Model-free functional MRI analysis based on unsupervised clustering

Axel Wismüller, Anke Meyer-Bäse, Oliver Lange, Dorothee Auer, Maximilian F. Reiser, DeWitt Sumners
2004 Journal of Biomedical Informatics  
Conventional model-based or statistical analysis methods for functional MRI (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms. However, they are not applicable in situations in which patterns of neural response are complicated and when fMRI response is unknown. In this paper the "neural gas" network is adapted and rigourosly studied for analyzing fMRI data. The algorithm supports spatial connectivity aiding in the identification of activation sites in
more » ... onal brain imaging. A comparison of this new method with KohonenÕs self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative evaluations. The most important findings in this paper are: (1) both "neural gas" and the fuzzy clustering technique outperform KohonenÕs map in terms of identifying signal components with high correlation to the fMRI stimulus, (2) the "neural gas" outperforms the two other methods with respect to the quantization error, and (3) KohonenÕs map outperforms the two other methods in terms of computational expense. The applicability of the new algorithm is demonstrated on experimental data.
doi:10.1016/j.jbi.2003.12.002 pmid:15016382 fatcat:ifzdabczuvgojc4oxjg3edcjka