Unsupervised learning of visual features through spike timing dependent plasticity

PLoS Computational Biology

Volumn 3, Issue 2, 2007, Pages 0247-0257

  Masquelier, Timothée ^a,b   Thorpe, Simon J ^a,b  

^a CNRS   (France)

^b SpikeNet Technology SARL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; OBJECT RECOGNITION; TIMING CIRCUITS;

FEED FORWARD; LEARNING RULES; NEURAL-NETWORKS; PRESYNAPTIC; RELATIVE TIMING; SPIKE TIMING DEPENDENT PLASTICITIES; SYNAPTIC STRENGTHS; SYNAPTIC WEIGHT; VISUAL FEATURE; VISUAL PATHWAYS;

NEURONS;

ARTICLE; NERVE CELL PLASTICITY; NERVE CONDUCTION; POSTSYNAPTIC POTENTIAL; PRESYNAPTIC POTENTIAL; SENSORY NERVE; SYNAPSE; VISUAL SYSTEM; ACTION POTENTIAL; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; COMPUTER SIMULATION; FEEDBACK SYSTEM; NERVE CELL NETWORK; PATTERN RECOGNITION; PHYSIOLOGY; SENSORY NERVE CELL; SYNAPTIC TRANSMISSION; VISUAL CORTEX;

ACTION POTENTIALS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; FEEDBACK; MODELS, NEUROLOGICAL; NERVE NET; NEURONAL PLASTICITY; NEURONS, AFFERENT; PATTERN RECOGNITION, VISUAL; SYNAPTIC TRANSMISSION; VISUAL CORTEX;

EID: 33847275584     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.0030031     Document Type: Article

References (49)

1. Kirchner H, Thorpe SJ (2006) Ultra-rapid object detection with saccadic eye movements: Visual processing speed revisited. Vision Res 46: 1762-1776.
2. Hung CP, Kreiman G, Poggio T, DiCarlo JJ (2005) Fast readout of object identity from macaque inferior temporal cortex. Science 310: 863-866.
3. VanRullen R, Thorpe SJ (2001) Rate coding versus temporal order coding: What the retinal ganglion cells tell the visual cortex. Neural Comput 13: 1255-1283.
4. Song S, Miller KD, Abbott LF (2000) Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nat Neurosci 3: 919-926.
5. Guyonneau R, VanRullen R, Thorpe SJ (2005) Neurons tune to the earliest spikes through STDP. Neural Comput 17: 859-879.
6. Serre T, Wolf L, Poggio T (2005) Object recognition with features inspired by visual cortex. CVPR 2: 994-1000.
7. Riesenhuber M, Poggio T (1999) Hierarchical models of object recognition in cortex. Nat Neurosci 2: 1019-1025.
8. Ullman S, Vidal-Naquet M, Sali E (2002) Visual features of intermediate complexity and their use in classification. Nat Neurosci 5: 682-687.
9. Fukushima K (1980) Neocognitron: A self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36: 193-202.
10. LeCun Y, Bengio Y (1995) Convolutional networks for images, speech, and time series. In: Arbib MA, editor. The handbook of brain theory and neural networks. Cambridge (Massachusetts): MIT Press. pp. 255-258.
11. Kobatake E, Tanaka K (1994) Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. J Neurophysiol 71: 856-867.
12. Oram MW, Perrett DI (1994) Modeling visual recognition from neurobiological constraints. Neural Networks 7: 945-972.
13. Albrecht DG, Geisler WS, Frazor RA, Crane AM (2002) Visual cortex neurons of monkeys and cats: Temporal dynamics of the contrast response function. J Neurophysiol 88: 888-913.
14. Gawne TJ, Kjaer TW, Richmond BJ (1996) Latency: Another potential code for feature binding in striate cortex. J Neurophysiol 76: 1356-1360.
15. Celebrini S, Thorpe S, Trotter Y, Imbert M (1993) Dynamics of orientation coding in area V 1 of the awake primate. Vis Neurosci 10: 811-825.
16. Delorme A, Gautrais J, VanRullen R, Thorpe SJ (2001) Networks of integrate-and-fire neurons using Rank Order Coding B: Spike timing dependent plasticity and emergence of orientation selectivity. Neurocomputing 38-40: 539-545.
17. Thorpe SJ (1990) Spike arrival times: A highly efficient coding scheme for neural networks. In: Eckmiller R, Hartmann G, Hauske G, editors. Parallel processing in neural systems and computers. Amsterdam: Elsevier. pp. 91-94.
18. Rousselet GA, Thorpe SJ, Fabre-Thorpe M (2003) Taking the MAX from neuronal responses. Trends Cogn Sci 7: 99-102.
19. Markram H, Lubke J, Frotscher M, Sakmann B (1997) Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275: 213-215.
20. Bi GQ, Poo MM (1998) Synaptic modifications in cultured hippocampal neurons: Dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18: 10464-10472.
21. Zhang LI, Tao HW, Holt CE, Harris WA, Poo M (1998) A critical window for cooperation and competition among developing retinotectal synapses. Nature 395: 37-44.
22. Feldman DE (2000) Timing-based LTP and LTD at vertical inputs to layer II/III pyramidal cells in rat barrel cortex. Neuron 27: 45-56.
23. VanRossum MCW, Bi GQ, Turrigiano GG (2000) Stable Hebbian learning from spike timing-dependent plasticity. J Neurosci 20: 8812-8821.
24. Gerstner W, Kistler WM (2002) Learning to be fast: Spiking neuron models. Cambridge University Press. pp. 421-432.
25. Fergus R, Perona P, Zisserman A (2003) Object class recognition by unsupervised scale-invariant learning. CVPR 2: 264-271.
26. Serre T, Kouh M, Cadieu C, Knoblich U, Kreiman G, et al. (2005) A theory of object recognition: Computations and circuits in the feedforward path of the ventral stream in primate visual cortex. Cambridge (Massachusetts): Massachusetts Institute of Technology CBCL Paper #259/AI Memo #2005-036.
27. Poggio T, Bizzi E (2004) Generalization in vision and motor control. Nature 431: 768-774.
28. Rolls ET, Deco G (2002) Computational neuroscience of vision. Oxford: Oxford University Press. 592 p.
29. Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20: 1254-1259.
30. Treue S (2003) Abstract visual attention: The where, what, how and why of saliency. Curr Opin Neurobiol 13: 428-432.
31. Uchida N, Kepecs A, Mainen ZF (2006) Seeing at a glance, smelling in a whiff: Rapid forms of perceptual decision making. Nat Rev Neurosci 7: 485-491.
32. Martinez-Conde S, Macknik SL, Hubel DH (2000) Microsaccadic eye movements and firing of single cells in the striate cortex of macaque monkeys. Nat Neurosci 3: 251-258.
33. Hopfield JJ (1995) Pattern recognition computation using action potential timing for stimulus representation. Nature 376: 33-36.
34. König P, Engel AK, Roelfsema PR, Singer W (1995) How precise is neuronal synchronization? Neural Comput 7: 469-485.
35. Vapnik VN, Chervonenkis AY (1971) On the uniform convergence of relative frequencies of events to their probabilities. Theor Probab Appl 17: 264-280.
36. Földiák P (1991) Learning invariance from transformation sequences. Neural Comput 3: 194-200.
37. Wallis G, Rolls ET (1997) Invariant face and object recognition in the visual system. Prog Neurobiol 51: 167-194.
38. Rolls ET, Milward T (2000) A model of invariant object recognition in the visual system: Learning rules, activation functions, lateral inhibition, and information-based performance measures. Neural Comput 12: 2547-2572.
39. Stringer SM, Rolls ET (2000) Position invariant recognition in the visual system with cluttered environments. Neural Networks 13: 305-315.
40. Logothetis NK, Pauls J, Poggio T (1995) Shape representation in the inferior temporal cortex of monkeys. Curr Biol 5: 552-563.
41. Thorpe S, Fize D, Marlot C (1996) Speed of processing in the human visual system. Nature 381: 520-522.
42. Sigala N, Logothetis NK (2002) Visual categorization shapes feature selectivity in the primate temporal cortex. Nature 415: 318-320.
43. Bichot NP, Rossi AF, Desimone R (2005) Parallel and serial neural mechanisms for visual search in macaque area v4. Science 308: 529-534.
44. Szabo M, Stetter M, Deco G, Fusi S, Giudice PD, et al. (2006) Learning to attend: Modeling the shaping of selectivity in infero-temporal cortex in a categorization task. Biol Cybern 94: 351-365.
45. Thorpe SJ, Imbert M (1989) Biological constraints on connectionist modelling. In: Pfeifer R, Schreter Z, Fogelman-Soulié F, Steels L, editors. Connectionism in perspective. Amsterdam: Elsevier. pp. 63-92.
46. Gautrais J, Thorpe S (1998) Rate coding versus temporal order coding: A theoretical approach. Biosystems 48: 57-65.
47. Amarasingham A, Chen TL, Geman S, Harrison MT, Sheinberg DL (2006) Spike count reliability and the Poisson hypothesis. J Neurosci 26: 801-809.
48. Kiani R, Esteky H, Tanaka K (2005) Differences in onset latency of macaque inferotemporal neural responses to primate and non-primate faces. J Neurophysiol 94: 1587-1596.
49. VanRullen R, Guyonneau R, Thorpe SJ (2005) Spike times make sense. Trends Neurosci 28: 1-4.