Limiting Factors for Mapping Corpus-Based Semantic Representations to Brain Activity

PLoS ONE

Volumn 8, Issue 3, 2013, Pages

  Bullinaria, John A ^a   Levy, Joseph P ^b  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b UNIVERSITY OF ROEHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; BRAIN MAPPING; BRAIN REGION; ELECTROENCEPHALOGRAM; EXPERIMENTAL DESIGN; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; MATHEMATICAL COMPUTING; NEUROIMAGING; PREDICTION; QUALITY CONTROL; RELIABILITY; SEMANTICS; STIMULUS RESPONSE; TASK PERFORMANCE;

ARTIFICIAL INTELLIGENCE; BRAIN; BRAIN MAPPING; HUMANS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; MODELS, PSYCHOLOGICAL; SEMANTICS;

EID: 84875097974     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0057191     Document Type: Article

References (37)

1. Martin A, Caramazza A, (2003) Neuropsychological and neuroimaging perspectives on conceptual knowledge: An introduction. Cognitive Neuropsychology 20: 195-212.
2. Tyler LK, Stamatakis EA, Dick E, Bright P, Fletcher P, et al. (2003) Objects and their actions: Evidence for a neurally distributed semantic system. NeuroImage 18: 542-557.
3. Binder JR, Desai RH, Graves WW, Conant LL, (2009) Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex 19: 2767-2796.
4. Wang J, Conder JA, Blitzer DN, Shinkareva SV, (2010) Neural representation of abstract and concrete concepts: A meta-analysis of neuroimaging studies. Human Brain Mapping 31: 1459-1468.
5. Binder JR, Desai RH, (2011) The neurobiology of semantic memory. Trends in Cognitive Sciences 15: 527-536.
6. Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, et al. (2001) Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293: 2425-2430.
7. Cox DD, Savoy RL, (2003) Functional magnetic resonance imaging (fMRI) "brain reading": Detecting and classifying distributed patterns of fMRI activity in human visual cortex. NeuroImage 19: 261-270.
8. Mitchell TM, Shinkareva SV, Carlson A, Chang K-M, Malave VL, et al. (2008) Predicting human brain activity associated with the meanings of nouns. Science 320: 1191-1195.
9. Lund K, Burgess C, (1996) Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments & Computers 28: 203-208.
10. Patel M, Bullinaria JA, Levy JP (1997) Extracting semantic representations from large text corpora. In: Bullinaria JA, Glasspool DW, Houghton G, editors, Fourth Neural Computation and Psychology Workshop: Connectionist Representations. London: Springer. pp. 199-212.
11. Landauer TK, Dumais ST, (1997) A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review 104: 211-240.
12. Bullinaria JA, Levy JP, (2007) Extracting semantic representations from word co-occurrence statistics: A computational study. Behavior Research Methods 39: 510-526.
13. Bullinaria JA, Levy JP, (2012) Extracting semantic representations from word co-occurrence statistics: Stop-lists, Stemming and SVD. Behavior Research Methods 44: 890-907.
14. Palatucci M, Hinton G, Pomerleau D, Mitchell TM, (2009) Zero-shot learning with semantic output codes. Neural Information Processing Systems 22: 1410-1418.
15. Devereux B, Kelly C, Korhonen A (2010) Using fMRI activation to conceptual stimuli to evaluate methods for extracting conceptual representations from corpora. In: Proceedings of the First Workshop on Computational Neurolinguistics. Stroudsburg, PA: ACL. pp. 70-78.
16. Jelodar AB, Alizaseh M, Khadevi S (2010) WordNet based features for predicting brain activity associated with meanings of nouns. In: Proceedings of the First Workshop on Computational Neurolinguistics. Stroudsburg, PA: ACL. pp. 18-26.
17. Pereira F, Botvinick M, Detre G (2010) Learning semantic features for fMRI data from definitional text. In: Proceedings of the First Workshop on Computational Neurolinguistics. Stroudsburg, PA: ACL. pp. 1-9.
18. Levy JP, Bullinaria JA (2012) Using enriched semantic representations in predictions of human brain activity. In: Davelaar EJ, editor, Connectionist Models of Neurocognition and Emergent Behavior: From Theory to Applications. Singapore: World Scientific. pp. 292-308.
19. Murphy B, Talukdar P, Mitchell T (2012) Selecting corpus-semantic models for neurolinguistic decoding. In: SEM 2012: The First Joint Conference on Lexical and Computational Semantics. pp. 114-123.
20. Pereira F, Botvinick M, Detre G, (2013) Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments. Artificial Intelligence 194: 240-252.
21. Bullinaria JA (2008) Semantic categorization using simple word co-occurrence statistics. In: Baroni M, Evert S, Lenci A, editors, Proceedings of the ESSLLI Workshop on Distributional Lexical Semantics. Hamburg, Germany: ESSLLI. pp. 1-8.
22. Just MA, Cherkassky VL, Aryal S, Mitchell TM, (2010) A neurosemantic theory of concrete noun representation based on the underlying brain codes. PLoS ONE 5(1): e8622.
23. Zhao Y, Karypis G, (2001) Criterion functions for document clustering: Experiments and analysis. Technical Report TR #01-040, Department of Computer Science, University of Minnesota Available: https://wwws.cs.umn.edu/tech_reports_upload/tr2001/01-040.pdf. Accessed 2013 Feb 22.
24. Karypis G, (2003) CLUTO: A Clustering Toolkit (Release 2.1.1). Technical Report: #02-017, Department of Computer Science, University of Minnesota Available from the CLUTO web-site: http://glaros.dtc.umn.edu/gkhome/views/cluto. Accessed 2013 Feb 22.
25. Brants T, Franz A, (2006) Web 1T 5-gram Version 1. Linguistic Data Consortium, Philadelphia Available: http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2006T13. Accessed 2013 February 22.
26. Baroni M, Bernardini S, Ferraresi A, Zanchetta E, (2009) The WaCky wide web: A collection of very large linguistically processed web-crawled corpora. Language Resources and Evaluation 43: 209-226 Corpus web-site: http://wacky.sslmit.unibo.it/doku.php. Accessed 2013 February 22.
27. Manning CD, Schütze H (1999) Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press.
28. French RM, Labiouse C. (2002) Four problems with extracting human semantics from large text corpora. In: Proceedings of the Twenty-fourth Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates. pp. 316-322.
29. Erk K (2010). What Is Word Meaning, Really? (And How Can Distributional Models Help Us Describe It?). In: Proceedings of the 2010 Workshop on GEometrical Models of Natural Language Semantics. ACL. pp. 17-26.
30. Caron J (2001) Experiments with LSA scoring: Optimal rank and basis. In: Berry MW, editor, Computational Information Retrieval. Philadelphia, PA: SIAM. pp. 157-169.
31. Wang J, Baucom LB, Shinkareva SV, (2012) (in press) Decoding abstract and concrete concept representations based on single-trial fMRI data. Human Brain Mapping 33.
32. Raizada RDS, Connolly AC, (2012) What makes different people's representations alike: Neural similarity space solves the problem of across-subject fMRI decoding. Journal of Cognitive Neuroscience 24: 868-877.
33. Shinkareva SV, Malave VL, Mason RA, Mitchell TM, Just MA, (2011) Commonality of neural representations of words and pictures. NeuroImage 54: 2418-2425.
34. Raposo A, Moss HE, Stamatakis EA, Tyler LK, (2009) Modulation of motor and premotor cortices by actions, action words and action sentences. Neuropsychologia 47: 388-396.
35. Mahon BZ, Caramazza A, (2010) Judging semantic similarity: An event-related fMRI study with auditory word stimuli. Neuroscience 169: 279-286.
36. Liu H, Palatucci M, Zhang J (2009) Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery. In: Proceedings of the 26th Annual International Conference on Machine Learning. New York, NY: ACM Press. pp. 649-656.
37. Chen X, He J, Lawrence R, Carbonell JG (2012) Adaptive multi-task sparse learning with an application to fMRI study. In: Proceedings of the Twelfth SIAM International Conference on Data Mining. Philadelphia, PA: SIAM. pp. 212-223.