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Visual Exploratory Analysis for Multiple T-Maze Studies (CROSBI ID 666537)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Bechtold, Fabrizia ; Splechtna, Rainer ; Matkovic, Kresimir Visual Exploratory Analysis for Multiple T-Maze Studies // Eurographics Workshop on Visual Computing for Biology and Medicine / Puig Puig, Anna ; Schultz, Thomas ; Vilanova, Anna et al. (ur.). Eurographics Association, 2018. str. 203-213

Podaci o odgovornosti

Bechtold, Fabrizia ; Splechtna, Rainer ; Matkovic, Kresimir

engleski

Visual Exploratory Analysis for Multiple T-Maze Studies

Evaluation 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.

Interactive Visual Analysis, Animal Trajectory, Movement Data, Spatial Learning, Memory Retention

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Podaci o prilogu

203-213.

2018.

objavljeno

Podaci o matičnoj publikaciji

Eurographics Workshop on Visual Computing for Biology and Medicine

Puig Puig, Anna ; Schultz, Thomas ; Vilanova, Anna ; Hotz, Ingrid ; Kozlikova, Barbora ; Vázquez, Pere-Pau

Eurographics Association

Podaci o skupu

Eurographics Workshop on Visual Computing for Biology and Medicine

predavanje

20.09.2018-21.09.2018

Granada, Španjolska

Povezanost rada

Računarstvo

Poveznice