Discrete combinatorial circuits emerging in neural networks: A mechanism for rules of grammar in the human brain?

Neural Networks

Volumn 22, Issue 2, 2009, Pages 161-172

  Pulvermüller, Friedemann ^a   Knoblauch, Andreas ^a,b  

^a MEDICAL RESEARCH COUNCIL   (United Kingdom)

^b HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

Brain; Correlation; Discrete combinatorial rule; Grammar; Language; Linguistics; Neural network; Neuronal assembly; Syntax; Unsupervised learning

Indexed keywords

CORRELATION; DISCRETE COMBINATORIAL RULE; GRAMMAR; LANGUAGE; NEURONAL ASSEMBLY; SYNTAX;

ANIMALS; DETECTORS; LINGUISTICS; NETWORKS (CIRCUITS); OVERLAY NETWORKS; SYNTACTICS; UNSUPERVISED LEARNING;

NEURAL NETWORKS;

ARTICLE; ASSOCIATION CORTEX; BRAIN CORTEX; GRAMMAR; LANGUAGE ABILITY; LANGUAGE PROCESSING; LINGUISTICS; MATHEMATICAL COMPUTING; NERVE CELL NETWORK; NERVE CONDUCTION; NERVE FUNCTION; NETWORK LEARNING; PRIORITY JOURNAL; SIMULATION; WORD RECOGNITION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER SIMULATION; COMPUTER SYSTEMS; HUMANS; LANGUAGE; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); PSYCHOLINGUISTICS;

EID: 61449252403     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2009.01.009     Document Type: Article

References (86)

1. Aviel Y., Horn D., and Abeles M. Memory capacity of balanced networks. Neural Computation 17 3 (2005) 691-713
2. Barlow H.B., Hill R.M., and Levick W.R. Retinal ganglion cells responding selectively to direction and speed of image motion in the rabbit. Journal of Physiology 173 (1964) 377-407
3. Braitenberg V., and Schüz A. Cortex: Statistics and geometry of neuronal connectivity. 2 ed. (1998), Springer, Berlin
4. Brent M. From grammar to lexicon: Unsupervised learning of lexical syntax. Computational Linguistics 19 3 (1993) 243-262
5. Briscoe, E., & Carroll, J. (1997). Automatic extraction of subcategorization from corpora. In Proceedings of the 5th ACL conference on applied natural language processing (pp. 1-9). Vol. 5
6. Catani M., Jones D.K., and Ffytche D.H. Perisylvian language networks of the human brain. Annals of Neurology 57 1 (2005) 8-16
7. Chomsky N. Syntactic structures (1957), Mouton, The Hague
8. Chomsky N. Aspects of the theory of syntax (1965), MIT Press, Cambridge
9. Christiansen M.H., and Chater N. Toward a connectionist model of recursion in human linguistic performance. Cognitive Science 23 2 (1999) 157-205
10. Dapretto M., and Bookheimer S.Y. Form and content: Dissociating syntax and semantics in sentence comprehension. Neuron 24 2 (1999) 427-432
11. Demonet J.F., Thierry G., and Cardebat D. Renewal of the neurophysiology of language: Functional neuroimaging. Physiological Reviews 85 1 (2005) 49-95
12. Elman J.L. Finding structure in time. Cognitive Science 14 (1990) 179-211
13. Elman J.L., Bates L., Johnson M., Karmiloff-Smith A., Parisi D., and Plunkett K. Rethinking innateness: A connectionist perspective on development (1996), MIT Press, Cambridge, MA
14. Fodor J., and McLaughlin B.P. Connectionism and the problem of systematicity: Why Smolensky's solution doesn't work. Cognition 35 2 (1990) 183-204
15. Friederici A.D., Hahne A., and Mecklinger A. Temporal structure of syntactic parsing: Early and late event-related brain potential effects. Journal of Experimental Psychology. Learning, Memory and Cognition 22 5 (1996) 1219-1248
16. Friederici A.D., Pfeifer E., and Hahne A. Event-related brain potentials during natural speech processing: Effects of semantic, morphological and syntactic violations. Cognitive Brain Research 1 3 (1993) 183-192
17. Fuster J.M. Network memory. Trends in Neurosciences 20 10 (1997) 451-459
18. Fuster J.M. Cortex and mind: Unifying cognition (2003), Oxford University Press, Oxford
19. Garagnani M., Wennekers T., and Pulvermüller F. A neuronal model of the language cortex. Neurocomputing 70 (2007) 1914-1919
20. Garagnani M., Wennekers T., and Pulvermüller F. A neuroanatomically-grounded Hebbian learning model of attention-language interactions in the human brain. European Journal of Neuroscience 27 2 (2008) 492-513
21. Gayler, R. W. (2003). Vector Symbolic Architectures answer Jackendoff's challenges for cognitive neuroscience. Paper presented at the Joint International Conference on Cognitive Science, University of New South Wales, Sydney, Australia
22. Gayler R.W. Vector symbolic architectures are a viable alternative for Jackendoff's challenges. Behavioral and Brain Sciences 29 1 (2006) 78-+
23. Gutig R., Aharonov R., Rotter S., and Sompolinsky H. Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity. Journal of Neuroscience 23 9 (2003) 3697-3714
24. Hanson S.J., and Negishi M. On the emergence of rules in neural networks. Neural Computation 14 9 (2002) 2245-2268
25. Harris Z.S. Structural linguistics (1951), Chicago University Press, Chicago
26. Hasting A.S., Kotz S.A., and Friederici A.D. Setting the stage for automatic syntax processing: The mismatch negativity as an indicator of syntactic priming. Journal of Cognitive Neuroscience 19 3 (2007) 386-400
27. Hayon G., Abeles M., and Lehmann D. A model for representing the dynamics of a system of synfire chains. Journal of Computational Neuroscience 18 1 (2005) 41-53
28. Hebb D.O. The organization of behavior: A neuropsychological theory (1949), John Wiley, New York
29. Hecht-Nielsen R. Cogent confabulation. Neural Networks 18 2 (2005) 111-115
30. Hecht-Nielsen R. Confabulation theory (2007), Springer-Verlag, New York
31. Hinton G.E. Mapping part-whole hierarchies into connectionist networks. Artificial Intelligence 46 1-2 (1990) 47-75
32. Honkela, T., Hyvärinen, A., & Väyrynen, J. (2005). Emergence of Linguistic Features: Independent Component Analysis of Contexts. In A. Cangelosi (Ed.), Proceedings of NCPW9, neural computation and psychology workshop (in press)
33. Honkela, T., Pulkki, V., & Kohonen, T. (1995). Contextual relations of words in grimm tales analyzed by self-organizing map. proceedings of international conference on artificial neural networks. In F. Fogelman-Soulie' & P. Gallinari (Eds.), Proceedings of the international conference on neural networks (ICANN)(pp. 3-7)
34. Hubel D. Eye, brain, and vision. 2 ed. (1995), Scientific American Library, New York
35. Jacobs B., Batal H.A., Lynch B., Ojemann G., Ojemann L.M., and Scheibel A.B. Quantitative dendritic and spine analyses of speech cortices: A case study. Brain and Language 44 (1993) 239-253
36. Jacobs B., Schall M., and Scheibel A.B. A quantitative dendritic analysis of Wernicke's area in humans: II. gender, hemispheric, and environmental factors. Journal of Comparative Neurology 327 (1993) 97-111
37. Kanerva P. The spatter code for encoding concepts at many levels. In: Marinaro M., and Morasso P.G. (Eds). ICANN '94, Proceedings of the International Conference On Neural Networks (1993), Springer Verlag, New York 226-229
38. Knoblauch, A. (2003). Synchronization and pattern separation in spiking associative memory and visual cortical areas, University of Ulm, Germany, Ulm
39. Knoblauch A., and Palm G. Pattern separation and synchronization in spiking associative memories and visual areas. Neural Networks 14 6-7 (2001) 763-780
40. Knoblauch A., and Pulvermüller F. Sequence detector networks and associative learning of grammatical categories. In: Wermter S., Palm G., and Elshaw M. (Eds). Biomimetic neural learning for intelligent robots (2005), Springer, Berlin 31-53
41. Lin, D. (1998). Automatic retrieval and clustering of similar words. In Proceedings of the 17th international conference on computational linguistics and 36th annual meeting of the association for computational linguistics (pp. 768-773) Vol. 17
42. Markram H., Toledo-Rodriguez M., Wang Y., Gupta A., Silberberg G., and Wu C. Interneurons of the neocortical inhibitory system. Nature Reviews Neuroscience 5 10 (2004) 793-807
43. McClelland J.L., and Patterson K. Rules or connections in past-tense inflections: What does the evidence rule out?. Trends in Cognitive Science 6 11 (2002) 465-472
44. Neville H., Nicol J.L., Barss A., Forster K.I., and Garrett M.F. Syntactically based sentence processing classes: Evidence from event-related brain potentials. Journal of Cognitive Neuroscience 3 (1991) 151-165
45. O'Reilly R.C. Generalization in interactive networks: the benefits of inhibitory competition and Hebbian learning. Neural Computation 13 6 (2001) 1199-1241
46. Palm G. On associative memory. Biological Cybernetics 36 1 (1980) 19-31
47. Palm G. Neural assemblies (1982), Springer, Berlin
48. Palm G., and Sommer F.T. Associative data storage and retrieval in neural networks. In: Domany E., van Hemmen J.L., and Schulten K. (Eds). Models of neural networks III (1995), Springer Verlag, New York 79-118
49. Pandya D.N., and Yeterian E.H. Architecture and connections of cortical association areas. In: Peters A., and Jones E.G. (Eds). Cerebral cortex. Vol. 4. Association and auditory cortices (1985), Plenum Press, London 3-61
50. Pickering M.J., and Branigan H.P. Syntactic priming in language production. Trends in Cognitive Sciences 3 (1999) 136-141
51. Pinker S. Language, learnability and language development (1984), Harvard University Press, Cambridge, MA
52. Pinker S. The language instinct. How the mind creates language (1994), Harper Collins Publishers, New York
53. Plate T.A. Holographic reduced representations: Distributed representations for cognitive structures (2003), CSLI Publications, Stanford, CA
54. Prince A., and Smolensky P. Optimality: from neural networks to universal grammar. Science 275 (1997) 1604-1610
55. Pulvermüller F. On connecting syntax and the brain. In: Aertsen A. (Ed). Brain theory-Spatio-temporal aspects of brain function (1993), Elsevier, New York 131-145
56. Pulvermüller F. Words in the brain's language. Behavioral and Brain Sciences 22 (1999) 253-336
57. Pulvermüller F. Brain reflections of words and their meaning. Trends in Cognitive Sciences 5 12 (2001) 517-524
58. Pulvermüller F. A brain perspective on language mechanisms: From discrete neuronal ensembles to serial order. Progress in Neurobiology 67 (2002) 85-111
59. Pulvermüller F. The neuroscience of language (2003), Cambridge University Press, Cambridge
60. Pulvermüller F. Sequence detectors as a basis of grammar in the brain. Theory in Biosciences 122 (2003) 87-103
61. Pulvermüller F., and Assadollahi R. Grammar or serial order?: Discrete combinatorial brain mechanisms reflected by the syntactic mismatch negativity. Journal of Cognitive Neuroscience 19 6 (2007) 971-980
62. Pulvermüller F., and Shtyrov Y. Automatic processing of grammar in the human brain as revealed by the mismatch negativity. Neuroimage 20 (2003) 159-172
63. Reichardt W., and Varju D. Übertragungseigenschaften im Auswertesystem für das Bewegungssehen. Zeitschrift für Naturforschung 14b (1959) 674-689
64. Rilling J.K., Glasser M.F., Preuss T.M., Ma X., Zhao T., Hu X., et al. The evolution of the arcuate fasciculus revealed with comparative DTI. Nature Neuroscience 11 4 (2008) 426-428
65. Rumelhart D.E., and McClelland J.L. Learning the past tense of English verbs: implicit rules or parallel distributed processing. In: MacWhinney B. (Ed). Mechanisms of language acquisition (1987), Erlbaum, Hillsdale, NJ
66. Saur D., Kreher B.W., Schnell S., Kummerer D., Kellmeyer P., Vry M.S., et al. Ventral and dorsal pathways for language. Proceedings of the National Academy of Sciences USA 105 46 (2008) 18035-18040
67. Schnelle H. Approaches to computational brain theories of language-A review of recent proposals. Theoretical Linguistics 22 (1996) 49-104
68. Schnelle H. Die Natur der Sprache. Die Dynamik der Prozesse des Sprechens und Verstehens. 2 ed. (1996), Walter de Gruyter, Berlin, New York
69. Seidenberg M.S., and Elman J.L. Networks are not 'hidden rules'. Trends in Cognitive Science 3 8 (1999) 288-289
70. Shtyrov Y., Pihko E., and Pulvermüller F. Determinants of dominance: Is language laterality explained by physical or linguistic features of speech?. Neuroimage 27 1 (2005) 37-47
71. Shtyrov Y., Pulvermüller F., Näätänen R., and Ilmoniemi R.J. Grammar processing outside the focus of attention: An MEG study. Journal of Cognitive Neuroscience 15 8 (2003) 1195-1206
72. Smolensky P. Tensor product variable binding and the representation of symbolic structures in connectionist systems. Artificial Intelligence 46 1-2 (1990) 159-216
73. Smolensky P. Grammar-based connectionist approaches to language. Cognitive Science 23 4 (1999) 589-613
74. Sommer F.T., and Wennekers T. Models of distributed associative memory networks in the brain. Theory in Biosciences 122 1 (2003) 55-69
75. Steedman M. The syntactic process (2000), MIT Press, Cambridge, MA
76. Tesnière L. Esquisse d'une syntax structurale (1953), Klincksieck, Paris
77. Tesnière L. Eléments de syntaxe structurale (1959), Klincksieck, Paris
78. Tsumoto T. Long-term potentiation and long-term depression in the neocortex. Progress in Neurobiology 39 (1992) 209-228
79. van der Velde F., and de Kamps M. Neural blackboard architectures of combinatorial structures in cognition. Behavioral and Brain Sciences 29 1 (2006) 37-70 discussion 70-108
80. Wennekers T., Garagnani M., and Pulvermüller F. Language models based on Hebbian cell assemblies. Journal de Physiologie (Paris) 100 (2006) 16-30
81. Wermter S., Weber C., Elshaw M., Panchev C., Erwin H., and Pulvermüller F. Towards multimodal neural network robot learning. Robotics and Autonomous Systems 47 (2004) 171-175
82. Willshaw D., and Dayan P. Optimal plasticity from matrix memories: What goes up must come down. Neural Computation 2 (1990) 85-93
83. Willshaw D.J., Buneman O.P., and Longuet-Higgins H.C. Non-holographic associative memory. Nature 222 197 (1969) 960-962
84. Young M.P., Scannell J.W., and Burns G. The analysis of cortical connectivity (1995), Springer, Heidelberg
85. Young M.P., Scannell J.W., Burns G., and Blakemore C. Analysis of connectivity: neural systems in the cerebral cortex. Review in Neuroscience 5 (1994) 227-249
86. Zipser D., Kehoe B., Littlewort G., and Fuster J. A spiking network model of short-term active memory. Journal of Neuroscience 13 8 (1993) 3406-3420