What makes different people's representations alike: Neural similarity space solves the problem of across-subject fMRI decoding

Journal of Cognitive Neuroscience

Volumn 24, Issue 4, 2012, Pages 868-877

  Raizada, Rajeev D S ^a   Connolly, Andrew C ^b  

^a Department of Molecular Biology and Genetics   (United States)

^b DARTMOUTH COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BRAIN MAPPING; CODING; CONCEPT MAPPING; EMPIRICISM; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; MEDICAL RESEARCH; NERVE CELL; NERVE CELL NETWORK; NEUROSCIENCE; POPULATION; PRIORITY JOURNAL; STIMULUS;

ACOUSTIC STIMULATION; ADOLESCENT; ADULT; BRAIN; BRAIN MAPPING; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LANGUAGE; MAGNETIC RESONANCE IMAGING; MALE; OXYGEN; PHOTIC STIMULATION; PROBLEM SOLVING; YOUNG ADULT;

EID: 84857519612     PISSN: 0898929X     EISSN: 15308898     Source Type: Journal    
DOI: 10.1162/jocn_a_00189     Document Type: Article

References (58)

1. Caramazza, A., & Shelton, J. R. (1998). Domain-specific knowledge systems in the brain the animate-inanimate distinction. Journal of Cognitive Neuroscience, 10, 1-34.
2. Chen, Y., Garcia, E., Gupta, M., Rahimi, A., & Cazzanti, L. (2009). Similarity-based classification: Concepts and algorithms. The Journal of Machine Learning Research, 10, 747-776.
3. Churchland, P. M. (1986). Some reductive strategies in cognitive neurobiology. Mind, 95, 279-309.
4. Churchland, P. M. (1998). Conceptual similarity across sensory and neural diversity: The Fodor/Lepore challenge answered. Journal of Philosophy, 95, 5-32.
5. Cleland, T. A., Morse, A., Yue, E. L., & Linster, C. (2002). Behavioral models of odor similarity. Behavioral Neuroscience, 116, 222-231.
6. Clithero, J. A., Smith, D. V., Carter, R. M., & Huettel, S. A. (2011). Within- and cross-participant classifiers reveal different neural coding of information. Neuroimage, 56, 699-708.
7. Connolly, A. C., Gobbini, M. I., & Haxby, J. V. (2012). Three virtues of similarity-based multivariate pattern analysis: An example from the human object vision pathway. In N. Kriegeskorte & G. Kreiman (Eds.), Understanding visual population codes: Toward a common multivariate framework for cell recording and functional imaging. Cambridge, MA: MIT Press.
8. Daubechies, I., Roussos, E., Takerkart, S., Benharrosh, M., Golden, C., D'Ardenne, K., et al. (2009). Independent component analysis for brain fMRI does not select for independence. Proceedings of the National Academy of Sciences, U.S.A., 106, 10415-10422.
9. Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31, 968-980.
10. Duncan, R. O., & Boynton, G. M. (2003). Cortical magnification within human primary visual cortex correlates with acuity thresholds. Neuron, 38, 659-671.
11. Dupuy, F., Josens, R., Giurfa, M., & Sandoz, J.-C. (2010). Calcium imaging in the ant camponotus fellah reveals a conserved odour-similarity space in insects and mammals. BMC Neuroscience, 11, 28.
12. Edelman, S. (1998). Representation is representation of similarities. Behavioral and Brain Sciences, 21, 449-498.
13. Edelman, S., Grill-Spector, K., Kushnir, T., & Malach, R. (1998). Toward direct visualization of the internal shape representation space by fMRI. Psychobiology, 26, 309-321.
14. Epstein, R., & Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature, 392, 598-601.
15. Fodor, J., & Lepore, E. (1999). All at sea in semantic space: Churchland on meaning similarity. Journal of Philosophy, 96, 381-403.
16. Fodor, J. A., & Lepore, E. (1992). Holism: A shopper's guide. Oxford, U.K.: Blackwell.
17. Goldstone, R. L., & Rogosky, B.J. (2002). Using relations within conceptual systems to translate across conceptual systems. Cognition, 84, 295-320.
18. Guerrieri, F., Schubert, M., Sandoz, J.-C, & Giurfa, M. (2005). Perceptual and neural olfactory similarity in honeybees. PLoS Biology, 3, e60.
19. Haddad, R., Khan, R., Takahashi, Y. K, Mori, K, Harel, D., & Sobel, N. (2008). A metric for odorant comparison. Nature Methods, 5, 425-429.
20. Han, J., & Kamber, M. (2006). Data mining: Concepts and techniques (2nd ed.). Amsterdam: Elsevier.
21. Hanke, M., Halchenko, Y. O., Sederberg, P. B., Olivetti, E., Fründ, I., Rieger, J. W., et al. (2009). PyMVPA: A unifying approach to the analysis of neuroscientific data. Frontiers in Neuroinformatics, 3, 3.
22. Hanson, S. J., Matsuka, T., & Haxby, J. V. (2004). Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: Is there a "face" area? Neuroimage, 23, 156-166.
23. Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425-2430.
24. Haxby, J. V., Guntupalli, J. S., Connolly, A. C, Halchenko, Y O., Conroy, B. R., Gobbini, M. I., et al. (2011). A common, high-dimensional model of the representational space in human ventral temporal cortex. Neuron, 72, 404-416.
25. Haynes, J.-D., & Rees, G. (2006). Decoding mental states from brain activity in humans. Nature Reviews Neuroscience, 7, 523-534.
26. Howard, J. D., Plailly, J., Grueschow, M., Haynes, J.-D., & Gottfried, J. A. (2009). Odor quality coding and categorization in human posterior piriform cortex. Nature Neuroscience, 12, 932-938.
27. Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17, 4302-4311.
28. Kay, K. N., Naselaris, T., Prenger, R. J., & Gallant, J. L. (2008). Identifying natural images from human brain activity. Nature, 452, 352-355.
29. Kiani, R., Esteky, H, Mirpour, K, & Tanaka, K. (2007). Object category structure in response patterns of neuronal population in monkey inferior temporal cortex. Journal of Neurophysiology, 97, 4296-4309.
30. Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H, et al. (2008). Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron, 60, 1126-1141.
31. Kuncheva, L. I., Rodriguez, J. J., Plumpton, C. O., Linden, D. E. J., & Johnston, S. J. (2010). Random subspace ensembles for fMRI classification. IEEE Transactions on Medical Imaging ing, 29, 531-542.
32. Laakso, A., & Cottrell, G. (2000). Content and cluster analysis: Assessing representational similarity in neural systems. Philosophical Psychology, 13, 47-76.
33. Landauer, T., & Dumais, S. (1997). A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211.
34. Martin, A. (2007). The representation of object concepts in the brain. Annual Review of Psychology, 58, 25-45.
35. McCarthy, G, Puce, A., Gore, J., & Allison, T. (1997). Face-specific processing in the human fusiform gyrus. Journal of Cognitive Neuroscience, 9, 605-610.
36. Medin, D. L., Goldstone, R. L., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100, 254-278.
37. Miller, G. (1995). WordNet: A lexical database for English. Communications of the ACM, 38, 39-41.
38. Mitchell, T. M., Shinkareva, S. V., Carlson, A., Chang, K.-M., Malave, V. L., Mason, R. A., et al. (2008). Predicting human brain activity associated with the meanings of nouns. Science, 320, 1191-1195.
39. Mourao-Miranda, J., Bokde, A. L. W., 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.
40. Norman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006). Beyond mind-reading: Multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10, 424-430.
41. O'Toole, A. J., Jiang, F., Abdi, H., & Haxby, J. V. (2005). Partially distributed representations of objects and faces in ventral temporal cortex. Journal of Cognitive Neuroscience, 17, 580-590.
42. O'Toole, A. J., Jiang, F., Abdi, H., Pénard, N., Dunlop, J. P., & Parent, M. A. (2007). Theoretical, statistical, and practical perspectives on pattern-based classification approaches to the analysis of functional neuroimaging data. Journal of Cognitive Neuroscience, 19, 1735-1752.
43. Pedersen, T., Patwardhan, S., & Michelizzi, J. (2004). Wordnet: Similarity: Measuring the relatedness of concepts. In S. Dumais, D. Marcu, & S. Roukos (Eds.), Demonstration papers at HLT-NAACL 2004 on XX (pp. 38-41). Boston, MA: Association for Computational Linguistics.
44. Pekalska, E., & Duin, R. P. W. (2005). The dissimilarity representation for pattern recognition: Foundations and applications. Hackensack, NJ: World Scientific.
45. Pereira, F., Mitchell, T., & Botvinick, M. (2009). Machine learning classifiers and fMRI: A tutorial overview. Neuroimage, 45(Suppl. 1), S199-S209.
46. Poldrack, R. A., Halchenko, Y. O., & Hanson, S. J. (2009). Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychological Science, 20, 1364-1372.
47. Raizada, R. D. S. (under review). Representing the meanings of words: Neural similarity matches semantic similarity.
48. Raizada, R. D. S., Kiani, R., & Kriegeskorte, N. (in preparation). Across-species neural decoding reveals the similarities and differences in how humans and monkeys represent the visual world.
49. Raizada, R. D. S., & Kriegeskorte, N. (2010). Pattern-information fMRI: New questions which it opens up, and challenges which face it. International Journal of Imaging Systems and Technology, 20, 31-41.
50. Shepard, R. N. (1962). The analysis of proximities: Multidimensional scaling with an unknown distance function. I. Psychometrika, 27, 125-140.
51. Shinkareva, S. V., Malave, V. L., Just, M. A., & Mitchell, T. M. (2011). Exploring commonalities across participants in the neural representation of objects. Human Brain Mapping. doi: 10.1002/hbm21296.
52. Shinkareva, S. V., Mason, R. A., Malave, V. L., Wang, W., Mitchell, T. M., & Just, M. A. (2008). Using fMRI brain activation to identify cognitive states associated with perception of tools and dwellings. PLoS ONE, 3, e1394.
53. Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl. 1), S208-S219.
54. Storms, G., Navarro, D. J., & Lee, M. D. (2010). Introduction to the special issue on formal modeling of semantic concepts. Acta Psychologica (Amsterdam), 133, 213-215.
55. Tversky, A. (1977). Features of similarity. Psychological Review, 84, 327.
56. Wang, X., Hutchinson, R., & Mitchell, T. (2003). Training fMRI classifiers to detect cognitive states across multiple human subjects. In S. Thrun (Ed.), Proceedings of the 2003 Conference on Neural Information Processing Systems, Vancouver.
57. Warrington, E. K., & Shallice, T. (1984). Category specific semantic impairments. Brain, 107, 829-854.
58. Xue, G., Dong, Q., Chen, C., Lu, Z., Mumford, J. A., & Poldrack, R. A. (2010). Greater neural pattern similarity across repetitions is associated with better memory. Science, 330, 97-101.