Modelling of syntactical processing in the cortex

BioSystems

Volumn 89, Issue 1-3, 2007, Pages 300-315

  Markert, Heiner ^a   Knoblauch, Andreas ^b   Palm, Günther ^a  

^a UNIVERSITY OF ULM   (Germany)

^b HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

Distributed representation; Global brain modelling; Language understanding; Neural assemblies; Sparse patterns; Spiking associative memory

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BRAIN; LANGUAGE; MEMORY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AWARENESS; BRAIN CORTEX; LANGUAGE PROCESSING; LOGIC; NERVE CONDUCTION; TASK PERFORMANCE; THEORETICAL MODEL;

ANIMALIA;

EID: 34247600666     PISSN: 03032647     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystems.2006.04.027     Document Type: Article

References (76)

1. Abeles M. Corticonics: Neural Circuits of the Cerebral Cortex (1991), Cambridge University Press, Cambridge, UK
2. Abeles M., Bergman H., Margalit E., and Vaadia E. Spatio-temporal firing patterns in frontal cortex of behaving monkeys. J. Neurophysiol. 70 (1993) 1629-1643
3. Ajjanagadde V., and Shastri L. Rules and variables in neural nets. Neural Comput. 3 (1991) 121-134
4. Alon N., Dewdney A., and Ott T.J. Efficient simulation of finite automata by neural nets. J. ACM 38 2 (1991) 495-514
5. Alquézar R., and Sanfeliu A. An algebraic framework to represent finite state machines in single-layer recurrent networks. Neural Comput. 7 5 (1996) 931-949
6. Arbib M.A., Billard A., Iacoboni M., and Oztop E. Synthetic brain imaging: grasping, mirror neurons and imitation. Neural Networks 13 8/9 (2000) 975-997
7. Arbib M.A., Fagg A.H., and Grafton S.T. Synthetic PET imaging for grasping: from primate neurophysiology to human behavior. In: Sommer F.T., and Wichert A. (Eds). Exploratory Analysis and Data Modelling in Functional Neuroimaging (2002), MIT Press, Boston, MA
8. Arbib M.A. The Handbook of Brain Theory and Neural Networks. 2nd ed. (2003), MIT Press, Cambridge, MA
9. Bienenstock E. Composition. In: Aertsen A., and Braitenberg V. (Eds). Brain Theory. Biological Basis and Computational Principles (1996), Elsevier, Amsterdam
10. Billard A., and Hayes G. DRAMA, a connectionist architecture for control and learning in autonomous robots. Adapt. Behav. J. 7 1 (1999) 35-64
11. Braitenberg V. Cell assemblies in the cerebral cortex. In: Hein R., and Palm G. (Eds). Lecture Notes in Biomathematics (21). Theoretical Approaches to Complex Systems (1978), Springer, Berlin/Heidelberg/New York
12. Braitenberg V. On the Texture of Brains (1977), Springer, Berlin/Heidelberg/New York
13. Braitenberg V., and Schüz A. Anatomy of the Cortex. Statistics and Geometry (1991), Springer-Verlag, Berlin
14. Brooks R.A., and Stein L.A. Building brains for bodies. Auton. Robot. 1 (1994) 7-25
15. Dayan P., and Abbot L.F. Theoretical Neuroscience (2001), MIT Press, Cambridge, MA
16. Diesmann M., Gewaltig M.O., and Aertsen A. Stable propagation of synchronous spiking in cortical neural networks. Nature 402 6761 (1999) 529-533
17. Eckhorn R., Bauer R., Jordan W., Brosch M., Kruse W., Munk M., and Reitboeck H.J. Coherent oscillations: a mechanism of feature linking in the visual cortex?. Biol. Cybern. 60 (1988) 121-130
18. Elman J.L. Finding structure in time. Cognitive Sci. 14 (1990) 179-211
19. Fay R., Kaufmann U., Knoblauch A., Markert H., and Palm G. Combining visual attention, object recognition and associative information processing in a neurobotic system. In: Wermter S., Palm G., and Elshaw M. (Eds). Biomimetic Neural Learning for Intelligent Robots (2004), Springer, Berlin/Heidelberg/New York
20. Fodor J.A., and Pylyshyn Z.W. Connectionism and cognitive architecture: a critical analysis. Cognition 28 (1988) 3-71
21. Frasconi P., Gori M., Maggini M., and Soda G. Representation of finite state automata in recurrent radial basis function networks. Mach. Learn. 23 1 (1996) 5-32
22. Giles L., and Gori M. Adaptive Processing of Sequences and Data Structures (1998), Springer, Heidelberg/New York
23. Giles C.L., and Omlin Ch.W. Extraction, insertion and refinement of symbolic rules in dynamically driven recurrent networks. Connect. Sci. 5 (1993) 307-337
24. Goonatikale S., and Khebbal S. Intelligent Hybrid Systems (1995), John Wiley and Sons Ltd.
25. Gori, M., Maggini, M., Soda, G., 1995. Learning Regular Grammars From Noisy Examples Using Recurrent Neural Networks Technical Report. Dipartimento di Sistemi e Informatica, Universita di Firenze.
26. Gori M., Küchler A., and Sperduti A. On the implementation of frontier-to-root tree automata in recursive neural networks. IEEE Trans. Neural Networks 10 6 (1999) 1305-1314
27. Grossberg S., and Pessoa L. Texture segregation, surface representation, and figure-ground separation. Vision Res. 38 (1998) 2657-2684
28. Harnad S. The symbol grounding problem. Physica D 42 (1990) 335-346
29. Hebb D.O. The Organization of Behavior. A Neuropsychological Theory (1949), Wiley, New York
30. Hopcroft J., and Ullman J. Formal Languages and their Relation to Automata (1969), Addison-Wesley, Reading, MA
31. Horne B.G., and Hush D.R. Bounds on the complexity of recurrent neural network implementations of finite state machines. Neural Networks 9 2 (1996) 243-252
32. Horwitz B., Friston K.J., and Taylor J.G. Neural modeling and functional brain imaging: an overview. Neural Networks 13 (2000) 829-846
33. Ikegaya Y., Aaron G., Cossart R., Aronov D., Lampl I., Ferster D., and Yuste R. Synfire chains and cortical songs: temporal modules of cortical activity. Science 304 (2004) 559-564
34. Knoblauch, A., 2003. Synchronization and Pattern Separation in Spiking Associative Memory and Visual Cortical Areas. PhD Thesis. Department of Neural Information Processing, University of Ulm, Germany.
35. Knoblauch A., and Palm G. Pattern separation and synchronization in spiking associative memories and visual areas. Neural Networks 14 (2001) 763-780
36. Knoblauch A., and Palm G. Scene segmentation by spike synchronization in reciprocally connected visual areas. II: Global assemblies and synchronization on larger space and time scales. Biol. Cybern. 87 3 (2002) 168-184
37. Knoblauch, A., Fay, R., Kaufmann, U., Markert, H., Palm, G., 2004. Associating words to visually recognized objects. In: Coradeschi, S., Saffiotti, A. (Eds.), Anchoring Symbols to Sensor Data. Papers from the AAAI Workshop. Technical Report WS-04-03. AAAI Press, Menlo Park, CA.
38. Knoblauch A., Markert H., and Palm G. An associative cortical model of language understanding and action planning. In: Mira J., and Alvarez J.R. (Eds). Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach (2005), Springer, Berlin/Heidelberg/New York
39. Krichmar J.L., and Edelman G. Machine psychology: autonomous behavior, perceptual categorization and conditioning in a brain-based device. Cereb. Cortex 12 8 (2002) 818-830
40. Lapicque L. Recherches quantitatives sur l'excitation electrique des nerfs traitee comme une polarization. J. Physiol. Pathol. Gen. 9 (1907) 620-635
41. Lin L., Osan R., and Tsien J.Z. Organizing principles of real-time memory encoding: neural clique assemblies and universal neural codes. Trends Neurosci. 29 1 (2006) 48-57
42. Maass W., and Sontag E. Analog neural nets with gaussian or other common noise distribution cannot recognize arbitrary regular languages. Neural Comput. 11 (1999) 771-782
43. Markert H., Knoblauch A., and Palm G. Associative language processing in cortical areas. Proceedings of the IEEE SMC UK-RI Chapter Conference 2005 on Applied Cybernetics (2005)
44. Markert H., Knoblauch A., and Palm G. Detecting sequences and understanding language with neural associative memories and cell assemblies. In: Wermter S., Palm G., and Elshaw M. (Eds). Biomimetic Neural Learning for Intelligent Robots (2005), Springer, Heidelberg/New York
45. Marr D. Vision (1982), W.H. Freeman, New York
46. McKinstry J.L., Edelman G.M., and Kirchmar J.L. A cerebellar model for predictive motor control tested in a brain-based device. Proc. Natl. Acad. Sci. U.S.A. 103 (2006) 3387-3392
47. Miikkulainen R., and Bijwaard D. Parsing embedded clauses with distributed neural networks. Proceedings of the 12th National Conference on AI (AAAI'94) (1994), AAAI Press/MIT Press, Menlo Park, CA
48. Nilsson N.J. Artificial Intelligence: A New Synthesis (1998), Morgan Kaufmann, San Francisco
49. O'Reilly R.C., Braver T.S., and Cohen J.D. A biologically based computational model of working memory. In: Miyake A., and Shah P. (Eds). Models of Working Memory: Mechanisms of Active Maintenance and Executive Control (1999), Cambridge University Press, New York
50. Palm G. On associative memories. Biol. Cybern. 36 (1980) 19-31
51. Palm G. Neural Assemblies. An Alternative Approach to Artificial Intelligence (1982), Springer, Berlin
52. Palm G. Rules for synaptic changes and their relevance for the storage of information in the brain. Cybern. Syst. Res. (1982)
53. Palm G. Associative networks and cell assemblies. In: Palm G., and Aertsen A. (Eds). Brain Theory (1986), Springer, Berlin/Heidelberg
54. Palm G. Computing with neural networks. Science 235 (1987) 1227-1228
55. Palm G. Cell assemblies as a guideline for brain research. Concepts Neurosci. 1 (1990) 133-148
56. Palm, G., 1990. Local rules for synaptic modification in neural networks. J. Comput. Neurosci.
57. Palm G. Memory capacities of local rules for synaptic modification. A comparative review. Concepts Neurosci. 2 (1991) 97-128
58. Palm G. On the information storage capacity of local learning. Neural Comput. 4 (1992) 703-711
59. Palm G., and Sommer F.T. Information capacity in recurrent McCulloch-Pitts networks with sparsely coded memory states. Network 3 (1992) 177-186
60. Pulvermüller F. Words in the brain's language. Behav. Brain Sci. 22 (1999) 253-336
61. Pulvermüller F. The Neuroscience of Language: On Brain Circuits of Words and Serial Order (2002), Cambridge University Press, Cambridge, UK
62. Pulvermüller F. Sequence detectors as a basis of grammar in the brain. Theory Biosci. 122 (2003) 87-103
63. Rabiner L. A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77 (1989) 257-285
64. Rabiner L., and Juang B.H. Fundamentals of Speech Recognition (1993), Prentice Hall, Englewood Cliffs, NJ
65. Roy D. Learning visually grounded words and syntax for a scene description task. Comput. Speech Lang. 16 3 (2002) 353-385
66. Rumelhart D., and McClelland J. Parallel Distributed Processing (1986), MIT Press, Cambridge, MA
67. Shastri L., and Ajjanagadde V. From simple associations to systematic reasoning: a connectionistic representation of rules, variables and dynamic bindings. Behav. Brain Sci. 16 3 (1993) 417-494
68. Siegelmann H.T., and Giles C.L. The complexity of language recognition by neural networks. Neurocomputing 15 (1997) 327-345
69. Singer W., and Gray C.M. Visual feature integration and the temporal correlation hypothesis. Annu. Rev. Neurosci. 18 (1995) 555-586
70. Somers D.C., Nelson S.B., and Sur M. An emergent model of orientation selectivity in cat visual cortical simple cells. J. Neurosci. 15 (1995) 5448-5465
71. Steels L., and Brooks R. The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents (1995), Erlbaum, Hillsdale, NJ
72. Sun R., and Bookman L.A. Computational Architectures Integrating Neural and Symbolic Processing (1995), Kluwer Academic Publishers
73. Talmy L. Toward a Cognitive Semantics. vol. I: Conceptual Structuring Systems (2000), MIT Press, Cambridge, MA
74. von der Malsburg C. Am I thinking assemblies?. In: Palm G., and Aertsen A. (Eds). Brain Theory (1986), Springer, Berlin/Heidelberg
75. Wermter S. Hybrid Connectionist Natural Language Processing (1995), Chapman and Hall, London
76. Willshaw D.J., Buneman O.P., and Longuet-Higgins H.C. Non-holographic associative memory. Nature 222 (1969) 960-962