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  • Open Access

Dopamine modulated dynamical changes in recurrent networks with short term plasticity

  • 1Email author,
  • 1 and
  • 1
BMC Neuroscience200910 (Suppl 1) :P261

  • Published:


  • Dopamine
  • Neural Network Model
  • Short Time Scale
  • Dopamine Level
  • Synaptic Weight

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 [1012].

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.



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

Authors’ Affiliations

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


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© Herzog et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.