Hierarchical models of object recognition in cortex

Thorpe, S. Fize, D. & Marlot., C. Speed of processing in the human visual system. Nature 381, 520–522 (1996).

Bruce, C., Desimone, R. & Gross, C. Visual properties of neurons in a polysensory area in the superior temporal sulcus of the macaque. J. Neurophysiol. 46, 369–384 (1981).

Ungerleider, L. & Haxby, J. 'What' and 'where' in the human brain. Curr. Opin. Neurobiol. 4, 157–165 (1994).

Hubel, D. & Wiesel, T. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J. Physiol. (Lond.) 160, 106–154 (1962).

Hubel, D. & Wiesel, T. Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. J. Neurophysiol. 28, 229–289 (1965).

Fukushima, K. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 36, 193–202 (1980).

Perrett, D. & Oram, M. Neurophysiology of shape processing. Imaging Vis. Comput. 11, 317–333 (1993).

Wallis, G. & Rolls, E. A model of invariant object recognition in the visual system. Prog. Neurobiol. 51, 167–194 (1997).

Anderson, C. & van Essen, D. Shifter circuits: a computational strategy for dynamic aspects of visual processing. Proc. Nat. Acad. Sci. USA 84, 6297–6301 (1987).

Olshausen, B., Anderson, C. & van Essen, D. A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. J. Neurosci. 13, 4700–4719 (1993).

Salinas, E. & Abbot, L. Invariant visual responses from attentional gain fields. J. Neurophysiol. 77, 3267–3272 (1997).

Riesenhuber, M. & Dayan, P. in Advances in Neural Information Processing Systems Vol. 9 (eds. Mozer, M, Jordan, M. & Petsche, T.) 17–23 (MIT Press, Cambridge, Massachusetts, 1997).

Moran, J. & Desimone, R. Selective attention gates visual processing in the extrastriate cortex. Science 229, 782–784 (1985).

Connor, C., Preddie, D., Gallant, J. & van Essen, D. Spatial attention effects in macaque area V4. J. Neurosci. 17, 3201–3214 (1997).

Poggio, T. & Edelman, S. A network that learns to recognize 3D objects. Nature 343, 263–266 (1990).

Bülthoff, H. & Edelman, S. Psychophysical support for a two-dimensional view interpolation theory of object recognition. Proc. Natl. Acad. Sci. USA 89, 60–64 (1992).

Logothetis, N., Pauls, J., Bülthoff, H. & Poggio, T. Shape representation in the inferior temporal cortex of monkeys. Curr. Biol. 4, 401–414 (1994).

Tarr, M. Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonom. Bull. Rev. 2, 55–82 (1995).

Booth, M. and Rolls, E. View-invariant representations of familiar objects by neurons in the inferior temporal visual cortex. Cereb. Cortex 8, 510–523 (1998).

Kobatake, E., Wang, G. & Tanaka, K. Effects of shape-discrimination training on the selectivity of inferotemporal cells in adult monkeys. J. Neurophysiol. 80, 324–330 (1998).

Logothetis, N., Pauls, J. & Poggio, T. Shape representation in the inferior temporal cortex of monkeys. Curr. Biol. 5, 552–563 (1995).

Perrett, D. et al. Viewer-centred and object-centred coding of heads in the macaque temporal cortex. Exp. Brain Res. 86, 159–173 (1991).

Missal, M., Vogels, R. & Orban, G. Responses of macaque inferior temporal neurons to overlapping shapes. Cereb. Cortex 7, 758–767 (1997).

Sato, T. Interactions of visual stimuli in the receptive fields of inferior temporal neurons in awake monkeys. Exp. Brain Res. 77, 23–30 (1989).

Riesenhuber, M. & Poggio, T. in Advances in Neural Information Processing Systems Vol. 10 (eds. Jordan, M., Kearns, M. & Solla, S.) 215–221 (MIT Press, Cambridge, Massachusetts, 1998).

Wang, G., Tanifuji, M. & Tanaka, K. Functional architecture in monkey inferotemporal cortex revealed by in vivo optical imaging. Neurosci. Res. 32, 33–46 (1998).

Logothetis, N. Object vision and visual awareness. Curr. Opin. Neurobiol. 8, 536–544 (1998).

Riesenhuber, M & Poggio, T. Are cortical models really bound by the "binding problem"? Neuron 24, 87–93 (1999).

Rolls, E. & Tovee, M. The responses of single neurons in the temporal visual cortical areas of the macaque when more than one stimulus is present in the receptive field. Exp. Brain Res. 103, 409–420 (1995).

Vogels, R. Categorization of complex visual images by rhesus monkeys. Part 2: single-cell study. Eur. J. Neurosci. 11, 1239–1255 (1999).

Rowley, H., Baluja, S. & Kanade, T. Neural network-based face detection. IEEE PAMI 20, 23–38 (1998).

Sung, K. & Poggio, T. Example-based learning for view-based human face detection. IEEE PAMI 20, 39–51 (1998).

Koch, C. & Ullman, S. Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurobiol. 4, 219–227 (1985).

Abbot, L., Varela, J., Sen, K. & Nelson, S. Synaptic depression and cortical gain control. Science 275, 220–224 (1997).

Grossberg, S. Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Net. 1, 17–61 (1988).

Chance, F., Nelson, S. & Abbott, L. Complex cells as cortically amplified simple cells. Nat. Neurosci. 2, 277–282 (1999).

Douglas, R., Koch, C. Mahowald, M., Martin, K. & Suarez, H. Recurrent excitation in neocortical circuits. Science 269, 981–985 (1995).

Reichardt, W., Poggio, T. & Hausen, K. Figure–ground discrimination by relative movement it the visual system of the fly – II: towards the neural circuitry. Biol. Cybern. 46, 1–30 (1983).

Lee, D., Itti, L., Koch, C. & Braun, J. Attention activates winner-take-all competition among visual filters. Nat. Neurosci. 2, 375–381 (1999).

Heeger, D. Normalization of cell responses in cat striate cortex. Vis. Neurosci. 9, 181–197 (1992).

Nowlan, S. & Sejnowski, T. A selection model for motion processing in area MT of primates. J. Neurosci. 15, 1195–1214 (1995).

Mumford, D. On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biol. Cybern. 66, 241–251 (1992).

Rao, R. & Ballard, D. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2, 79–87 (1999).

Reynolds, J., Chelazzi, L. & Desimone, R. Competitive mechanisms subserve attention in macaque areas V2 and V4. J. Neurosci. 19, 1736–1753 (1999).

Mel, B. SEEMORE: combining color, shape, and texture histogramming in a neurally inspired approach to visual object recognition. Neural Comput. 9, 777–804 (1997).

Kobatake, E. & Tanaka, K. Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. J. Neurophysiol. 71, 856–867 (1994).

Földiák, P. Learning invariance from transformation sequences. Neural Comput. 3, 194–200 (1991).