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Volumn 9, Issue JAN, 2015, Pages

A framework for plasticity implementation on the SpiNNaker neural architecture

Author keywords

BCM; Learning; Neuromorphic hardware; Plasticity; SpiNNaker; STDP

Indexed keywords

ARTICLE; COMPUTER; EXCITATION; HUMAN; LEARNING; MEMBRANE POTENTIAL; MEMORY; NERVE CELL; NERVE CELL PLASTICITY; PLASTICITY; SIMULATION; SPIKE; SPIKE TIMING DEPENDENT PLASTICITY; VOLTAGE DEPENDENT SPIKE TIMING DEPENDENT PLASTICITY; WEIGHT;

EID: 84921798570     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2014.00429     Document Type: Article
Times cited : (48)

References (87)
  • 1
    • 0033667165 scopus 로고    scopus 로고
    • Synaptic plasticity: taming the beast
    • Abbott, L. F., and Nelson, S. B. (2000). Synaptic plasticity: taming the beast. Nat. Neurosci. 3, 1178-1183. doi: 10.1038/81453
    • (2000) Nat. Neurosci. , vol.3 , pp. 1178-1183
    • Abbott, L.F.1    Nelson, S.B.2
  • 3
    • 84883397026 scopus 로고    scopus 로고
    • Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule
    • Beyeler, M., Dutt, N. D., and Krichmar, J. L. (2013). Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule. Neural Netw. 48, 109-124. doi: 10.1016/j.neunet.2013.07.012
    • (2013) Neural Netw. , vol.48 , pp. 109-124
    • Beyeler, M.1    Dutt, N.D.2    Krichmar, J.L.3
  • 4
    • 0032535029 scopus 로고    scopus 로고
    • Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type
    • Bi, G., and Poo, M. (1998). Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464-10472.
    • (1998) J. Neurosci. , vol.18 , pp. 10464-10472
    • Bi, G.1    Poo, M.2
  • 5
    • 0020074887 scopus 로고
    • Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex
    • Bienenstock, E. L., Cooper, L. N., and Munro, P. W. (1982). Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci. 2, 32-48.
    • (1982) J. Neurosci. , vol.2 , pp. 32-48
    • Bienenstock, E.L.1    Cooper, L.N.2    Munro, P.W.3
  • 6
    • 84904066998 scopus 로고    scopus 로고
    • Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity
    • Binas, J., Rutishauser, U., Indiveri, G., and Pfeiffer, M. (2014). Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity. Front. Comput. Neurosci. 8:68. doi: 10.3389/fncom.2014.00068
    • (2014) Front. Comput. Neurosci. , vol.8 , pp. 68
    • Binas, J.1    Rutishauser, U.2    Indiveri, G.3    Pfeiffer, M.4
  • 7
    • 36248934673 scopus 로고    scopus 로고
    • Learning real-world stimuli in a neural network with spike-driven synaptic dynamics
    • Brader, J. M., Senn, W., and Fusi, S. (2007). Learning real-world stimuli in a neural network with spike-driven synaptic dynamics. Neural Comput. 19, 2881-2912. doi: 10.1162/neco.2007.19.11.2881
    • (2007) Neural Comput. , vol.19 , pp. 2881-2912
    • Brader, J.M.1    Senn, W.2    Fusi, S.3
  • 8
    • 84870686500 scopus 로고    scopus 로고
    • Simulating spiking neural networks on gpu
    • Brette, R., and Goodman, D. F. (2012). Simulating spiking neural networks on gpu. Netw. Comput. Neural Syst. 23, 167-182. doi: 10.3109/0954898X.2012.730170
    • (2012) Netw. Comput. Neural Syst. , vol.23 , pp. 167-182
    • Brette, R.1    Goodman, D.F.2
  • 9
    • 35248866865 scopus 로고    scopus 로고
    • Simulation of networks of spiking neurons: a review of tools and strategies
    • Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J., et al. (2007). Simulation of networks of spiking neurons: a review of tools and strategies. J. Comput. Neurosci. 23, 349-398. doi: 10.1007/s10827-007-0038-6
    • (2007) J. Comput. Neurosci. , vol.23 , pp. 349-398
    • Brette, R.1    Rudolph, M.2    Carnevale, T.3    Hines, M.4    Beeman, D.5    Bower, J.6
  • 10
    • 84856442166 scopus 로고    scopus 로고
    • Conditional modulation of spike-timing-dependent plasticity for olfactory learning
    • Cassenaer, S., and Laurent, G. (2012). Conditional modulation of spike-timing-dependent plasticity for olfactory learning. Nature 482, 47-52. doi: 10.1038/nature10776
    • (2012) Nature , vol.482 , pp. 47-52
    • Cassenaer, S.1    Laurent, G.2
  • 11
    • 77649152514 scopus 로고    scopus 로고
    • Connectivity reflects coding: a model of voltage-based STDP with homeostasis
    • Clopath, C., Busing, L., Vasilaki, E., and Gerstner, W. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature Neurosci. 13, 344-352. doi: 10.1038/nn.2479
    • (2010) Nature Neurosci. , vol.13 , pp. 344-352
    • Clopath, C.1    Busing, L.2    Vasilaki, E.3    Gerstner, W.4
  • 12
    • 84898051894 scopus 로고    scopus 로고
    • A robust sound perception model suitable for neuromorphic implementation
    • Coath, M., Sheik, S., Chicca, E., Indiveri, G., Denham, S. L., and Wennekers, T. (2013). A robust sound perception model suitable for neuromorphic implementation. Front. Neurosci. 7:278. doi: 10.3389/fnins.2013.00278
    • (2013) Front. Neurosci. , vol.7 , pp. 278
    • Coath, M.1    Sheik, S.2    Chicca, E.3    Indiveri, G.4    Denham, S.L.5    Wennekers, T.6
  • 13
    • 84861770528 scopus 로고    scopus 로고
    • A forecast-based STDP rule suitable for neuromorphic implementation
    • Davies, S., Galluppi, F., Rast, A., and Furber, S. (2012). A forecast-based STDP rule suitable for neuromorphic implementation. Neural Netw. 32, 3-14. doi: 10.1016/j.neunet.2012.02.018
    • (2012) Neural Netw. , vol.32 , pp. 3-14
    • Davies, S.1    Galluppi, F.2    Rast, A.3    Furber, S.4
  • 15
    • 84908471912 scopus 로고    scopus 로고
    • Efficient implementation of STDP rules on SpiNNaker neuromorphic hardware
    • (Beijing)
    • Diehl, P. U., and Cook, M. (2014). "Efficient implementation of STDP rules on SpiNNaker neuromorphic hardware," in International Conference on Neural Networks (IJCNN) 2014 (Beijing), 4288-4295.
    • (2014) International Conference on Neural Networks (IJCNN) , pp. 4288-4295
    • Diehl, P.U.1    Cook, M.2
  • 18
    • 79959853243 scopus 로고    scopus 로고
    • Spatio-temporal credit assignment in neuronal population learning
    • Friedrich, J., Urbanczik, R., and Senn, W. (2011). Spatio-temporal credit assignment in neuronal population learning. PLoS Computat. Biol. 7:e1002092. doi: 10.1371/journal.pcbi.1002092
    • (2011) PLoS Computat. Biol. , vol.7
    • Friedrich, J.1    Urbanczik, R.2    Senn, W.3
  • 19
    • 84900504664 scopus 로고    scopus 로고
    • The SpiNNaker project
    • Furber, S., Galluppi, F., Temple, S., and Plana, A. (2014). The SpiNNaker project. Proc. IEEE 102, 652-665. doi: 10.1109/JPROC.2014.2304638
    • (2014) Proc. IEEE , vol.102 , pp. 652-665
    • Furber, S.1    Galluppi, F.2    Temple, S.3    Plana, A.4
  • 20
    • 44849127927 scopus 로고    scopus 로고
    • Neural systems engineering
    • Furber, S., and Temple, S. (2008). Neural systems engineering. Computat. Intell. 4, 763-796. doi: 10.1098/rsif.2006.0177
    • (2008) Computat. Intell. , vol.4 , pp. 763-796
    • Furber, S.1    Temple, S.2
  • 24
    • 0029821128 scopus 로고    scopus 로고
    • A neuronal learning rule for sub-millisecond temporal coding
    • Gerstner, W., Kempter, R., van Hemmen, J. L., and Wagner, H. (1996). A neuronal learning rule for sub-millisecond temporal coding. Nature 383, 76-78. doi: 10.1038/383076a0
    • (1996) Nature , vol.383 , pp. 76-78
    • Gerstner, W.1    Kempter, R.2    van Hemmen, J.L.3    Wagner, H.4
  • 25
    • 84867216457 scopus 로고    scopus 로고
    • Theory and simulation in neuroscience
    • Gerstner, W., Sprekeler, H., and Deco, G. (2012). Theory and simulation in neuroscience. Science 338, 60-65. doi: 10.1126/science.1227356
    • (2012) Science , vol.338 , pp. 60-65
    • Gerstner, W.1    Sprekeler, H.2    Deco, G.3
  • 27
    • 77953735451 scopus 로고    scopus 로고
    • Classification of correlated patterns with a configurable analog VLSI neural network of spiking neurons and self-regulating plastic synapses
    • Giulioni, M., Pannunzi, M., Badoni, D., Dante, V., and Del Giudice, P. (2009). Classification of correlated patterns with a configurable analog VLSI neural network of spiking neurons and self-regulating plastic synapses. Neural Comput. 21, 3106-3129. doi: 10.1162/neco.2009.08-07-599
    • (2009) Neural Comput. , vol.21 , pp. 3106-3129
    • Giulioni, M.1    Pannunzi, M.2    Badoni, D.3    Dante, V.4    Del Giudice, P.5
  • 28
    • 17044424557 scopus 로고    scopus 로고
    • Neurons tune to the earliest spikes through STDP
    • Guyonneau, R., Van Rullen, R., and Thorpe, S. J. (2005). Neurons tune to the earliest spikes through STDP. Neural Comput. 17, 859-879. doi: 10.1162/0899766053429390
    • (2005) Neural Comput. , vol.17 , pp. 859-879
    • Guyonneau, R.1    Van Rullen, R.2    Thorpe, S.J.3
  • 29
    • 0001049083 scopus 로고
    • Inhibition in the eye of the limulus
    • Hartline, H. K., Wagner, H. G., and Ratliff, F. (1956). Inhibition in the eye of the limulus. J. Gen. Physiol. 39, 651-673. doi: 10.1085/jgp.39.5.651
    • (1956) J. Gen. Physiol. , vol.39 , pp. 651-673
    • Hartline, H.K.1    Wagner, H.G.2    Ratliff, F.3
  • 31
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computational abilities
    • Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. U.S.A. 79, 2554-2558. doi: 10.1073/pnas.79.8.2554
    • (1982) Proc. Natl. Acad. Sci. U.S.A. , vol.79 , pp. 2554-2558
    • Hopfield, J.J.1
  • 32
    • 33244465845 scopus 로고    scopus 로고
    • A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity
    • Indiveri, G., Chicca, E., and Douglas, R. (2006). A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Trans. Neural Netw. 17, 211-221. doi: 10.1109/TNN.2005.860850
    • (2006) IEEE Trans. Neural Netw. , vol.17 , pp. 211-221
    • Indiveri, G.1    Chicca, E.2    Douglas, R.3
  • 35
    • 84883543408 scopus 로고    scopus 로고
    • Integration of nanoscale memristor synapses in neuromorphic computing architectures
    • Indiveri, G., Linares-Barranco, B., Legenstein, R., Deligeorgis, G., and Prodromakis, T. (2013). Integration of nanoscale memristor synapses in neuromorphic computing architectures. IOP Nanotechnol. 24:384010. doi: 10.1088/0957-4484/24/38/384010
    • (2013) IOP Nanotechnol. , vol.24 , pp. 384010
    • Indiveri, G.1    Linares-Barranco, B.2    Legenstein, R.3    Deligeorgis, G.4    Prodromakis, T.5
  • 36
    • 33644898137 scopus 로고    scopus 로고
    • Polychronization: computation with spikes
    • Izhikevich, E. (2006). Polychronization: computation with spikes. Neural Comput. 18, 245-282. doi: 10.1162/089976606775093882
    • (2006) Neural Comput. , vol.18 , pp. 245-282
    • Izhikevich, E.1
  • 37
    • 34948906745 scopus 로고    scopus 로고
    • Solving the distal reward problem through linkage of STDP and dopamine signaling
    • Izhikevich, E. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cereb. Cortex 17, 2443-2452. doi: 10.1093/cercor/bhl152
    • (2007) Cereb. Cortex , vol.17 , pp. 2443-2452
    • Izhikevich, E.1
  • 38
  • 41
    • 76649135818 scopus 로고    scopus 로고
    • Implementing learning on the SpiNNaker universal neural chip multiprocessor
    • Chapter 48, eds C. S. Leung, M. Lee, and J. H. Chan (Berlin; Heidelberg: Springer)
    • Jin, X., Rast, A., Galluppi, F., Khan, M., and Furber, S. (2009). "Implementing learning on the SpiNNaker universal neural chip multiprocessor," in Neural Information Processing, Volume 5863, Chapter 48, eds C. S. Leung, M. Lee, and J. H. Chan (Berlin; Heidelberg: Springer), 425-432.
    • (2009) Neural Information Processing , vol.5863 , pp. 425-432
    • Jin, X.1    Rast, A.2    Galluppi, F.3    Khan, M.4    Furber, S.5
  • 42
    • 84897460337 scopus 로고    scopus 로고
    • STDP installs in winner-take-all circuits an online approximation to hidden markov model learning
    • Kappel, D., Nessler, B., and Maass, W. (2014). STDP installs in winner-take-all circuits an online approximation to hidden markov model learning. PLoS Computat. Biol. 10:e1003511. doi: 10.1371/journal.pcbi.1003511
    • (2014) PLoS Computat. Biol. , vol.10
    • Kappel, D.1    Nessler, B.2    Maass, W.3
  • 43
    • 0035653423 scopus 로고    scopus 로고
    • Intrinsic stabilization of output rates by spike-based hebbian learning
    • Kempter, R., Gerstner, W., and van Hemmen, J. L. (2001). Intrinsic stabilization of output rates by spike-based hebbian learning. Neural Comput. 13, 2709-2741. doi: 10.1162/089976601317098501
    • (2001) Neural Comput. , vol.13 , pp. 2709-2741
    • Kempter, R.1    Gerstner, W.2    van Hemmen, J.L.3
  • 44
    • 84900525248 scopus 로고    scopus 로고
    • Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity
    • Kleberg, F. I., Fukai, T., and Gilson, M. (2014). Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity. Front. Comput. Neurosci. 8:53. doi: 10.3389/fncom.2014.00053
    • (2014) Front. Comput. Neurosci. , vol.8 , pp. 53
    • Kleberg, F.I.1    Fukai, T.2    Gilson, M.3
  • 45
  • 46
    • 77957343940 scopus 로고    scopus 로고
    • {SORN}: a self-organizing recurrent neural network
    • Lazar, A., Pipa, G., and Triesch, J. (2009). {SORN}: a self-organizing recurrent neural network. Front. Comput. Neurosci. 3:23. doi: 10.3389/neuro.10.023.2009
    • (2009) Front. Comput. Neurosci. , vol.3 , pp. 23
    • Lazar, A.1    Pipa, G.2    Triesch, J.3
  • 48
    • 55449121121 scopus 로고    scopus 로고
    • A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback
    • Legenstein, R., Pecevski, D., and Maass, W. (2008). A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback. PLoS Comput. Biol. 4:e1000180. doi: 10.1371/journal.pcbi.1000180
    • (2008) PLoS Comput. Biol. , vol.4
    • Legenstein, R.1    Pecevski, D.2    Maass, W.3
  • 49
    • 0031012615 scopus 로고    scopus 로고
    • Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs
    • Markram, H., Lbke, J., Frotscher, M., and Sakmann, B. (1997). Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275, 213-215. doi: 10.1126/science.275.5297.213
    • (1997) Science , vol.275 , pp. 213-215
    • Markram, H.1    Lbke, J.2    Frotscher, M.3    Sakmann, B.4
  • 50
    • 84877760437 scopus 로고    scopus 로고
    • Waveform driven plasticity in BiFeO3 memristive devices: model and implementation
    • (Lake Tahoe, NV)
    • Mayr, C., Stärke, P., Partzsch, J., Schueffny, R., Cederstroem, L., Shuai, Y., et al. (2012). "Waveform driven plasticity in BiFeO3 memristive devices: model and implementation," in NIPS (Lake Tahoe, NV), 1709-1717.
    • (2012) NIPS , pp. 1709-1717
    • Mayr, C.1    Stärke, P.2    Partzsch, J.3    Schueffny, R.4    Cederstroem, L.5    Shuai, Y.6
  • 51
    • 0004116444 scopus 로고
    • London: Addison-Wesley Longman Publishing Co., Inc
    • Mead, C. (1989). Analog VLSI and Neural Systems. London: Addison-Wesley Longman Publishing Co., Inc.
    • (1989) Analog VLSI and Neural Systems
    • Mead, C.1
  • 52
    • 0033681558 scopus 로고    scopus 로고
    • Experience-dependent asymmetric shape of hippocampal receptive fields
    • Mehta, M. R., Quirk, M. C., and Wilson, M. A. (2000). Experience-dependent asymmetric shape of hippocampal receptive fields. Neuron 25, 707-715. doi: 10.1016/S0896-6273(00)81072-7
    • (2000) Neuron , vol.25 , pp. 707-715
    • Mehta, M.R.1    Quirk, M.C.2    Wilson, M.A.3
  • 53
    • 84868108811 scopus 로고    scopus 로고
    • The computational power of astrocyte mediated synaptic plasticity
    • Min, R., Santello, M., and Nevian, T. (2012). The computational power of astrocyte mediated synaptic plasticity. Front. Comput. Neurosci. 6:93. doi: 10.3389/fncom.2012.00093
    • (2012) Front. Comput. Neurosci. , vol.6 , pp. 93
    • Min, R.1    Santello, M.2    Nevian, T.3
  • 54
    • 60149108117 scopus 로고    scopus 로고
    • Real-time classification of complex patterns using spike-based learning in neuromorphic VLSI
    • Mitra, S., Fusi, S., and Indiveri, G. (2009). Real-time classification of complex patterns using spike-based learning in neuromorphic VLSI. IEEE Trans. Biomed. Circ. Syst. 3, 32-42. doi: 10.1109/TBCAS.2008.2005781
    • (2009) IEEE Trans. Biomed. Circ. Syst. , vol.3 , pp. 32-42
    • Mitra, S.1    Fusi, S.2    Indiveri, G.3
  • 55
    • 84860515201 scopus 로고    scopus 로고
    • Development of orientation tuning in simple cells of primary visual cortex
    • Moore, B. D., and Freeman, R. D. (2012). Development of orientation tuning in simple cells of primary visual cortex. J. Neurophysiol. 107, 2506-2516. doi: 10.1152/jn.00719.2011
    • (2012) J. Neurophysiol. , vol.107 , pp. 2506-2516
    • Moore, B.D.1    Freeman, R.D.2
  • 56
    • 43949102027 scopus 로고    scopus 로고
    • Phenomenological models of synaptic plasticity based on spike timing
    • Morrison, A., Diesmann, M., and Gerstner, W. (2008). Phenomenological models of synaptic plasticity based on spike timing. Biol. Cybern. 98, 459-478. doi: 10.1007/s00422-008-0233-1
    • (2008) Biol. Cybern. , vol.98 , pp. 459-478
    • Morrison, A.1    Diesmann, M.2    Gerstner, W.3
  • 57
    • 20844460509 scopus 로고    scopus 로고
    • Advancing the boundaries of high-connectivity network simulation with distributed computing
    • Morrison, A., Mehring, C., and Geisel, T. (2005). Advancing the boundaries of high-connectivity network simulation with distributed computing. Neural Comput. 17, 1776-1801. doi: 10.1162/0899766054026648
    • (2005) Neural Comput. , vol.17 , pp. 1776-1801
    • Morrison, A.1    Mehring, C.2    Geisel, T.3
  • 59
    • 68149182671 scopus 로고    scopus 로고
    • A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors
    • Nageswaran, J., Dutt, N., Krichmar, J., and Nicolau, A. (2007). A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors. Neural Netw. 22, 791-800. doi: 10.1016/j.neunet.2009.06.028
    • (2007) Neural Netw. , vol.22 , pp. 791-800
    • Nageswaran, J.1    Dutt, N.2    Krichmar, J.3    Nicolau, A.4
  • 60
    • 84898035691 scopus 로고    scopus 로고
    • Event-driven contrastive divergence for spiking neuromorphic systems
    • Neftci, E., Das, S., Pedroni, B., Kreutz-Delgado, K., and Cauwenberghs, G. (2014). Event-driven contrastive divergence for spiking neuromorphic systems. Front. Neurosci. 7:272. doi: 10.3389/fnins.2013.00272
    • (2014) Front. Neurosci. , vol.7 , pp. 272
    • Neftci, E.1    Das, S.2    Pedroni, B.3    Kreutz-Delgado, K.4    Cauwenberghs, G.5
  • 62
    • 84876928403 scopus 로고    scopus 로고
    • Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity
    • Nessler, B., Pfeiffer, M., Buesing, L., and Maass, W. (2013). Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity. PLoS Comput. Biol. 9:e1003037. doi: 10.1371/journal.pcbi.1003037
    • (2013) PLoS Comput. Biol. , vol.9
    • Nessler, B.1    Pfeiffer, M.2    Buesing, L.3    Maass, W.4
  • 63
    • 0020464111 scopus 로고
    • Simplified neuron model as a principal component analyzer
    • Oja, E. (1982). Simplified neuron model as a principal component analyzer. J. Math. Biol. 15, 267-273. doi: 10.1007/BF00275687
    • (1982) J. Math. Biol. , vol.15 , pp. 267-273
    • Oja, E.1
  • 65
    • 84862213022 scopus 로고    scopus 로고
    • Timing is not everything: neuromodulation opens the STDP gate
    • Pawlak, V., Wickens, J. R., Kirkwood, A., and Kerr, J. N. D. (2010). Timing is not everything: neuromodulation opens the STDP gate. Front. Synaptic Neurosci. 2:146. doi: 10.3389/fnsyn.2010.00146
    • (2010) Front. Synaptic Neurosci. , vol.2 , pp. 146
    • Pawlak, V.1    Wickens, J.R.2    Kirkwood, A.3    Kerr, J.N.D.4
  • 66
    • 84865180086 scopus 로고    scopus 로고
    • Is a 4-Bit synaptic weight resolution enough? constraints on enabling spike-timing dependent plasticity in neuromorphic hardware
    • Pfeil, T., Potjans, T. C., Schrader, S., Potjans, W., Schemmel, J., Diesmann, M., et al. (2012). Is a 4-Bit synaptic weight resolution enough? constraints on enabling spike-timing dependent plasticity in neuromorphic hardware. Front. Neurosci. 6:90. doi: 10.3389/fnins.2012.00090
    • (2012) Front. Neurosci. , vol.6 , pp. 90
    • Pfeil, T.1    Potjans, T.C.2    Schrader, S.3    Potjans, W.4    Schemmel, J.5    Diesmann, M.6
  • 67
    • 35348906788 scopus 로고    scopus 로고
    • A GALS infrastructure for a massively parallel multiprocessor
    • Plana, L., Furber, S., Temple, S., Khan, M., Shi, Y., Wu, J., et al. (2007). A GALS infrastructure for a massively parallel multiprocessor. IEEE Des. Test Comput. 24, 454-463. doi: 10.1109/MDT.2007.149
    • (2007) IEEE Des. Test Comput. , vol.24 , pp. 454-463
    • Plana, L.1    Furber, S.2    Temple, S.3    Khan, M.4    Shi, Y.5    Wu, J.6
  • 68
    • 38049110006 scopus 로고    scopus 로고
    • Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers
    • (Berlin; Heidelberg: Springer)
    • Plesser, H., Eppler, J., Morrison, A., Diesmann, M., and Gewaltig, M. (2007). "Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers," in Euro-Par 2007 Parallel Processing (Berlin; Heidelberg: Springer), 672-681.
    • (2007) Euro-Par 2007 Parallel Processing , pp. 672-681
    • Plesser, H.1    Eppler, J.2    Morrison, A.3    Diesmann, M.4    Gewaltig, M.5
  • 69
    • 79958078227 scopus 로고    scopus 로고
    • An imperfect dopaminergic error signal can drive temporal-difference learning
    • Potjans, W., Diesmann, M., and Morrison, A. (2011). An imperfect dopaminergic error signal can drive temporal-difference learning. PLoS Comput. Biol. 7:e1001133. doi: 10.1371/journal.pcbi.1001133
    • (2011) PLoS Comput. Biol. , vol.7
    • Potjans, W.1    Diesmann, M.2    Morrison, A.3
  • 70
    • 84900482869 scopus 로고    scopus 로고
    • Spike-based synaptic plasticity in silicon: design, implementation, application, and challenges
    • Rahimi Azghadi, M., Iannella, N., Al-Sarawi, S. F., Indiveri, G., and Abbott, D. (2014). Spike-based synaptic plasticity in silicon: design, implementation, application, and challenges. Proc. IEEE 102, 717-737. doi: 10.1109/JPROC.2014.2314454
    • (2014) Proc. IEEE , vol.102 , pp. 717-737
    • Rahimi Azghadi, M.1    Iannella, N.2    Al-Sarawi, S.F.3    Indiveri, G.4    Abbott, D.5
  • 71
    • 77954576671 scopus 로고    scopus 로고
    • Independent component analysis in spiking neurons
    • Savin, C., Joshi, P., and Triesch, J. (2010). Independent component analysis in spiking neurons. PLoS Comput. Biol. 6:e1000757. doi: 10.1371/journal.pcbi.1000757
    • (2010) PLoS Comput. Biol. , vol.6
    • Savin, C.1    Joshi, P.2    Triesch, J.3
  • 75
    • 84862183463 scopus 로고    scopus 로고
    • Emergent auditory feature tuning in a real-time neuromorphic VLSI system
    • Sheik, S., Coath, M., Indiveri, G., Denham, S. L., Wennekers, T., and Chicca, E. (2012). Emergent auditory feature tuning in a real-time neuromorphic VLSI system. Front. Neurosci. 6:17. doi: 10.3389/fnins.2012.00017
    • (2012) Front. Neurosci. , vol.6 , pp. 17
    • Sheik, S.1    Coath, M.2    Indiveri, G.3    Denham, S.L.4    Wennekers, T.5    Chicca, E.6
  • 76
    • 0030733281 scopus 로고    scopus 로고
    • BCM network develops orientation selectivity and ocular dominance in natural scene environment
    • Shouval, H., Intrator, N., and Cooper, L. N. (1997). BCM network develops orientation selectivity and ocular dominance in natural scene environment. Vis. Res. 37, 3339-3342. doi: 10.1016/S0042-6989(97)00087-4
    • (1997) Vis. Res. , vol.37 , pp. 3339-3342
    • Shouval, H.1    Intrator, N.2    Cooper, L.N.3
  • 77
    • 0035924588 scopus 로고    scopus 로고
    • Rate, timing, and cooperativity jointly determine cortical synaptic plasticity
    • Sjöström, P. J., Turrigiano, G. G., and Nelson, S. B. (2001). Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149-1164. doi: 10.1016/S0896-6273(01)00542-6
    • (2001) Neuron , vol.32 , pp. 1149-1164
    • Sjöström, P.J.1    Turrigiano, G.G.2    Nelson, S.B.3
  • 78
    • 0035950280 scopus 로고    scopus 로고
    • Cortical development and remapping through spike timing-dependent plasticity
    • Song, S., and Abbott, L. F. (2001). Cortical development and remapping through spike timing-dependent plasticity. Neuron 32, 339-350. doi: 10.1016/S0896-6273(01)00451-2
    • (2001) Neuron , vol.32 , pp. 339-350
    • Song, S.1    Abbott, L.F.2
  • 79
    • 0033860923 scopus 로고    scopus 로고
    • Competitive hebbian learning through spike-timing-dependent synaptic plasticity
    • Song, S., Miller, K. D., and Abbott, L. F. (2000). Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nat. Neurosci. 3, 919-926. doi: 10.1038/78829
    • (2000) Nat. Neurosci. , vol.3 , pp. 919-926
    • Song, S.1    Miller, K.D.2    Abbott, L.F.3
  • 80
    • 84862684572 scopus 로고    scopus 로고
    • Python scripting in the nengo simulator
    • Stewart, T. C., Tripp, B., and Eliasmith, C. (2009). Python scripting in the nengo simulator. Front. Neuroinformat. 3:7. doi: 10.3389/neuro.11.007.2009
    • (2009) Front. Neuroinformat. , vol.3 , pp. 7
    • Stewart, T.C.1    Tripp, B.2    Eliasmith, C.3
  • 82
    • 84888815818 scopus 로고    scopus 로고
    • Synthesis of neural networks for spatio-temporal spike pattern recognition and processing
    • Tapson, J. C., Cohen, G. K., Afshar, S., Stiefel, K. M., Buskila, Y., Wang, R. M., et al. (2013). Synthesis of neural networks for spatio-temporal spike pattern recognition and processing. Front. Neurosci. 7:153. doi: 10.3389/fnins.2013.00153
    • (2013) Front. Neurosci. , vol.7 , pp. 153
    • Tapson, J.C.1    Cohen, G.K.2    Afshar, S.3    Stiefel, K.M.4    Buskila, Y.5    Wang, R.M.6
  • 85
    • 84878868253 scopus 로고    scopus 로고
    • An FPGA implementation of a polychronous spiking neural network with delay adaptation
    • Wang, R., Cohen, G., Stiefel, K. M., Hamilton, T. J., Tapson, J., and van Schaik, A. (2013). An FPGA implementation of a polychronous spiking neural network with delay adaptation. Front. Neurosci. 7:14. doi: 10.3389/fnins.2013.00014
    • (2013) Front. Neurosci. , vol.7 , pp. 14
    • Wang, R.1    Cohen, G.2    Stiefel, K.M.3    Hamilton, T.J.4    Tapson, J.5    van Schaik, A.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.