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1 Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta, Georgia, United States; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States
2 NINDS/Cellular and Systems Neurobiology Section, National Institutes of Health, Bethesda, Maryland, United States
3 Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta, Georgia, United States; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States; Wallace H. Coulter Dept. of Biomedical Eng., Georgia Institute of Technology, Atlanta, Georgia, United States
* To whom correspondence should be addressed. E-mail: rbutera{at}gatech.edu.
The pre-Botzinger complex (pBC) is a vital sub-circuit of the respiratory central pattern generator. Although the existence of neurons with pacemaker-like bursting properties in this network is not questioned, their role in network rhythmogenesis is unresolved. Modeling is ideally suited to address this debate because of the ease with which biophysical parameters of individual cells and network architecture can be manipulated. We modeled the parameter variability of experimental data from pBC bursting pacemaker and non-pacemaker neurons using a modified version of our previously developed pBC neuron and network models. In order to investigate the role of pacemakers in network-wide rhythmogenesis, we simulated networks of these neurons and varied the fraction of the population made up of pacemakers. For each number of pacemaker neurons, we varied the amount of tonic drive to the network and measured the frequency of synchronous network-wide bursting produced. Excitatory networks with all-to-all coupling, as well as sparsely connected networks were explored for several levels of synaptic coupling strength. Networks containing only non-pacemakers were able to produce network-wide bursting, but with a low probability of bursting and a low input and output range. Our results indicate that inclusion of pacemakers in an excitatory network increases robustness of the network by more than tripling the input and output range compared to networks containing no pacemakers. The largest increase in dynamic range occurs when the number of pacemakers in the network increases above 20% of the population. Experimental tests of our model predictions are proposed.
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