A Neural Model of Object Naming

Authors: Alessio Plebe

Abstract:

One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.

Keywords: Auditory cortex, object recognition, self-organizingmaps

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1077581

References:

[1] I. Akirav and M. Maroun. Ventromedial prefrontal cortex is obligatory for consolidation and reconsolidation of object recognition memory. Cerebral Cortex, 16:1759-1765, 2006.
[2] M. Atzori, S. Lei, D. I. P. Evans, P. O. Kanold, E. Phillips-Tansey, O. McIntyre, and C. J. McBain. Differential synaptic processing separates stationary from transient inputs to the auditory cortex. Neural Networks, 4:1230-1237, 2001.
[3] J. A. Bednar. Learning to See: Genetic and Environmental Influences on Visual Development. PhD thesis, University of Texas at Austin, 2002. Tech Report AI-TR-02-294.
[4] P. Belin, R. J. Zatorre, and P. Ahad. Human temporal-lobe response to vocal sounds. Cognitive Brain Research, 13:17-26, 2002.
[5] A. W. Black and P. A. Taylor. The festival speech synthesis system: System documentation. Technical Report HCRC/TR- 83, Human Communciation Research Centre, University of Edinburgh, Edinburgh, UK, 1997.
[6] G. G. Blasdel. Orientation selectivity, preference, and continuity in monkey striate cortex. Journal of Neuroscience, 12:3139- 3161, 1992.
[7] A. A. Brewer, J. Liu, A. R. Wade, and B. A. Wandell. Visual field maps and stimulus selectivity in human ventral occipital cortex. Nature Neuroscience, 8:1102-1109, 2005.
[8] J. L. Dannemiller. A test of color constancy in 9- and 20-weeks-old human infants following simulated illuminant changes. Developmental Psychology, 25:171-184, 1989.
[9] G. Deco and E. Rolls. A neurodynamical cortical model of visual attention and invariant object recognition. Vision Research, 44:621-642, 2004.
[10] S. Edelman and S. Duvdevani-Bar. A model of visual recognition and categorization. Philosophical transactions of the Royal Society of London, 352:1191-1202, 1997.
[11] M. A. Escabi and H. L. Read. Representation of spectrotemporal sound information in the ascending auditory pathway. Biological Cybernetics, 89:350-362, 2003.
[12] D. J. Freedman, M. Riesenhuber, T. Poggio, and E. K. Miller. Categorical representation of visual stimuli in the primate prefrontal cortex. Science, 291:312-316, 2001.
[13] L. Gershkoff-Stowe and L. B. Smith. Shape and the first hundred nouns. Child Development, 75:1098-1114, 2004.
[14] K. Grill-Spector, Z. Kourtzi, and N. Kanwisher. The lateral occipital complex and its role in object recognition. Vision Research, 41:1409-1422, 2001.
[15] M. Ito and H. Komatsu. Representation of angles embedded within contour stimuli in area V2 of macaque monkeys. Journal of Neuroscience, 24:3313-3324, 2004.
[16] N. Kanwisher. The ventral visual object pathway in humans: Evidence from fMRI. In L. Chalupa and J. Werner, editors, The Visual Neurosciences. MIT Press, Cambridge (MA), 2003.
[17] L. C. Katz and E. M. Callaway. Development of local circuits in mammalian visual cortex. Science, 255:209-212, 1992.
[18] A. Kirkwood and M. F. Bear. Hebbian synapses in visual cortex. Journal of Neuroscience, 14:1634-1645, 1994.
[19] T. Kohonen. Self-Organizing Maps. Springer-Verlag, Berlin, 1995.
[20] B. Landau, L. B. Smith, and S. Jones. Syntactic context and the shape bias in children-s and adults- lexical learning. Journal of Memory and Language, 31:807-825, 1992.
[21] D. R. Langers, W. H. Bacjes, and P. van Dijk. Representation of lateralization and tonotopy in primary versus secondary human auditory cortex. NeuroImage, 34:264-273, 2007.
[22] J. F. Linden and C. E. Schreiner. Columnar transformations in auditory cortex? a comparison to visual and somatosensory cortices. Cerebral Cortex, 13:83-89, 2006.
[23] S. L¨owel and W. Singer. Experience-dependent plasticity of intracortical connections. In M. Fahle and T. Poggio, editors, Perceptual Learning. MIT Press, Cambridge (MA), 2002.
[24] R. Malach, J. B. Reppas, R. R. Benson, K. K. Kwong, H. Jiang, W. A. Kennedy, P. J. Ledden, T. J. Brady, B. R. Rosen, and R. B. Tootell. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Proceedings of the Natural Academy of Science USA, 92:8135-8139, 1995.
[25] M. Mjdan and C. J. Shatz. Effects of visual experience on activity-dependent gene regulation in cortex. Neural Networks, 9:650-659, 2006.
[26] H. Murase and S. Nayar. Visual learning and recognition of 3-d object by appearence. International Journal of Computer Vision, 14:5-24, 1995.
[27] C. N¨ager, J. Storck, and G. Deco. Speech recognition with spiking neurons and dynamic synapses: a model motivated by the human auditory pathway. Neurocomputing, 44-46:937-942, 2002.
[28] A. Plebe. Learning visual invariance. In M. Verleysen, editor, ESANN 2006 - 14th European Symposium on Artificial Neural Networks, pages 71-76, Evere (BE), 2006. d-side Publications.
[29] A. Plebe. A model of angle selectivity development in visual area v2. Neurocomputing, in press.
[30] A. Plebe and R. G. Domenella. The emergence of visual object recognition. In W. Duch, J. Kacprzyk, E. Oja, and S. Zadrony, editors, Artificial Neural Networks - ICANN 2005 15th International Conference, Warsaw, pages 507-512, Berlin, 2005. Springer-Verlag.
[31] A. Plebe and R. G. Domenella. Early development of visual recognition. Bio Systems, 86:63-74, 2006.
[32] S. R. Quartz. Innateness and the brain. Biology and Philosophy, 18:13-40, 2003.
[33] M. Riesenhuber and T. Poggio. Models of object recognition. Nature Neuroscience, 3:1199-1204, 2000.
[34] D. Roy and A. Pentland. Learning words from sights and sounds: a computational model. Cognitive Science, 26:113-146, 2002.
[35] F. Sengpiel and P. C. Kind. The role of activity in development of the visual system. Current Biology, 12:818-826, 2002.
[36] J. Sirosh and R. Miikkulainen. Topographic receptive fields and patterned lateral interaction in a self-organizing model of the primary visual cortex. Neural Computation, 9:577-594, 1997.
[37] W. Vanduffel, R. B. Tootell, A. A. Schoups, and G. A. Orban. The organization of orientation selectivity throughout the macaque visual cortex. Cerebral Cortex, 12:647-662, 2002.
[38] C. Verkindt, O. Bertrand, F. Echallier, and J. Pernier. Tonotopic organization of the human auditory cortex: N100 topography and multiple dipole model analysis. Electroencephalography and Clinical Neurophisiology, 96:143-156, 1995.
[39] M. Volkmer. A pulsed neural network model of spectrotemporal receptive fileds and population coding in auditory cortex. Neural Computing, 3:177-193, 2004.