Abstract
This paper investigates spike-timing dependent plasticity (STDP) for recurrently connected weights in a network with fixed external inputs (homogeneous Poisson pulse trains). We use a dynamical system to model the network activity and predict its asymptotic evolution, which turns out to qualitatively depend on the learning parameters and the correlation structure of the inputs. Our predictions are supported by numerical simulations of Poisson neuron networks in general cases as well as for certain cases when using Integrate-And-Fire (IF) neurons.
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References
Bi, G.Q., Poo, M.M.: Synaptic modification by correlated activity: Hebb’s postulate revisited. Annual Review of Neuroscience 24, 139–166 (2001)
Burkitt, A.N., Gilson, M., van Hemmen, J.L.: Spike-timing-dependent plasticity for neurons with recurrent connections. Biological Cybernetics 96, 533–546 (2007)
Gerstner, W., Kempter, R., van Hemmen, J.L., Wagner, H.: A neuronal learning rule for sub-millisecond temporal coding. Nature 383, 76–78 (1996)
Gutig, R., Aharonov, R., Rotter, S., Sompolinsky, H.: Learning input correlations through nonlinear temporally asymmetric hebbian plasticity. Journal of Neuroscience 23, 3697–3714 (2003)
Hawkes, A.G.: Point spectra of some mutually exciting point processes. Journal of the Royal Statistical Society Series B-Statistical Methodology 33, 438–443 (1971)
Hebb, D.O.: The organization of behavior: a neuropsychological theory. Wiley, Chichester (1949)
Kempter, R., Gerstner, W., van Hemmen, J.L.: Hebbian learning and spiking neurons. Physical Review E 59, 4498–4514 (1999)
van Rossum, M.C.W., Bi, G.Q., Turrigiano, G.G.: Stable hebbian learning from spike timing-dependent plasticity. Journal of Neuroscience 20, 8812–8821 (2000)
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© 2008 Springer-Verlag Berlin Heidelberg
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Gilson, M., Grayden, D.B., van Hemmen, J.L., Thomas, D.A., Burkitt, A.N. (2008). Spike-Timing Dependent Plasticity in Recurrently Connected Networks with Fixed External Inputs. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4984. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69158-7_12
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DOI: https://doi.org/10.1007/978-3-540-69158-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69154-9
Online ISBN: 978-3-540-69158-7
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