Imagej

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Batch Processing in ImageJ (PDF) EMBL/CMCI ImageJ Course Textbooks; ImageJ Basics (PDF) Image Processing with ImageJ (PDF) ImageJ Tutorial (PPT) and Example Images; ImageJ Batch Processing in ImageJ (PDF) EMBL/CMCI ImageJ Course Textbooks; ImageJ Basics (PDF) Image Processing with ImageJ (PDF) ImageJ Tutorial (PPT) and Example Images; ImageJ

ImageJ - ImageJ - imagej.github.io

除了 ImageJ，大家应该还听说过 Fiij（Fiij is just Image J ）、Image pro plus。如果你不知道这三者该选哪一个作为你的生物图像分析处理软件，不妨看看以下对这三个软件的对比分析。文章内也分享了安装教程，三个工具的安装包以及工具的配套教程打包好了，有需要在福麦斯生物公众hao回复“实验06”就能下载。一、Image J 1、ImageJ 介绍基于强大的图片分析与处理功能，Image J在科研中的应用极为广泛。2021年被Nature评为十大影响科学的代码。最关键的，这款软件是完全免费！ImageJ 是一个基于 java 的公共的图像处理软件，能够显示，编辑，分析，处理，保存，打印 8 位，16 位，32 位的图片， 支持 TIFF，PNG， GIF， JPEG， BMP， DICOM， FITS 等多种格式。支持图像栈（stack）功能，即在一个窗口里以多线程的形式层叠多个图像， 并行处理。只要内存允许，ImageJ 能打开任意多的图像进行处理。除了基本的图像操作， 比如缩放，旋转， 扭曲， 平滑处理外，ImageJ 还能进行图片的区域和像素统计，间距，角度计算，能创建柱状图和剖面图，进行傅里叶变换。ImageJ 的科研应用：①免疫组织化学/原位杂交目的区域光密度分析② 共聚焦图像中两种蛋白共定位的程度（相关系数计算）③免疫荧光图像分析:计数兴趣区大小、阳性点密度、数量，结构长度分析④ 高尔基染色的神经元或者共聚焦显微图像中表达EGFP等神经元突起（树突、轴突）长度测量，Sholl分析，突触棘计数⑤阳性细胞技术等等...ImageJ 的优点：免费（不用担心知识产权问题），程序小，运行快，操作简单，不断有新的插件加入，非常适用于经费有限的实验室以及初入门的神经科学研究生。如果只需要一些基础的操作，例如Western Blot条带定量、荧光定量等，推荐大家选择ImageJ。如果基本功能不满足，也可以自行安装其它插件。小tips：如果需要使用的插件比较多（正好你还是生命科学领域的研究人员），更推荐下面说到的fiji（fijiis just ImageJ），它是ImageJ的版本之一。详细介绍可看下文对fiji的介绍。2、lmageJ 安装lmageJ 可运行于 Microsoft Windows，Mac OS，Mac OS X，Linux，和 Sharp Zaurus PDA 等多种平台。安装包文章开头分享了。根据电脑系统选择的安装包，双击安装文件之后开始安装，安装步骤非常简单，这里就不做分享了。注意：要在预装JAVA的计算机上安装lmageJ。二、fiji is just ImageJ1、fiji介绍fiji 是 ImageJ 的版本之一，全称为 fiji is just ImageJ。fiji 就是预装了很多生物医学分析常用插件的ImageJ。如果不想手动安装插件，更推荐你安装 fiji。fiji 由于预装的插件非常丰富（如神经元追踪、荧光共定位等），所以安装包略大一些，打开速度也会略慢。fiji 和 ImageJ 的区别：fiji 里绑定的命令和插件超过五百个，目标用户是生命科学领域的研究人员，为此捆绑了很多该领域用户会经常用到的插件。而 ImageJ 需要手动安装插件。另外对于 fiji 里绑定的超过五百个命令和插件，你不需要记住他们在哪个菜单和子菜单里，只要在搜索栏里输入命令的名字，就可以直接调用。做个小补充：fiji 不是一个全新的软件，只是 ImageJ 的一个针对生命科学用户的发布版本。但是 fiji 不是 ImageJ 唯一的发布版本。比如，面向天文学研究人员的SalsaJ，用于显微镜控制和图像获取的 µManager 等。用一句话概括的话，fiji is just imageJ， but ImageJ is not just fiji.2、fiji 安装安装包在文章开头分享了。fiji 在 macosx、windows（7以及7以上的版本）、Linux (64-bit) 上都能使用。根据自己的电脑系统选择对应的安装包进行解压。如windows 64位就选择fiji-win64.zip进行解压，解压之后点击ImageJ-win64exe，fiji直接双击就能打开软件使用，没有安装步骤。注意：下载好安装包之后不要把安装包保存在C盘，同时保存到磁盘的文件夹命名不要出现中文字，否则软件会出现出发打开或者闪退的现象。3、fiji 闪退的解决办法①可能你的fiji is just ImageJ的储存目录有中文命名的文件夹。就是你解压路径中不包含中文名称目录，并且不要解压在“program files”路径中。②不要把安装包放在C盘。③fiji is just ImageJ需要Java环境，如果闪退那么可能是你的电脑Java版本太低。Java下载地址如下：Java SE Development Kit： ImageJ 和 fiji 的介绍和对比之后，相信你对于这两个版本该如何选择，心里应该有了答案！如果你是生命科学领域的从业者，选 fiji 就好了。没有特殊的需求，它绑定的插件足够你使用，之后就不需要你自己再手动安装插件。什么情况下需要选择 ImageJ（ImageJ1.X）？① ImageJ 菜单里的基本功能就能满足你的要求，不需要其他插件，这种情况下可以选择单独的ImageJ（ImageJ1.X）。因为体积比fiji小，它的启动速度也比 fiji 要快，这也是使用ImageJ的之一。②有一些早期开发的 ImageJ 插件，只提供了后缀为.java的文件。这种情况下可以用ImageJ的plugins > compile and run命令将之编译为.class文件，然后再放到 fiji 里使用。但这种方法也有失灵的时候，这种情况下就只能在ImageJ里使用该插件了。四、Image pro plus1、Image pro plus 介绍除了ImageJ和fiji，还有一个 Image pro plus，身边也有很多大佬都在用这个软件。或许你也听说过这个软件。Image-Pro Plus 也是一款用于科学图像处理和分析的软件，它是 Image-Pro 软件系列的一部分，广泛应用于医学、生物学、材料科学和工程学等领域，可与其他软件和设备进行无缝集成。由于 Image-Pro Plus 是商业软件，用户需要购买许可证才能使用。文末分享了 image pro plus 的破解版安装包免费使用（仅供学习使用）。image pro plus 的功能包括：图像增强和校正功能图像分割和测量工具图像拼接，图像配准和图像融合，可用于创建全景图像和多模态图像跟踪和测量运动对象，生成动态图像直方图分析，图像分类，颜色分析和形状分析等自动化处理流程和批量处理大量图像数据Image pro plus 的科研应用：合成荧光图片、免疫组化图片光密度测量、凝胶电泳图片的测量、凝胶电泳图片的测量、荧光强度测量、测量鼠脑切片的梗塞面积测量心肌纤维截面积、找两张图片的差异之处、测量划痕实验的细胞间距、测量网状的细胞壁等等。2、Image pro plus 安装安装包分享在文章开头了解压文件，确保软件所放置的路径里没有中文（既所有文件夹名字里都没有中文，分区名字也没有中文，如有同学喜欢把分区命名为“软件”什么的，改成英文即可），暂时关闭 360 等卫士。以前如果装过Image-Pro Plus 需要先卸载。打开【ipp6.0】文件夹，双击运行【start】文件点击 Install Image-Pro Plus 开始安装按照默认路径安装(不能修改，一定要按默认安装在c 盘，否则会导致软件不可使用)。选Typical 安装，遇到要填名称和单位的界面，随便填即可。一路 next 即可。有部分笔记本电脑(如华硕)会出现 EnTech Taiwan 驱动的错误提示，这是电脑触摸板的驱动，点关闭就行。打开【crack 文件】文件夹，复制里面三个文件，覆盖软件安装路径下（C:\IPWIN60）的文件。运行【ipwin32】即可打开软件，选 complete。弹出的注册对话框，勾选不再提醒，点 remind me later 即可。不用注册(其实已注册)。另一个对话框也是关掉就行。五、imagej和image pro plus如何选择？Image-Pro Plus 与 ImageJ均具有强大的图像分析功能。总体来看，更推荐Image J。①在标定方面，Image-Pro Plus 标定方法及具体操作与 Image J 无明显差别；②在 ROI 选择及基本参数测试方面，Image-Pro Plus 的操作选择方式及备选参数数量较Image J丰富；③在添加插件功能方面，Image J 可供下载及利用的插件数量远远多于 Image-Pro Plus；④在操作实现方面，ImagePro Plus 的一些常用操作，如 ROI 选择，参数测试等较 Image J 复杂。⑤image pro plus 其实和 ImageJ 分析的指标都差不多，但是 image pro plus 操作起会更复杂，对初学者来说不太实用。⑥从费用上来说，实验室资金充足完全可以购买 image pro plus 这类收费软件。但是相比起来 ImageJ 的免费使用就更经济实惠。如何选择？①当 Image J 和 Image-Pro Plus 基本功能都能满足测试要求时，首选 Image J。②如果图像分割困难，或不想借助插件而能测试较多的参数，推荐 Image-Pro Plus 为首选图像分析软件。③如果 Image-Pro Plus 和 Image J 软件的基本功能不足以满足具体测试需求，需通过添加插件来扩展功能，或者是直接安装 fiji。以上就是对于 Image J、fiji、Image pro plus 三个生物图像分析处理软件的详细介绍，希望能对你有所帮助！科研资源汇总扫描下方【福麦斯生物】公众hao二维码，回复对应的资源关键词就能在公众号下载资源。举个栗子：如果你想下载endnote安装包，你就在【福麦斯生物】公众hao回复：软件314，之后会自动弹出安装包。endnote、zotero、spss、GraphPadPrism都有激活版的安装包！顶级图像分析工具，ImageJ、Fiji、Image pro plus，选这3款准没错！科研绘图王炸：11款矢量素材免费网站/软件合集！画科研插图一定要选ScienceSlides！好用到离谱！打包科研大佬的绘图软件，使用频率最高的Top 9安装！（带安装包）OriginPro 2022，更多拓展图形模板！GraphPad Prism 9.3 英文版，（含激活码）+软件教程 白嫖这12个插件，让你的Zotero成为地表最强文献管理器！ EndNote X9突然提示要激活？最新解决办法来了！Adobe Acrobat Pro 2023，科研人必备的PDF编辑器！ StyleWriter最新白嫖方案 | 神器在手！润色不愁！附报错解决 润色出神仙SCI，WhiteSmoke来了 引物设计神器Oligo 6、Oligo 7安装教程（带安装包）引物设计神器！Primer Premier 5&6安装分项（带安装包）Primer Premier 6，3分钟教你完成引物设计（含软件安装）SnapGene 6.02，DNA可视化，分子克隆、序列编辑就用它！（可切换中文） Please use version inside folder "03-18-2016_release".Instructions:1. Place all files inside the "jars" folder inside the following directory: Program Files > ImageJ > plugins2. Simply drag moco_.jar onto ImageJ.Alternatively (if that doesn't work for some reason),Open ImageJ, clickPlugins > Install Plugin...and choose 10092015_release>moco_.jar.3. Restart ImageJ, and and the moco plugin should show up under Plugins.---------------------------------Directions: You must have open the stack and the template image that you want to align the stack with (i.e. the first image in the stack, or the average image of all frames in the stack).w: The maximimum distance (in pixels) to be translated in the x and y directions. (i.e. w = 2 means that the maximum translation can be 2 pixels up/downand 2 pixels left/right).Downsample value: The amount of times to downsample by 2 for faster processing. (i.e. downsampling 512x512 image by 1 makes it 256x256). Leads to problems if downsample value is too large.Generate log file: Generates a results table that shows the amount by which each image was translated. Can be saved and used for other images/channels.Plot: Plots the sqrt(x^2 + y^2), i.e. the amount of total translation for each frame(to plot RMS, you must also choose to generate the log file).If an image in the stack to be registered is translated by amounts that seem too large, then the program will warn you and will allow you to normalize the intensity in the image (which can improve results).We recommend that you use 8-bit stacks for registration (there are sometimes issues with 16-bit stacks that lead to translation terms that are too large as noted above). If you generate a log file and save it, you can use it later to register the original 16-bit stack really fast. Email [email protected] to ask any questions or report any bugs or feature requests.

imagej tutorial for beginners-imagej threshold-imagej

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ImageJ/ij/IJ.java at master imagej/ImageJ - GitHub

Save As is a good habit for ImageJ, as it ensures you never accidentally save over any raw files that may be used for later analysis. A note on colourIn most fluorescence microscopy, images are captured in grayscale. As we’ve seen in ImageJ, pseudocolour can be added to these images using LUTs - this was done automatically when we produced our composite image. A researcher’s choice of colour when presenting fluorescence imagery is entirely a matter of preference. However, it is well understood that the human eye perceives colour information in a non-linear fashion. We are more sensitive to colours in the yellow range and have decreased sensitivity in the blue range. This is why purples and blues are harder to see in comparison to yellows and greens of the same luminance. To circumvent these hardwired biases, single-channel fluorescence images should always be shown in grayscale. This is not to say that coloured images are never useful, however. For example, colocalisation studies are often facilitated by multi-channel overlay images, where analogous colours like red and green are chosen to highlight areas of overlap, appearing yellow. In these cases, single-channel grayscale images should be displayed alongside the merged images. Lastly, presenting grayscale images avoid issues relating to colourblindness. Where colour is required, careful consideration should be taken and red-green alternatives like cyan-magenta are preferable. Finding a colourblind-safe palette becomes increasingly difficult with multi-channel images of 3 or more, therefore, the inclusion of separated grayscale images is again preferable. To help generate such palettes, try our Colour Palette Generator which allows you to create striking new colour palettes or includes several colourblind-safe and perceptually uniform options easily that can be easily ported into Illustrator in our final step.With that in mind, we can now begin to piece together our final figure using Adobe Illustrator.4. Figure preparationTo ensure the highest quality, we’ll copy our images directly from ImageJ into Illustrator. Select the first channel using the Grayscale option in the Channels Tool, then select Edit -> Copy to System and paste it into your Illustrator document. Repeat this process for all the individual channels you would like to show, as well as the merged colour images and the image containing the scale bar. You can then align, group and resize all the images using the Align and Distribute tools (Shift+F7). Next, I overlay the scale bar image on top of my first single-channel PyImageJ: Python wrapper for ImageJ2PyImageJ provides a set of wrapper functions for integration between ImageJ2and Python. It also supports the original ImageJ API and data structures.A major advantage of this approach is the ability to combine ImageJ and ImageJ2with other tools available from the Python software ecosystem, including NumPy,SciPy, scikit-image, CellProfiler, OpenCV, ITK and many more.Quick StartJump into the documentation and tutorials to get started!System RequirementsHardware RequirementsPyImageJ requires at minimum a standard computer with enough RAM and CPUperformance to support the workflow operations defined by the user. WhilePyImageJ will run on a range of hardware, we recommend the following RAMand CPU specifications:RAM: >= 2 GB (64 MB minimum)CPU: >= 1 coreNotably, PyImageJ can be installed and used on server infrastructure forlarge scale image processing.OS RequirementsPyImageJ has been tested on the following operating systems:Linux (Ubuntu 20.04 LTS)WindowsmacOSSoftware RequirementsPyImageJ requires the following packages:Python >= 3.7imglyb >= 2.1.0jgo >= 1.0.3JPype >= 1.3.0labeling >= 0.1.14matplotlib (optional, for ij.py.show function only)NumPyscyjava >= 1.8.0xarrayPyImageJ will not function properly if dependency versions are too old.In addition, PyImageJ requires OpenJDK and Maven to be installed.InstallationOn Mac and Linux, PyImageJ can be installed using Conda+Mamba. Here is how to createand activate a new conda environment with PyImageJ available:conda install mamba -n base -c conda-forgemamba create -n pyimagej -c conda-forge pyimagej openjdk=8conda activate pyimagejYou can also pip install pyimagej, but will then need to install OpenJDK and Maven manually.Installation time takes approximately 20 seconds. Initializing PyImageJtakes an additional ~30 seconds to ~2-3 minutes (depending on bandwidth)while it downloads and caches the needed Java libraries.For detailed installation instructions and requirements, seeInstallation.UsageThe first step when using PyImageJ is to create an ImageJ2 gateway.This gateway can point to any official release of ImageJ2 or to a localinstallation. Using the gateway, you have full access to the ImageJ2 API,plus utility functions for translating between Python (NumPy, xarray,pandas, etc.) and Java (ImageJ2, ImgLib2, etc.) structures.For instructions on how to start up the gateway for various settings, seeHow to initialize PyImageJ.Here is an example of opening an image using ImageJ2 and displaying it:# Create an ImageJ2 gateway with the newest available version of ImageJ2.import imagejij =

A Tutorial for using OpenCL in ImageJ - ImageJ

Nikon microscope, we export our image datasets as .nd2 files. I prefer to open these in NIS-Elements to peruse my images, as it’s fast and easy to scroll through large sets. Find the images to display in the figure and take note of the corresponding metadata found along the upper blue bar of each one. In this case, we can identify the images using the XY image number. 3. Image processingTo make raw images more visually appealing and clear for presentation, you can edit them using ImageJ. In ImageJ, open or drag in the raw file, click “OK” in the Bio-Formats Importer and select the chosen images by ticking the “Series” numbers that match the XY numbers of our chosen images. Currently, the two images are in what’s called an image stack (below, left), where the individual channels are displayed as separate slices that can be navigated by scrolling along the horizontal channel (c) bar at the bottom of each window. To see all of the channels together, select Image -> Color -> Make Composite to convert the image stack into a composite image (below, right). Now, the channels remain separated but can be displayed together to create an overlay image by selecting them in the Channels Tool (Ctrl+Shift+Z) window. The next thing we want to do is make a crop of the particular cells or part of our images that we’d like to show. Cropping is often necessary to show close details like intracellular structure or cut out any erroneous parts of the image. This is especially important when working with large-format montage images like the ones shown. It’s generally best to use the same crop size for all images in a figure panel to ensure you maintain the scale of cells you are comparing.To make a crop of a particular region of interest (ROI), open the ROI Manager using Analyze -> Tools -> ROI Manager or the shortcut “t”. The ROI Manager allows you to work with multiple selections from different parts of a single image or multiple images. Using the rectangle selection tool, create a box around the area you’d like to crop, then click Add or press “t” again to add that selection to the manager. Then select your image on the right and add a same sized selection by clicking the newly saved ROI in the manager. You can then reposition this selection to the

ImageJ - Image SXM vs. ImageJ

Photo editing Table of Content Bric is a cross-platform batch image processor. You can convert, resize, rotate and add watermark to your images. Multiple file types are supported for input and output.Batch image processing gets easier with the use of BRIC, an operating system independent tool. Its main featueres are currently converting, resizing, rotating and watermarking. Supports multiple image types, including PDF. But what sets it apart, from the other tools, is its speed, which are attained by the use of multithreading techniques.The project started back in 2011 and was maintained for a couple of years. In 2020 BRIC is again in active development, so some of the features written below might be outdated. Please be patient, until everything is reviewed and rewritten.Featuresreads jpg, jpeg, png, gif, tiff, tif, bmp, pdf, psd (photoshop), pnm (raw), pnm (ascii), pbm, ppm, pgm, wbmpwrites jpg, jpeg, png, pnm. pgm, pbm, ppm, gif, bmp, tif, tiff, pdfmultithreading (incredibly fast)convert, resize, rotate, watermark (image/text/html), merge pdfeasy watermark placementrandom rotationresize filters, rendering, sharpencross platform (Windows, Linux, Mac ...)LicenseGNU General Public License version 3.0 (GPLv3).Bric is JAVA based with Swing User interface which utilizes java image proccessing libraries Apache Sanselan, ImageIO and ImageJ. It is licenced under GNU General Public License version 3.0 (GPLv3).Resources & DownloadsDownloadHomeBRICDownload BRIC for free. BRIC is a powerful tool for batch image processing. Bric is a cross-platform batch image processor. You can convert, resize, rotate and add watermark to your images.SourceForges-r-grassBric homepage. Batch Processing in ImageJ (PDF) EMBL/CMCI ImageJ Course Textbooks; ImageJ Basics (PDF) Image Processing with ImageJ (PDF) ImageJ Tutorial (PPT) and Example Images; ImageJ Batch Processing in ImageJ (PDF) EMBL/CMCI ImageJ Course Textbooks; ImageJ Basics (PDF) Image Processing with ImageJ (PDF) ImageJ Tutorial (PPT) and Example Images; ImageJ

imagej/imagej-plugins-tools: Core ImageJ tool plugins - GitHub

To record the position of the larva inside the shuttle box at 1 second intervals. Custom software was designed integrating R (R Core Team 2014, version 3.1.2, R Foundation for Statistical Computing, and ImageJ (W.S. Rasband, version 1.46r, NIH, Bethesda, MD; to process each image sequence. Briefly, the user manually selected the boundary of both chambers, used a portion of the shuttle box with known length to calibrate pixels to centimeters, and then selected the approximate position of the larva’s head in every frame. The program used these positional records to determine the amount of time spent in each chamber, instantaneous velocities, and turning angles. Records of larval position in the center pathway were excluded from analysis.Statistical AnalysisA second level of statistical analysis was performed in R to examine group behavioral trends on both sides of the shuttle box. First, we investigated the average amount of time spent on the two sides of the chamber. Next, we calculated the “count difference”, which is, for each individual trial, the number of positional records in the odorous chamber minus the number of positional records in the control chamber. This count difference variable, if there is no overall preference for the odor, should be normally distributed with a mean of 0. A one-sample t-test (α = 0.01) was used to test the hypothesis that the mean was indeed equal to 0 when data met the assumptions of normality, independence, and random sampling. For data that was not normally distributed, a nonparametric Wilcoxon signed