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Graphical neuroimaging informatics: Application to Alzheimer’s disease

  • SI: Genetic Neuroimaging in Aging and Age-Related Diseases
  • Published:
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Abstract

The Informatics Visualization for Neuroimaging (INVIZIAN) framework allows one to graphically display image and meta-data information from sizeable collections of neuroimaging data as a whole using a dynamic and compelling user interface. Users can fluidly interact with an entire collection of cortical surfaces using only their mouse. In addition, users can cluster and group brains according in multiple ways for subsequent comparison using graphical data mining tools. In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients with Alzheimer’s Disease, mild cognitive impairment, as well as healthy control subjects. Alzheimer’s Disease is particularly interesting due to the wide-spread effects on cortical architecture and alterations of volume in specific brain areas associated with memory. We demonstrate INVIZIAN’s ability to render multiple brain surfaces from multiple diagnostic groups of subjects, showcase the interactivity of the system, and showcase how INVIZIAN can be employed to generate hypotheses about the collection of data which would be suitable for direct access to the underlying raw data and subsequent formal statistical analysis. Specifically, we use INVIZIAN show how cortical thickness and hippocampal volume differences between group are evident even in the absence of more formal hypothesis testing. In the context of neurological diseases linked to brain aging such as AD, INVIZIAN provides a unique means for considering the entirety of whole brain datasets, look for interesting relationships among them, and thereby derive new ideas for further research and study.

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Acknowledgements

The authors wish to thank the faculty and staff of the Institute of Neuroimaging and Informatics of the University of Southern California and the Laboratory of Neuro Imaging (LONI) at the University of California Los Angeles. This work was supported by RC1 MH088194 and R01 MH100028 (sub-award) grants to JVH.

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Authors and Affiliations

  1. The Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 North Soto Street – SSB1-102, Los Angeles, CA, 90032, USA

    John Darrell Van Horn, Ian Bowman & Vaughan Greer

  2. Department of Neurology, UCLA School of Medicine, 635 Charles E. Young Drive, NRB #225, Los Angeles, CA, 90095, USA

    Shantanu H. Joshi

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  1. John Darrell Van Horn
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  2. Ian Bowman
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Correspondence to John Darrell Van Horn.

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Submitted to: Brain Imaging and Behavior Special Issue on Neuroimaging and Genetics in Aging and Age-related Disease

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Van Horn, J.D., Bowman, I., Joshi, S.H. et al. Graphical neuroimaging informatics: Application to Alzheimer’s disease. Brain Imaging and Behavior 8, 300–310 (2014). https://doi.org/10.1007/s11682-013-9273-9

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  • DOI: https://doi.org/10.1007/s11682-013-9273-9

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