Abstract
Aiming to exploit the rich fundus of available functional neuroimaging data, we present a coordinate-based pattern-mining approach. Gaussian mixture modeling is applied on three-dimensional brain coordinates obtained from neuroimaging databases collecting peak activations seen in functional neuroimaging experiments. We show how the Apriori algorithm used in association analysis can be applied to the obtained results, revealing frequent patterns of the identified coordinate clusters. These patterns can be interpreted as common networks of functionally connected brain regions and hence give deeper insights into the functional organization of the human brain.
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References
Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proc. ACM SIGMOD 1993, pp. 207–216. ACM Press, New York (1993)
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proc. VLDB 1994, pp. 487–499. Morgan Kaufmann, San Francisco (1994)
BrainMap, http://www.brainmap.org/
Caspers, J., Zilles, K., Eickhoff, S.B., Beierle, C.: PaMiNI: a comprehensive system for mining frequent neuronal patterns of the human brain. In: Proc. CBMS 2012. IEEE Press, New York (2012)
Cherry, S.R., Phelps, M.E.: Imaging brain function with positron emission tomography. In: Toga, A.W., Mazziotta, J.C. (eds.) Brain Mapping: the Methods, 2nd edn., pp. 485–511. Academic Press, San Diego (2002)
Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Statistical Society, Series B 39, 1–38 (1977)
Eickhoff, S.B., Grefkes, C.: Approaches for the integrated analysis of structure, function and connectivity of the human brain. Clin. EEG Neurosci. 42(2), 107–121 (2011)
Eickhoff, S.B., Laird, A.R., Grefkes, C., Wang, L.E., Zilles, K., Fox, P.T.: Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty. Hum. Brain. Map. 30, 2907–2926 (2009)
Evans, A.C., Collins, D.L., Mills, S.R., Brown, E.D., Kelly, R.L., Peters, T.M.: 3D statistical neuroanatomical models from 305 MRI volumes. In: Proc. IEEE-NSS 1993, vol. 3, pp. 1813–1817. IEEE Press, New York (1993)
Friston, K.J.: Functional and effective connectivity in neuroimaging: a synthesis. Hum. Brain. Map. 2, 56–78 (1994)
Gan, G., Ma, C., Wu, J.: Data clustering: theory, algorithms, and applications, ch. 14, pp. 227–242. SIAM, Philadelphia (2007)
Jezzard, P., Matthews, P.M., Smith, S.M.: Functional MRI: an introduction to methods. Oxford University Press, Oxford (2001)
Laird, A.R., Lancaster, J.L., Fox, P.T.: Brainmap: the social evolution of a human brain mapping database. Neuroinformatics 3, 65–78 (2005)
Raichle, M.E.: Behind the scenes of functional brain imaging: a history and physiological perspective. Proc. Natl. Acad. Sci. USA 95, 765–772 (1998)
Robinson, J.L., Laird, A.R., Glahn, D.C., Lovallo, W.R., Fox, P.T.: Metaanalytic connectivity modeling: delineating the functional connectivity of the human amygdala. Hum. Brain. Map. 31, 173–184 (2010)
Rottschy, C., Langner, R., Dogan, I., Reetz, K., Laird, A.R., Schulz, J.B., Fox, P.T., Eickhoff, S.B.: Modelling neural correlates of working memory: a coordinate-based meta-analysis. Neuroimage 60, 830–846 (2012)
Savoy, R.L.: History and future directions of human brain mapping and functional neuroimaging. Acta Psychol. 107, 9–42 (2001)
Schwarz, G.: Estimating the dimension of a model. Ann. Stat. 6(2), 461–464 (1978)
Talairach, J., Tournoux, P.: Coplanar stereotaxic atlas of the human brain. Thieme, Stuttgart (1988)
The MathWorks, Inc., http://www.mathworks.com/
Turkeltaub, P.E., Eden, G.F., Jones, K.M., Zeffiro, T.A.: Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. Neuroimage 16(3), 765–780 (2002)
Wager, T.D., Jonides, J., Reading, S.: Neuroimaging studies of shifting attention: a meta-analysis. Neuroimage 22(4), 1679–1693 (2004)
Wager, T.D., Lindquist, M.: Kaplan L. Meta-analysis of functional neuroimaging data: current and future directions. Soc. Cogn. Affect. Neurosci. 2(2), 150–158 (2007)
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Caspers, J., Zilles, K., Eickhoff, S.B., Beierle, C. (2012). Coordinate-Based Pattern-Mining on Functional Neuroimaging Databases. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_25
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DOI: https://doi.org/10.1007/978-3-642-31709-5_25
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