiple T-Maze studies can be enhanced through interactive visual analysis. We explain our solution for analyzing a whole ensemble of data at once and support the finding of orientational characteristics and migration patterns within the ensemble. We also abstract the analysis tasks for Multiple TMaze studies and, based on these tasks, we extend a coordinated multiple views system to support the solving of fundamental problems which behavioral researchers face. Besides views of standard charts we deploy a multi-resolution heat map and the Gate-O-Gon, which is a novel visual element. It gives clues on the animals' general movement orientation and distribution of revisited gates, as well as enhances the discovery of patterns in movement and identifying of irregular behavior. Finally we demonstrate the usefulness of the newly proposed approach using a real life data set consisting of 400 Multiple T-Maze runs.en_US
dc.description.sectionheadersBiology
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20181246
dc.identifier.isbn978-3-03868-056-7
dc.identifier.issn2070-5786
dc.identifier.pages203-213
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20181246
dc.identifier.urihttps://doi.org/10.2312/vcbm.20181246
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman centered computing
dc.subjectVisualization application domains
dc.subjectVisual analytics
dc.subjectInteractive Visual Analysis
dc.subjectAnimal Trajectory
dc.subjectMovement Data
dc.subjectSpatial Learning
dc.subjectMemory Retention
dc.titleVisual Exploratory Analysis for Multiple T-Maze Studiesen_US
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VCBM 18: Eurographics Workshop on Visual Computing for Biology and Medicine