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Modelling the effect of Dopamine through changing causality in STDP.

Simon M. Vogt1*, Simon M. Vogt1 and Ulrich G. Hofmann1
  • 1 University of Lübeck, Institute for Signal Processing, Germany

The inclusion of reinforcement into learning rules with spike timing dependent plasticity is often simulated as a third factor in weight adjustment. This is used as a way to simulate delayed reward but ignores instant changes to firing behavior that are correlated to changing levels of phasic dopamine. In particular, the discovery of novel actions may be influenced by existing levels of dopamine while new input patterns arrive.
We present an alternative way of looking at how a novelty signal may be influencing the behaviour of synapses to modulate the causal reaction to input spike patterns. By modulating the causal relationship between input spikes and output spikes of a trained two-layer network, we also gain effects on network learning that can in turn be used for reinforcement learning.
The suggested method is not in conflict with existing methods of dopamine simulation, and the two methods may be combined if wanted.

References

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Keywords: Learning and plasticity, neural coding and decoding

Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.

Presentation Type: Poster

Topic: learning and plasticity (please use "learning and plasticity" as keyword)

Citation: Vogt SM, Vogt SM and Hofmann UG (2011). Modelling the effect of Dopamine through changing causality in STDP.. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00217

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Received: 16 Aug 2011; Published Online: 04 Oct 2011.

* Correspondence: Mr. Simon M Vogt, University of Lübeck, Institute for Signal Processing, Lübeck, 23562, Germany, vogt@isip.uni-luebeck.de