Graph Representation for Content–based fMRI Activation Map Retrieval.

de Herrera G, Long LR, Antani SK

Proceedings of 1st Life Sciences Conference, Sydney, Australia, December 2017 pp. 129-32 DOI: https://doi.org/10.1109/LSC.2017.8268160.

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Abstract:

The use of functional magnetic resonance imaging (fMRI) to visualize brain activity in a non-invasive way is an emerging technique in neuroscience. It is expected that data sharing and the development of better search tools for the large amount of existing fMRI data may lead to a better understanding of the brain through the use of larger sample sizes or allowing collaboration among experts in various areas of expertise. In fact, there is a trend toward such sharing of fMRI data, but there is a lack of tools to effectively search fMRI data repositories, a factor which limits further research use of these repositories. Content-based (CB) fMRI brain map retrieval tools may alleviate this problem. A CB-fMRI brain map retrieval tool queries a brain activation map collection (containing brain maps showing activation areas after a stimulus is applied to a subject), and retrieves relevant brain activation maps, i.e. maps that are similar to the query brain activation map. In this work, we propose a graph-based representation for brain activation maps with the goal of improving retrieval accuracy as compared to existing methods. In this brain graph, nodes represent different specialized regions of a functional-based brain atlas. We evaluated our approach using human subject data obtained from eight experiments where a variety of stimuli were applied.

de Herrera G, Long LR, Antani SK. Graph Representation for Content–based fMRI Activation Map Retrieval. 
Proceedings of 1st Life Sciences Conference, Sydney, Australia, December 2017 pp. 129-32 DOI: https://doi.org/10.1109/LSC.2017.8268160.