Name: analyzing dendritic morphology in columns and layers
Uploaded: 2017-03-23T15:00:00.000+00:00
Duration: 8 min 41 s
Description: Watch this Scientific Journal Video about Analyzing Dendritic Morphology in Columns and Layers at JoVE.com

この作品は、国立衛生研究所の学内研究プログラムによってサポートされていた、子どもの健康と人間開発（C.-HLへの助成金HD008913）のユニス・ケネディ・シュライバー国立研究所、情報技術のためのセンター（PGM、NP、ESM 、およびMM）。

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著者らは、開示することは何もありません。

ここでは、画像にどのように表示し、 ショウジョウバエの延髄ニューロンの樹状アーバーを分析します。最初のセクション、デュアルビュー画像は、高解像度の画像をスタックに2つの画像スタックのデコンボリューションおよび組み合わせが記載されています。第二セクション、樹状突起のトレースと登録は、参照列配列に延髄の神経細胞の樹状突起のトレースと登録について説明?...

開発中に複雑で、ニューロン精巧な樹状突起が、そのシナプス前パートナーとシナプスを形成するための分岐パターンをステレオタイプ。樹状分岐パターンは、ニューロンのアイデンティティと機能と相関します。樹状分岐の複雑さとフィールドのサイズは、入力された番号を管理しながら、樹状アーバーの場所は、彼らが受け取るシナプス前入力のタイプを決定します。このように、樹枝状の形態学的特性は、シナプス接続と神経計算のための重要な決定因子です。フライ視神経ローブと脊椎動物の網膜のような複雑な脳の多くの地域では、シナプス回路は、情報処理1、2を容易にするために、列およびレイヤーで構成されています。このようなコラムと層組織では、明確なモダリティプロジェクトの軸索のシナプス前ニューロンは特定の層（いわゆる層特異的標的）で終了すると整然とした2次元アレイを形成する（いわゆるのcalleD地形図）、シナプス後ニューロンは、正しい種類と数のシナプス前入力を受信するために特定の層に適切なサイズの樹状突起を拡張しながら。層と列への標的軸索は、よく3、4を研究してきたが、はるかに少ないが、樹状突起は、特定の層にルーティングし、正しいシナプス前パートナー5とのシナプス結合を形成するために、受容野を適切に展開する大きさであるかについては知られています。イメージングおよび層と列への標的定量化する樹状の難しさは、柱状の積層脳構造における樹状開発の研究を妨げてきました。 ショウジョウバエ髄質ニューロンは、列と層における樹状ルーティングおよび回路アセンブリを研究するための理想的なモデルです。フライ髄質の神経網は、3D 10層の格子と約750列として編成されています。各列は、pを含む求心性神経のセットによって神経支配されますその軸索端子層特異的なファッション6で地形を形成L5、 - hotoreceptors R7 / R8およびラミナニューロンL1。延髄のニューロンの約38種類が、これらの求心性神経7からの入力を受信するための特定の層で、適切なフィールドサイズを持つすべての髄質列と精巧な樹状突起に存在しています。髄質におけるシナプス回路は、電子顕微鏡レベルで再構築されてきました。従って、シナプスパートナーシップウェル7,8を設置しています。さらに、髄質ニューロンの様々な種類を標識するための遺伝的ツールは、9、10、11入手可能です。 transmedullaの3種類（Tm）は、ニューロン（TM2、TM9及びTM20）を調べることによって、我々は以前に二つの細胞型特異的な樹枝状の属性を特定した：（ⅰ）のTmニューロンは、平面PROJ（前方または後方方向のいずれかに樹状突起を投影しますection方向）、細胞の種類に応じて、及び（ii）の延髄の神経細胞の樹状突起は、細胞型特異的な様式（層特異的な終端）12で特定の髄質層で終端します。層および列合図へのTmの応答を破壊する突然変異が、これらの属性の異なる側面に影響を与えながら、平面投影方向と層固有の終端は、Tmのニューロンのこの3種類を区別するのに十分です。 ここでは、列および層（ 図1）におけるショウジョウバエ延髄ニューロンの樹状突起パターン形成を調べるための完全なワークフローを提示します。まず、2つの共焦点画像を結合するカスタマイズされたソフトウェアを使用してデュアルビューイメージング法は、高品質の等方性の画像を生成するためにスタックを示しています。この方法は、超解像顕微鏡法に頼らずに、樹状分岐の信頼性トレースを可能にする高品質の画像を生成するためにのみ、従来の共焦点顕微鏡検査を必要とするようなsのSTED（誘導放出枯渇）または構造的照明。第二に、我々は、樹状アーバをトレースするための、参照列配列に生じた神経突起のトレースを登録するための方法を提示します。第三に、我々は、樹状分岐および終了周波数の推定値を導出するための樹状突起の平面投影方向と層固有の終了に関する情報、ならびにを抽出するための計算方法を示しています。一緒に、これらの方法は、3D、樹状突起の形態に基づいて細胞種の分類における樹状パターンの特徴付け、および変異体における潜在的な欠陥の同定を可能にします。

<table><tbody><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Huygens Professional</td><td>Scientific Volume Imaging</td><td>version 16.05</td><td>for image deconvolution (https://svi.nl).&amp;nbsp; commercial software</td></tr><tr><td>MIPAV</td><td></td><td>version 7.3.0</td><td>for image recombination and registration (http://mipav.cit.nih.gov/); freeware</td></tr><tr><td>MIPAV plugin: PlugInDrosophila&lt;br/&gt;RetinalRegistration.class</td><td></td><td></td><td>freeware</td></tr><tr><td>MIPAV plugin: PlugInDrosophilaStandard&lt;br/&gt;ColumnRegistration.class</td><td></td><td></td><td>freeware</td></tr><tr><td>Imaris</td><td>Bitplane</td><td></td><td>for tracing neurites and assigning reference points for image registration (http://www.bitplane.com); commercial software</td></tr><tr><td>Vaa3D</td><td></td><td></td><td>for visualizing swc files (https://github.com/Vaa3D/release/releases/); freeware</td></tr><tr><td>Matlab</td><td>Mathworks</td><td>R2014b</td><td>for morphometric analysis of dendrites (http://www.mathworks.com); commercial software</td></tr><tr><td>Matlab toolbox: TREES1.14</td><td></td><td>v1.14</td><td>for analyzing dendritic morphometric parameters (http://www.treestoolbox.org/download.html); freeware</td></tr><tr><td>Matlab toolbox: Dendritic_Tree_Toolbox</td><td></td><td>v1.0</td><td>For calculating morphometric parameters (https://science.nichd.nih.gov/confluence/display/snc/Data+collections+for+imagines+combination+and+standardize+column+registration). Freeware</td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Sample files&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>SWC file definition</td><td></td><td></td><td>http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html</td></tr><tr><td>The codes and sample files for image combination and registration</td><td></td><td></td><td>https://science.nichd.nih.gov/confluence/display/snc/Data+collections+for+imagines+combination+and+standardize+column+registration</td></tr><tr><td>Reference point example&amp;nbsp;</td><td></td><td></td><td>https://science.nichd.nih.gov/confluence/download/attachments/117216914/points.csv?version=1&amp;amp;modificationDate=&lt;br/&gt;1471880596000&amp;amp;api=v2</td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Computer system&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>MS Windows Windows 7 x64 or Macintosh OS X 10.7 or later</td><td></td><td></td><td>3GHz 64-bit quad-core processor, 16G RAM (minimal)</td></tr><tr><td>Optional: Quadro4000&amp;nbsp; (or above) graphic card</td><td>Nvidia</td><td></td><td>for stereographic visualization of dendrites.</td></tr><tr><td>Optional: NVIDIA 3D vision2</td><td>Nvidia</td><td></td><td>http://www.nvidia.com/object/3d-vision-main.html</td></tr><tr><td>Optional: 120 Hz LCD display for NVIDIA 3D vision2</td><td></td><td></td><td>http://www.nvidia.com/object/3d-vision-system-requirements.html</td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Reagents for imaging&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>24B10 antibody</td><td>The Developmental Studies Hybridoma Bank</td><td>24B10</td><td></td></tr><tr><td>GFP Tag Antibody</td><td>Thermofisher Scientific</td><td>G10362</td><td></td></tr><tr><td>Goat anti-Rabbit (H+L), Alexa Fluor 488</td><td>Thermofisher Scientific</td><td>A11034</td><td></td></tr><tr><td>Goat anti-Mouse (H+L), Alexa Fluor 568</td><td>Thermofisher Scientific</td><td>A21124</td><td></td></tr><tr><td>VECTASHIELD Antifade Mounting Medium</td><td>Vector Laboratories</td><td>H-1000</td><td></td></tr><tr><td>Mounting&amp;nbsp;Clay&amp;nbsp;</td><td>Fisher</td><td>S04179</td><td></td></tr><tr><td>70% glycerol in 1x PBS</td><td></td><td></td><td></td></tr><tr><td>Cover glasses, high performance, D = 0.17&amp;nbsp;mm</td><td>Zeiss</td><td>474030-9000-000</td><td></td></tr></tbody></table>

analyzing dendritic morphology in columns and layers

このようなフライ光学ローブと脊椎動物皮質などの中枢神経系の多くの地域では、シナプス回路が発達した動物での開発と情報の処理中に脳の配線を容易にするための層と列に編成されています。特定の層における型特異的なパターンで精巧な樹状突起シナプス後ニューロンは、適切なシナプス前終末とシナプスします。フライ髄質の神経網は10層と約750列で構成されます。各カラムは、型特異的様式で求心性のいくつかの7種類の軸索の端末と一致延髄のニューロンの38種類以上の樹状突起によって神経支配されています。このレポートでは、画像に手順を詳しく説明し、延髄の神経細胞の樹状突起を分析します。ワークフローは、次の3つのセクションを含む：（I）デュアルビュー撮像部は、樹状突起の高解像度3D画像に直交する方向で集め2の共焦点画像スタックを結合します。 （ⅱ）デンドライトはトレースと登録部は、樹状をトレース3Dでアーバーと参照列配列に樹枝状のトレースを登録します。 （iii）は、樹状分析部は、樹状アーバーの層特異的な終端と平面投影方向を含む列と層に対する樹状パターンを解析して、樹状分岐および終了周波数の推定値を導出します。プロトコルは、マトリックス研究所言語でオープンソースのMIPAV（医療画像処理、分析、および可視化）プラットフォームとカスタムツールボックス上に構築されたカスタムプラグインを利用しています。一緒に、これらのプロトコルは、層および列にショウジョウバエ髄質ニューロンの樹状経路を分析する細胞型を同定するため、および変異体の欠陥を決定するために、完全なワークフローを提供します。

ここで提示デュアルビュー画像化手順を使用して、まばらに標識TM20ニューロンを含むハエの脳は、二つの直交する方向で画像化しました。撮影の前に、脳は、膜繋留GFPと感光体軸索を可視化するための適切な一次および二次抗体で染色しました。イメージングのために、脳の第1の水平方向に取り付けた（ 図2A、B）。 GFP標識TM20ニューロンと周囲の光受容...

Watch this Scientific Journal Video about Analyzing Dendritic Morphology in Columns and Layers at JoVE.com

Analyzing Dendritic Morphology in Columns and Layers

ここでは、列およびレイヤーにショウジョウバエ延髄ニューロンの樹状突起のルーティングを分析する方法を示しています。ワークフローは、トレース基準列配列の樹状アーバーを登録すると、3次元空間内の樹枝状構造を分析するための画像品質と計算ツールを改善するためのデュアルビューイメージング技術を含みます。

列およびレイヤーで樹状形態を分析します

In many regions of the central nervous systems, such as the fly optic lobes and the vertebrate cortex, synaptic circuits are organized in layers and ...

analyzing-dendritic-morphology-in-columns-and-layers

Research

JoVE Journal

Neuroscience

9.3K ビュー.  National Institutes of Health (NIH). ここでは、列およびレイヤーにショウジョウバエ延髄ニューロンの樹状突起のルーティングを分析する方法を示しています。ワークフローは、トレース基準列配列の樹状アーバーを登録すると、3次元空間内の樹枝状構造を分析するための画像品質と計算ツールを改善するためのデュアルビューイメージング技術を含みます。 

ビデオ: Analyzing Dendritic Morphology in Columns and Layers

Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3. Specifically, it affects the ability of neurons to receive inputs from other cells2 and contributes to the propagation of action potentials4,5. The morphology of the neurites also affects how information is processed. The diversity of dendrite morphologies facilitate local and long range signaling and allow individual neurons or groups of neurons to carry out specialized functions within the neuronal network6,7. Alterations in dendrite morphology, including fragmentation of dendrites and changes in branching patterns, have been observed in a number of disease states, including Alzheimer's disease8, schizophrenia9,10, and mental retardation11. The ability to both understand the factors that shape dendrite morphologies and to identify changes in dendrite morphologies is essential in the understanding of nervous system function and dysfunction.
Neurite morphology is often analyzed by Sholl analysis and by counting the number of neurites and the number of branch tips. This analysis is generally applied to dendrites, but it can also be applied to axons. Performing this analysis by hand is both time consuming and inevitably introduces variability due to experimenter bias and inconsistency. The Bonfire program is a semi-automated approach to the analysis of dendrite and axon morphology that builds upon available open-source morphological analysis tools. Our program enables the detection of local changes in dendrite and axon branching behaviors by performing Sholl analysis on subregions of the neuritic arbor. For example, Sholl analysis is performed on both the neuron as a whole as well as on each subset of processes (primary, secondary, terminal, root, etc.) Dendrite and axon patterning is influenced by a number of intracellular and extracellular factors, many acting locally. Thus, the resulting arbor morphology is a result of specific processes acting on specific neurites, making it necessary to perform morphological analysis on a smaller scale in order to observe these local variations12.
The Bonfire program requires the use of two open-source analysis tools, the NeuronJ plugin to ImageJ and NeuronStudio. Neurons are traced in ImageJ, and NeuronStudio is used to define the connectivity between neurites. Bonfire contains a number of custom scripts written in MATLAB (MathWorks) that are used to convert the data into the appropriate format for further analysis, check for user errors, and ultimately perform Sholl analysis. Finally, data are exported into Excel for statistical analysis. A flow chart of the Bonfire program is shown in Figure 1.

We have developed a computer program to analyze neuronal morphology. In combination with two existing open source analysis tools, our program performs Sholl analysis and determines the number of neurites, branch points, and neurite tips. The analyses are performed so that local changes in neurite morphology can be observed.

複数のスケールでデジタル化された神経形態の自動化されたショールの分析

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3.  Specifically, it affects the ability of neurons to ...

神経科学

Analysis of Dendritic Spine Morphology in Cultured CNS Neurons

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These structures are rich in actin and have been shown to be highly dynamic. In response to classical Hebbian plasticity 
as well as neuromodulatory signals, dendritic spines can change shape and number, which is thought to be critical for the refinement of neural 
circuits and the processing and storage of information within the brain. Within dendritic spines, a complex network of proteins link extracellular 
signals with the actin cyctoskeleton allowing for control of dendritic spine morphology and number. Neuropathological studies have demonstrated that 
a number of disease states, ranging from schizophrenia to autism spectrum disorders, display abnormal dendritic spine morphology or numbers. 
Moreover, recent genetic studies have identified mutations in numerous genes that encode synaptic proteins, leading to suggestions that these 
proteins may contribute to aberrant spine plasticity that, in part, underlie the pathophysiology of these disorders. In order to study the potential 
role of these proteins in controlling dendritic spine morphologies/number, the use of cultured cortical neurons offers several advantages. Firstly, 
this system allows for high-resolution imaging of dendritic spines in fixed cells as well as time-lapse imaging of live cells. Secondly, this in 
vitro system allows for easy manipulation of protein function by expression of mutant proteins, knockdown by shRNA constructs, or pharmacological 
treatments. These techniques allow researchers to begin to dissect the role of disease-associated proteins and to predict how mutations of these 
proteins may function in vivo.

Numerous recent studies have identified mutations in synaptic proteins associated with brain pathologies. Primary cultured cortical neurons offer great flexibility in examining the effects of these disease-associated proteins on dendritic spine morphology and motility.

培養中枢神経系ニューロンの樹状突起スパイン形態の解析

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These ...

Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics

Nervous system development requires the correct specification of neuron position and identity, followed by accurate neuron class-specific dendritic development and axonal wiring. Recently the dendritic arborization (DA) sensory neurons of the Drosophila larval peripheral nervous system (PNS) have become powerful genetic models in which to elucidate both general and class-specific mechanisms of neuron differentiation.
There are four main DA neuron classes (I-IV)1. They are named in order of increasing dendrite arbor complexity, and have class-specific differences in the genetic control of their differentiation2-10. The DA sensory system is a practical model to investigate the molecular mechanisms behind the control of dendritic morphology11-13 because: 1) it can take advantage of the powerful genetic tools available in the fruit fly, 2) the DA neuron dendrite arbor spreads out in only 2 dimensions beneath an optically clear larval cuticle making it easy to visualize with high resolution in vivo, 3) the class-specific diversity in dendritic morphology facilitates a comparative analysis to find key elements controlling the formation of simple vs. highly branched dendritic trees, and 4) dendritic arbor stereotypical shapes of different DA neurons facilitate morphometric statistical analyses.
DA neuron activity modifies the output of a larval locomotion central pattern generator14-16. The different DA neuron classes have distinct sensory modalities, and their activation elicits different behavioral responses14,16-20. Furthermore different classes send axonal projections stereotypically into the Drosophila larval central nervous system in the ventral nerve cord (VNC)21. These projections terminate with topographic representations of both DA neuron sensory modality and the position in the body wall of the dendritic field7,22,23. Hence examination of DA axonal projections can be used to elucidate mechanisms underlying topographic mapping7,22,23, as well as the wiring of a simple circuit modulating larval locomotion14-17.
We present here a practical guide to generate and analyze genetic mosaics24 marking DA neurons via MARCM (Mosaic Analysis with a Repressible Cell Marker)1,10,25 and Flp-out22,26,27 techniques (summarized in Fig. 1).

Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics

The dendritic arborization sensory neurons of the Drosophila larval peripheral nervous system are useful models to elucidate both general and neuron class-specific mechanisms of neuron differentiation. We present a practical guide to generate and analyze dendritic arborization neuron genetic mosaics.

の形態素解析ショウジョウバエ</em遺伝モザイクを使用>幼虫末梢感覚ニューロンの樹状突起と軸索

Nervous system development requires the correct specification of neuron position and identity, followed by accurate neuron class-specific dendritic ...

The Analysis of Purkinje Cell Dendritic Morphology in Organotypic Slice Cultures

Purkinje cells are an attractive model system for studying dendritic development, because they have an impressive dendritic tree which is strictly oriented in the sagittal plane and develops mostly in the postnatal period in small rodents 3. Furthermore, several antibodies are available which selectively and intensively label Purkinje cells including all processes, with anti-Calbindin D28K being the most widely used. For viewing of dendrites in living cells, mice expressing EGFP selectively in Purkinje cells 11 are available through Jackson labs. Organotypic cerebellar slice cultures cells allow easy experimental manipulation of Purkinje cell dendritic development because most of the dendritic expansion of the Purkinje cell dendritic tree is actually taking place during the culture period 4. We present here a short, reliable and easy protocol for viewing and analyzing the dendritic morphology of Purkinje cells grown in organotypic cerebellar slice cultures. For many purposes, a quantitative evaluation of the Purkinje cell dendritic tree is desirable. We focus here on two parameters, dendritic tree size and branch point numbers, which can be rapidly and easily determined from anti-calbindin stained cerebellar slice cultures. These two parameters yield a reliable and sensitive measure of changes of the Purkinje cell dendritic tree. Using the example of treatments with the protein kinase C (PKC) activator PMA and the metabotropic glutamate receptor 1 (mGluR1) we demonstrate how differences in the dendritic development are visualized and quantitatively assessed. The combination of the presence of an extensive dendritic tree, selective and intense immunostaining methods, organotypic slice cultures which cover the period of dendritic growth and a mouse model with Purkinje cell specific EGFP expression make Purkinje cells a powerful model system for revealing the mechanisms of dendritic development.

We present a protocol that permits to view and to quantitatively asses the morphology of the dendritic tree of individual Purkinje cells grown in organotypic cerebellar slice cultures. This protocol is intended to promote studies on the mechanisms of Purkinje cell dendritic development.

器官切片培養におけるプルキンエ細胞の樹状突起の形態分析

Purkinje cells are an attractive model system for studying dendritic development, because they have an impressive dendritic tree which is strictly ...

Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings

The combination of patch clamp recordings from two (or more) synaptically coupled neurons (paired recordings) in acute brain slice preparations with simultaneous intracellular biocytin filling allows a correlated analysis of their structural and functional properties. With this method it is possible to identify and characterize both pre- and postsynaptic neurons by their morphology and electrophysiological response pattern. Paired recordings allow studying the connectivity patterns between these neurons as well as the properties of both chemical and electrical synaptic transmission. Here, we give a step-by-step description of the procedures required to obtain reliable paired recordings together with an optimal recovery of the neuron morphology. We will describe how pairs of neurons connected via chemical synapses or gap junctions are identified in brain slice preparations. We will outline how neurons are reconstructed to obtain their 3D morphology of the dendritic and axonal domain and how synaptic contacts are identified and localized. We will also discuss the caveats and limitations of the paired recording technique, in particular those associated with dendritic and axonal truncations during the preparation of brain slices because these strongly affect connectivity estimates. However, because of the versatility of the paired recording approach it will remain a valuable tool in characterizing different aspects of synaptic transmission at identified neuronal microcircuits in the brain.

Patch-clamp recordings and simultaneous intracellular biocytin filling of synaptically coupled neurons in acute brain slices allow a correlated analysis of their structural and functional properties. The aim of this protocol is to describe the essential technical steps of electrophysiological recording from neuronal microcircuits and their subsequent morphological analysis.

急性脳スライスにおけるニューロンマイクロ回路の電気生理学的および形態学的特徴は、ペアパッチクランプ記録を使用して、

The combination of patch clamp recordings from two (or more) synaptically coupled neurons (paired recordings) in acute brain slice preparations with ...

Assessment of Dendritic Arborization in the Dentate Gyrus of the Hippocampal Region in Mice

Dendritic arborization has been shown to be a reliable marker for examination of structural and functional integrity of neurons. Indeed, the complexity and extent of dendritic arborization correlates well with the synaptic plasticity in these cells. A reliable method for assessment of dendritic arborization is needed to characterize the deleterious effects of neurological disorders on these structures and to determine the effects of therapeutic interventions. However, quantification of these structures has proven to be a formidable task given their complex and dynamic nature. Fortunately, sophisticated imaging techniques can be paired with conventional staining methods to assess the state of dendritic arborization, providing a more reliable and expeditious means of assessment. Below is an example of how these imaging techniques were paired with staining methods to characterize the dendritic arborization in wild type mice. These complementary imaging methods can be used to qualitatively and quantitatively assess dendritic arborization that span a rather wide area within the hippocampal region.

We describe two methods for visualization and quantification of dendritic arborization in the hippocampus of mouse models: real-time and extended depth of field imaging. While the former method allows sophisticated topographical tracing and quantification of the extent of branching, the latter allows speedy visualization of the dendritic tree.

マウスの海馬領域の歯状回における樹状樹枝状分岐の評価

Dendritic arborization has been shown to be a reliable marker for examination of structural and functional integrity of neurons. Indeed, the complexity ...

Assessment of Hippocampal Dendritic Complexity in Aged Mice Using the Golgi-Cox Method

Dendritic spines are the protuberances from the neuronal dendritic shafts that contain&#160; excitatory synapses. The morphological and branching variations of the neuronal dendrites within the hippocampus are implicated in cognition and memory formation. There are several approaches to Golgi staining, all of which have been useful for determining the morphological characteristics of dendritic arbors and produce a clear background. The present Golgi-Cox method, (a slight variation of the protocol that is provided with a commercial Golgi staining kit), was designed to assess how a relatively low dose of the chemotherapeutic drug 5-flurouracil (5-Fu) would affect dendritic morphology, the number of spines, and the complexity of arborization within the hippocampus. The 5-Fu significantly modulated the dendritic complexity and decreased the spine density throughout the hippocampus in a region-specific manner. The data presented show that the Golgi staining method effectively stained the mature neurons in the CA1, the CA3, and the dentate gyrus (DG) of the hippocampus. This protocol reports the details for each step so that other researchers can reliably stain tissue throughout the brain with high quality results and minimal troubleshooting.

Here we present a Golgi-Cox protocol in extensive detail. This reliable tissue stain method allows for a high-quality assessment of the cytoarchitecture in the hippocampus, and throughout the entire brain, with minimal troubleshooting.

Golgi-Cox法を用いた老齢マウスにおける海馬の樹状突起の複雑さの評価

Dendritic spines are the protuberances from the neuronal dendritic shafts that contain&#160; excitatory synapses. The morphological and branching ...

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

The mammalian neocortex is composed of many types of excitatory and inhibitory neurons, each with specific electrophysiological and biochemical properties, synaptic connections, and in vivo functions, but their basic functional and anatomical organization from cellular to network scale is poorly understood. Here we describe a method for the three-dimensional imaging of fluorescently-labeled neurons across large areas of the brain for the investigation of the cortical cellular organization. Specific types of neurons are labeled by the injection of fluorescent retrograde neuronal tracers or expression of fluorescent proteins in transgenic mice. Block brain samples, e.g., a hemisphere, are prepared after fixation, made transparent with tissue clearing methods, and subjected to fluorescent immunolabeling of the specific cell types. Large areas are scanned using confocal or two-photon microscopes equipped with large working distance objectives and motorized stages. This method can resolve the periodic organization of the cell type-specific microcolumn functional modules in the mouse neocortex. The procedure can be useful for the study of three-dimensional cellular architecture in the diverse brain areas and other complex tissues.

Here we describe a procedure for tissue clearing, fluorescent labeling, and large-scale imaging of mouse brain tissue which, thereby, enables visualization of the three-dimensional organization of cell types in the neocortex.

マウス大脳皮質における細胞組織の大規模三次元イメージング

The mammalian neocortex is composed of many types of excitatory and inhibitory neurons, each with specific electrophysiological and biochemical ...

Ballistic Labeling of Pyramidal Neurons in Brain Slices and in Primary Cell Culture

It has been reported that the size and shape of dendritic spines is related to their structural plasticity. To identify the morphological structure of pyramidal neurons and dendritic spines, a ballistic labeling technique can be utilized. In the present protocol, pyramidal neurons are labeled with DilC18(3) dye and analyzed using neuronal reconstruction software to assess neuronal morphology and dendritic spines. To investigate neuronal structure, dendritic branching analysis and Sholl analysis are performed, allowing researchers to draw inferences about dendritic branching complexity and neuronal arbor complexity, respectively. The evaluation of dendritic spines is conducted using an automatic assisted classification algorithm integral to the reconstruction software, which classifies spines into four categories (i.e., thin, mushroom, stubby, filopodia). Furthermore, an additional three parameters (i.e., length, head diameter, and volume) are also chosen to assess alterations in dendritic spine morphology. To validate the potential of wide application of the ballistic labeling technique, pyramidal neurons from in vitro cell culture were successfully labeled. Overall, the ballistic labeling method is unique and useful for visualizing neurons in different brain regions in rats, which in combination with sophisticated reconstruction software, allows researchers to elucidate the possible mechanisms underlying neurocognitive dysfunction.

We present a protocol to label and analyze pyramidal neurons, which is critical for evaluating potential morphological alterations in neurons and dendritic spines that may underlie neurochemical and behavioral abnormalities.

脳スライスと一次細胞培養における錐体ニューロンの弾道標識

It has been reported that the size and shape of dendritic spines is related to their structural plasticity. To identify the morphological structure of ...

Automatic Identification of Dendritic Branches and their Orientation

The structure of neuronal dendritic trees plays a key role in the integration of synaptic inputs in neurons. Therefore, characterization of the morphology of dendrites is essential for a better understanding of neuronal function. However, the complexity of dendritic trees, both when isolated and especially when located within neuronal networks, has not been completely understood. We developed a new computational tool, SOA (Segmentation and Orientation Analysis), which allows automatic measurement of the orientation of dendritic branches from fluorescence images of 2D neuronal cultures. SOA, written in Python, uses segmentation to distinguish dendritic branches from the image background and accumulates a database on the spatial direction of each branch. The database is then used to calculate morphological parameters such as the directional distribution of dendritic branches in a network and the prevalence of parallel dendritic branch growth. The data obtained can be used to detect structural changes in dendrites in response to neuronal activity and to biological and pharmacological stimuli.

Presented is a computational tool that allows simple and direct automatic measurement of orientations of neuronal dendritic branches from 2D fluorescence images.

樹状枝の自動同定とその向き

The structure of neuronal dendritic trees plays a key role in the integration of synaptic inputs in neurons. Therefore, characterization of the morphology ...