Methods for detecting functional classifications in neuroimaging data

Human Brain Mapping

Volumn 23, Issue 2, 2004, Pages 109-119

  Bowman, F DuBois ^a,b   Patel, Rajan ^a   Lu, Chengxing ^a  

^a EMORY UNIVERSITY   (United States)

^b EMORY UNIVERSITY   (United States)

Author keywords

Cluster analysis; F score; Hierarchical clustering; PET; Stopping rules

Indexed keywords

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; CONTROLLED STUDY; HUMAN; HUMAN EXPERIMENT; INTERMETHOD COMPARISON; NEUROIMAGING; NORMAL HUMAN; POSITRON EMISSION TOMOGRAPHY; PRIORITY JOURNAL; SIMULATION;

ALGORITHMS; BRAIN; BRAIN MAPPING; CLUSTER ANALYSIS; HUMANS; POSITRON-EMISSION TOMOGRAPHY; REPRODUCIBILITY OF RESULTS;

EID: 4344583045     PISSN: 10659471     EISSN: None     Source Type: Journal    
DOI: 10.1002/hbm.20050     Document Type: Article

References (27)

1. Balslev D, Nielsen FA, Frutiger SA, Sidtis JJ, Christiansen TB, Svarer C, Strother SC, Rottenberg DA, Hansen LK, Paulson OB, Law I (2002): Cluster analysis of activity-time series in motor learning. Hum Brain Mapp 15:135-145.
2. Baumgartner R, Ryner L, Richter W, Summers R, Jarmasz M, Somorjai R (2000): Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis. Magn Reson Imag 18:89-94.
3. Baune A, Sommer FT, Erb M, Wildgruber D, Kardatzki B, Palm G, Grodd W (1999): Dynamical cluster analysis of cortical fMRI activation. Neuroimage 9:477-489.
4. Bezdek J, Ehrlich R, Full W (1984): FCM: the fuzzy c-means clustering algorithm. Comp Geosci 10:191-203.
5. Bowman FD, Patel R (2004): Identifying spatial relationships in neural processing using a multiple classification approach. Neuroimage (in press).
6. Brodmann K (1909): Vergleichende Lokalisationlehre der Grosshirnrinde in ihren Prinzipien Dargestellt auf Grund des Zellenbaues. [Reprinted as: Garey LJ, translator. Brodmann's "Localisation in the cerebral cortex." London: Smith-Gordon; 1994.]
7. Calinski RB, Harabasz J (1974): A dendrite method for cluster analysis. Comm Stat 3:1-27.
8. Carlin BP, Louis TL. (2000): Bayes and empirical Bayes methods for data analysis, 2nd ed. New York: Chapman and Hall; p.40-42.
9. Cordes D, Haughton V, Carew JD, Arfanakis K, Maravilla K (2002): Hierarchical clustering to measure connectivity in fMRI resting-state data. Magn Reson Imag 20:305-317.
10. Duda RO, Hart PE. 1973. Pattern classification and scene analysis. New York: John Wiley and Sons.
11. Fadili MJ, Ruan S, Bloyet D, Mazoyer B (2000): A multistep unsupervised fuzzy clustering analysis of fMRI time series. Hum Brain Mapp 10:160-178.
12. Fadili MJ, Ruan S, Bloyet D, Mazoyer B (2001): On the number of clusters and the fuzziness index for unsupervised FCA application to BOLD fMRI time series. Medical Image Analysis 5:55-67.
13. Filzmoser P, Baumgartner R, Moser E (1999): A hierarchical clustering method for analyzing functional MR images. Magn Reson Imag 17:817-826.
14. Goutte C, Hansen LK, Liptrot MG, Rostrup E (2001): Feature-space clustering for fMRI meta-analysis. Hum Brain Mapp 13:165-183.
15. Goutte C, Toft P, Rostrup E, Nielsen FA, Hansen LK (1999): On clustering fMRI time series. Neuroimage 9:298-310.
16. Lance GN, Williams, WT (1967): A general theory of classificatory sorting strategies: I. Hierarchical Systems. Comput J 9:373-380.
17. Larsen B, Aone C (1999): Fast and effective text mining using linear-time document clustering. In: Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p 16-22.
18. MacQueen J (1967): Some methods for classification and analysis of multivariate observations. In: Le Cam LM, Neyman J, editors. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, CA: University of California Press. p 281-297.
19. Maitra R (1997): Estimating precision in functional images. J Comput Graph Stat 6:132-142.
20. Milligan GW, Cooper MC (1985): An examination of procedures for determining the number of clusters in a data set. Psychometrika 50:159-179.
21. Rencher A. (2002): Methods of multivariate analysis, 2nd ed. New York: John Wiley and Sons. p 470.
22. Sarle WS (1983): Cubic clustering criterion, SAS Technical Report A-108. Cary, NC: SAS Institute Inc.
23. Schwarz G (1978): Estimating the dimension of a model. Ann Stat 6:461-464.
24. Sommer FT, Wichert A (2003): Exploratory analysis and data modeling in functional neuroimaging. Cambridge, MA: The MIT Press. p 17-42.
25. Stanberry L, Nandy R, Cordes D (2003): Cluster analysis of fMRI data using dendrogram sharpening. Hum Brain Mapp 20:201-219.
26. Wong MA, Lane T (1983): A kth nearest neighbor clustering procedure. J R Stat Soc B 45:362-368.
27. Zhu C, Jiang T (2003): Multi-context fuzzy clustering for separation of brain tissues in MRI images. Neuroimage 18:685-696.