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This article is part of the supplement: Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access Poster presentation

Dopamine modulated dynamical changes in recurrent networks with short term plasticity

Andreas Herzog*, Sebastian Handrich and Christoph S Herrmann

Author Affiliations

Institute of Psychology, Otto-von-Guericke University, Magdeburg, Germany

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BMC Neuroscience 2009, 10(Suppl 1):P261  doi:10.1186/1471-2202-10-S1-P261

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/10/S1/P261


Published:13 July 2009

© 2009 Herzog et al; licensee BioMed Central Ltd.

Poster presentation

Dopamine is commonly considered as reward signal [1] and also as punishment signal [2] and is tightly coupled with memory and learning processes. In computational models, learning is simulated often on synapses by spike-timing-dependent plasticity (STDP), which depends on fine-timescale relationships between pre and postsynaptic spikes. However, most neocortical synapses exhibit also a mixture of depression and facilitation in a short time scale of few hundred milliseconds, which is referred as short-term plasticity [3,4]. The short-term plasticity stabilizes the network activity and changes dramatically the network dynamics, up to evidences of behavior dependency [5].

In our modeling study, we investigate the dynamic changes in a recurrent, spiking neural network model at different dopamine levels and its interaction with the short-term plasticity. The network consists of excitatory and inhibitory biologically plausible neurons [6]. The network was established by local and long-range (displaced) connections [7] with GABAA, GABAB, NMDA and AMPA synapses. The synaptic efficiency (short-term plasticity) is modeled with the phenomenological model in [8]. The values and statistical distributions are taken from [8,9]. The influence of dopamine is approximated by up and down regulating of the maximal conductance of the GABAA and NMDA synapses on excitatory cells in same direction [10-12].

We analyze STDP relevant events (pairs of pre- and postsynaptic spikes) in a range of -20...+20 ms on each synapse and found a clear dependency on dopamine level. Up regulating the conductance increases the number of such events and changes the distribution of the time differences. We demonstrate the effects of dopamine over a large variation of initial synaptic weights and stimulation patterns.

Acknowledgements

Supported by the Deutsche Forschungsgemeinschaft (SFB 779), Saxony-Anhalt FKZ XN3590C/0305M and BMBF Bernstein Group Magdeburg.

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