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Proceedings Paper

Investigating the use of mutual information and non-metric clustering for functional connectivity analysis on resting-state functional MRI
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Paper Abstract

Functional MRI (fMRI) is currently used to investigate structural and functional connectivity in human brain networks. To this end, previous studies have proposed computational methods that involve assumptions that can induce information loss, such as assumed linear coupling of the fMRI signals or requiring dimension reduction. This study presents a new computational framework for investigating the functional connectivity in the brain and recovering network structure while reducing the information loss inherent in previous methods. For this purpose, pair-wise mutual information (MI) was extracted from all pixel time series within the brain on resting-state fMRI data. Non-metric topographic mapping of proximity (TMP) data was subsequently applied to recover network structure from the pair-wise MI analysis. Our computational framework is demonstrated in the task of identifying regions of the primary motor cortex network on resting state fMRI data. For ground truth comparison, we also localized regions of the primary motor cortex associated with hand movement in a task-based fMRI sequence with a finger-tapping stimulus function. The similarity between our pair-wise MI clustering results and the ground truth is evaluated using the dice coefficient. Our results show that non-metric clustering with the TMP algorithm, as performed on pair-wise MI analysis, was able to detect the primary motor cortex network and achieved a dice coefficient of 0.53 in terms of overlap with the ground truth. Thus, we conclude that our computational framework can extract and visualize valuable information concerning the underlying network structure between different regions of the brain in resting state fMRI.

Paper Details

Date Published: 17 March 2015
PDF: 9 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 94171N (17 March 2015); doi: 10.1117/12.2082565
Show Author Affiliations
Xixi Wang, Univ. of Rochester Medical Ctr. (United States)
Univ. of Rochester (United States)
Mahesh B. Nagarajan, Univ. of Rochester Medical Ctr. (United States)
Anas Z. Abidin, Univ. of Rochester Medical Ctr. (United States)
Univ. of Rochester (United States)
Adora DSouza, Univ. of Rochester (United States)
Susan K. Hobbs, Univ. of Rochester Medical Ctr. (United States)
Axel Wismüller, Univ. of Rochester Medical Ctr. (United States)
Univ. of Rochester (United States)
Ludwig Maximilian Univ. (Germany)


Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)

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