A programmable spike-timing based circuit block for reconfigurable neuromorphic computing

Neurocomputing

Volumn 72, Issue 16-18, 2009, Pages 3609-3616

  Koickal, Thomas Jacob ^a   Gouveia, Luiz C ^a   Hamilton, Alister ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

On chip learning; Reconfigurable neuromorphic arrays; Spike timing dependent plasticity; Spiking neurons

Indexed keywords

ANALOG VLSI; AUSTRIA; BUILDING BLOCKES; CIRCUIT BLOCKS; CMOS TECHNOLOGY; FUNCTIONAL CIRCUITS; NEUROMORPHIC; NEUROMORPHIC COMPUTING; ON-CHIP LEARNING; RE-CONFIGURABLE; RECONFIGURABLE NEUROMORPHIC ARRAYS; SPIKE-TIMING; SPIKE-TIMING-DEPENDENT PLASTICITY; SPIKING NEURONS; TIME EVENT;

CMOS INTEGRATED CIRCUITS; ELECTRIC NETWORK ANALYSIS; NEURONS; PLASTICITY; TIME MEASUREMENT;

TIMING CIRCUITS;

SILICON;

ARTICLE; ELECTRIC POTENTIAL; INTEGRATED CIRCUIT; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NERVE CELL; NERVE CELL PLASTICITY; PRIORITY JOURNAL; SIMULATION; SPIKE; SYNAPSE;

EID: 69249213506     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.12.036     Document Type: Article

References (31)

1. Ros E., Ortigosa E.M., Agis R., Carillo R., and Arnold M. Real-time computing platform for spiking neurons (RT-spike). IEEE Trans. Neural Networks 17 4 (2006) 1050-1063
2. Vogelstein R.J., Mallik U., Vogelstein J.T., and Cauwenberghs G. Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses. IEEE Trans. Neural Networks 18 1 (2007)
3. Goldberg D.H., Cauwenberghs G., and Andreou A.G. Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons. Neural Networks 14 (2001) 781-793
4. Badoni D., Giulioni M., Dante V., and Giudice P.D. An aVLSI recurrent network of spiking neurons with reconfigurable and plastic synapses. Proceedings of the International Symposium on Circuits and Systems (2006) 1227-1230
5. Indiveri G., Chicca E., and Douglas R.J. A VLSI reconfigurable network of integrate-and-fire neurons with spike based learning synapses. Proceedings of the European Symposium on Artificial Neural Networks (2004)
6. Farquhar E., Gordon C., and Hasler P. A field programmable neural array. Proceedings of the International Symposium on Circuits and Systems (2006) 4114-4117
7. Schemmel J., Meier K., and Mueller E. A new VLSI model of neural microcircuits including spike time dependent plasticity. Proceedings of the ESANN 2004 (2004) 405-410
8. Zou Q., Bornat Y., Salumlghi S., Tomas J., Renaud S., and Desteshe A. Analog-digital simulations of full conductance-based networks of spiking neurons with spike timing dependent plasticity. Network Comput. Neural Syst. 17 3 (2006) 211-233
9. N. Lewis, S. Renaud, Spiking neural networks "in silico": from single neurons to large scale networks, in: SSD 2007, Hammamet, Tunisia, March 2007.
10. Markram H., Lubke J., Frotscher M., and Sakmann B. Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275 (1997) 213-215
11. Bi G.-Q., and Wang H.-X. Temporal asymmetry in spike timing-dependent plasticity. Physiol. Behav. 77 (2002) 551-555
12. H. Tanakaa, T. Moriea, K. Aiharab, A CMOS circuit for STDP with a symmetric time window, in: International Congress Series, vol. 1301, 2007, pp. 152-155.
13. Bofill-i-Petit A., and Murray A.F. Synchrony detection and amplification by silicon neurons with STDP synapses. IEEE Trans. Neural Networks 15 5 (2004) 1296-1304
14. Arthur J.V., and Boahen K. Learning in silicon: timing is everything. In: Sholkopf B., and Weiss Y. (Eds). Advances in Neural Information Processing Systems vol. 18 (2006), MIT Press, Cambridge 75-82
15. Hopfield J.J., and Brody C.J. Learning rules and network repair in spike-timing-based computation networks. Proc. Natl. Acad. Sci. 101 1 (2004) 337-342
16. Roberts P.D., and Bell C.C. Spike timing dependent synaptic plasticity in biological systems. Biol. Cybernet. 87 (2002) 392-403
17. Gerstner W., Kemter R., van Hemmen J.L., and Wagner H. A neuronal rule for sub-millisecond temporal coding. Nature 76-78 (1996) 383
18. Song S., Miller K.D., and Abbott L.F. Competitive Hebbian learning through spike-timing-dependent-plasticity. Nat. Neurosci. 3 9 (2000) 919-926
19. Koickal T.J., Hamilton A., Tan S.L., Covington J.A., Gardner J.W., and Pearce T.C. Analog VLSI circuit implementation of an adaptive neuromorphic olfaction chip. IEEE Trans. Circuits Syst. 54 1 (2007) 60-73
20. Koickal T.J., Gouveia L.C., and Hamilton A. A programmable time event circuit block for reconfigurable neuromorphic computing. In: Sandoval F., Prieto A., Cabestany J., and Grana M. (Eds). Lecture Notes in Computer Science vol. 4507 (2007), Springer, Berlin 430-437
21. Dan Y., and Poo M.-m. Hebbian depression of isolated neuromuscular synapse in vitro. Science 256 (1992) 1570-1573
22. Egger V., Feldmeyer D., and Sakmann B. Coincidence detection and changes of synaptic efficacy in spiny stellate neurons in rat barrel cortex. Nat. Neurosci. 2 (1999) 1098-1105
23. T.J. Koickal, A. Hamilton, An on-chip adaptive spike timing based offset cancellation scheme for neuromorphic sensing, in: NASA/ESA Conference on Adaptive Hardware Systems, 2007, pp. 536-540.
24. van Rossum M.C.W., Bi G.Q., and Turrigiano G.G. Stable Hebbian learning from spike timing-dependent plasticity. J. Neurosci. 20 23 (2000) 8812-8821
25. Zou Q., and Destexhe A. Kinetic models of spike-timing dependent plasticity and their functional consequences in detecting correlations. Biol. Cybernet. 97 1 (2007) 81-97
26. Xilinx homepage. [Online]. Available at: 〈http://www.xilinx.com/〉.
27. Anadigm homepage. [Online]. Available at: 〈http://www.anadigm.com/〉.
28. Cassidy A., Denham S., Kanold P., and Andreou A. FPGA based silicon spiking neural array. Proceedings of the Biomedical Circuits and Systems (2007) 75-78
29. P. Rocke, B. McGinley, J. Maher, F. Morgan, J. Harkin, Investigating the suitability of FPAAs for evolved hardware spiking neural networks, in: ICES 2008, Prague, 2008.
30. Boahen K. Point-to-point connectivity between neuromorphic chips using address events. IEEE Trans. Circuits Syst. II Analog Digital Signal Process. 47 5 (2000) 416-434
31. L.C. Gouveia, T.J. Koickal, A. Hamilton, An asynchronous spike coding scheme for programmable analog arrays, in: IEEE Symposium on Circuits and Systems, Seattle, 2008, pp. 1364-1367.