Abstract:
:Postganglionic sympathetic axons in awake healthy human subjects, regardless of their identity as muscle vasoconstrictor, cutaneous vasoconstrictor, or sudomotor neurons, discharge with a low firing probability (∼30%), generate low firing rates (∼0.5 Hz) and typically fire only once per cardiac interval. The purpose of the present study was to use modeling of spike trains in an attempt to define the number of preganglionic neurons that drive an individual postganglionic neuron. Artificial spike trains were generated in 1-3 preganglionic neurons converging onto a single postganglionic neuron. Each preganglionic input fired with a mean interval distribution of either 1000, 1500, 2000, 2500, or 3000 ms and the SD varied between 0.5×, 1.0×, and 2.0× the mean interval; the discharge frequency of each preganglionic neuron exhibited positive skewness and kurtosis. Of the 45 patterns examined, the mean discharge properties of the postganglionic neuron could only be explained by it being driven by, on average, two preganglionic neurons firing with a mean interspike interval of 2500 ms and SD of 5000 ms. The mean firing rate resulting from this pattern was 0.22 Hz, comparable to that of spontaneously active muscle vasoconstrictor neurons in healthy subjects (0.40 Hz). Likewise, the distribution of the number of spikes per cardiac interval was similar between the modeled and actual data: 0 spikes (69.5 vs 66.6%), 1 spike (25.6 vs 21.2%), 2 spikes (4.3 vs 6.4%), 3 spikes (0.5 vs 1.7%), and 4 spikes (0.1 vs 0.7%). Although some features of the firing patterns could be explained by the postganglionic neuron being driven by a single preganglionic neuron, none of the emulated firing patterns generated by the firing of three preganglionic neurons matched the discharge of the real neurons. These modeling data indicate that, on average, human postganglionic sympathetic neurons are driven by two preganglionic inputs.
journal_name
Front Neuroscijournal_title
Frontiers in neuroscienceauthors
Macefield VGdoi
10.3389/fnins.2011.00132subject
Has Abstractpub_date
2011-12-06 00:00:00pages
132eissn
1662-4548issn
1662-453Xjournal_volume
5pub_type
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