A complete guide to imaging and analyzing spines and neurons with Neurolucida 360

Following a well-designed protocol is essential to achieving accurate and consistent results in scientific research. Now, scientists using Neurolucida 360 for dendritic spine and neuron analysis can follow a published set of guidelines to ensure optimal confocal data series for proper dendritic spine quantification and neuron reconstruction. The paper, written by MBF Bioscience scientists and researchers from the Icahn School of Medicine at Mount Sinai in New York, was published in Current Protocols in Neuroscience.

The four protocols describe best practices for imaging and analyzing dendritic spines and entire neurons. Clearly laid out procedures specify necessary materials, image acquisition techniques, and analysis procedures with Neurolucida 360.

Imaging technique is crucial to obtaining unbiased, reproducible results. Clear, crisp images captured with an appropriate z-interval will make analysis with Neurolucida 360 easier and more accurate. Throughout the paper, the authors emphasize the importance of image scaling parameters and unbiased sampling for achieving repeatable results. They also discuss the benefits of correcting optical distortion, especially in the Z-plane, with deconvolution to acquire clear images – a process critical to getting the most accurate representation of dendrites and spines.

Dendritic spine analysis is traditionally performed through tedious, time-consuming manual techniques. According to the paper, this has spawned a growing interest in a more efficient solution for spine quantification and morphological analysis like the one Neurolucida 360 provides. A software platform for automatic neuron reconstruction and spine detection in a 3D environment, Neurolucida 360 offers a variety of benefits, including:


  • Fast and accurate spine detection and neuron reconstruction
  • Accurate spine classification and length quantification using a five-point segment that more accurately models the spine backbone.
  • 3 user-guided and automatic algorithms to accurately model neurons visualized with multiple methodologies and imaging techniques.
  • A large number of metrics, including volume, length, and surface area.


“We believe that the new quantitative software package, Neurolucida 360, provides the neuroscience research community with the ability to perform higher throughput automated 3D quantitative light microscopy spine analysis under standardized conditions to accelerate the characterization of dendritic spines with greater objectivity and reliability,” (Dickstein, et al. 2016)

The full paper can be found here.

An infographic quickly outlines Protocol 1: Imaging of fluorescently labeled dendritic segments. Use this as a quick reference tool in your lab (right-click on it to save as an image):

Dickstein, D.L., Dickstein, D.R., Janssen, W.G.M., Hof, P.R., Glaser, J.R., Rodriguez, A., O’Connor, N., Angstman, P., and Tappan, S.J. 2016. Automatic dendritic spine quantification from confocal data with Neurolucida 360. Curr. Protoc. Neurosci. 77:1.27.1-1.27.21. doi: 10.1002/cpns.16

Scientists Discover Anorexia-Driven Changes to Dendrites With Neurolucida

A digital reconstruction of a CA1 pyramidal cell from the ventral hippocampus, traced using Neurolucida with Sholl spheres at 20 micron intervals. Cells in this region featured greater dendritic length and branching versus controls.

A digital reconstruction of a CA1 pyramidal cell from the ventral hippocampus of a rat with activity-based anorexia, traced using Neurolucida with Sholl spheres at 20 micron intervals. Cells in this region featured greater dendritic length and branching versus controls.

Gaunt facial features and a frighteningly thin figure are physical hallmarks of anorexia nervosa, an eating disorder that predominantly affects adolescent girls. But in addition to extreme weight loss, changes take place that aren’t as visually apparent. For the first time, scientists in New York have found evidence of brain plasticity in the activity-based anorexia (ABA) mouse model.

Led by Dr. Chiye Aoki of New York University, the research team used Neurolucida to analyze pyramidal neurons in the rat brain. Since anorexia is linked to elevated stress hormones and anxiety, the researchers focused on the hippocampus, a region that regulates anxiety and is known to change structurally in response to hormones and stress.

“Using Neurolucida, we were able to collect, store, and analyze large amounts of data with more precision and accuracy than would have been possible without the digital interface,” said Tara Chowdhury, a graduate student working in Dr. Aoki’s lab, and first author of the paper.

“Additionally, with its very approachable interface, the software allowed us to trace dendrites, get precise thickness measurements, and categorize spine types easily during tracing. The built-in Sholl analysis and spine analysis tools resulted in quick quantification of all the measurements that would have taken hours to achieve without Neurolucida.”

Continue reading “Scientists Discover Anorexia-Driven Changes to Dendrites With Neurolucida” »

Neuroscientists in Germany Outline Protocol for Best Accuracy in Neuron Reconstruction, including Use of Neurolucida

biocytinNo two neurons are exactly alike. Structure dictates function, so for scientists to fully understand the way different types of neurons work, they must first get to know their forms.

Scientists at the Institute for Neuroscience and Medicine at the Research Center Jülich in Jülich, Germany use Neurolucida to perform neuron reconstruction, the most effective method for studying neuron morphology.

In their paper “Improved biocytin labeling and neuronal 3D reconstruction,” published last year in Nature Protocols, the German team describes a distinct series of steps, which must be carried out before a truly accurate model of a neuron can be created. From brain dissection and slice preparation to fixation, staining, embedding, and 3D reconstruction, the authors clearly lay out the process.

In detailing their protocol, the team took into consideration common issues that occur with the embedding and labeling of neuronal tissue such as shrinkage, distortion, and fading. Biocytin labeling, they say, is superior to other methods because of the “extremely durable and strong staining” it achieves. According to them, the labeling method also allows for tissue to be re-examined “to test a new scientific hypothesis or to verify the findings in a different context.”

In one section of the protocol, entitled “Suggestions for 3D, light-microscopic reconstructions of neurons,” the authors describe how to perform 3D reconstructions of biocytin labeled neurons with Neurolucida. “This software allows manual reconstructions of neurons in all three dimensions and generates reconstruction data files in the Neurolucida format for a quantitative morphological analysis,” they explain.

Read “Improved biocytin labeling and neuronal 3D reconstruction” at nature.com.

(Note that the image above is for illustration purposes only and was not actually used in the study described in this post.)

Marx, M., Günter, R. H., Hucko, W., Radnikow, G., & Feldmeyer, D. (2012). Improved biocytin labeling and neuronal 3D reconstruction. Nature protocols,7(2), 394-407.

Neurolucida and Stereo Investigator 10 Available Now

From Alzheimer’s disease to Multiple Sclerosis, genetic disorders, stroke recovery, and stress, Stereo Investigator and Neurolucida are helping scientists around the globe carry out their research. Our flagship products are the leading tools for unbiased stereology and neuron reconstruction. With the release of Version 10, we’re pleased to unveil a whole new set of exceptional features.

Stereo Investigator allows researchers to use unbiased stereology to count cells in a microscope specimen, and to quantify the size and volume of microscopic objects and areas. Neurolucida is the leading software for neuron reconstruction and analysis in labs around the world.

The new Version 10 of both Stereo Investigator and Neurolucida gives researchers numerous new features including:

• The ability to create 3D mosaics from image stacks from confocal, brightfield and fluorescent microscopes

• Integrated deconvolution

• The ability to create 3D focusable slides

• 3D visualization/solid modeling

• Integration with most major confocal microscopes

• Integration with the Zeiss ApoTome 2

Jack Glaser, President and Co-founder of MBF, says “We’re grateful to have a global network of loyal users who give us a constant flow of ideas for improving and expanding our products’ capabilities to match scientists’ evolving research needs. We also use our systems in our own contract research organization, MBF Labs. This gives us first-hand experience using our software, which is another rich source of inspiration. We’ve taken the most powerful ideas from all those sources and developed them into productive features in Version 10, so our users can continue to get the best images, data and analysis possible from their microscopes.”

Get the full list of Stereo Investigator 10 and Neurolucida 10 features on our website, and read our interview with Vice President Paul Angstman to find out about some of his favorite things in Neurolucida 10 and Stereo Investigator 10.

The Inside View

Jack Glaser, MBF Bioscience President

by Jack Glaser, President

We pride ourselves on designing cutting edge applications that are comprehensive, easy-to-use, and tailored to your research.

Three years ago, we launched AutoNeuron for automated neuron reconstruction. Today, I am proud to announce that we are continuing our tradition of innovation with version 9.0 of Stereo Investigator, which includes automated 3D cell detection with colocalization. It significantly reduces the time and effort required to get reliable cell counts, providing you with the tools you need to be even more productive. It also automatically measures volume and shape. And we have included tools to determine how well the automated cell detection is performing, so you can be sure that the cell count is accurate.

Stereo Investigator 9, Automated 3D Cell Detection

We are also introducing automatic 2D contouring for serial section reconstruction and region delineation from acquired images or directly from a live digital camera image feed. On the hardware side, we have expanded our support for confocal and structured illumination with two new cost-effective solutions (The CARV II and the Qioptiq OptiGrid). All of these enhancements and more will be on display at Neuroscience 2008 next month in Washington, D.C. I invite you to stop by Exhibit #1435 to take a look for yourself.

I, and all of us at MBF, thank you for your continued support.

First published in The Scope, fall 2008.