- spiking neural networks
- spiking neuron models
- spike timing-dependent plasticity
- neuron encoding
- co-ordinate transformation.
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Learning Mechanisms in Networks of Spiking Neurons. / Wu, Qingxiang; McGinnity, TM; Maguire, LP; Glackin, Brendan; Belatreche, Ammar.Studies in Computational Intelligence. ed. / Ke Chen; Lipo Wang. Vol. 35 Springer, 2007. p. 171-197.
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
TY - CHAP
T1 - Learning Mechanisms in Networks of Spiking Neurons
AU - Wu, Qingxiang
AU - McGinnity, TM
AU - Maguire, LP
AU - Glackin, Brendan
AU - Belatreche, Ammar
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Knill: Experience-dependent visual cue recalibration based on discrepancies between visual and haptic percepts. Vision Research, Vol.43(25) (2003) 2603-2613 31. Spence, C., Pavani, F., Driver, J.: Crossmodal links between vision and touch in covert endogenous spatial attention. J. Exp. Psychol. Hum. Percept. Perform. 26 (2000) 1298–1319 32. Eimer M., Driver, J.: An event-related brain potential study of crossmodal links in spatial attention between vision and touch, Psychophysiology, 37 (2000) 697–705 33. Graziano, M.S.A., Gross, C.G.: The representation of extrapersonal space: A possible role for bimodal, visual–tactile neurons, in: M.S. Gazzaniga (Ed.), The Cognitive Neurosciences, MIT Press, Cambridge, MA, (1994) 1021–1034 34. Zhou, Y.D., Fuster, J.M.: Visuo-tactile cross-modal associations in cortical somatosensory cells. Proc. Natl. Acad. Sci. USA 97 (2000) 9777–9782 35. 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Neuroscien-tist, 1 (1995) 43-50 41. Rizzolatti, G., Fogassi, L.& Gallese, V.: Parietal cortex: from sight to action. Curr. Opin. Neurobiol., 7 (1997) 562-567 42. Taylor-Clarke M., Kennett S., Haggard P.: Vision modulates somatosensory cortical pro-cessing. Curr. Biol. 12 (2002) 233–236 43. Iriki, A., Tanaka, M., Iwamura, Y.: Attention-induced neuronal activity in the monkey somatosensory cortex revealed by pupillometrics. Neurosci. Res. 25 (1996) 173–181 44. Simon Thorpe, Arnaud Delorme and Rufin Van Rullen: Spike-based strategies for rapid processing. Neural Networks, Vol.14, Issue 6-7 (2001)715-725 45. Wu, Q.X., McGinnity, T.M., Maguire, L.P., Belatreche, A. and Glackin, B.: Adaptive Co-Ordinate Transformation Based on Spike Timing-Dependent Plasticity Learning Paradigm. Proceedings of The First International Conference on Natural Computation, LNCS, Vol.3610 (2005)420-429
PY - 2007/1/1
Y1 - 2007/1/1
N2 - In spiking neural networks, signals are transferred by action potentials. The information is encoded in the patterns of neuron activities or spikes. These features create significant differences between spiking neural networks and classical neural networks. Since spiking neural networks are based on spiking neuron models that are very close to the biological neuron model, many of the principles found in biological neuroscience can be used in the networks. In this chapter, a number of learning mechanisms for spiking neural networks are introduced. The learning mechanisms can be applied to explain the behaviours of networks in the brain, and also can be applied to artificial intelligent systems to process complex information represented by biological stimuli.
AB - In spiking neural networks, signals are transferred by action potentials. The information is encoded in the patterns of neuron activities or spikes. These features create significant differences between spiking neural networks and classical neural networks. Since spiking neural networks are based on spiking neuron models that are very close to the biological neuron model, many of the principles found in biological neuroscience can be used in the networks. In this chapter, a number of learning mechanisms for spiking neural networks are introduced. The learning mechanisms can be applied to explain the behaviours of networks in the brain, and also can be applied to artificial intelligent systems to process complex information represented by biological stimuli.
KW - spiking neural networks
KW - learning
KW - spiking neuron models
KW - spike timing-dependent plasticity
KW - neuron encoding
KW - co-ordinate transformation.
UR - http://www.springerlink.com/content/n605v2m520478859/
UR - http://www.springerlink.com/content/n605v2m520478859/
U2 - 10.1007/978-3-540-36122-0_7
DO - 10.1007/978-3-540-36122-0_7
M3 - Chapter
SN - 1860-949X
VL - 35
SP - 171
EP - 197
BT - Studies in Computational Intelligence
A2 - Chen, Ke
A2 - Wang, Lipo
PB - Springer