A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data

Simple item page
dc.contributor.authorJönsson, Danielen_US
dc.contributor.authorBergström, Albinen_US
dc.contributor.authorForsell, Camillaen_US
dc.contributor.authorSimon, Rozalynen_US
dc.contributor.authorEngström, Mariaen_US
dc.contributor.authorYnnerman, Andersen_US
dc.contributor.authorHotz, Ingriden_US
dc.contributor.editorKozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgiaen_US
dc.date.accessioned2019-09-03T13:49:05Z
dc.date.available2019-09-03T13:49:05Z
dc.date.issued2019
dc.description.abstractWe present an interactive visual environment for linked analysis of brain imaging and clinical measurements. The environment is developed in an iterative participatory design process involving neuroscientists investigating the causes of brain-related complex diseases. The hypotheses formation process about correlations between active brain regions and physiological or psychological factors in studies with hundreds of subjects is a central part of the investigation. Observing the reasoning patterns during hypotheses formation, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration, thus limiting the scientific scope and preventing extraction of knowledge from available data. Based on these observations, we designed methods that support neuroscientists by integrating their existing statistical analysis of multivariate subject data with interactive visual exploration to enable them to better understand differences between patient groups and the complex bidirectional interplay between clinical measurement and the brain. These exploration concepts enable neuroscientists, for the first time during their investigations, to interactively move between and reason about questions such as 'which clinical measurements are correlated with a specific brain region?' or 'are there differences in brain activity between depressed young and old subjects?'. The environment uses parallel coordinates for effective overview and selection of subject groups, Welch's t-test to filter out brain regions with statistically significant differences, and multiple visualizations of Pearson correlations between brain regions and clinical parameters to facilitate correlation analysis. A qualitative user study was performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights, and is an effective support tool for hypothesis formation.en_US
dc.description.sectionheadersVisual Analytics in Medicine and Biology
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20191232
dc.identifier.isbn978-3-03868-081-9
dc.identifier.issn2070-5786
dc.identifier.pages57-68
dc.identifier.urihttps://doi.org/10.2312/vcbm.20191232
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20191232
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.subjectVisual analytics
dc.subjectApplied computing
dc.subjectImaging
dc.titleA Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Dataen_US
Files
Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
057-068.pdf
Size:
12.39 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
a_visual_environment_for_hypothesis_formation_and_reasoning_in_studies_with_fmri_and_multivariate_clinical_data.mp4
Size:
13.23 MB
Format:
Unknown data format
Download
Collections
VCBM 19: Eurographics Workshop on Visual Computing for Biology and Medicine