Conductance-based model of rodent thoracic sympathetic postganglionic neuron (McKinnon et al 2019)

 Download zip file 
Help downloading and running models
Accession:245926
"Thoracic sympathetic postganglionic neurons (tSPNs) represent the final neural output for control of vasomotor and thermoregulatory function. We used whole-cell recordings and computational modeling to provide broad insight on intrinsic cellular mechanisms controlling excitability and capacity for synaptic integration. Compared to past intracellular recordings using microelectrode impalement, we observed dramatically higher membrane resistivity with primacy in controlling enhanced tSPN excitability and recruitment via synaptic integration. Compared to reported phasic firing, all tSPNs fire repetitively and linearly encode injected current magnitude to firing frequency over a broad range. Modeling studies suggest microelectrode impalement injury accounts for differences in tSPN properties previously observed. Overall, intrinsic tSPN excitability plays a much greater role in the integration and maintenance of sympathetic output than previously thought."
Reference:
1 . McKinnon ML, Tian K, Li Y, Sokoloff AJ, Galvin ML, Choi MH, Prinz A, Hochman S (2019) Dramatically Amplified Thoracic Sympathetic Postganglionic Excitability and Integrative Capacity Revealed with Whole-Cell Patch-Clamp Recordings. eNeuro [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s): I A; I K; I Na, leak; I h; I M; I K,Ca; I L high threshold;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Python;
Model Concept(s):
Implementer(s): Prinz, Astrid [astrid.prinz at emory.edu]; Tian, Kun [io.kuntian at gmail.com];
Search NeuronDB for information about:  I L high threshold; I A; I K; I M; I h; I K,Ca; I Na, leak;
 
/
tSPN_SIngleNeuron_2018
init.py
ode_solver.py
tspn.py
                            
File not selected

<- Select file from this column.
Loading data, please wait...