Volume 10 Supplement 1

Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access

Dopamine modulated dynamical changes in recurrent networks with short term plasticity

  • Andreas Herzog1Email author,
  • Sebastian Handrich1 and
  • Christoph S Herrmann1
BMC Neuroscience200910(Suppl 1):P261

DOI: 10.1186/1471-2202-10-S1-P261

Published: 13 July 2009

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.

Declarations

Acknowledgements

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

Authors’ Affiliations

(1)
Institute of Psychology, Otto-von-Guericke University

References

  1. Schultz W: Multiple reward signals in the brain. Nat Rev Neurosci. 2000, 1: 199-207. 10.1038/35044563.PubMedView ArticleGoogle Scholar
  2. Ungless MA, Magill PJ, Bolam JP: Uniform inhibition of dopamine neurons in the ventral tegmental area by aversive stimuli. Science. 2004, 303: 2040-2042. 10.1126/science.1093360.PubMedView ArticleGoogle Scholar
  3. Abbott LF, Regehr WG: Synaptic computation. Nature. 2004, 431: 796-803. 10.1038/nature03010.PubMedView ArticleGoogle Scholar
  4. Sussillo D, Toyoizumi T, Maass W: Self-tuning of neural circuits through short-term synaptic plasticity. J Neurophysiol. 2007, 97: 4079-4095. 10.1152/jn.01357.2006.PubMedView ArticleGoogle Scholar
  5. Fujisawa S, Amarasingham A, Harrison MT, Buzsáki G: Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex. Nat Neurosci. 2008, 11: 823-833. 10.1038/nn.2134.PubMed CentralPubMedView ArticleGoogle Scholar
  6. Izhikevich EM, Gally JA, Edelman GM: Spike-timing dynamicsof neuronal groups. Cereb Cortex. 2004, 14: 933-944. 10.1093/cercor/bhh053.PubMedView ArticleGoogle Scholar
  7. Herzog A, Kube K, Michaelis B, de Lima AD, Voigt T: Displaced strategies optimize connectivity in neocortical networks. Neurocomputing. 2007, 70: 1121-1129. 10.1016/j.neucom.2006.11.016.View ArticleGoogle Scholar
  8. Markram H, Wang Y, Tsodyks M: Differential signaling via the same axon of neocortical pyramidal neurons. Proc Natl Acad Sci. 1998, 95: 5323-5328. 10.1073/pnas.95.9.5323.PubMed CentralPubMedView ArticleGoogle Scholar
  9. Gupta A, Wang Y, Markram H: Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science. 2000, 287: 273-278. 10.1126/science.287.5451.273.PubMedView ArticleGoogle Scholar
  10. Wang X, Zhong P, Yan Z: Dopamine D4 receptors modulate GABAergic signaling in pyramidal neurons of prefrontal cortex. J Neurosci. 2002, 22: 9185-9193.PubMedGoogle Scholar
  11. Wang X, Zhong P, Gu Z, Yan Z: Regulation of NMDA receptors by dopamine D4 signaling in prefrontal cortex. J Neurosci. 2003, 23: 9852-9861.PubMedGoogle Scholar
  12. Durstewitz D, Seamans JK: The computational role of dopamine D1 receptors in working memory. Neural Netw. 2002, 15: 561-572. 10.1016/S0893-6080(02)00049-7.PubMedView ArticleGoogle Scholar

Copyright

© Herzog et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.

Advertisement