III. VLSI D EVICE ' S N EURONS
Fig. 2. Circuit diagram of the I&F neuron. See Section€III-A for
Fig. 3. (a) Mean response of all neurons in the array to increas
Fig. 4. (a) Raster plot showing the response of the array of neu
Fig. 5. Mean power dissipation of the neuron as a function of $V
Fig. 6. Excitatory synapse circuit. The bistability circuit comp
Fig. 7. (a) Spike traces obtained by stimulating the short-term
Fig. 8. Synaptic efficacy STDP circuit.
Fig. 9. Changes in synaptic efficacy, as a function of the diffe
Fig. 10. (a) Mean probability of LTP over all STDP synapses in t
R. J. Vogelstein, U. Mallik, and G. Cauwenberghs, Silicon spike-
F. Tenore, R. Etienne-Cummings, and M. Lewis, A programmable arr
E. Chicca, D. Badoni, V. Dante, M. D'Andreagiovanni, G. Salina,
S. Fusi, M. Annunziato, D. Badoni, A. Salamon, and D. Amit, Spik
P. Merolla and K. Boahen, A recurrent model of orientation maps
S.-C. Liu and R. Douglas, Temporal coding in a silicon network o
A. Bofill-i Petit and A. F. Murray, Synchrony detection and ampl
T. Y. W. Choi, B. E. Shi, and K. Boahen, An on-off orientation s
G. Indiveri, A neuromorphic VLSI device for implementing 2-D sel
J. Lazzaro, J. Wawrzynek, M. Mahowald, M. Sivilotti, and D. Gill
M. Mahowald, An Analog VLSI System for Stereoscopic Vision . Bos
K. Boahen, Communicating neuronal ensembles between neuromorphic
S. R. Deiss, R. J. Douglas, and A. M. Whatley, A pulse-coded com
G. Indiveri, Neuromorphic bistable VLSI synapses with spike-timi
P. Häfliger, M. Mahowald, and L. Watts, A spike based learning n
H. Markram, J. Lübke, M. Frotscher, and B. Sakmann, Regulation o
G.-Q. Bi and M.-M. Poo, Synaptic modifications in cultured hippo
L. F. Abbott and S. Song, Asymmetric Hebbian learning, spike tim
R. Kempter, W. Gerstner, and J. L. van Hemmen, Hebbian learning
M. C. W. van Rossum, G.-Q. Bi, and G. G. Turrigiano, Stable Hebb
W. Senn, Beyond spike timing: The role of nonlinear plasticity a
V. Dante, P. Del Giudice, and A. M. Whatley, PCI-AER hardware an
C. Mead, Analog VLSI and Neural Systems . Reading, MA: Addison-W
E. M. Izhikevich, Which model to use for cortical spiking neuron
S. R. Schultz and M. A. Jabri, Analogue VLSI 'integrate-and-fire
A. van Schaik, Building blocks for electronic spiking neural net
E. Culurciello, R. Etienne-Cummings, and K. Boahen, Arbitrated a
B. W. Connors, M. J. Gutnick, and D. A. Prince, Electrophysiolog
S.-C. Liu, J. Kramer, G. Indiveri, T. Delbrück, and R. Douglas,
D. D. Ben Dayan Rubin, E. Chicca, and G. Indiveri, Characterizin
C. Diorio, P. Hasler, B. Minch, and C. Mead, A single-transistor
G. Indiveri, R. Mürer, and J. Kramer, Active vision using an ana
S.-C. Liu, J. Kramer, G. Indiveri, T. Delbruck, T. Burg, and R.
E. Chicca, G. Indiveri, and R. Douglas, An adaptive silicon syna
W. Maass and E. D. Sontag, Neural systems as nonlinear filters,
R. S. Zucker and W. G. Regehr, Short-term synaptic plasticity, A
T. V. P. Bliss and G. L. Collingridge, A synaptic model of memor
A. M. Zador and L. E. Dobrunz, Dynamic synapses in cortex, Neuro
C. Rasche and R. Hahnloser, Silicon synaptic depression, Biol. C
M. Boegerhausen, P. Suter, and S.-C. Liu, Modeling short-term sy
F. S. Chance, S. B. Nelson, and L. F. Abbott, Synaptic depressio
L. Abbott, K. Sen, J. Varela, and S. Nelson, Synaptic depression
C. C. H. Petersen, R. C. Malenka, R. A. Nicoll, and J. J. Hopfie
D. J. Amit and S. Fusi, Dynamic learning in neural networks with
K. Boahen, A burst-mode word-serial address-event link III: Anal
P. Lichtsteiner, T. Delbruck, and J. Kramer, Improved ON/OFF tem
J. Kramer, An integrated optical transient sensor, IEEE Trans. C
A. van Schaik and S. Liu, AER EAR: A matched silicon cochlea pai