Dendritic spines are membranous protrusions that receive essentially all excitatory inputs in most mammalian neurons. Spines, with a bulbous head connected to the dendrite by a thin neck, have a variety of morphologies that likely impact their functional properties. Nevertheless, the question of whether spines belong to distinct morphological subtypes is still open. Addressing this quantitatively requires clear identification and measurements of spine necks. Recent advances in electron microscopy enable large-scale systematic reconstructions of spines with nanometer precision in 3D. Analyzing ultrastructural reconstructions from mouse neocortical neurons with computer vision algorithms, we demonstrate that the vast majority of spine structures can be rigorously separated into heads and necks, enabling morphological measurements of spine necks. We then used a database of spine morphological parameters to explore the potential existence of different spine classes. Without exception, our analysis revealed unimodal distributions of individual morphological parameters of spine heads and necks, without evidence for subtypes of spines. The postsynaptic density size was strongly correlated with the spine head volume. The spine neck diameter, but not the neck length, was also correlated with the head volume. Spines with larger head volumes often had a spine apparatus and pairs of spines in a post-synaptic cell contacted by the same axon had similar head volumes. Our data reveal a lack of morphological subtypes of spines and indicate that the spine neck length and head volume must be independently regulated. These results have repercussions for our understanding of the function of dendritic spines in neuronal circuits.
Keywords: dendritic spines; electron microscopy; plasticity; pyramidal cells.
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