A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity

Indiveri G, Chicca E, Douglas RJ (2006)
IEEE Transactions on Neural Networks 17(1): 211-221.

Zeitschriftenaufsatz | Veröffentlicht| Englisch
 
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Autor/in
Indiveri, G.; Chicca, ElisabettaUniBi ; Douglas, R. J.
Abstract / Bemerkung
We present a mixed-mode analog/digital VLSI device comprising an array of leaky integrate-and-fire (I&F) neurons, adaptive synapses with spike-timing dependent plasticity, and an asynchronous event based communication infrastructure that allows the user to (re)con figure networks of spiking neurons with arbitrary topologies. The asynchronous communication protocol used by the silicon neurons to transmit spikes (events) off-chip and the silicon synapses to receive spikes from the outside is based on the "address-event representation" (AER). We describe the analog circuits designed to implement the silicon neurons and synapses and present experimental data showing the neuron's response properties and the synapses characteristics, in response to AER input spike trains. Our results indicate that these circuits can be used in massively parallel VLSI networks of I&F neurons to simulate real-time complex spike-based learning algorithms.
Stichworte
spike-based learning; address-event representation (AER); neuromorphic circuits; spike-timing; analog VLSI; integrate-and-fire (I &; F) neurons; dependent plasticity (STDP)
Erscheinungsjahr
2006
Zeitschriftentitel
IEEE Transactions on Neural Networks
Band
17
Ausgabe
1
Seite(n)
211-221
ISSN
1045-9227
Page URI
https://pub.uni-bielefeld.de/record/2426586

Zitieren

Indiveri G, Chicca E, Douglas RJ. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks. 2006;17(1):211-221.
Indiveri, G., Chicca, E., & Douglas, R. J. (2006). A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks, 17(1), 211-221. doi:10.1109/TNN.2005.860850
Indiveri, G., Chicca, E., and Douglas, R. J. (2006). A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks 17, 211-221.
Indiveri, G., Chicca, E., & Douglas, R.J., 2006. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks, 17(1), p 211-221.
G. Indiveri, E. Chicca, and R.J. Douglas, “A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity”, IEEE Transactions on Neural Networks, vol. 17, 2006, pp. 211-221.
Indiveri, G., Chicca, E., Douglas, R.J.: A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks. 17, 211-221 (2006).
Indiveri, G., Chicca, Elisabetta, and Douglas, R. J. “A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity”. IEEE Transactions on Neural Networks 17.1 (2006): 211-221.
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Kalita H, Krishnaprasad A, Choudhary N, Das S, Dev D, Ding Y, Tetard L, Chung HS, Jung Y, Roy T., Sci Rep 9(1), 2019
PMID: 30631087
Odor Recognition with a Spiking Neural Network for Bioelectronic Nose.
Li M, Ruan H, Qi Y, Guo T, Wang P, Pan G., Sensors (Basel) 19(5), 2019
PMID: 30813574
An On-Chip Learning Neuromorphic Autoencoder With Current-Mode Transposable Memory Read and Virtual Lookup Table.
Cho H, Son H, Seong K, Kim B, Park HJ, Sim JY., IEEE Trans Biomed Circuits Syst 12(1), 2018
PMID: 29377804
Mimicking Synaptic Plasticity and Neural Network Using Memtranstors.
Shen JX, Shang DS, Chai YS, Wang SG, Shen BG, Sun Y., Adv Mater 30(12), 2018
PMID: 29399893
Spike-Timing Dependent Plasticity in Unipolar Silicon Oxide RRAM Devices.
Zarudnyi K, Mehonic A, Montesi L, Buckwell M, Hudziak S, Kenyon AJ., Front Neurosci 12(), 2018
PMID: 29472837
Weighted Synapses Without Carry Operations for RRAM-Based Neuromorphic Systems.
Liao Y, Deng N, Wu H, Gao B, Zhang Q, Qian H., Front Neurosci 12(), 2018
PMID: 29615856
Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation.
Parihar A, Jerry M, Datta S, Raychowdhury A., Front Neurosci 12(), 2018
PMID: 29670508
Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing.
Frascaroli J, Brivio S, Covi E, Spiga S., Sci Rep 8(1), 2018
PMID: 29740004
An On-Chip Trainable and the Clock-Less Spiking Neural Network With 1R Memristive Synapses.
Shukla A, Ganguly U., IEEE Trans Biomed Circuits Syst 12(4), 2018
PMID: 29993721
Artificial Synapses Emulated by an Electrolyte-Gated Tungsten-Oxide Transistor.
Yang JT, Ge C, Du JY, Huang HY, He M, Wang C, Lu HB, Yang GZ, Jin KJ., Adv Mater (), 2018
PMID: 29974526
Spiking Elementary Motion Detector in Neuromorphic Systems.
Milde MB, Bertrand OJN, Ramachandran H, Egelhaaf M, Chicca E., Neural Comput 30(9), 2018
PMID: 30021082
Breaking Liebig's Law: An Advanced Multipurpose Neuromorphic Engine.
Wang R, van Schaik A., Front Neurosci 12(), 2018
PMID: 30210278
Artificial Shape Perception Retina Network Based on Tunable Memristive Neurons.
Bao L, Kang J, Fang Y, Yu Z, Wang Z, Yang Y, Cai Y, Huang R., Sci Rep 8(1), 2018
PMID: 30213964
Ionotronic Halide Perovskite Drift-Diffusive Synapses for Low-Power Neuromorphic Computation.
John RA, Yantara N, Ng YF, Narasimman G, Mosconi E, Meggiolaro D, Kulkarni MR, Gopalakrishnan PK, Nguyen CA, De Angelis F, Mhaisalkar SG, Basu A, Mathews N., Adv Mater 30(51), 2018
PMID: 30334296
Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.
Thakur CS, Molin JL, Cauwenberghs G, Indiveri G, Kumar K, Qiao N, Schemmel J, Wang R, Chicca E, Olson Hasler J, Seo JS, Yu S, Cao Y, van Schaik A, Etienne-Cummings R., Front Neurosci 12(), 2018
PMID: 30559644
A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach.
Jimenez-Fernandez A, Cerezuela-Escudero E, Miro-Amarante L, Dominguez-Moralse MJ, de Asis Gomez-Rodriguez F, Linares-Barranco A, Jimenez-Moreno G., IEEE Trans Neural Netw Learn Syst 28(4), 2017
PMID: 27479979
Complete Neuron-Astrocyte Interaction Model: Digital Multiplierless Design and Networking Mechanism.
Haghiri S, Ahmadi A, Saif M., IEEE Trans Biomed Circuits Syst 11(1), 2017
PMID: 27662685
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing.
Wang Z, Joshi S, Savel'ev SE, Jiang H, Midya R, Lin P, Hu M, Ge N, Strachan JP, Li Z, Wu Q, Barnell M, Li GL, Xin HL, Williams RS, Xia Q, Yang JJ., Nat Mater 16(1), 2017
PMID: 27669052
A Hybrid CMOS-Memristor Neuromorphic Synapse.
Azghadi MR, Linares-Barranco B, Abbott D, Leong PH., IEEE Trans Biomed Circuits Syst 11(2), 2017
PMID: 28026782
A 4-fJ/Spike Artificial Neuron in 65 nm CMOS Technology.
Sourikopoulos I, Hedayat S, Loyez C, Danneville F, Hoel V, Mercier E, Cappy A., Front Neurosci 11(), 2017
PMID: 28360831
A Synaptic Transistor based on Quasi-2D Molybdenum Oxide.
Yang CS, Shang DS, Liu N, Shi G, Shen X, Yu RC, Li YQ, Sun Y., Adv Mater 29(27), 2017
PMID: 28485032
A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.
Soleimani H, Drakakis EM., IEEE Trans Biomed Circuits Syst 11(3), 2017
PMID: 28410111
2D MoS2 Neuromorphic Devices for Brain-Like Computational Systems.
Jiang J, Guo J, Wan X, Yang Y, Xie H, Niu D, Yang J, He J, Gao Y, Wan Q., Small 13(29), 2017
PMID: 28561996
Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.
Milde MB, Blum H, Dietmüller A, Sumislawska D, Conradt J, Indiveri G, Sandamirskaya Y., Front Neurorobot 11(), 2017
PMID: 28747883
Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.
Dutta S, Kumar V, Shukla A, Mohapatra NR, Ganguly U., Sci Rep 7(1), 2017
PMID: 28811481
A High-On/Off-Ratio Floating-Gate Memristor Array on a Flexible Substrate via CVD-Grown Large-Area 2D Layer Stacking.
Vu QA, Kim H, Nguyen VL, Won UY, Adhikari S, Kim K, Lee YH, Yu WJ., Adv Mater 29(44), 2017
PMID: 28949418
Scalable excitatory synaptic circuit design using floating gate based leaky integrators.
Kornijcuk V, Lim H, Kim I, Park JK, Lee WS, Choi JH, Choi BJ, Jeong DS., Sci Rep 7(1), 2017
PMID: 29242504
Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film.
Chang CT, Zeng F, Li XJ, Dong WS, Lu SH, Gao S, Pan F., Sci Rep 6(), 2016
PMID: 26739613
Stochastic phase-change neurons.
Tuma T, Pantazi A, Le Gallo M, Sebastian A, Eleftheriou E., Nat Nanotechnol 11(8), 2016
PMID: 27183057
Mapping Generative Models onto a Network of Digital Spiking Neurons.
Pedroni BU, Das S, Arthur JV, Merolla PA, Jackson BL, Modha DS, Kreutz-Delgado K, Cauwenberghs G., IEEE Trans Biomed Circuits Syst 10(4), 2016
PMID: 27214915
Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator.
Kornijcuk V, Lim H, Seok JY, Kim G, Kim SK, Kim I, Choi BJ, Jeong DS., Front Neurosci 10(), 2016
PMID: 27242416
Structural Plasticity Denoises Responses and Improves Learning Speed.
Spiess R, George R, Cook M, Diehl PU., Front Comput Neurosci 10(), 2016
PMID: 27660610
Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses.
Serb A, Bill J, Khiat A, Berdan R, Legenstein R, Prodromakis T., Nat Commun 7(), 2016
PMID: 27681181
Doping modulated carbon nanotube synapstors for a spike neuromorphic module.
Shen AM, Kim K, Tudor A, Lee D, Chen Y., Small 11(13), 2015
PMID: 25423906
Controlling Ion Conductance and Channels to Achieve Synaptic-like Frequency Selectivity.
Lu S, Zeng F, Dong W, Liu A, Li X, Luo J., Nanomicro Lett 7(2), 2015
PMID: 30464962
Digital implementation of a biological astrocyte model and its application.
Soleimani H, Bavandpour M, Ahmadi A, Abbott D., IEEE Trans Neural Netw Learn Syst 26(1), 2015
PMID: 25532161
Switched-capacitor realization of presynaptic short-term-plasticity and stop-learning synapses in 28 nm CMOS.
Noack M, Partzsch J, Mayr CG, Hänzsche S, Scholze S, Höppner S, Ellguth G, Schüffny R., Front Neurosci 9(), 2015
PMID: 25698914
On the non-STDP behavior and its remedy in a floating-gate synapse.
Gopalakrishnan R, Basu A., IEEE Trans Neural Netw Learn Syst 26(10), 2015
PMID: 25675466
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.
Probst D, Petrovici MA, Bytschok I, Bill J, Pecevski D, Schemmel J, Meier K., Front Comput Neurosci 9(), 2015
PMID: 25729361
Spatiotemporal features for asynchronous event-based data.
Lagorce X, Ieng SH, Clady X, Pfeiffer M, Benosman RB., Front Neurosci 9(), 2015
PMID: 25759637
Plasticity in memristive devices for spiking neural networks.
Saïghi S, Mayr CG, Serrano-Gotarredona T, Schmidt H, Lecerf G, Tomas J, Grollier J, Boyn S, Vincent AF, Querlioz D, La Barbera S, Alibart F, Vuillaume D, Bichler O, Gamrat C, Linares-Barranco B., Front Neurosci 9(), 2015
PMID: 25784849
A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.
Qiao N, Mostafa H, Corradi F, Osswald M, Stefanini F, Sumislawska D, Indiveri G., Front Neurosci 9(), 2015
PMID: 25972778
Reliability of neuronal information conveyed by unreliable neuristor-based leaky integrate-and-fire neurons: a model study.
Lim H, Kornijcuk V, Seok JY, Kim SK, Kim I, Hwang CS, Jeong DS., Sci Rep 5(), 2015
PMID: 25966658
A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks.
Wang RM, Hamilton TJ, Tapson JC, van Schaik A., Front Neurosci 9(), 2015
PMID: 26041985
Breaking the millisecond barrier on SpiNNaker: implementing asynchronous event-based plastic models with microsecond resolution.
Lagorce X, Stromatias E, Galluppi F, Plana LA, Liu SC, Furber SB, Benosman RB., Front Neurosci 9(), 2015
PMID: 26106288
Single pairing spike-timing dependent plasticity in BiFeO3 memristors with a time window of 25 ms to 125 μs.
Du N, Kiani M, Mayr CG, You T, Bürger D, Skorupa I, Schmidt OG, Schmidt H., Front Neurosci 9(), 2015
PMID: 26175666
A generalized analog implementation of piecewise linear neuron models using CCII building blocks.
Soleimani H, Ahmadi A, Bavandpour M, Sharifipoor O., Neural Netw 51(), 2014
PMID: 24365534
Artificial synapse network on inorganic proton conductor for neuromorphic systems.
Zhu LQ, Wan CJ, Guo LQ, Shi Y, Wan Q., Nat Commun 5(), 2014
PMID: 24452193
A framework for plasticity implementation on the SpiNNaker neural architecture.
Galluppi F, Lagorce X, Stromatias E, Pfeiffer M, Plana LA, Furber SB, Benosman RB., Front Neurosci 8(), 2014
PMID: 25653580
Tunable low energy, compact and high performance neuromorphic circuit for spike-based synaptic plasticity.
Rahimi Azghadi M, Iannella N, Iannella N, Al-Sarawi S, Abbott D., PLoS One 9(2), 2014
PMID: 24551089
Efficient spiking neural network model of pattern motion selectivity in visual cortex.
Beyeler M, Richert M, Dutt ND, Krichmar JL., Neuroinformatics 12(3), 2014
PMID: 24497233
Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array.
Eryilmaz SB, Kuzum D, Jeyasingh R, Kim S, BrightSky M, Lam C, Wong HS., Front Neurosci 8(), 2014
PMID: 25100936
PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.
Stefanini F, Neftci EO, Sheik S, Indiveri G., Front Neuroinform 8(), 2014
PMID: 25232314
Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms.
Petrovici MA, Vogginger B, Müller P, Breitwieser O, Lundqvist M, Muller L, Ehrlich M, Destexhe A, Lansner A, Schüffny R, Schemmel J, Meier K., PLoS One 9(10), 2014
PMID: 25303102
Multiprotocol-induced plasticity in artificial synapses.
Kornijcuk V, Kavehei O, Lim H, Seok JY, Kim SK, Kim I, Lee WS, Choi BJ, Jeong DS., Nanoscale 6(24), 2014
PMID: 25373422
A carbon nanotube synapse with dynamic logic and learning.
Kim K, Chen CL, Truong Q, Shen AM, Chen Y., Adv Mater 25(12), 2013
PMID: 23281020
A learning-enabled neuron array IC based upon transistor channel models of biological phenomena.
Brink S, Nease S, Hasler P, Ramakrishnan S, Wunderlich R, Basu A, Degnan B., IEEE Trans Biomed Circuits Syst 7(1), 2013
PMID: 23853281
An FPGA Implementation of a Polychronous Spiking Neural Network with Delay Adaptation.
Wang R, Cohen G, Stiefel KM, Hamilton TJ, Tapson J, van Schaik A., Front Neurosci 7(), 2013
PMID: 23408739
STDP and STDP variations with memristors for spiking neuromorphic learning systems.
Serrano-Gotarredona T, Masquelier T, Prodromakis T, Indiveri G, Linares-Barranco B., Front Neurosci 7(), 2013
PMID: 23423540
Six networks on a universal neuromorphic computing substrate.
Pfeil T, Grübl A, Jeltsch S, Müller E, Müller P, Petrovici MA, Schmuker M, Brüderle D, Schemmel J, Meier K., Front Neurosci 7(), 2013
PMID: 23423583
A neuromorphic VLSI design for spike timing and rate based synaptic plasticity.
Rahimi Azghadi M, Al-Sarawi S, Abbott D, Iannella N, Iannella N., Neural Netw 45(), 2013
PMID: 23566339
Low-temperature fabrication of spiking soma circuits using nanocrystalline-silicon TFTs.
Subramaniam A, Cantley KD, Stiegler HJ, Chapman RA, Vogel EM., IEEE Trans Neural Netw Learn Syst 24(9), 2013
PMID: 24808583
Spike-timing dependent plasticity in a transistor-selected resistive switching memory.
Ambrogio S, Balatti S, Nardi F, Facchinetti S, Ielmini D., Nanotechnology 24(38), 2013
PMID: 23999495
Finding a roadmap to achieve large neuromorphic hardware systems.
Hasler J, Marr B., Front Neurosci 7(), 2013
PMID: 24058330
Reward-based learning under hardware constraints-using a RISC processor embedded in a neuromorphic substrate.
Friedmann S, Frémaux N, Schemmel J, Gerstner W, Meier K., Front Neurosci 7(), 2013
PMID: 24065877
Neuron array with plastic synapses and programmable dendrites.
Ramakrishnan S, Wunderlich R, Hasler J, George S., IEEE Trans Biomed Circuits Syst 7(5), 2013
PMID: 24144669
Stochastic learning in oxide binary synaptic device for neuromorphic computing.
Yu S, Gao B, Fang Z, Yu H, Kang J, Wong HS., Front Neurosci 7(), 2013
PMID: 24198752
Hardware friendly probabilistic spiking neural network with long-term and short-term plasticity.
Hsieh HY, Tang KT., IEEE Trans Neural Netw Learn Syst 24(12), 2013
PMID: 24805223
Experimental implementation of a biometric laser synaptic sensor.
Pisarchik AN, Sevilla-Escoboza R, Jaimes-Reátegui R, Huerta-Cuellar G, García-Lopez JH, Kazantsev VB., Sensors (Basel) 13(12), 2013
PMID: 24351638
"Machine" consciousness and "artificial" thought: an operational architectonics model guided approach.
Fingelkurts AA, Fingelkurts AA, Neves CF., Brain Res 1428(), 2012
PMID: 21130079
Small-signal neural models and their applications.
Basu A., IEEE Trans Biomed Circuits Syst 6(1), 2012
PMID: 23852746
Asynchronous event-based binocular stereo matching.
Rogister P, Benosman R, Ieng SH, Lichtsteiner P, Delbruck T., IEEE Trans Neural Netw Learn Syst 23(2), 2012
PMID: 24808513
Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.
Sheik S, Coath M, Indiveri G, Denham SL, Wennekers T, Chicca E., Front Neurosci 6(), 2012
PMID: 22347163
VLSI circuits implementing computational models of neocortical circuits.
Wijekoon JH, Dudek P., J Neurosci Methods 210(1), 2012
PMID: 22342970
Dynamic state and parameter estimation applied to neuromorphic systems.
Neftci EO, Toth B, Indiveri G, Abarbanel HD., Neural Comput 24(7), 2012
PMID: 22428591
A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.
Jimenez-Fernandez A, Jimenez-Moreno G, Linares-Barranco A, Dominguez-Morales MJ, Paz-Vicente R, Civit-Balcells A., Sensors (Basel) 12(4), 2012
PMID: 22666004
Spiking neuron computation with the time machine.
Garg V, Shekhar R, Harris JG., IEEE Trans Biomed Circuits Syst 6(2), 2012
PMID: 23852979
Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.
Cantley KD, Subramaniam A, Stiegler HJ, Chapman RA, Vogel EM., IEEE Trans Neural Netw Learn Syst 23(4), 2012
PMID: 24805040
Energy-efficient neuron, synapse and STDP integrated circuits.
Cruz-Albrecht JM, Yung MW, Srinivasa N., IEEE Trans Biomed Circuits Syst 6(3), 2012
PMID: 23853146
A spiking neuron circuit based on a carbon nanotube transistor.
Chen CL, Kim K, Truong Q, Shen A, Li Z, Chen Y., Nanotechnology 23(27), 2012
PMID: 22710137
Hardware implementation of stochastic spiking neural networks.
Rosselló JL, Canals V, Morro A, Oliver A., Int J Neural Syst 22(4), 2012
PMID: 22830964
Spike-timing-dependent plasticity with weight dependence evoked from physical constraints.
Bamford SA, Murray AF, Willshaw DJ., IEEE Trans Biomed Circuits Syst 6(4), 2012
PMID: 23853183
Adaptive visual and auditory map alignment in barn owl superior colliculus and its neuromorphic implementation.
Huo J, Murray A, Wei D., IEEE Trans Neural Netw Learn Syst 23(9), 2012
PMID: 24807931
Silicon-based dynamic synapse with depressing response.
Dowrick T, Hall S, McDaid LJ., IEEE Trans Neural Netw Learn Syst 23(10), 2012
PMID: 24807998
Ultrafast all-optical implementation of a leaky integrate-and-fire neuron.
Kravtsov KS, Fok MP, Prucnal PR, Rosenbluth D., Opt Express 19(3), 2011
PMID: 21369031
Silicon-Neuron Design: A Dynamical Systems Approach.
Arthur JV, Boahen K., IEEE Trans Circuits Syst I Regul Pap 58(5), 2011
PMID: 21617741
Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.
Giulioni M, Camilleri P, Mattia M, Dante V, Braun J, Del Giudice P., Front Neurosci 5(), 2011
PMID: 22347151
A library of analog operators based on the hodgkin-huxley formalism for the design of tunable, real-time, silicon neurons.
Saïghi S, Bornat Y, Tomas J, Le Masson G, Renaud S., IEEE Trans Biomed Circuits Syst 5(1), 2011
PMID: 23850974
Analog memory and spike-timing-dependent plasticity characteristics of a nanoscale titanium oxide bilayer resistive switching device.
Seo K, Kim I, Jung S, Jo M, Park S, Park J, Shin J, Biju KP, Kong J, Lee K, Lee B, Hwang H., Nanotechnology 22(25), 2011
PMID: 21572200
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.
Brüderle D, Petrovici MA, Vogginger B, Ehrlich M, Pfeil T, Millner S, Grübl A, Wendt K, Müller E, Schwartz MO, de Oliveira DH, Jeltsch S, Fieres J, Schilling M, Müller P, Breitwieser O, Petkov V, Muller L, Davison AP, Krishnamurthy P, Kremkow J, Lundqvist M, Muller E, Partzsch J, Scholze S, Zühl L, Mayr C, Destexhe A, Diesmann M, Potjans TC, Lansner A, Schüffny R, Schemmel J, Meier K., Biol Cybern 104(4-5), 2011
PMID: 21618053
Floating gate synapses with spike-time-dependent plasticity.
Ramakrishnan S, Hasler PE, Gordon C., IEEE Trans Biomed Circuits Syst 5(3), 2011
PMID: 23851475
Short-term plasticity and long-term potentiation mimicked in single inorganic synapses.
Ohno T, Hasegawa T, Tsuruoka T, Terabe K, Gimzewski JK, Aono M., Nat Mater 10(8), 2011
PMID: 21706012
A systematic method for configuring VLSI networks of spiking neurons.
Neftci E, Chicca E, Indiveri G, Douglas R., Neural Comput 23(10), 2011
PMID: 21732859
A Model of Stimulus-Specific Adaptation in Neuromorphic Analog VLSI.
Mill R, Sheik S, Indiveri G, Denham SL., IEEE Trans Biomed Circuits Syst 5(5), 2011
PMID: 23852174
Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.
Yu T, Sejnowski TJ, Cauwenberghs G., IEEE Trans Biomed Circuits Syst 5(5), 2011
PMID: 22227949
Large developing receptive fields using a distributed and locally reprogrammable address-event receiver.
Bamford SA, Murray AF, Willshaw DJ., IEEE Trans Neural Netw 21(2), 2010
PMID: 20071258
Analog VLSI Biophysical Neurons and Synapses With Programmable Membrane Channel Kinetics.
Yu T, Cauwenberghs G., IEEE Trans Biomed Circuits Syst 4(3), 2010
PMID: 23853338
A spiking neural network model of the medial superior olive using spike timing dependent plasticity for sound localization.
Glackin B, Wall JA, McGinnity TM, Maguire LP, McDaid LJ., Front Comput Neurosci 4(), 2010
PMID: 20802855
Rate and pulse based plasticity governed by local synaptic state variables.
Mayr CG, Partzsch J., Front Synaptic Neurosci 2(), 2010
PMID: 21423519
Neural dynamics in reconfigurable silicon.
Basu A, Ramakrishnan S, Petre C, Koziol S, Brink S, Hasler PE., IEEE Trans Biomed Circuits Syst 4(5), 2010
PMID: 23853376
Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity.
Bill J, Schuch K, Brüderle D, Schemmel J, Maass W, Meier K., Front Comput Neurosci 4(), 2010
PMID: 21031027
Real-Time Classification of Complex Patterns Using Spike-Based Learning in Neuromorphic VLSI.
Mitra S, Fusi S, Indiveri G., IEEE Trans Biomed Circuits Syst 3(1), 2009
PMID: 23853161
Compact silicon neuron circuit with spiking and bursting behaviour.
Wijekoon JH, Dudek P., Neural Netw 21(2-3), 2008
PMID: 18262751
Real-time reconfigurable subthreshold CMOS perceptron.
Aunet S, Oelmann B, Norseng PA, Berg Y., IEEE Trans Neural Netw 19(4), 2008
PMID: 18390310
Transistor analogs of emergent iono-neuronal dynamics.
Rachmuth G, Poon CS., HFSP J 2(3), 2008
PMID: 19404469
The linearity of emergent spectro-temporal receptive fields in a model of auditory cortex.
Coath M, Balaguer-Ballester E, Denham SL, Denham M., Biosystems 94(1-2), 2008
PMID: 18616976
Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses.
Vogelstein RJ, Mallik U, Vogelstein JT, Cauwenberghs G., IEEE Trans Neural Netw 18(1), 2007
PMID: 17278476
Adaptive WTA with an analog VLSI neuromorphic learning chip.
Häfliger P., IEEE Trans Neural Netw 18(2), 2007
PMID: 17385639
Implementing spiking neural networks for real-time signal-processing and control applications: a model-validated FPGA approach.
Pearson MJ, Pipe AG, Mitchinson B, Gurney K, Melhuish C, Gilhespy I, Nibouche M., IEEE Trans Neural Netw 18(5), 2007
PMID: 18220195
Synaptic dynamics in analog VLSI.
Bartolozzi C, Indiveri G., Neural Comput 19(10), 2007
PMID: 17716003
A biologically inspired spiking neural network for sound source lateralization.
Voutsas K, Adamy J., IEEE Trans Neural Netw 18(6), 2007
PMID: 18051193
An address-event vision sensor for multiple transient object detection.
Chan V, Jin C, van Schaik A., IEEE Trans Biomed Circuits Syst 1(4), 2007
PMID: 23852009

48 References

Daten bereitgestellt von Europe PubMed Central.

Silicon synaptic depression.
Rasche C, Hahnloser RH., Biol Cybern 84(1), 2001
PMID: 11204399
Dynamic synapses in the cortex.
Zador AM, Dobrunz LE., Neuron 19(1), 1997
PMID: 9247258
Orientation-selective aVLSI spiking neurons.
Liu SC, Kramer J, Indiveri G, Delbruck T, Burg T, Douglas R., Neural Netw 14(6-7), 2001
PMID: 11665759

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
characterizing the firing proprieties of an adaptive analog vlsi neuron
ben, Proc BioADIT 3141 2004(), 2004
A synaptic model of memory: long-term potentiation in the hippocampus.
Bliss TV, Collingridge GL., Nature 361(6407), 1993
PMID: 8421494
Short-term synaptic plasticity.
Zucker RS, Regehr WG., Annu. Rev. Physiol. 64(), 2002
PMID: 11826273
Neural systems as nonlinear filters.
Maass W, Sontag ED., Neural Comput 12(8), 2000
PMID: 10953237

AUTHOR UNKNOWN, 0
Silicon auditory processors as computer peripherals.
Lazzaro J, Wawrzynek J, Mahowald M, Sivilotti M, Gillespie D., IEEE Trans Neural Netw 4(3), 1993
PMID: 18267754
Modeling short-term synaptic depression in silicon.
Boegerhausen M, Suter P, Liu SC., Neural Comput 15(2), 2003
PMID: 12590810

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
a pulse-coded communications infrastructure for neuromorphic systems
deiss, Pulsed Neural Networks (), 1998
neuromorphic bistable vlsi synapses with spike-timing-dependent plasticity
indiveri, Advances in neural information processing systems 15(), 2002
a spike based learning neuron in analog vlsi
häfliger, Advances in Neural Processing Systems 9(), 1997
Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs.
Markram H, Lubke J, Frotscher M, Sakmann B., Science 275(5297), 1997
PMID: 8985014
synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type
bi, J Neurosci 18(), 1998
asymmetric hebbian learning, spike timing and neural response variability
abbott, Adv Neural Inf Process Syst 11(), 1999

AUTHOR UNKNOWN, 0
electrophysiological properties of neocortical neurons in vitro
connors, J Neurophysiol (), 1982
Spike-driven synaptic plasticity: theory, simulation, VLSI implementation.
Fusi S, Annunziato M, Badoni D, Salamon A, Amit DJ., Neural Comput 12(10), 2000
PMID: 11032032

AUTHOR UNKNOWN, 0
A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.
Chicca E, Badoni D, Dante V, D'Andreagiovanni M, Salina G, Carota L, Fusi S, Del Giudice P., IEEE Trans Neural Netw 14(5), 2003
PMID: 18244578
Temporal coding in a silicon network of integrate-and-fire neurons.
Liu SC, Douglas R., IEEE Trans Neural Netw 15(5), 2004
PMID: 15484903

liu, Analog VLSI Circuits and Principles (), 2002
a recurrent model of orientation maps with simple and complex cells
merolla, Advances in neural information processing systems 16(), 2004

AUTHOR UNKNOWN, 0
Synchrony detection and amplification by silicon neurons with STDP synapses.
Bofill-i-petit A, Murray AF., IEEE Trans Neural Netw 15(5), 2004
PMID: 15484902

AUTHOR UNKNOWN, 0
A neuromorphic VLSI device for implementing 2-D selective attention systems.
Indiveri G., IEEE Trans Neural Netw 12(6), 2001
PMID: 18249973

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
Stable Hebbian learning from spike timing-dependent plasticity.
van Rossum MC, Bi GQ, Turrigiano GG., J. Neurosci. 20(23), 2000
PMID: 11102489

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
pci-aer hardware and software for interfacing to address-event based neuromorphic systems
dante, Neuromorph Eng Newslett 2(), 2005

AUTHOR UNKNOWN, 0
Synaptic depression and cortical gain control.
Abbott LF, Varela JA, Sen K, Nelson SB., Science 275(5297), 1997
PMID: 8985017
Which model to use for cortical spiking neurons?
Izhikevich EM., IEEE Trans Neural Netw 15(5), 2004
PMID: 15484883
Synaptic depression and the temporal response characteristics of V1 cells.
Chance FS, Nelson SB, Abbott LF., J. Neurosci. 18(12), 1998
PMID: 9614252

mead, Analog VLSI and Neural Systems (), 1989

AUTHOR UNKNOWN, 0
Building blocks for electronic spiking neural networks.
van Schaik A., Neural Netw 14(6-7), 2001
PMID: 11665758
All-or-none potentiation at CA3-CA1 synapses.
Petersen CC, Malenka RC, Nicoll RA, Hopfield JJ., Proc. Natl. Acad. Sci. U.S.A. 95(8), 1998
PMID: 9539807

AUTHOR UNKNOWN, 0

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