Abstract
Spike-timing dependent synaptic plasticity (STDP) circuitry is designed in 0.35μm CMOS VLSI. By setting different circuit parameters and generating diverse spike inputs, we got different steady weight distributions. Through analysing these simulation results, we show the effect of membrane threshold and input rate in STDP adaptation.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
van Rossum, G.G.M.C.W., Bi Turrigiano, G.Q.: Stable hebbian learning from spike timing-dependent plasticity. J. Neurosci. 20, 8812–8821 (2000)
Morris, R.G.M., Martin, S.J., Grimwood, P.D.: Synaptic plasticity and memory: An evaluation of the hypothesis. Annual Review of Neuroscience 23, 649–711 (2000)
Miller, K.D., Song, S., Abbott, L.F.: Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neurosci. 3, 919–926 (2000)
Di Paolo, E.: Spike-timing dependent plasticity for evolved robots. Adaptive Behavior 10, 243–263 (2002)
Bofill-I-Petit, A., Murray, A.F.: Synchrony detection and amplification by silicon neurons with stdp synapses. IEEE Transactions on Neural Networks 15, 1296–1304 (2004)
Tsodyks, M.: Spike-timing-dependent synaptic plasticity - the long road towards understanding neuronal mechanisms of learning and memory. Trends in Neurosciences 25(12), 599–600 (2002)
Koch, C.: Biophysics of Computation: Information Processing in Single Neurons. Oxford University Press, New York (1999)
Aertsen, A., Kuhn, A., Rotter, S.: Correlated input spike trains and their effects on the response of the leaky integrate-and-fire neuron. Neurocomputing 44-46, 121–126 (2002)
Sjostrom, G.G., Turrigiano, P.J., Nelson, S.B.: Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149–1164 (2001)
Ferster, D., Carandini, M.: Membrane potential and firing rate in cat primary visual cortex. Neuroscience 20, 470–484 (2000)
Curtin, J.: Determinants of Spike Timing-Dependent Synaptic Plasticity. Neuron. 32(6), 966–968 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huo, J., Murray, A. (2005). The Role of Membrane Threshold and Rate in STDP Silicon Neuron Circuit Simulation. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_159
Download citation
DOI: https://doi.org/10.1007/11550907_159
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28755-1
Online ISBN: 978-3-540-28756-8
eBook Packages: Computer ScienceComputer Science (R0)