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

We 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.

, booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine
}, editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data
}}, author = {
Jönsson, Daniel
Bergström, Albin
Forsell, Camilla
Simon, Rozalyn
Engström, Maria
Ynnerman, Anders
Hotz, Ingrid
}, year = {
}, publisher = {
The Eurographics Association
}, ISSN = {
}, ISBN = {
}, DOI = {
} }