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Innervation and geometry of rabbit ciliary ganglion cells after preganglionic nerve regeneration
Author(s) -
Hadley Robert D.
Publication year - 1990
Publication title -
journal of comparative neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.855
H-Index - 209
eISSN - 1096-9861
pISSN - 0021-9967
DOI - 10.1002/cne.902950209
Subject(s) - biology , postsynaptic potential , ciliary ganglion , neuroscience , ganglion , anatomy , autonomic ganglion , receptor , biochemistry
Previous studies have shown a consistent relationship between the dendritic complexity of autonomic neurons and the number of preganglionic axons that innervate them. This relationship is established postnatally, probably through mitigation of preganglionic competition on neurons with increasing dendritic complexity. The present study examines whether a similar relationship between neuronal geometry and the number of axons that innervate rabbit ciliary ganglion neurons is established when the preganglionic nerve is interrupted and then allowed to regenerate. Such a pattern would indicate that the mechanisms responsible for establishing the relationship between innervation and postsynaptic geometry in neonates persist in the adult animal. Ganglion cells were fully reinnervated by about 8 weeks after preganglionic nerve crush. On average, the number of inputs to reinnervated neurons was similar to normal (range = 1 to 4 inputs/cell, mean = 2.1). The number of inputs that cells received was related to their dendritic complexity. Neurons that received a single input had very simple dendritic arbors, or lacked dendrites altogether, whereas neurons that received 2 or more inputs had considerably more complex arbors. The correlation between dendritic complexity and innervation suggests that the geometry of postsynaptic neurons continues to influence the number of inputs each ganglion cell receives in maturity. As a corollary, changes in the dendritic arbors of adult neurons would presumably influence the arrangement of their synaptic inputs.

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