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Volumn , Issue 7 FEB, 2013, Pages

Six networks on a universal neuromorphic computing substrate

Author keywords

Accelerated neuromorphic hardware system; Classifier; Cortical model; Highly configurable; Mixed signal VLSI; Soft winner take all; Spiking neural networks; Universal computing substrate

Indexed keywords

ANTENNA; ARTICLE; COMPUTER MODEL; COMPUTER SYSTEM; INSECT; NERVE CELL; NERVE CELL NETWORK; NERVE CELL PLASTICITY; NERVE POTENTIAL; NONHUMAN; SCIENTIST; SYNAPSE; TISSUE STRUCTURE;

EID: 84878827374     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2013.00011     Document Type: Article
Times cited : (165)

References (86)
  • 1
    • 4344560353 scopus 로고    scopus 로고
    • Modeling compositionality by dynamic binding of synfire chains
    • Abeles, M., Hayon, G., and Lehmann, D. (2004). Modeling compositionality by dynamic binding of synfire chains. J. Comput. Neurosci. 17, 179-201.
    • (2004) J. Comput. Neurosci. , vol.17 , pp. 179-201
    • Abeles, M.1    Hayon, G.2    Lehmann, D.3
  • 2
    • 0030468253 scopus 로고    scopus 로고
    • Propagation of synchronous spiking activity in feedforward neural networks
    • Aertsen, A., Diesmann, M., and Gewaltig, M.-O. (1996). Propagation of synchronous spiking activity in feedforward neural networks. J. Physiol. (Paris) 90, 243-247.
    • (1996) J. Physiol. (Paris) , vol.90 , pp. 243-247
    • Aertsen, A.1    Diesmann, M.2    Gewaltig, M.-O.3
  • 4
    • 0038604429 scopus 로고    scopus 로고
    • On embedding synfire chains in a balanced network
    • Aviel, Y., Mehring, C., Abeles, M., and Horn, D. (2003). On embedding synfire chains in a balanced network. Neural Comput. 15, 1321-1340.
    • (2003) Neural Comput. , vol.15 , pp. 1321-1340
    • Aviel, Y.1    Mehring, C.2    Abeles, M.3    Horn, D.4
  • 5
    • 0035125819 scopus 로고    scopus 로고
    • Synchronization in monkey motor cortex during a precision grip task, I. Task-dependent modulation in single-unit synchrony
    • Baker, S. N., Spinks, R., Jackson, A., and Lemon, R. N. (2001). Synchronization in monkey motor cortex during a precision grip task. I. Task-dependent modulation in single-unit synchrony. J. Neurophysiol. 85, 869-885.
    • (2001) J. Neurophysiol. , vol.85 , pp. 869-885
    • Baker, S.N.1    Spinks, R.2    Jackson, A.3    Lemon, R.N.4
  • 7
    • 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
  • 8
    • 79955749812 scopus 로고    scopus 로고
    • Compensating inhomogeneities of neuromorphic VLSI devices via short-term synaptic plasticity
    • doi:10.3389/fncom.2010.00129
    • Bill, J., Schuch, K., Brüderle, D., Schemmel, J., Maass, W., and Meier, K. (2010). Compensating inhomogeneities of neuromorphic VLSI devices via short-term synaptic plasticity. Front. Comput. Neurosci. 4:129. doi:10.3389/fncom.2010.00129
    • (2010) Front. Comput. Neurosci. , vol.4 , pp. 129
    • Bill, J.1    Schuch, K.2    Brüderle, D.3    Schemmel, J.4    Maass, W.5    Meier, K.6
  • 11
    • 77955987285 scopus 로고    scopus 로고
    • Establishing a novel modeling tool: a Python-based interface for a neuromorphic hardware system
    • doi:10.3389/neuro.11.017.2009
    • Brüderle, D., Müller, E., Davison, A., Muller, E., Schemmel, J., and Meier, K. (2009). Establishing a novel modeling tool: a Python-based interface for a neuromorphic hardware system. Front. Neuroinform. 3:17. doi:10.3389/neuro.11.017.2009
    • (2009) Front. Neuroinform. , vol.3 , pp. 17
    • Brüderle, D.1    Müller, E.2    Davison, A.3    Muller, E.4    Schemmel, J.5    Meier, K.6
  • 12
    • 80052931593 scopus 로고    scopus 로고
    • A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems
    • Brüderle, D., Petrovici, M., Vogginger, B., Ehrlich, M., Pfeil, T., Millner, S., et al. (2011). A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biol. Cybern. 104, 263-296.
    • (2011) Biol. Cybern. , vol.104 , pp. 263-296
    • Brüderle, D.1    Petrovici, M.2    Vogginger, B.3    Ehrlich, M.4    Pfeil, T.5    Millner, S.6
  • 13
    • 0034006515 scopus 로고    scopus 로고
    • Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons
    • Brunel, N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8, 183-208.
    • (2000) J. Comput. Neurosci. , vol.8 , pp. 183-208
    • Brunel, N.1
  • 14
    • 84924618721 scopus 로고    scopus 로고
    • The NEURON Book
    • Cambridge: Cambridge University Press
    • Carnevale, T., and Hines, M. (2006). The NEURON Book. Cambridge: Cambridge University Press.
    • (2006)
    • Carnevale, T.1    Hines, M.2
  • 15
    • 77956344864 scopus 로고    scopus 로고
    • Real-time simulation of biologically realistic stochastic neurons in VLSI
    • Chen, H., Saïghi, S., Buhry, L., and Renaud, S. (2010). Real-time simulation of biologically realistic stochastic neurons in VLSI. IEEE Trans. Neural Netw. 21, 1511-1517.
    • (2010) IEEE Trans. Neural Netw. , vol.21 , pp. 1511-1517
    • Chen, H.1    Saïghi, S.2    Buhry, L.3    Renaud, S.4
  • 19
    • 78649342351 scopus 로고    scopus 로고
    • A common language for neuronal networks in software and hardware
    • doi:10.2417/1201001.1712
    • Davison, A., Muller, E., Brüderle, D., and Kremkow, J. (2010). A common language for neuronal networks in software and hardware. Neuromorph. Eng. doi:10.2417/1201001.1712
    • (2010) Neuromorph. Eng.
    • Davison, A.1    Muller, E.2    Brüderle, D.3    Kremkow, J.4
  • 21
    • 0033518170 scopus 로고    scopus 로고
    • Stable propagation of synchronous spiking in cortical neural networks
    • Diesmann, M., Gewaltig, M.-O., and Aertsen, A. (1999). Stable propagation of synchronous spiking in cortical neural networks. Nature 402, 529-533.
    • (1999) Nature , vol.402 , pp. 529-533
    • Diesmann, M.1    Gewaltig, M.-O.2    Aertsen, A.3
  • 22
    • 3943088427 scopus 로고    scopus 로고
    • Neuronal circuits of the neocortex
    • Douglas, R. J., and Martin, K. A. C. (2004). Neuronal circuits of the neocortex. Annu. Rev. Neurosci. 27, 419-451.
    • (2004) Annu. Rev. Neurosci. , vol.27 , pp. 419-451
    • Douglas, R.J.1    Martin, K.A.C.2
  • 23
    • 84890861283 scopus 로고    scopus 로고
    • PyNEST: a convenient interface to the NEST simulator
    • doi:10.3389/neuro.11.012.2008
    • Eppler, J. M., Helias, M., Muller, E., Diesmann, M., and Gewaltig, M. (2009). PyNEST: a convenient interface to the NEST simulator. Front. Neuroinform. 2:12. doi:10.3389/neuro.11.012.2008
    • (2009) Front. Neuroinform. , vol.2 , pp. 12
    • Eppler, J.M.1    Helias, M.2    Muller, E.3    Diesmann, M.4    Gewaltig, M.5
  • 27
    • 84867330171 scopus 로고    scopus 로고
    • Dynamical system guided mapping of quantitative neuronal models onto neuromorphic hardware
    • Gao, P., Benjamin, B., and Boahen, K. (2012). Dynamical system guided mapping of quantitative neuronal models onto neuromorphic hardware. IEEE Trans. Circuits Syst. I Regul. Pap. 59, 2383-2394.
    • (2012) IEEE Trans. Circuits Syst. I Regul. Pap. , vol.59 , pp. 2383-2394
    • Gao, P.1    Benjamin, B.2    Boahen, K.3
  • 28
    • 43949092150 scopus 로고    scopus 로고
    • NEST (neural simulation tool)
    • Gewaltig, M.-O., and Diesmann, M. (2007). NEST (neural simulation tool). Scholarpedia 2, 1430.
    • (2007) Scholarpedia , vol.2 , pp. 1430
    • Gewaltig, M.-O.1    Diesmann, M.2
  • 29
    • 84862165597 scopus 로고    scopus 로고
    • Tunable neuromimetic integrated system for emulating cortical neuron models
    • doi:10.3389/fnins.2011.00134
    • Grassia, F., Buhry, L., Lévi, T., Tomas, J., Destexhe, A., and Saïghi, S. (2011). Tunable neuromimetic integrated system for emulating cortical neuron models. Front. Neurosci. 5:134. doi:10.3389/fnins.2011.00134
    • (2011) Front. Neurosci. , vol.5 , pp. 134
    • Grassia, F.1    Buhry, L.2    Lévi, T.3    Tomas, J.4    Destexhe, A.5    Saïghi, S.6
  • 30
    • 84961365499 scopus 로고
    • Contour enhancement, short term memory, and constancies in reverberating neural networks
    • Grossberg, S. (1973). Contour enhancement, short term memory, and constancies in reverberating neural networks. Stud. Appl. Math. 52, 213-257.
    • (1973) Stud. Appl. Math. , vol.52 , pp. 213-257
    • Grossberg, S.1
  • 31
    • 0033959161 scopus 로고    scopus 로고
    • Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex
    • Gupta, A., Wang, Y., and Markram, H. (2000). Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science 287, 273-278.
    • (2000) Science , vol.287 , pp. 273-278
    • Gupta, A.1    Wang, Y.2    Markram, H.3
  • 32
    • 33344478663 scopus 로고    scopus 로고
    • The tempotron: a neuron that learns spike timing-based decisions
    • Gütig, R., and Sompolinsky, H. (2006). The tempotron: a neuron that learns spike timing-based decisions. Nat. Neurosci. 9, 420-428.
    • (2006) Nat. Neurosci. , vol.9 , pp. 420-428
    • Gütig, R.1    Sompolinsky, H.2
  • 34
    • 77955504196 scopus 로고    scopus 로고
    • NEURON and Python
    • doi:10.3389/neuro.11.001.2009
    • Hines, M., Davison, A. P., and Muller, E. (2009). NEURON and Python. Front. Neuroinform. 3:1. doi:10.3389/neuro.11.001.2009
    • (2009) Front. Neuroinform. , vol.3 , pp. 1
    • Hines, M.1    Davison, A.P.2    Muller, E.3
  • 36
    • 84862637851 scopus 로고    scopus 로고
    • Implementation of olfactory bulb glomerular layer computations in a digital neurosynaptic core
    • doi:10.3389/fnins.2012.00083
    • Imam, N., Cleland, T. A., Manohar, R., Merolla, P. A., Arthur, J. V., Akopyan, F., et al. (2012b). Implementation of olfactory bulb glomerular layer computations in a digital neurosynaptic core. Front. Neurosci. 6:83. doi:10.3389/fnins.2012.00083
    • (2012) Front. Neurosci. , vol.6 , pp. 83
    • Imam, N.1    Cleland, T.A.2    Manohar, R.3    Merolla, P.A.4    Arthur, J.V.5    Akopyan, F.6
  • 37
    • 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.
    • (2006) IEEE Trans. Neural Netw. , vol.17 , pp. 211-221
    • Indiveri, G.1    Chicca, E.2    Douglas, R.3
  • 38
    • 77957775251 scopus 로고    scopus 로고
    • Artificial cognitive systems: from VLSI networks of spiking neurons to neuromorphic cognition
    • Indiveri, G., Chicca, E., and Douglas, R. (2009). Artificial cognitive systems: from VLSI networks of spiking neurons to neuromorphic cognition. Cognit. Comput. 1, 119-127.
    • (2009) Cognit. Comput. , vol.1 , pp. 119-127
    • Indiveri, G.1    Chicca, E.2    Douglas, R.3
  • 40
    • 0035286497 scopus 로고    scopus 로고
    • Computational modeling of visual attention
    • Itti, L., and Koch, C. (2001). Computational modeling of visual attention. Nat. Rev. Neurosci. 2, 194-203.
    • (2001) Nat. Rev. Neurosci. , vol.2 , pp. 194-203
    • Itti, L.1    Koch, C.2
  • 41
    • 1842436050 scopus 로고    scopus 로고
    • The Echo State Approach to analysing and Training Recurrent Neural Networks
    • Technical Report GMD Report 148, German National Research Center for Information Technology St. Augustine
    • Jaeger, H. (2001). The "Echo State" Approach to analysing and Training Recurrent Neural Networks. Technical Report GMD Report 148. German National Research Center for Information Technology, St. Augustine.
    • (2001)
    • Jaeger, H.1
  • 43
    • 78649419669 scopus 로고    scopus 로고
    • Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition
    • Kremkow, J., Aertsen, A., and Kumar, A. (2010a). Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition. J. Neurosci. 30, 15760-15768.
    • (2010) J. Neurosci. , vol.30 , pp. 15760-15768
    • Kremkow, J.1    Aertsen, A.2    Kumar, A.3
  • 44
    • 77953326266 scopus 로고    scopus 로고
    • Functional consequences of correlated excitatory and inhibitory conductances in cortical networks
    • Kremkow, J., Perrinet, L. U., Masson, G. S., and Aertsen, A. (2010b). Functional consequences of correlated excitatory and inhibitory conductances in cortical networks. J. Comput. Neurosci. 28, 579-594.
    • (2010) J. Comput. Neurosci. , vol.28 , pp. 579-594
    • Kremkow, J.1    Perrinet, L.U.2    Masson, G.S.3    Aertsen, A.4
  • 45
  • 47
    • 0030798369 scopus 로고    scopus 로고
    • A computational model of the response of honey bee antennal lobe circuitry to odor mixtures: overshadowing, blocking and unblocking can arise from lateral inhibition
    • Linster, C., and Smith, B. H. (1997). A computational model of the response of honey bee antennal lobe circuitry to odor mixtures: overshadowing, blocking and unblocking can arise from lateral inhibition. Behav. Brain Res. 87, 1-14.
    • (1997) Behav. Brain Res. , vol.87 , pp. 1-14
    • Linster, C.1    Smith, B.H.2
  • 48
    • 0037387041 scopus 로고    scopus 로고
    • On the transmission of rate code in long feed-forward networks with excitatory-inhibitory balance
    • Litvak, V., Sompolinsky, H., Segev, I., and Abeles, M. (2003). On the transmission of rate code in long feed-forward networks with excitatory-inhibitory balance. J. Neurosci. 23, 3006-3015.
    • (2003) J. Neurosci. , vol.23 , pp. 3006-3015
    • Litvak, V.1    Sompolinsky, H.2    Segev, I.3    Abeles, M.4
  • 49
    • 77955487287 scopus 로고    scopus 로고
    • Bistable, irregular firing and population oscillations in a modular attractor memory network
    • doi:10.1371/journal.pcbi.1000803
    • Lundqvist, M., Compte, A., and Lansner, A. (2010). Bistable, irregular firing and population oscillations in a modular attractor memory network. PLoS Comput. Biol. 6:e1000803. doi:10.1371/journal.pcbi.1000803
    • (2010) PLoS Comput. Biol. , vol.6
    • Lundqvist, M.1    Compte, A.2    Lansner, A.3
  • 50
    • 33845421947 scopus 로고    scopus 로고
    • Attractor dynamics in a modular network model of neocortex
    • Lundqvist, M., Rehn, M., Djurfeldt, M., and Lansner, A. (2006). Attractor dynamics in a modular network model of neocortex. Network 17, 253-276.
    • (2006) Network , vol.17 , pp. 253-276
    • Lundqvist, M.1    Rehn, M.2    Djurfeldt, M.3    Lansner, A.4
  • 51
    • 0034321873 scopus 로고    scopus 로고
    • On the computational power of winner-take-all
    • Maass, W. (2000). On the computational power of winner-take-all. Neural Comput. 12, 2519-2535.
    • (2000) Neural Comput. , vol.12 , pp. 2519-2535
    • Maass, W.1
  • 52
    • 0036834701 scopus 로고    scopus 로고
    • Real-time computing without stable states: a new framework for neural compuation based on perturbation
    • Maass, W., Natschläger, T., and Markram, H. (2002). Real-time computing without stable states: a new framework for neural compuation based on perturbation. Neural Comput. 14, 2531-2560.
    • (2002) Neural Comput. , vol.14 , pp. 2531-2560
    • Maass, W.1    Natschläger, T.2    Markram, H.3
  • 53
    • 33745712893 scopus 로고    scopus 로고
    • Variability, compensation and homeostasis in neuron and network function
    • Marder, E., and Goaillard, J.-M. (2006). Variability, compensation and homeostasis in neuron and network function. Nat. Rev. Neurosci. 7, 563-574.
    • (2006) Nat. Rev. Neurosci. , vol.7 , pp. 563-574
    • Marder, E.1    Goaillard, J.-M.2
  • 54
    • 0032574789 scopus 로고    scopus 로고
    • Differential signaling via the same axon of neocortical pyramidal neurons
    • Markram, H., Wang, Y., and Tsodyks, M. (1998). Differential signaling via the same axon of neocortical pyramidal neurons. Proc. Natl. Acad. Sci. U.S.A. 95, 5323-5328.
    • (1998) Proc. Natl. Acad. Sci. U.S.A. , vol.95 , pp. 5323-5328
    • Markram, H.1    Wang, Y.2    Tsodyks, M.3
  • 58
    • 80053989520 scopus 로고    scopus 로고
    • A systematic method for configuring VLSI networks of spiking neurons
    • Neftci, E., Chicca, E., Indiveri, G., and Douglas, R. (2011). A systematic method for configuring VLSI networks of spiking neurons. Neural Comput. 23, 2457-2497.
    • (2011) Neural Comput. , vol.23 , pp. 2457-2497
    • Neftci, E.1    Chicca, E.2    Indiveri, G.3    Douglas, R.4
  • 60
    • 0004156740 scopus 로고    scopus 로고
    • An Introduction to Copulas
    • (Lecture Notes in Statistics), 1st Edn., New York: Springer
    • Nelsen, R. B. (1998). An Introduction to Copulas. (Lecture Notes in Statistics), 1st Edn. New York: Springer.
    • (1998)
    • Nelsen, R.B.1
  • 61
    • 70349237556 scopus 로고    scopus 로고
    • Computation with spikes in a winner-take-all network
    • Oster, M., Douglas, R., and Liu, S. (2009). Computation with spikes in a winner-take-all network. Neural Comput. 21, 2437-2465.
    • (2009) Neural Comput. , vol.21 , pp. 2437-2465
    • Oster, M.1    Douglas, R.2    Liu, S.3
  • 62
    • 3042757977 scopus 로고    scopus 로고
    • Intrinsic and circuit properties favor coincidence detection for decoding oscillatory input
    • Perez-Orive, J., Bazhenov, M., and Laurent, G. (2004). Intrinsic and circuit properties favor coincidence detection for decoding oscillatory input. J. Neurosci. 24, 6037-6047.
    • (2004) J. Neurosci. , vol.24 , pp. 6037-6047
    • Perez-Orive, J.1    Bazhenov, M.2    Laurent, G.3
  • 63
    • 0014104894 scopus 로고
    • Neuronal spike trains and stochastic point processes, II. Simultaneous spike trains
    • Perkel, D. H., Gerstein, G. L., and Moore, G. P. (1967). Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. Biophys. J. 7, 419-440.
    • (1967) Biophys. J. , vol.7 , pp. 419-440
    • Perkel, D.H.1    Gerstein, G.L.2    Moore, G.P.3
  • 64
    • 84865180086 scopus 로고    scopus 로고
    • Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardware
    • doi:10.3389/fnins.2012.00090
    • 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
  • 65
    • 0031820640 scopus 로고    scopus 로고
    • Spatiotemporal structure of cortical activity: properties and behavioral relevance
    • Prut, Y., Vaadia, E., Bergman, H., Haalman, I., Hamutal, S., and Abeles, M. (1998). Spatiotemporal structure of cortical activity: properties and behavioral relevance. J. Neurophysiol. 79, 2857-2874.
    • (1998) J. Neurophysiol. , vol.79 , pp. 2857-2874
    • Prut, Y.1    Vaadia, E.2    Bergman, H.3    Haalman, I.4    Hamutal, S.5    Abeles, M.6
  • 66
    • 77955049085 scopus 로고    scopus 로고
    • PAX: a mixed hardware/software simulation platform for spiking neural networks
    • Renaud, S., Tomas, J., Lewis, N., Bornat, Y., Daouzli, A., Rudolph, M., et al. (2010). PAX: a mixed hardware/software simulation platform for spiking neural networks. Neural Netw. 23, 905-916.
    • (2010) Neural Netw. , vol.23 , pp. 905-916
    • Renaud, S.1    Tomas, J.2    Lewis, N.3    Bornat, Y.4    Daouzli, A.5    Rudolph, M.6
  • 71
    • 84878892702 scopus 로고    scopus 로고
    • Ten thousand times faster: classifying multidimensional data on a spiking neuromorphic hardware system
    • 11: Computational Neuroscience&Neurotechnology Bernstein Conference&Neurex Annual Meeting 2011, doi:10.3389/conf.fncom.2011.53.00109
    • 11: Computational Neuroscience&Neurotechnology Bernstein Conference&Neurex Annual Meeting 2011 109. doi:10.3389/conf.fncom.2011.53.00109
    • (2011) Front. Comput. Neurosci. , pp. 109
    • Schmuker, M.1    Brüderle, D.2    Schrader, S.3    Nawrot, M.P.4
  • 72
    • 84855588292 scopus 로고    scopus 로고
    • Parallel Representation of Stimulus Identity and Intensity in a Dual Pathway Model Inspired by the Olfactory System of the Honeybee
    • doi:10.3389/fneng.2011.00017
    • Schmuker, M., Yamagata, N., Nawrot, M. P., and Menzel, R. (2011b). Parallel Representation of Stimulus Identity and Intensity in a Dual Pathway Model Inspired by the Olfactory System of the Honeybee. Front. Neuroeng. 4:17. doi:10.3389/fneng.2011.00017
    • (2011) Front. Neuroeng. , vol.4 , pp. 17
    • Schmuker, M.1    Yamagata, N.2    Nawrot, M.P.3    Menzel, R.4
  • 73
    • 38049165680 scopus 로고    scopus 로고
    • Processing and classification of chemical data inspired by insect olfaction
    • Schmuker, M., and Schneider, G. (2007). Processing and classification of chemical data inspired by insect olfaction. Proc. Natl. Acad. Sci. U.S.A. 104, 20285-20289.
    • (2007) Proc. Natl. Acad. Sci. U.S.A. , vol.104 , pp. 20285-20289
    • Schmuker, M.1    Schneider, G.2
  • 74
    • 84855244551 scopus 로고    scopus 로고
    • A compositionality machine realized by a hierarchic architecture of synfire chains
    • doi:10.3389/fncom.2010.00154
    • Schrader, S., Diesmann, M., and Morrison, A. (2010). A compositionality machine realized by a hierarchic architecture of synfire chains. Front. Comput. Neurosci. 4:154. doi:10.3389/fncom.2010.00154
    • (2010) Front. Comput. Neurosci. , vol.4 , pp. 154
    • Schrader, S.1    Diesmann, M.2    Morrison, A.3
  • 75
    • 57449088226 scopus 로고    scopus 로고
    • Detecting synfire chain activity using massively parallel spike train recording
    • Schrader, S., Grün, S., Diesmann, M., and Gerstein, G. (2008). Detecting synfire chain activity using massively parallel spike train recording. J. Neurophysiol. 100, 2165-2176.
    • (2008) J. Neurophysiol. , vol.100 , pp. 2165-2176
    • Schrader, S.1    Grün, S.2    Diesmann, M.3    Gerstein, G.4
  • 77
    • 73949142431 scopus 로고    scopus 로고
    • Synaptic computation underlying probabilistic inference
    • Soltani, A., and Wang, X.-J. (2010). Synaptic computation underlying probabilistic inference. Nat. Neurosci. 13, 112-119.
    • (2010) Nat. Neurosci. , vol.13 , pp. 112-119
    • Soltani, A.1    Wang, X.J.2
  • 78
    • 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.
    • (2000) Nat. Neurosci. , vol.3 , pp. 919-926
    • Song, S.1    Miller, K.D.2    Abbott, L.F.3
  • 79
    • 0030666028 scopus 로고    scopus 로고
    • Impaired odour discrimination on desynchronization of odour-encoding neural assemblies
    • Stopfer, M., Bhagavan, S., Smith, B. H., and Laurent, G. (1997). Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390, 70-74.
    • (1997) Nature , vol.390 , pp. 70-74
    • Stopfer, M.1    Bhagavan, S.2    Smith, B.H.3    Laurent, G.4
  • 81
    • 0031018015 scopus 로고    scopus 로고
    • The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability
    • Tsodyks, M. V., and Markram, H. (1997). The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc. Natl. Acad. Sci. U.S.A. 94, 719-723.
    • (1997) Proc. Natl. Acad. Sci. U.S.A. , vol.94 , pp. 719-723
    • Tsodyks, M.V.1    Markram, H.2
  • 82
    • 0029835892 scopus 로고    scopus 로고
    • Chaos in neuronal networks with balanced excitatory and inhibitory activity
    • van Vreeswijk, C., and Sompolinsky, H. (1996). Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274, 1724-1726.
    • (1996) Science , vol.274 , pp. 1724-1726
    • van Vreeswijk, C.1    Sompolinsky, H.2
  • 83
    • 28044448948 scopus 로고    scopus 로고
    • Signal propagation and logic gating in networks of integrate-and-fire neurons
    • Vogels, T. P., and Abbott, L. F. (2005). Signal propagation and logic gating in networks of integrate-and-fire neurons. J. Neurosci. 25, 10786-10795.
    • (2005) J. Neurosci. , vol.25 , pp. 10786-10795
    • Vogels, T.P.1    Abbott, L.F.2
  • 84
    • 33846098196 scopus 로고    scopus 로고
    • Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses
    • Vogelstein, R., Mallik, U., Vogelstein, J., and Cauwenberghs, G. (2007). Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses. IEEE Trans. Neural Netw. 18, 253-265.
    • (2007) IEEE Trans. Neural Netw. , vol.18 , pp. 253-265
    • Vogelstein, R.1    Mallik, U.2    Vogelstein, J.3    Cauwenberghs, G.4
  • 85
    • 27144466423 scopus 로고    scopus 로고
    • Role of GABAergic inhibition in shaping odor-evoked spatiotemporal patterns in the drosophila antennal lobe
    • Wilson, R. I., and Laurent, G. (2005). Role of GABAergic inhibition in shaping odor-evoked spatiotemporal patterns in the drosophila antennal lobe. J. Neurosci. 25, 9069-9079.
    • (2005) J. Neurosci. , vol.25 , pp. 9069-9079
    • Wilson, R.I.1    Laurent, G.2
  • 86
    • 0036583894 scopus 로고    scopus 로고
    • New attractor states for synchronous activity in synfire chains with excitatory and inhibitory coupling
    • Yazdanbakhsh, A., Babadi, B., Rouhani, S., Arabzadeh, E., and Abbassian, A. (2002). New attractor states for synchronous activity in synfire chains with excitatory and inhibitory coupling. Biol. Cybern. 86, 367-378.
    • (2002) Biol. Cybern. , vol.86 , pp. 367-378
    • Yazdanbakhsh, A.1    Babadi, B.2    Rouhani, S.3    Arabzadeh, E.4    Abbassian, A.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.