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Volumn 18, Issue 3, 2007, Pages 249-266

Hebbian learning in a model with dynamic rate-coded neurons: An alternative to the generative model approach for learning receptive fields from natural scenes

Author keywords

Attention; Natural scenes; Network models; Visual system

Indexed keywords

ANIMAL; BIOLOGICAL MODEL; CONFERENCE PAPER; HUMAN; LEARNING; METHODOLOGY; NATURAL SCIENCE; NERVE CELL; NONLINEAR SYSTEM; PHOTOSTIMULATION; PHYSIOLOGY; PSYCHOLOGICAL MODEL; VISION; VISUAL SYSTEM;

EID: 35148823957     PISSN: 0954898X     EISSN: 13616536     Source Type: Journal    
DOI: 10.1080/09548980701661210     Document Type: Conference Paper
Times cited : (7)

References (47)
  • 1
    • 0000302918 scopus 로고
    • Towards a theory of early visual processing
    • Atick JJ, Redlich A. 1990. Towards a theory of early visual processing. Neural Comput 2:308-320.
    • (1990) Neural Comput , vol.2 , pp. 308-320
    • Atick, J.J.1    Redlich, A.2
  • 2
    • 33646826830 scopus 로고    scopus 로고
    • Changes in visual receptive fields with microstimulation of frontal cortex
    • Armstrong KM, Fitzgerald JK, Moore T. 2006. Changes in visual receptive fields with microstimulation of frontal cortex. Neuron 50:791-798.
    • (2006) Neuron , vol.50 , pp. 791-798
    • Armstrong, K.M.1    Fitzgerald, J.K.2    Moore, T.3
  • 4
    • 0043264798 scopus 로고    scopus 로고
    • Redundancy reduction revisited
    • Barlow HB. 1998. Redundancy reduction revisited. Network 12:241-253.
    • (1998) Network , vol.12 , pp. 241-253
    • Barlow, H.B.1
  • 5
    • 4344700748 scopus 로고    scopus 로고
    • Disambiguating visual motion through contextual feedback modulation
    • Bayerl P, Neumann H. 2004. Disambiguating visual motion through contextual feedback modulation. Neural Comput 16:2041-2066.
    • (2004) Neural Comput , vol.16 , pp. 2041-2066
    • Bayerl, P.1    Neumann, H.2
  • 6
    • 0030832881 scopus 로고    scopus 로고
    • The 'independent components' of natural scenes are edge filters
    • Bell AJ, Sejnowski TJ. 1997. The 'independent components' of natural scenes are edge filters. Vis Res 37:3327-3338.
    • (1997) Vis Res , vol.37 , pp. 3327-3338
    • Bell, A.J.1    Sejnowski, T.J.2
  • 7
    • 0035783251 scopus 로고    scopus 로고
    • The role of feedback connections in shaping the responses of visual cortical neurons
    • Bullier J, Hupe JM, James AC, Girard P. 2001. The role of feedback connections in shaping the responses of visual cortical neurons. Prog Brain Res 134:193-204.
    • (2001) Prog Brain Res , vol.134 , pp. 193-204
    • Bullier, J.1    Hupe, J.M.2    James, A.C.3    Girard, P.4
  • 8
    • 3843090696 scopus 로고    scopus 로고
    • Natural stimulus statistics alter the receptive field structure of v1 neurons
    • David SV, Vinje WE, Gallant JL. 2004. Natural stimulus statistics alter the receptive field structure of v1 neurons. J Neurosci 24:6991-7006.
    • (2004) J Neurosci , vol.24 , pp. 6991-7006
    • David, S.V.1    Vinje, W.E.2    Gallant, J.L.3
  • 9
    • 0001219231 scopus 로고
    • Feature linking via synchronisation among distributed assemblies: Simulations of results from Cat Visual Cortex
    • Eckhorn R, Reitboeck E, Arndt M, Dicke P. 1990. Feature linking via synchronisation among distributed assemblies: Simulations of results from Cat Visual Cortex. Neural Comput 2:293-307.
    • (1990) Neural Comput , vol.2 , pp. 293-307
    • Eckhorn, R.1    Reitboeck, E.2    Arndt, M.3    Dicke, P.4
  • 10
    • 33644887746 scopus 로고    scopus 로고
    • A simple Hebbian/anti-Hebbian network learns the sparse, independent components of natural images
    • Falconbridge MS, Stamps RL, Badcock DR. 2006. A simple Hebbian/anti-Hebbian network learns the sparse, independent components of natural images. Neural Comput 18:415-429.
    • (2006) Neural Comput , vol.18 , pp. 415-429
    • Falconbridge, M.S.1    Stamps, R.L.2    Badcock, D.R.3
  • 11
    • 0018861680 scopus 로고
    • How does the brain build a cognitive code?
    • Grossberg S. 1980. How does the brain build a cognitive code? Psychol Rev 87:1-51.
    • (1980) Psychol Rev , vol.87 , pp. 1-51
    • Grossberg, S.1
  • 12
    • 0346219339 scopus 로고    scopus 로고
    • A dynamic model of how feature cues guide spatial attention
    • Hamker FH. 2004. A dynamic model of how feature cues guide spatial attention. Vision Res 44:501-521.
    • (2004) Vision Res , vol.44 , pp. 501-521
    • Hamker, F.H.1
  • 13
    • 15244362261 scopus 로고    scopus 로고
    • The reentry hypothesis: The putative interaction of the frontal eye field, ventrolateral prefrontal cortex, and areas V4, IT for attention and eye movement
    • Hamker FH. 2005. The reentry hypothesis: The putative interaction of the frontal eye field, ventrolateral prefrontal cortex, and areas V4, IT for attention and eye movement. Cereb Cortex 15:431-447.
    • (2005) Cereb Cortex , vol.15 , pp. 431-447
    • Hamker, F.H.1
  • 14
    • 33749056140 scopus 로고    scopus 로고
    • Modeling feature-based attention as an active top-down inference process
    • Hamker FH. 2006. Modeling feature-based attention as an active top-down inference process. BioSystems 86:91-99.
    • (2006) BioSystems , vol.86 , pp. 91-99
    • Hamker, F.H.1
  • 15
    • 35148819428 scopus 로고    scopus 로고
    • The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making
    • Hamker FH. 2007. The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making. Adv Cogn Psychol 3:111-123.
    • (2007) Adv Cogn Psychol , vol.3 , pp. 111-123
    • Hamker, F.H.1
  • 17
    • 0000852458 scopus 로고    scopus 로고
    • Development of low entropy coding in a recurrent network
    • Harpur G, Prager R. 1996. Development of low entropy coding in a recurrent network. Network: Comput Neural Syst 7:277-284.
    • (1996) Network: Comput Neural Syst , vol.7 , pp. 277-284
    • Harpur, G.1    Prager, R.2
  • 18
    • 0037780988 scopus 로고    scopus 로고
    • Modeling receptive fields with non-negative sparse coding
    • Hoyer PO. 2003. Modeling receptive fields with non-negative sparse coding. Neurocomputing 52-54:547-552.
    • (2003) Neurocomputing , vol.52-54 , pp. 547-552
    • Hoyer, P.O.1
  • 19
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • Hoyer PO. 2004. Non-negative matrix factorization with sparseness constraints. J Mach Learn Res 5:1457-1469.
    • (2004) J Mach Learn Res , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 20
    • 0036284161 scopus 로고    scopus 로고
    • A multi-layer sparse coding network learns contour coding from natural images
    • Hoyer PO, Hyvärinen A. 2002. A multi-layer sparse coding network learns contour coding from natural images. Vision Res 42:1593-1605.
    • (2002) Vision Res , vol.42 , pp. 1593-1605
    • Hoyer, P.O.1    Hyvärinen, A.2
  • 22
    • 0347517574 scopus 로고    scopus 로고
    • Learning higher-order structures in natural images
    • Karklin Y, Lewicki MS. 2003. Learning higher-order structures in natural images. Network 14:483-499.
    • (2003) Network , vol.14 , pp. 483-499
    • Karklin, Y.1    Lewicki, M.S.2
  • 23
    • 0034333184 scopus 로고    scopus 로고
    • The distinct modes of vision offered by feedforward and recurrent processing
    • Lammé VAF, Roelfsema PR. 2000. The distinct modes of vision offered by feedforward and recurrent processing. Trend Neurosci 23:571-579.
    • (2000) Trend Neurosci , vol.23 , pp. 571-579
    • Lammé, V.A.F.1    Roelfsema, P.R.2
  • 24
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee DD, Seung HS. 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401:788-791.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 25
    • 0001518291 scopus 로고
    • Towards a theory of striate cortex
    • Li Z, Atick JJ. 1994. Towards a theory of striate cortex. Neural Comput 6:127-146.
    • (1994) Neural Comput , vol.6 , pp. 127-146
    • Li, Z.1    Atick, J.J.2
  • 26
    • 0009381628 scopus 로고
    • From basic network principles to neural architecture: Emergence of orientation-selective cells
    • Linsker R. 1986. From basic network principles to neural architecture: Emergence of orientation-selective cells. Proc Natl Acad Sci USA 83:8390-8394.
    • (1986) Proc Natl Acad Sci USA , vol.83 , pp. 8390-8394
    • Linsker, R.1
  • 27
    • 0000772267 scopus 로고
    • Nonlinear neurons in the low-noise limit: A factorial code maximizes information transfer
    • Nadal J-P, Parga N. 1994. Nonlinear neurons in the low-noise limit: A factorial code maximizes information transfer. Network: Comput Neural Sys 5:565-581.
    • (1994) Network: Comput Neural Sys , vol.5 , pp. 565-581
    • Nadal, J.-P.1    Parga, N.2
  • 28
    • 0036829081 scopus 로고    scopus 로고
    • Attention modulates responses in the human lateral geniculate nucleus
    • O'Connor DH, Fukui MM, Pinsk MA, Kastner S. 2002. Attention modulates responses in the human lateral geniculate nucleus. Nat Neurosci 5:1203-1209.
    • (2002) Nat Neurosci , vol.5 , pp. 1203-1209
    • O'Connor, D.H.1    Fukui, M.M.2    Pinsk, M.A.3    Kastner, S.4
  • 29
    • 0020464111 scopus 로고
    • A simplified neuron model as a principal component analyzer
    • Oja E. 1982. A simplified neuron model as a principal component analyzer. J Math Biol 15:267-273.
    • (1982) J Math Biol , vol.15 , pp. 267-273
    • Oja, E.1
  • 30
    • 0029938380 scopus 로고    scopus 로고
    • Emergence of simple-cell receptive field properties by learning a sparse code for natural images
    • Olshausen BA, Field DJ. 1996. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381:607-609.
    • (1996) Nature , vol.381 , pp. 607-609
    • Olshausen, B.A.1    Field, D.J.2
  • 31
    • 0030779611 scopus 로고    scopus 로고
    • Sparse coding with an overcomplete basis set: A strategy employed by V1?
    • Olshausen BA, Field DJ. 1997. Sparse coding with an overcomplete basis set: A strategy employed by V1? Vision Res 37:3311-3325.
    • (1997) Vision Res , vol.37 , pp. 3311-3325
    • Olshausen, B.A.1    Field, D.J.2
  • 32
    • 0033360288 scopus 로고    scopus 로고
    • Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects
    • Rao RP, Ballard DH. 1999. Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nat Neurosci 2:79-87.
    • (1999) Nat Neurosci , vol.2 , pp. 79-87
    • Rao, R.P.1    Ballard, D.H.2
  • 33
    • 33847100046 scopus 로고    scopus 로고
    • A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields
    • Rehn M, Sommer FT. 2007. A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. J Comput Neurosci 22:135-146.
    • (2007) J Comput Neurosci , vol.22 , pp. 135-146
    • Rehn, M.1    Sommer, F.T.2
  • 34
    • 3943082074 scopus 로고    scopus 로고
    • Attentional modulation of visual processing
    • Reynolds JH, Chelazzi L. 2004. Attentional modulation of visual processing. Annu Rev Neurosci 27:611-647.
    • (2004) Annu Rev Neurosci , vol.27 , pp. 611-647
    • Reynolds, J.H.1    Chelazzi, L.2
  • 35
    • 0036314487 scopus 로고    scopus 로고
    • Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex
    • Ringách DL. 2002. Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex. J Neurophysiol 88:455-463.
    • (2002) J Neurophysiol , vol.88 , pp. 455-463
    • Ringách, D.L.1
  • 36
    • 0028363829 scopus 로고
    • Direct temporal-occipital feedback connections to striate cortex (V1) in the macaque monkey
    • Rockland KS, van Hoesen GW. 1994. Direct temporal-occipital feedback connections to striate cortex (V1) in the macaque monkey. Cereb Cortex 4:300-313.
    • (1994) Cereb Cortex , vol.4 , pp. 300-313
    • Rockland, K.S.1    van Hoesen, G.W.2
  • 37
    • 0028430194 scopus 로고
    • Divergent feedback connections from areas V4 and TEO in the macaque
    • Rockland KS, Saleem KS, Tanata K. 1994. Divergent feedback connections from areas V4 and TEO in the macaque. Visual Neurosci 11:579-600.
    • (1994) Visual Neurosci , vol.11 , pp. 579-600
    • Rockland, K.S.1    Saleem, K.S.2    Tanata, K.3
  • 38
    • 0017745276 scopus 로고
    • Storing covariance with nonlinearly interacting neurons
    • Sejnowski T. 1977. Storing covariance with nonlinearly interacting neurons. J Math Biol 4:303-321.
    • (1977) J Math Biol , vol.4 , pp. 303-321
    • Sejnowski, T.1
  • 39
    • 0038734336 scopus 로고    scopus 로고
    • Vision and the statistics of the visual environment
    • Simoncelli EP. 2003. Vision and the statistics of the visual environment. Curr Opin Neurobiol 13:144-149.
    • (2003) Curr Opin Neurobiol , vol.13 , pp. 144-149
    • Simoncelli, E.P.1
  • 40
    • 1342280517 scopus 로고    scopus 로고
    • What the brain stem tells the frontal cortex. I. Oculomotor signals sent from superior colliculus to frontal eye field via mediodorsal thalamus
    • Sommer MA, Wurtz RH. 2004. What the brain stem tells the frontal cortex. I. Oculomotor signals sent from superior colliculus to frontal eye field via mediodorsal thalamus. J Neurophysiol 91:1381-1402.
    • (2004) J Neurophysiol , vol.91 , pp. 1381-1402
    • Sommer, M.A.1    Wurtz, R.H.2
  • 41
    • 0036717024 scopus 로고    scopus 로고
    • Pre-integration lateral inhibition enhances unsupervised learning
    • Spratling MW, Johnson MH. 2002. Pre-integration lateral inhibition enhances unsupervised learning. Neural Comput 14:2157-2179.
    • (2002) Neural Comput , vol.14 , pp. 2157-2179
    • Spratling, M.W.1    Johnson, M.H.2
  • 42
    • 0742323527 scopus 로고    scopus 로고
    • Homeostatic plasticity in the developing nervous system
    • Turrigiano GG, Nelson SB. 2004. Homeostatic plasticity in the developing nervous system. Nat Rev Neurosci 5:97-107.
    • (2004) Nat Rev Neurosci , vol.5 , pp. 97-107
    • Turrigiano, G.G.1    Nelson, S.B.2
  • 43
    • 0032492432 scopus 로고    scopus 로고
    • Independent component filters of natural images compared with simple cells in primary visual cortex
    • van Hateren JH, van der Schaaf A. 1998. Independent component filters of natural images compared with simple cells in primary visual cortex. Proc Biol Sci 265:359-366.
    • (1998) Proc Biol Sci , vol.265 , pp. 359-366
    • van Hateren, J.H.1    van der Schaaf, A.2
  • 44
    • 0015749493 scopus 로고
    • Self-organization of orientation selective cells in the striate cortex
    • von der Marlsburg C. 1973. Self-organization of orientation selective cells in the striate cortex. Kybernetic 14:85-100.
    • (1973) Kybernetic , vol.14 , pp. 85-100
    • von der Marlsburg, C.1
  • 45
    • 0001032906 scopus 로고
    • Optimal plasticity in matrix memories: What goes up must come down
    • Willshaw DJ, Dayan P. 1990. Optimal plasticity in matrix memories: What goes up must come down. Neural Comput 2:85-93.
    • (1990) Neural Comput , vol.2 , pp. 85-93
    • Willshaw, D.J.1    Dayan, P.2
  • 47
    • 0036886971 scopus 로고    scopus 로고
    • Biophysiologically plausible implementations of the maximum operation
    • Yu A, Giese MA, Poggio T. 2002. Biophysiologically plausible implementations of the maximum operation. Neural Comput 14:2857-2881.
    • (2002) Neural Comput , vol.14 , pp. 2857-2881
    • Yu, A.1    Giese, M.A.2    Poggio, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.