Dynamic-Clamp pp 261-273 | Cite as

Dynamic-Clamp-Constructed Hybrid Circuits for the Study of Synchronization Phenomena in Networks of Bursting Neurons

  • Carmen C Canavier
  • Fred H Sieling
  • Astrid A Prinz
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 1)


Hybrid circuits comprised of one biological bursting neuron and one model bursting neuron were constructed using the dynamic clamp to create artificial synaptic conductances in both neurons. The strength and duration of reciprocal inhibitory and excitatory synaptic inputs were varied in a number of such circuits. The phase resetting curves (PRCs) for each component neuron were constructed for each isolated neuron using a pulse in postsynaptic conductance elicited by a single burst in the other neuron. The PRCs from the two component neurons were then used to predict whether a one to one phase-locked mode would be observed in the hybrid network, and if so, to predict the phase angle and network period. The predictions were qualitatively correct for 161 of 164 inhibitory networks and for 64 of 86 excitatory networks. The failures in the case of inhibition resulted from very weak coupling and in the case of excitation from two special cases, one in which the coupling becomes effectively continuous and another in which complex behavior results from a discontinuous PRC. The firing intervals and network period predictions were generally accurate within 10% of the values actually observed in the hybrid networks, a level similar to the level of variability observed in the measurement of the PRC and of the intrinsic period in the biological neuron.


Model Neuron Stimulus Interval Synaptic Conductance Biological Neuron Recovery Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Some of the work presented here was supported by NIH NS54281 grant which was awarded under the CRCNS program. Sorinel Oprisan performed some of the analyses presented herein. We also acknowledge Eve Marder for her support.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Carmen C Canavier
    • 1
  • Fred H Sieling
  • Astrid A Prinz
  1. 1.Neuroscience Center of Excellence, Louisiana State University Health Sciences CenterNew OrleansUSA

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