Effective functional mapping of fMRI data with support-vector machines

Human Brain Mapping

Volumn 31, Issue 10, 2010, Pages 1502-1511

  Lee, Sangkyun ^a,b   Halder, Sebastian ^a   Kübler, Andrea ^a,c   Birbaumer, Niels ^a,d,e   Sitaram, Ranganatha ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

^b UNIVERSITY OF TÜBINGEN   (Germany)

^c UNIVERSITY OF WÜRZBURG   (Germany)

^d SAN CAMILLO FORLANINI HOSPITAL   (Italy)

^e UNIVERSITAT DE LES ILLES BALEARS   (Spain)

Author keywords

FMRI; Multivariate analysis; Multivariate pattern analysis; Support vector machine

Indexed keywords

ACCURACY; ADULT; ARTICLE; BRAIN; BRAIN MAPPING; CORRELATION COEFFICIENT; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; NEUROIMAGING; NORMAL HUMAN; PRIORITY JOURNAL; SIGNAL PROCESSING; SUPPORT VECTOR MACHINE;

ADULT; BRAIN; BRAIN MAPPING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MOTOR ACTIVITY; YOUNG ADULT;

EID: 78349260157     PISSN: 10659471     EISSN: 10970193     Source Type: Journal    
DOI: 10.1002/hbm.20955     Document Type: Article

References (23)

1. Cover TM, Thomas JA (1991): Elements of Information Theory. New York: Wiley. 542 p.
2. Davatzikos C, Ruparel K, Fan Y, Shen DG, Acharyya M, Loughead JW, Gur RC, Langleben DD (2005): Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection. Neuroimage 28: 663-668.
3. Hastie T, Tibshirani R, Friedman JH (2001): The Elements of Statistical Learning: Data Mining, Inference, and Prediction: With 200 Full-Color Illustrations. New York: Springer. 533 p.
4. Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, Pietrini P (2001): Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293: 2425-2430.
5. Haynes JD, Rees G (2006): Decoding mental states from brain activity in humans. Nat Rev Neurosci 7: 523-534.
6. Haynes JD, Sakai K, Rees G, Gilbert S, Frith C, Passingham RE (2007): Reading hidden intentions in the human brain. Curr Biol 17: 323-328.
7. Jain K, Duin APW, JianchangMao R (2000): Statistical pattern recognition: A review. IEEE Trans Pattern Anal 22: 4-37.
8. Joachims T (1999): Making large-scale SVM learning practical. In: Schölkopf B, Burges C, Smola A, editors. Advances in Kernel Methods - Support Vector Learning: MIT-Press.
9. Kamitani Y, Tong F (2005): Decoding the visual and subjective contents of the human brain. Nat Neurosci 8: 679-685.
10. Kriegeskorte N, Simmons WK, Bellgowan PS, Baker CI (2009): Circular analysis in systems neuroscience: The dangers of double dipping. Nat Neurosci 12: 535-540.
11. LaConte S, Strother S, Cherkassky V, Anderson J, Hu X (2005): Support vector machines for temporal classification of block design fMRI data. Neuroimage 26: 317-329.
12. Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P (1997): Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging 16: 187-198.
13. Mourao-Miranda J, Bokde AL, Born C, Hampel H, Stetter M (2005): Classifying brain states and determining the discriminating activation patterns: Support vector machine on functional MRI data. Neuroimage 28: 980-995.
14. Mourao-Miranda J, Reynaud E, McGlone F, Calvert G, Brammer M (2006): The impact of temporal compression and space selection on SVM analysis of single-subject and multi-subject fMRI data. Neuroimage 33: 1055-1065.
15. Mourao-Miranda J, Friston KJ, Brammer M (2007): Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage 36: 88-99.
16. Norman KA, Polyn SM, Detre GJ, Haxby JV (2006): Beyond mind-reading: Multi-voxel pattern analysis of fMRI data. Trends Cogn Sci 10: 424-430.
17. Op de Beeck HP, Haushofer J, Kanwisher NG (2008): Interpreting fMRI data: Maps, modules and dimensions. Nat Rev Neurosci 9: 123-135.
18. Polyn SM, Natu VS, Cohen JD, Norman KA (2005): Category-specific cortical activity precedes retrieval during memory search. Science 310: 1963-1966.
19. Schölkopf B, Smola AJ (2002): Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, Mass.: MIT Press. 626 p.
20. Schölkopf B, Burges CJC, Smola AJ (1999): Advances in Kernel Methods: Support Vector Learning. Cambridge, Mass.: MIT Press. 376 p.
21. Soon CS, Brass M, Heinze HJ, Haynes JD (2008): Unconscious determinants of free decisions in the human brain. Nat Neurosci 11: 543-545.
22. Thurfjell L, Bengtsson E, Nordin B (1992): A new three-dimensional connected components labeling algorithm with simultaneous object feature extraction capability. CVGIP: Graph Models Image Process 54: 357-364.
23. Vapnik VN (1995): The Nature of Statistical Learning Theory. New York: Springer. 188 p.