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Public Library of Science, PLoS ONE, 11(7), p. e48470, 2012

DOI: 10.1371/journal.pone.0048470

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Neurons of the Dentate Molecular Layer in the Rabbit Hippocampus

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

The molecular layer of the dentate gyrus appears as the main entrance gate for information into the hippocampus, i.e., where the perforant path axons from the entorhinal cortex synapse onto the spines and dendrites of granule cells. A few dispersed neuronal somata appear intermingled in between and probably control the flow of information in this area. In rabbits, the number of neurons in the molecular layer increases in the first week of postnatal life and then stabilizes to appear permanent and heterogeneous over the individuals’ life span, including old animals. By means of Golgi impregnations, NADPH histochemistry, immunocytochemical stainings and intracellular labelings (lucifer yellow and biocytin injections), eight neuronal morphological types have been detected in the molecular layer of developing adult and old rabbits. Six of them appear as interneurons displaying smooth dendrites and GABA immunoreactivity: those here called as globoid, vertical, small horizontal, large horizontal, inverted pyramidal and polymorphic. Additionally there are two GABA negative types: the sarmentous and ectopic granular neurons. The distribution of the somata and dendritic trees of these neurons shows preferences for a definite sublayer of the molecular layer: small horizontal, sarmentous and inverted pyramidal neurons are preferably found in the outer third of the molecular layer; vertical, globoid and polymorph neurons locate the intermediate third, while large horizontal and ectopic granular neurons occupy the inner third or the juxtagranular molecular layer. Our results reveal substantial differences in the morphology and electrophysiological behaviour between each neuronal archetype in the dentate molecular layer, allowing us to propose a new classification for this neural population.