Large-scale dendritic spine extraction and analysis through petascale computing (original) (raw)
Related papers
Neuroscience, 2013
Because dendritic spines are the sites of excitatory synapses, pathological changes in spine morphology should be considered as part of pathological changes in neuronal circuitry in the forms of synaptic connections and connectivity strength. In the past, spine pathology has usually been measured by changes in their number or shape. A more complete understanding of spine pathology requires visualization at the nanometer level to analyze how the changes in number and size affect their presynaptic partners and associated astrocytic processes, as well as organelles and other intracellular structures. Currently, serial section electron microscopy (ssEM) offers the best approach to address this issue because of its ability to image the volume of brain tissue at the nanometer resolution. Renewed interest in ssEM has led to recent technological advances in imaging techniques and improvements in computational tools indispensable for three-dimensional analyses of brain tissue volumes. Here we consider the small but growing literature that has used ssEM analysis to unravel ultrastructural changes in neuropil including dendritic spines. These findings have implications in altered synaptic connectivity and cell biological processes involved in neuropathology, and serve as anatomical substrates for understanding changes in network activity that may underlie clinical symptoms. This article is part of a Special Issue entitled: Dendritic Spine Plasticity in Brain Disorders.
An Image Analysis Algorithm for Dendritic Spines
Neural Computation, 2002
The structure of neuronal dendrites and their spines underlie the connectivity of neural networks. Dendrites, spines, and their dynamics are shaped by genetic programs as well as sensory experience. Dendritic structures and dynamics may therefore be important predictors of the function of neural networks. Based on new imaging approaches and increases in the speed of computation, it has become possible to acquire large sets of high-resolution optical micrographs of neuron structure at length scales small enough to resolve spines. This advance in data acquisition has not been accompanied by comparable advances in data analysis techniques; the analysis of dendritic and spine morphology is still accomplished largely manually. In addition to being extremely time intensive, manual analysis also introduces systematic and hard-to-characterize biases. We present a geometric approach for automatically detecting and quantifying the three-dimensional structure of dendritic spines from stacks of...
Ultrastructural analysis of dendritic spine necks reveals a continuum of spine morphologies
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.
Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies
Frontiers in Neuroscience, 2007
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.
Semiautomated correlative 3D electron microscopy of in vivo–imaged axons and dendrites
Nature Protocols, 2014
this protocol describes how in vivo-imaged dendrites and axons in adult mouse brains can subsequently be prepared and imaged with focused ion beam scanning electron microscopy (FIBseM). the procedure starts after in vivo imaging with chemical fixation, followed by the identification of the fluorescent structures of interest. their position is then highlighted in the fixed tissue by burning fiducial marks with the two-photon laser. once the section has been stained and resin-embedded, a small block is trimmed close to these marks. serially aligned eM images are acquired through this region, using FIBseM, and the neurites of interest are then reconstructed semiautomatically by using the ilastik software (http://ilastik.org/). this reliable imaging and reconstruction technique avoids the use of specific labels to identify the structures of interest in the electron microscope, enabling optimal chemical fixation techniques to be applied and providing the best possible structural preservation for 3D analysis. the entire protocol takes ~4 d.
Quantitative 3-D morphometric analysis of individual dendritic spines
Scientific Reports
The observation and analysis of dendritic spines morphological changes poses a major challenge in neuroscience studies. The alterations of their density and/or morphology are indicators of the cellular processes involved in neural plasticity underlying learning and memory, and are symptomatic in neuropsychiatric disorders. Despite ongoing intense investigations in imaging approaches, the relationship between changes in spine morphology and synaptic function is still unknown. The existing quantitative analyses are difficult to perform and require extensive user intervention. Here, we propose a new method for (1) the three-dimensional (3-D) segmentation of dendritic spines using a multi-scale opening approach and (2) define 3-D morphological attributes of individual spines for the effective assessment of their structural plasticity. The method was validated using confocal light microscopy images of dendritic spines from dissociated hippocampal cultures and brain slices (1) to evaluate accuracy relative to manually labeled ground-truth annotations and relative to the state-of-the-art Imaris tool, (2) to analyze reproducibility of user-independence of the segmentation method, and (3) to quantitatively analyze morphological changes in individual spines before and after chemically induced long-term potentiation. The method was monitored and used to precisely describe the morphology of individual spines in real-time using consecutive images of the same dendritic fragment. Dendritic spines are small membranous extensions on neuronal dendrites that form the postsynaptic site of most of excitatory synapses in the central nervous system. Dendritic spines have distinct structural features and are a heterogeneous group in terms of size and shape 1. Morphologically, dendritic spines consist of a spine head, where the excitatory synapse is located, which is separated from the parent dendrite by a thin neck that isolates the spine cytoplasm from the dendrite (Harris and Kater, 1994). Such a specific shape allows electrical and biochemical compartmentalization 2-5. Dendritic spines are essential for the accurate activity and signal transmission of neural circuits, but their exact function is still elusive and remains under intensive investigation 6-8. The shape of dendritic spines may undergo activity-and experience-dependent modifications that are believed to associate synaptic plasticity 4,9-12 with biological phenomena that are critical for synaptic function 13,14. Although the functional consequences of these morphological changes are not fully understood, the structural and functional plasticity of dendritic spines is widely believed to accompany learning and memory 8 and many pathological processes e.g. Alzheimer's disease 15 , Parkinson's disease 16. Presently, it is believed that the structural plasticity of dendritic spines is indeed related to synaptic function, since time-dependent morphological dynamics of spines accompany the learning processes 17. Recent works propose the structural models of synaptic plasticity, linking long-term potentiation with spine enlargement, as opposite to long-term depression, where the synaptic strength weakening is associated with spine shrinkage 18,19. Many aspects of the tight structure-function relationship that exists in dendritic spines remain unknown, mainly because of their complex morphology. Whether and the degree to which synaptic strength is modified by structural changes remain unclear 20. Dendritic spines are unstable structures, and their dynamic nature contributes to existing analytical problems 21. The limited optical resolution of images obtained using popular confocal
Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360
Current Protocols in Neuroscience, 2016
Determining the density and morphology of dendritic spines is of high biological significance given the role of spines in synaptic plasticity and in neurodegenerative and neuropsychiatric disorders. Precise quantification of spines in three dimensions (3D) is essential for understanding the structural determinants of normal and pathological neuronal function. However, this quantification has been restricted to time-and labor-intensive methods such as electron microscopy and manual counting, which have limited throughput and are impractical for studies of large samples. While there have been some automated software packages that quantify spine number, they are limited in terms of their characterization of spine structure. This unit presents methods for objective dendritic spine morphometric analysis by providing image acquisition parameters needed to ensure optimal data series for proper spine detection, characterization, and quantification with Neurolucida 360. These protocols will be a valuable reference for scientists working towards quantifying and characterizing spines.
Fine structure of synapses on dendritic spines
Frontiers in Neuroanatomy, 2014
Camillo Golgi's "Reazione Nera" led to the discovery of dendritic spines, small appendages originating from dendritic shafts. With the advent of electron microscopy (EM) they were identified as sites of synaptic contact. Later it was found that changes in synaptic strength were associated with changes in the shape of dendritic spines. While live-cell imaging was advantageous in monitoring the time course of such changes in spine structure, EM is still the best method for the simultaneous visualization of all cellular components, including actual synaptic contacts, at high resolution. Immunogold labeling for EM reveals the precise localization of molecules in relation to synaptic structures. Previous EM studies of spines and synapses were performed in tissue subjected to aldehyde fixation and dehydration in ethanol, which is associated with protein denaturation and tissue shrinkage. It has remained an issue to what extent fine structural details are preserved when subjecting the tissue to these procedures. In the present review, we report recent studies on the fine structure of spines and synapses using high-pressure freezing (HPF), which avoids protein denaturation by aldehydes and results in an excellent preservation of ultrastructural detail. In these studies, HPF was used to monitor subtle fine-structural changes in spine shape associated with chemically induced long-term potentiation (cLTP) at identified hippocampal mossy fiber synapses. Changes in spine shape result from reorganization of the actin cytoskeleton. We report that cLTP was associated with decreased immunogold labeling for phosphorylated cofilin (p-cofilin), an actin-depolymerizing protein. Phosphorylation of cofilin renders it unable to depolymerize F-actin, which stabilizes the actin cytoskeleton. Decreased levels of p-cofilin, in turn, suggest increased actin turnover, possibly underlying the changes in spine shape associated with cLTP. The findings reviewed here establish HPF as an appropriate method for studying the fine structure and molecular composition of synapses on dendritic spines. Citation: Frotscher M, Studer D, Graber W, Chai X, Nestel S and Zhao S (2014) Fine structure of synapses on dendritic spines. Front. Neuroanat. 8:94.
3dSpAn: An interactive software for 3D segmentation and analysis of dendritic spines
2019
Three dimensional segmentation and analysis of dendritic spines involve two major challenges: 1) how to segment individual spines from the dendrites and 2) how to quantitatively assess the morphology of individual spines. We developed a software named 3dSpAn to address these two issues by implementing our previously published 3D multiscale opening algorithm in shared intensity space and using effective morphological features for individual dendritic spine plasticity analysis. 3dSpAn consists of four modules: Preprocessing and ROI selection, Intensity thresholding and seed selection, Multiscale segmentation and Quantitative morphological feature extraction. We show the results of segmentation and morphological analysis for different observation methods, including in vitro and ex vivo imaging with confocal microscopy, and in vivo samples, using high-resolution two-photon microscopy. The software is freely available, the source code, windows installer, the software manual and video tut...