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1 Volen Center, Brandeis University, Waltham, MA, USA; Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, USA
2 Biological Sciences, Rutgers University, Newark, NJ, USA
3 Volen Center, Brandeis University, Waltham, MA, USA; Biology, Brandeis University, Waltham, MA, USA
4 Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, USA; Biological Sciences, Rutgers University, Newark, NJ, USA
* To whom correspondence should be addressed. E-mail: farzan{at}njit.edu.
Electrical coupling between neurons with similar properties is often studied. Nonetheless, the role of electrical coupling between neurons with widely different intrinsic properties also occurs, but is less well-understood. Inspired by the pacemaker group of the crustacean pyloric network, we developed a multi-compartment, conductance-based model of a small network of intrinsically distinct, electrically coupled neurons. In the pyloric network, a small intrinsically bursting neuron, through gap-junctions, drives two larger, tonically spiking neurons to reliably burst in-phase with it. Each model neuron has two compartments, one responsible for spike-generation and the other for producing a slow, large amplitude oscillation. We illustrate how these compartments interact, and determine the dynamics of the model neurons. Our model captures the dynamic oscillation range measured from the isolated and coupled biological neurons. At the network level, we explore the range of coupling strengths for which synchronous bursting oscillations are possible. The spatial segregation of ionic currents significantly enhances the ability of the two neurons to burst synchronously, and the oscillation range of the model pacemaker network depends not only on the strength of the electrical synapse but also on the identity of the neuron receiving inputs. We also compare the activity of the electrically coupled, distinct neurons with that of a network of coupled identical bursting neurons. For small to moderate coupling strengths, the network of identical elements, when receiving asymmetrical inputs, can have a smaller dynamic range of oscillation than that of its constituent neurons in isolation.
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