A cortical-type modular neural network for hypothetical reasoning

Neural Networks

Volumn 10, Issue 5, 1997, Pages 791-814

  Koerner, Edgar ^a   Tsujino, Hiroshi ^a   Masutani, Tomohiko ^a  

^a HONDA R AND D CO LTD   (Japan)

Author keywords

Analysis by synthesis; Hypothetical reasoning; Modular neural network; Object recognition; Recurrent network; Signal symbol processing; Visual cortex

Indexed keywords

COMPUTER SIMULATION; CONSTRAINT THEORY; LEARNING SYSTEMS; OBJECT RECOGNITION; SENSORY PERCEPTION;

CORTICAL TYPE MODULAR NEURAL NETWORKS; HYPOTHETICAL REASONING; NEUROCORTICAL COLUMNS;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; PRIORITY JOURNAL; RECOGNITION; REVIEW; VISUAL CORTEX;

EID: 0031193386     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(96)00126-8     Document Type: Article

References (25)

1. Adolphs, R., Tranel, D., Damasio, H., & Damasio, A. (1994). Impaired recognition of emotion in facial expressions following damage to the human amygdala. Nature, 372, 669-672.
2. Allison, J. D., Casagrande, V. A., & Bonds, A. B. (1995). The influence of input from the lower cortical layers on the orientation tuning of upper layer V1 cells in a primate. Visual Neuroscience, 12, 309-320.
3. Ando, H. (1996). 3D Object Recognition Using Bidirectional Modular Networks. In S. Z. Li, D. P. Mital, E. K. Teoh, H. Wang (Eds.), Recent Developments in Computer Vision, (ACCV'95) Invited Session Papers) (pp. 467-478). Berlin, Heidelberg, New York: Springer-Verlag.
4. Barlow, H. (1994). What is the computational goal of the neocortex?. In C. Koch & J.L. Davis (Eds.), Large-scale theories of the brain (pp. 1-22). Cambridge, MA: MIT Press.
5. Barnden, J.A. (1995). Artificial intelligence and neural networks. In M.A. Arbib (Ed.), The handbook of brain theory and neural networks (pp. 98-102). Cambridge, MA and London, England: MIT Press.
6. Brunelli, R., & Poggio, T. (1993). Face recognition: features versus templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15, 1042-1052.
7. Cauller, L. J., & Connors, B. W. (1994). Synaptic physiology of horizontal afferents to layer 1 in slices of rat SI cortex. Journal of Neuroscience, 14, 751-762.
8. Cavanagh, P. (1991). What's up in top-down processing? In A. Gorea (Ed.), Representations of vision (pp. 295-304). Cambridge, UK: Cambridge.
9. Celebrini, S., Thorpe, S., Trotter, Y., & Imbert, M. (1993). Dynamics of orientation coding in area VI of the awake primate. Visual Neuroscience, 10, 811-825.
10. Churchland, P., Ramachandran, V.S. & Sejnowski, T.J. (1994). A critique of pure vision. In C. Koch & J.L. Davis (Eds.), Large-scale neuronal theories of the brain (pp. 23-60). Cambridge, MA: MIT Press.
11. Davis, G., & Driver, J. (1994). Parallel detection of Kansiza subjective figures in the human visual system. Nature, 371, 791-793.
12. Dinse, H.R. (1994). A time-based approach towards cortical functions: neural mechanisms underlying dynamic aspects of information processing before and after postontogenetic plastic processes. Physica D, 75, 129-150.
13. Fahle, M., & Koch, C. (1995). Spatial displacement, but not temporal synchrony, destroys figural binding. Vision Research, 35, 491-494.
14. Felleman, D.J., & VanEssen, D.C. (1991). Distributed hierarchical processing in primate visual cortex. Cerebral Cortex, 1, 1-47.
15. Freeman, R.D. (1995). Space and time in the central visual pathways. Proceedings of 5th International Symposium on Bioelectronic and Molecular Electronic Devices, Okinawa, Japan, B1-01.
16. Fujita, I., & Fujita, T. (1996). Intrinsic connections in the macaque inferior temporal cortex. The Journal of Comparative Neurology, 368, 467-486.
17. Fukushima, K. (1986). A neural network model for selective attention in visual pattern recognition. Biological Cybernetics, 55, 5-15.
18. Gregory, R.L. (1995). Seeing backwards in time. Nature, 373, 21-22.
19. Grosof, D. H., Shapley, R. M., & Hawken, M. J. (1993). Macaque V1 neurons can signal "illusory" contours. Nature, 365, 550-552.
20. Hecht-Nielssen, R. (1995). Replicator neural networks for universal optimal source coding. Science, 269, 1860-1864.
21. Hernandez-Gonzales, A., Cavada, C., & Reinoso-Suarez, F. (1994). The lateral geniculate nucleus projects to the inferior temporal cortex in the macaque monkey. Neuro Report, 5, 2693-2696.
22. Hinton, G. (Ed.) (1991). Connectionist symbol processing. Cambridge, MA: MIT Press.
23. Jeannerod, M. (1995). Mental imagery in the motor context. Neuropsychologia, 33, 1419-1432.
24. Kawato, M., Hayakawa, H., & Inui, T. (1993). A forward-inverse optics model of reciprocal connections between visual cortical areas. Network, 4, 415-422.
25. Keele, S. W., Cohen, A., Ivry, R., Liotti, M., & Yee, P. (1988). Tests of temporal theory of attentional binding. Journal of Experimental Psychology, 14, 444-452.