Title: Stabilising the output frequency in multiplicative STDP
1Stabilising the output frequency in
multiplicative STDP
- Fleur Zeldenrust
- 7 November 2005
2Contents
- Recapitulation
- STDP
- Homeostatic scaling
- Model
- Aim of research
- Net
- 4 scenarios
- Conclusion and Discussion
3 Bi Poo (1998)
Spike Timing Dependent Plasticity
4Spike Timing Dependent PlasticitySong et al.,
2000
- If the presynaptic cell fires first, the synapse
is potentiated - If the postsynaptic cell fires first, the synapse
is depressed - Important ratio between potentiation and
depression a
5Homeostatic Scaling of Excitability
- keep the neuron within its working range
- adjust excitability
- e.g. van Welie et al. (2004)
- Ca CaT regulates gL to attain target firing
rate (Golowasch et al. 99)
6Net
- 1000 inputs
- homeostatic scaling
- STDP
- Poisson
7Model
- Input-output relation
- Weight changes (STDP)
- Homeostatic scaling
8Aim of research
- Interactions of STDP with homeostatic scaling of
excitability - Can homeostatic scaling stabilise the output
frequency? - Would learning still be possible?
94 scenarios
- Homogeneous inputs, uncorrelated
- Homogeneous inputs, homogeneously correlated
- Homogeneous inputs, inhomogeneously correlated
- Inhomogeneous inputs, uncorrelated
10Homogeneous inputs, uncorrelated
- all inputs have the same mean frequency
- only autocorrelations
- assumption all weights have the same value
11Homogeneous inputs, uncorrelated
- 2 steady state solutions of which one is stable
- output rate stabilisation
- dependence on potentiation/ depression ratio
12Homogeneous inputs, homogeneously correlated
- all inputs have the same mean frequency
- varying correlations between all the inputs
- assumption all weights have the same value
13Homogeneous inputs, homogeneously correlated
- 2 steady state solutions of which one is stable
- output rate stabilisation
- dependence on potentiation/ depression ratio and
amount of correlation
14Homogeneous inputs, inhomogeneously correlated
- all inputs have the same mean frequency
- the group im1 iN is correlated
- assumption two groups of homogeneous weights
15Homogeneous inputs, inhomogeneously correlated
- 4 steady state solutions of which one is stable
- output rate stabilisation
- dependence on potentiation/ depression ratio,
amount of correlation and group size m
16Homogeneous inputs, inhomogeneously correlated
17Inhomogeneous inputs, uncorrelated
- two groups of input frequencies
- only autocorrelations
- assumption two groups of homogeneous weights
18Inhomogeneous inputs, uncorrelated
- 4 steady state solutions of which one is stable
- w1 and w2 overlap
- output rate stabilisation
- dependence only on potentiation/ depression ratio
19Conclusion
- A net with STDP and homeostatic scaling of
excitability can stabilise the output frequency
while the weights remain sensitive to
correlations (not to frequencies).
20Discussion
- What is the role of the timescale of homeostatic
scaling? - Stability of the homogeneous states?
- More groups than two?
- What happens without homeostatic scaling of
excitability? - Dependence on the target frequency?
21References
- 1 Bi, G. and Poo, M., Synaptic Modifications in
Cultured Hippocampal Neurons Dependence on Spike
Timing, Synaptic Strength, and Postsynaptic Cell
Type, The Journal of Neuroscience, Vol.18, pp.
10464-10472, 1998 - 2 Brunel, N., Dynamics of Sparsely Connected
Networks of Excitatory and Inhibitory Spiking
Neurons, Journal of Computational Neuroscience 8,
pp. 183-208, 2000 - 3 Rossem, M.C.W. van, Bi, G.Q. and Turrigiano,
G.G., Stable Hebbian learning from Spike
Timing-Dependent Plasticity, The Journal of
Neuroscience, Vol.20, pp. 8812-8821, 2000 - 4 Song, S., Miller, K.D. and Abbott, L.F.,
Competitive Hebbian learning through
spike-timing-dependent synaptic plasticity,
Nature, Vol.3 no. 9, pp. 919-926, 2000 - 5 Welie, I. van, Hooft, J.A. van and Wadman,
W.J., Homeostatic scaling of neuronal
excitability by synaptic modulation of somatic
hyperpolarization activated Ih channels, PNAS,
Vol. 101, no. 14, pp. 5123-5128, 2004