Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies

Dendritic spines are critical elements of cortical circuits, since they establish most excitatory synapses. Recent studies have reported correlations between morphological and functional parameters of spines. Specifically, the spine head volume is correlated with the area of the postsynaptic density...

Full description

Bibliographic Details
Main Authors: Jon I Arellano, Ruth Benavides-Piccione, Javier DeFelipe, Rafael Yuste
Format: Article
Language:English
Published: Frontiers Media S.A. 2007-10-01
Series:Frontiers in Neuroscience
Subjects:
PSD
Online Access:http://journal.frontiersin.org/Journal/10.3389/neuro.01.1.1.010.2007/full
id doaj-7e0227b4365148108c80b4660c50b1ca
record_format Article
spelling doaj-7e0227b4365148108c80b4660c50b1ca2020-11-24T22:35:55ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2007-10-01110.3389/neuro.01.1.1.010.200742Ultrastructure of dendritic spines: correlation between synaptic and spine morphologiesJon I Arellano0Ruth Benavides-Piccione1Javier DeFelipe2Rafael Yuste3Instituto CajalInstituto CajalInstituto CajalHHMI, Department of Biological Sciences, Columbia UniversityDendritic spines are critical elements of cortical circuits, since they establish most excitatory synapses. Recent studies have reported correlations between morphological and functional parameters of spines. Specifically, the spine head volume is correlated with the area of the postsynaptic density (PSD), the number of postsynaptic receptors and the ready-releasable pool of transmitter, whereas the length of the spine neck is proportional to the degree of biochemical and electrical isolation of the spine from its parent dendrite. Therefore, the morphology of a spine could determine its synaptic strength and learning rules. <br> To better understand the natural variability of neocortical spine morphologies, we used a combination of gold-toned Golgi impregnations and serial thin-section electron microscopy and performed three-dimensional reconstructions of spines from layer 2/3 pyramidal cells from mouse visual cortex. We characterized the structure and synaptic features of 144 completed reconstructed spines, and analyzed their morphologies according to their positions. For all morphological parameters analyzed, spines exhibited a continuum of variability, without clearly distinguishable subtypes of spines or clear dependence of their morphologies on their distance to the soma. On average, the spine head volume was correlated strongly with PSD area and weakly with neck diameter, but not with neck length. The large morphological diversity suggests an equally large variability of synaptic strength and learning rules.http://journal.frontiersin.org/Journal/10.3389/neuro.01.1.1.010.2007/fullElectron microscopyPSDpyramidalserial section
collection DOAJ
language English
format Article
sources DOAJ
author Jon I Arellano
Ruth Benavides-Piccione
Javier DeFelipe
Rafael Yuste
spellingShingle Jon I Arellano
Ruth Benavides-Piccione
Javier DeFelipe
Rafael Yuste
Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
Frontiers in Neuroscience
Electron microscopy
PSD
pyramidal
serial section
author_facet Jon I Arellano
Ruth Benavides-Piccione
Javier DeFelipe
Rafael Yuste
author_sort Jon I Arellano
title Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
title_short Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
title_full Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
title_fullStr Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
title_full_unstemmed Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
title_sort ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2007-10-01
description Dendritic spines are critical elements of cortical circuits, since they establish most excitatory synapses. Recent studies have reported correlations between morphological and functional parameters of spines. Specifically, the spine head volume is correlated with the area of the postsynaptic density (PSD), the number of postsynaptic receptors and the ready-releasable pool of transmitter, whereas the length of the spine neck is proportional to the degree of biochemical and electrical isolation of the spine from its parent dendrite. Therefore, the morphology of a spine could determine its synaptic strength and learning rules. <br> To better understand the natural variability of neocortical spine morphologies, we used a combination of gold-toned Golgi impregnations and serial thin-section electron microscopy and performed three-dimensional reconstructions of spines from layer 2/3 pyramidal cells from mouse visual cortex. We characterized the structure and synaptic features of 144 completed reconstructed spines, and analyzed their morphologies according to their positions. For all morphological parameters analyzed, spines exhibited a continuum of variability, without clearly distinguishable subtypes of spines or clear dependence of their morphologies on their distance to the soma. On average, the spine head volume was correlated strongly with PSD area and weakly with neck diameter, but not with neck length. The large morphological diversity suggests an equally large variability of synaptic strength and learning rules.
topic Electron microscopy
PSD
pyramidal
serial section
url http://journal.frontiersin.org/Journal/10.3389/neuro.01.1.1.010.2007/full
work_keys_str_mv AT joniarellano ultrastructureofdendriticspinescorrelationbetweensynapticandspinemorphologies
AT ruthbenavidespiccione ultrastructureofdendriticspinescorrelationbetweensynapticandspinemorphologies
AT javierdefelipe ultrastructureofdendriticspinescorrelationbetweensynapticandspinemorphologies
AT rafaelyuste ultrastructureofdendriticspinescorrelationbetweensynapticandspinemorphologies
_version_ 1725722189677723648