Maceﬁeld Modeling human postganglionic neuronal ﬁring interval. With the exception of some that were greater than 1 Hz, average, one can conclude that the population behavior is of each the mean ﬁring rates of the model postganglionic neurons were postganglionic neuron being driven, on average, by two pregan- all within the physiological range recorded from real muscle vaso- glionic neurons. This then provides us with an upper limit as to constrictor neurons. And while some of the patterning could be how many preganglionic neurons are responsible for the genera- partially explained by a postganglionic neuron being driven by one tion of action potentials in a single postganglionic neuron: two. preganglionic neuron exclusively (see asterisks in Table 1), there We know from studies in the anesthetized rat that some post- were no ﬁring distributions generated by the summed inputs of all ganglionic neurons in the superior cervical ganglion, which supply three preganglionic neurons that matched those of the real muscle many different tissues, are driven by two (rarely three) pregan- vasoconstrictor neurons. Indeed, of the 45 patterns examined, the glionic neurons with “strong” synapses, but that most are driven by mean discharge properties of the model postganglionic neuron only one (McLachlan et al., 1997, 1998; Li and Horn, 2006; Rimmer could best be explained by it being driven by – on average – two and Horn, 2010). Moreover, close temporal coincidence of EPSPs preganglionic neurons ﬁring with a mean interspike interval of from two preganglionic neurons with “weak” synapses can bring 2500 ms and SD of 5000 ms (Figure 3). Table 1 also shows that the postganglionic neuron to threshold (Rimmer and Horn, 2010). for all patterns the incidence of short interspike intervals was very Like those in the superior cervical ganglion, most postganglionic low; intervals ≤20 ms typically occurred <2% of the time. neurons recorded from a lumbar sympathetic ganglion in the rat – the majority of which are vasoconstrictor in function – are driven DISCUSSION by one “primary” preganglionic neuron, but inputs from two (or This study has shown that the characteristic ﬁring pattern of post- rarely three) “secondary” preganglionic neurons can occasionally ganglionic muscle vasoconstrictor neurons recorded from awake contribute to the ﬁring of a single postganglionic neuron (Brat- healthy human subjects can be emulated by a limited set of patterns ton et al., 2010). The current modeling study suggests that the of ﬁring in the preganglionic neurons. Obviously, it is not possible synaptic organization of postganglionic neurons in awake human to directly record from preganglionic neurons in awake human subjects is similar to that seen in the anesthetized rat. However, subjects, which would require inserting a microelectrode into the it should be noted that the studies of ganglionic transmission in intermediolateral column of the spinal cord or the white rami that the superior cervical ganglion (McLachlan et al., 1997, 1998) were connect the cord to the sympathetic chain. Accordingly, this mod- made under conditions in which the postganglionic neurons were eling study was an attempt to increase our understanding of how hyperpolarized, which may have blocked the production of action the sympathetic nervous system grades its output, given that the potentials from “weak inputs,” whereas the studies conducted in a discharge properties of postganglionic neurons are remarkably lumbar sympathetic ganglion (Bratton et al., 2010) were made at consistent in healthy subjects (Maceﬁeld et al., 2002). A similar the resting membrane potential. Nevertheless, both sets of studies modeling approach had been used by McLachlan et al. (1998) were undertaken in very reduced preparations, and the inﬂuence to compare the ﬁring of simulated postganglionic neurons and of anesthesia may well have affected the underlying ﬁring prop- real postganglionic neurons recorded from the superior cervical erties of both the preganglionic neurons and the postganglionic ganglion in the rat. neurons to which they project. Despite these differences between Of the 45 spike emulation patterns examined, the discharge the rat and human studies, it would appear that the underlying properties of a typical postganglionic muscle vasoconstrictor neu- ganglionic neurophysiology is remarkably similar. ron could best be explained by it being driven by, on average, two If human postganglionic neurons are driven by, on average, preganglionic neurons ﬁring with a mean interspike interval of two preganglionic neurons then this ﬁts with our interpretation 2500 ms and SD of 5000 ms: ﬁring probability and the numbers of of how short “spike doublets” are generated in muscle vasocon- spikes generated within a cardiac interval matched those of spon- strictor, cutaneous vasoconstrictor, and sudomotor neurons – by taneously active muscle vasoconstrictor neurons; mean ﬁring rate the chance occurrence of temporally coincident action potentials was also in the physiological range (Maceﬁeld et al., 1994; Mace- in the preganglionic neurons that synapse onto a given postgan- ﬁeld and Wallin, 1999a). Moreover, given that the ﬁring patterns glionic neuron (Maceﬁeld et al., 2002). Indeed, we had argued that are similar for cutaneous vasoconstrictor and sudomotor neurons this observation alone suggests that each postganglionic neuron in healthy subjects exhibiting cold-induced cutaneous vasocon- is driven by two preganglionic neurons, so the current mod- striction (Maceﬁeld and Wallin, 1999b) or heat-induced sweating eling study lends credence to this interpretation. Importantly, (Maceﬁeld and Wallin, 1996), the current modeling data can also we had noted previously that “although the generation of high explain the discharge properties of these neurons. It should be instantaneous frequencies requires an increase in synaptic drive pointed out that some postganglionic neurons comprising the to the neuron, these events were usually not associated with large population of real neurons recorded do discharge with a pattern bursts – rather they occurred essentially randomly” (Maceﬁeld that closely reﬂects the input from a single preganglionic neuron, et al., 2002). but none discharged with a pattern that reﬂected the combined Because our model preganglionic neurons were set up to ﬁre inputs from three preganglionic neurons. Moreover, individual stochastically, there were no constraints as to whether the discharge neurons vary in their ﬁring probabilities, with some having low of two or three closely ﬁring neurons could inﬂuence a post- and some high ﬁring probabilities. Such patterns have also been ganglionic neuron. Physiologically, of course, the capacity of a observed when using wavelet decomposition techniques to extract postganglionic neuron to follow excitatory postsynaptic poten- the ﬁring of individual spikes comprising a multiunit recording tials and generate action potentials is limited by the absolute (Steinback et al., 2010; Salmanpour et al., 2011). Nevertheless, on refractory period of the neuron (∼2 ms); indeed, our recordings Frontiers in Neuroscience | Autonomic Neuroscience December 2011 | Volume 5 | Article 132 | 4