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Bartolozzi C, Indiveri G (2007) Synaptic dynamics in analog VLSI. Neural Comput 19:2581-603 [PubMed]

References and models cited by this paper

References and models that cite this paper

Anderson JS, Carandini M, Ferster D (2000) Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. J Neurophysiol 84:909-26 [Journal] [PubMed]

Arthur J, Boahen K (2004) Recurrently connected silicon neurons with active dendrites for one-shot learning IEEE Intl Joint Conf Neural Networks 3:1699-1704

Arthur J, Boahen K (2006) Learning in silicon: Timing is everything Advances in neural information processing systems, Weiss Y:Scholkopf B:Platt J, ed.

Bartolozzi C, Indiveri G (2006) Silicon synaptic homeostasis Brain Inspired Cognitive Systems

Boahen K (1998) Communicating neuronal ensembles between neuromorphic chips Neuromorphic systems engineering, Smith S:Hamilton A, ed.

Boahen KA (1997) Retinomorphic vision systems: Reverse engineering the vertebrate retina Unpublished doctoral dissertation, California Institute of Technology

Boegerhausen M, Suter P, Liu SC (2003) Modeling short-term synaptic depression in silicon. Neural Comput 15:331-48 [Journal] [PubMed]

Bofill A, Murray A, Thompson D (2002) Circuits for VLSI implementation of temporally asymmetric Hebbian learning Advances in neural information processing systems, Dietlerich TG:Becker S:Ghahramani Z, ed.

Borgstrom T, Ismail M, Bibyk S (1990) Programmable current-mode neural network for implementation in analogue MOS VLSI IEEE Proc 137:175-184

Carandini M, Heeger DJ, Movshon JA (1997) Linearity and normalization in simple cells of the macaque primary visual cortex. J Neurosci 17:8621-44 [PubMed]

Chance FS, Abbott LF, Reyes AD (2002) Gain modulation from background synaptic input. Neuron 35:773-82 [PubMed]

Chance FS, Nelson SB, Abbott LF (1998) Synaptic depression and the temporal response characteristics of V1 cells. J Neurosci 18:4785-99 [PubMed]

Chicca E (2006) A neuromorphic VLSI system for modeling spike-based cooperative competitive neural networks Unpublished doctoral dissertation, ETH Zurich

Chicca E, Badoni D, Dante V, D'Andreagiovanni M, Salina G, Carota L, Fusi S, Del Giudice P (2003) A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory. IEEE Trans Neural Netw 14:1297-307 [Journal] [PubMed]

Chicca E, Indiveri G, Douglas R (2003) An adaptive silicon synapse IEEE International Symposium on Circuits and Systems

Destexhe A, Mainen ZF, Sejnowski TJ (1998) Kinetic models of synaptic transmission Methods In Neuronal Modeling, Koch C:Segev I, ed. pp.1

   Kinetic synaptic models applicable to building networks (Destexhe et al 1998) [Model]

Fusi S, Annunziato M, Badoni D, Salamon A, Amit DJ (2000) Spike-driven synaptic plasticity: theory, simulation, VLSI implementation. Neural Comput 12:2227-58 [PubMed]

Gordon C, Farquhar E, Hasler P (2004) A family of floating-gate adapting synapses based upon transistor channel models IEEE Intl Symposium on Circuits and Systems 1:317-320

G├╝tig R, Sompolinsky H (2006) The tempotron: a neuron that learns spike timing-based decisions. Nat Neurosci 9:420-8 [Journal] [PubMed]

Hertz J, Krogh A, Palmer RG (1991) Introduction to the Theory of Neural Computation.

Horiuchi T, Hynna K (2001) A VLSI-based model of azimuthal echolocation in the big brown bat Autonomous Robots 11:241-247

Hynna K, Boahen K (2006) Space-rate coding in an adaptive silicon neuron. Neural Netw 14:645-56

Hynna KM, Boahen K (2006) Neuronal ion-channel dynamics in silicon IEEE Intl Symposium on Circuits and Systems :3614-3617

Indiveri G (2000) Modeling selective attention using a neuromorphic analog VLSI device. Neural Comput 12:2857-80 [PubMed]

Indiveri G, Chicca E, Douglas R (2006) A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Trans Neural Netw 17:211-21 [Journal] [PubMed]

Kandel ER, Schwartz JH, Jessell TM (2000) Principles of neural science (4th ed), Kandel ER:Schwartz JH:Jessell TM, ed.

Koch C (1999) Biophysics Of Computation: Information Processing in Single Neurons

Koch C, Poggio T, Torre V (1983) Nonlinear interactions in a dendritic tree: localization, timing, and role in information processing. Proc Natl Acad Sci U S A 80:2799-802 [PubMed]

Lazzaro JP (1994) Low-power silicon axons, neurons, and synapses Silicon implementation of pulse coded neural networks, Zaghloul ME:Meador JL:Newcomb RW, ed. pp.153

Liu SC, Kramer J, Indiveri G, Delbruck T, Burg T, Douglas R (2006) Orientation-selective aVLSI spiking neurons. Neural Netw 14:629-43

Liu SC, Kramer J, Indiveri G, Delbruck T, Douglas R (2002) Analog VLSI: Circuits and principles

Mead C (1989) Analog VLSI and neural systems.

Merolla P, Boahen K (2004) A recurrent model of orientation maps with simple and complex cells Advances in neural information processing systems, Thrun S:Saul LK:Scholkopf B, ed. pp.995

Mitra S, Fusi S, Indiveri G (2006) A VLSI spike-driven dynamic synapse which learns only when necessary IEEE Int Symposium On Circuits And Systems :2777-2780

Morris RG, Davis S, Butcher SP (1990) Hippocampal synaptic plasticity and NMDA receptors: a role in information storage? Philos Trans R Soc Lond B Biol Sci 329:187-204 [Journal] [PubMed]

Murray AF (1998) Pulse-based computation in VLSI neural networks Pulsed neural networks, Maass W:Bishop CM, ed. pp.87

Northmore DPM, Elias JG (1998) Building silicon nervous systems with dendritic tree neuromorphs Pulsed neural networks, Maass W:Bishop CM, ed. pp.135

Rasche C, Hahnloser RH (2001) Silicon synaptic depression. Biol Cybern 84:57-62 [Journal] [PubMed]

Satyanarayana S, Tsividis Y, Graf H (1992) A reconfigurable VLSI neural network IEEE J Solid-State Circuits 27:67-81

Shi R, Horiuchi T (2004) A summating, exponentially-decaying CMOS synapse for spiking neural systems Advances in neural information processing systems, Thrun S:Saul L:Scholkopf B, ed.

Shi R, Horiuchi T (2004) A VLSI model of the bat lateral superior olive for azimuthal echolocation. Proc Intl Symposium On Circuits and Systems 4:900-903

Turrigiano GG, Leslie KR, Desai NS, Rutherford LC, Nelson SB (1998) Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature 391:892-6 [Journal] [PubMed]

Wang XJ (1999) Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory. J Neurosci 19:9587-603 [PubMed]

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