Neurolucida Helps Florida Researchers Reconstruct a Region of the Rat Brain

by Dan Peruzzi, PhD

A rat uses its whiskers to get information about its environment. As it scurries along the subway tracks, or burrows into a dumpster, its whiskers send signals to ascending parts of its brain that let it know for example, whether it is safe to jump over that gap or not.

Scientists at the Max Planck Florida Institute are studying the functional responses of neurons in the rat vibrissal cortex. Using a “pipeline” method, developed to use data obtained from animals to recreate parts of the brain “in silico” (1), they have constructed a 3D model of a vibrissal cortical column. The scientists used Neurolucida® to trace neurons so they could be classified according to dendritic morphology and cell body location.

In their paper (2) “Cell Type-Specific Three-Dimensional Structure of Thalamocortical Circuits in a Column of Rat Vibrissal Cortex,” the scientists classified nine cell types in the barrel cortex, a region of the vibrissal area of the rodent somatosensory cortex. They used these cell-types and parameters such as 3D cell location and quantity, spine and bouton densities, and definitions of pre and post-synaptic partners, to assemble an anatomically realistic network that included synapses at points where boutons and spines overlapped.  Continue reading “Neurolucida Helps Florida Researchers Reconstruct a Region of the Rat Brain” »

In the Forest of the Mind

Using Neurolucida, microscopy, and mice genetically engineered to express a random amount of red, yellow, and blue fluorescent proteins, Okinawa Institute of Science and Technology researcher Hermina Nedelescu has created a fascinating and hypnotic movie of neurons. Nedelescu and colleagues at the Institute’s Computational Neuroscience Unit used Neurolucida and its Virtual Tissue 3D Extension Module and Montaging tools to acquire and stitch together multiple images of Purkinje cells—large neurons  that form elongated branching structures called “dendritic trees”—into a recording showing each tree from different angles and visual locations. As you move around and through the video, the traced cells, highlighted by the “Brainbow” coloring, show the complexity of the structures and location and how the Purkinje cells relate to each other.

Visit the  OIST Computational Neuroscience Unit page for more information on their work.

Movie by Hermina Nedelescu of the OIST Computational Neuroscience Unit (Erik De Schutter, Principal Investigator), in collaboration with Alanna Watt of McGill University, Canada, and Hermann Cuntz of Goethe University, Germany.

This article was edited to add mention of the Montaging tool.

Columbia Scientists Map Neocortical Circuit Connectivity with Neurolucida

A willowy pair of pyramidal cells engage in an intricate dance with a dense mass of basket cells on the cover of the September 14, 2011 issue of the Journal of Neuroscience.

This exquisite image illustrates recent work by Columbia University researchers Dr. Adam M. Packer and Dr. Rafael Yuste, who used Neurolucida to study circuit connectivity in the mammalian neocortex.

According to the paper “Successfully filled and stained neurons were reconstructed using Neurolucida software (MicroBrightField). The neurons were viewed with a 100× oil objective on an Olympus IX71 inverted light microscope or an Olympus BX51 upright light microscope. The Neurolucida program projected the microscope image onto a computer drawing tablet. The neuron’s processes were traced manually while the program recorded the coordinates of the tracing to create a digital, three-dimensional reconstruction. The x- and y-axes formed the horizontal plane of the slice, while the z-axis was the depth. The user defined an initial reference point for each tracing. The z-coordinate was then determined by adjustment of the focus. In addition to the neuron, the pia and white matter were drawn. Axon and dendrite densities were calculated from the Neurolucida reconstruction using the TREES toolbox (Cuntz et al., 2010). The densities were calculated with voxels 5 μm on each side.” (Packer, Yuste, 2011)

Read the open access article in The Journal of Neuroscience.

Packer, Yuste. “Dense, Unspecific Connectivity of Neocortical Parvalbumin-Positive Interneurons: A Canonical Microcircuit for Inhibition?” The Journal of Neuroscience, 14 September 2011, 31(37):13260-13271; doi:10.1523/JNEUROSCI.3131-11.2011

Scientists use Neurolucida Reconstructions to Analyze Dendritic Trees

No two trees are exactly alike, in the forest or in the brain. Though despite the diversity of dendritic arborizations, when it comes to branching out different types of neurons do have a couple things in common, say researchers at the National Institute for Physiological Sciences in Okazaki, Japan.

Led by longtime MBF Bioscience customer Dr. Yoshiyuki Kubota, the research team identified two organizational principles common to the dendritic trees of four different types of neurons.

“First, dendritic cross-sectional areas were found to be proportional to the total lengths of all distal dendritic segments. Second, nonpyramidal neuron dendrites were found to be elliptical, rather than circular, with the degree of ellipticity decreasing with dendritic size and increasing with distance from the soma,” according to the paper published last week in Scientific Reports.

The scientists used Neurolucida to carry out their analysis, forming 3D reconstructions of a Martinotti cell, a fast-spiking basket cell, a double-bouquet cell, and a large basket cell.

“Our data suggest that, in healthy neurons, dendritic structure is more precisely regulated than might be guessed given the diversity of dendritic tree morphologies,” the researchers say in their study. “It will be important for future work to assess the detailed morphology of dendrites in pathological tissue to test if alterations in dendritic tapering and branch point uniformity might participate in generating the cognitive deficits associated with disease.”

Read the full paper “Conserved properties of dendritic trees in four cortical interneuron subtypes” on Scientific Reports.

Yoshiyuki Kubota, Fuyuki Karube, Masaki Nomura, Allan T. Gulledge, Atsushi Mochizuki, Andreas Schertel, Yasuo Kawaguchi. “Conserved properties of dendritic trees in four cortical interneuron subtypes” Scientific Reports, 2011; 1 DOI: 10.1038/srep00089

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Neurolucida Helps Look at Whether Dendrites Can Tell Inputs Apart

What would you do with a neuron if you could activate its synapses in any combination you wanted? Tiago Branco, Beverley A. Clark and Michael Hauser created a chance to do just that (Branco, 2010). The authors, using in-vitro brain slices containing layer II/III pyramidal cells in visual or somatosensory cortex of rats, were able to excite identified spines in any order and with whatever timing. They activated the synapses in one direction and then in the other direction (above is a dendrite not from this study;  “In” is the direction towards the cell body, and “Out” is the direction away from the cell body) to see if the output-signal of the cell would be different.  Along the way they collected more evidence that signal integration happens at the level of the dendrite. The most exciting result is that the output-signals generated in the soma are dependent on the order that the spines were activated.

To study the oblique radial dendrite of the cortical pyramidal cell, one of the smallest dendrites in the brain, multi-site two-photon glutamate uncaging (Judkewitz, 2006; Losonczy, 2006) was used, achieving exquisite control of which spines will be activated when. The idea is to keep the excitatory neurotransmitter, glutamate, hanging around in an inactive form (represented as pink circles above). Photons are used to both convert the glutamate to its active form and to observe the fluorescently-labeled tissue. The amount of glutamate released is believed to only affect one spine, and the time course is such that it can be used to approach physiological conditions. The spines on the dendritic branch can be activated with a spatial and temporal pattern of the authors’ choosing; and the resulting voltage change that can be thought of as the output-signal of the cell, is recorded with an intracellular electrode at the cell body (see the figure below graciously provided by the authors).

Why is the order and timing of synapse activation worth looking at? A neuron functions to collect from the axons of other neurons signals that cause voltage changes in its dendrites; and to pass these signals along to its cell body and axon where the voltage-threshold for an axonal action potential (AP) might or might not be reached. Features of stimuli in sensory pathways can be coded for by the timing of dendritic excitation. One example is in the retina, where individual dendritic branches of retinal starburst amacrine cells show directionally selective signals (Häusser, 2003; Euler, 2002). The authors (Branco, 2010) also point out that temporal and spatial variability in dendritic excitation patterns is especially relevant for circuits with layered input, like the hippocampus, where it could be used by dentate gyrus granule cells to directly detect the sequence of entorhinal cortex activation. Integrative properties of the dendrites appear to be at least one mechanism that can differentially encode spatial and temporal synchrony.

The sensitivity of single dendrites to the order of activation of a defined set of synapses was tested. When activated in isolation, the glutamate excitatory post-synaptic potentials, measured with an intracellular electrode at the cell body, were within physiological range. When the same spines along the dendrite were activated sequentially instead of in isolation, the IN direction always produced a larger somatic voltage response than the OUT direction, and this went along with a bigger chance for an axonal AP. Calcium signals were also larger in the IN than in the OUT direction. The most effective speed to show direction sensitivity was 2.6 microns per second. The dendrite itself can signal the difference between inputs that travel along it in one direction or the other!

What is going on in the dendrites that would cause activation of spines in one direction to give a different output-signal than activation of spines in the other direction? One idea is that dendrites of a neuron see all synapses as equal, and the voltage changes of the membrane caused by the synapses are summed linearly at the axon, possibly resulting in an axonal AP if the threshold is reached. But if they are all equal, and simply summed, the order of activation shouldn’t matter. Another idea is that the dendrites have active conductances, which would result in non-linearities (Häusser, 2003; Losonczy, 2006; Larkum, 2007). Non-linearity means that the whole is different than the sum of its parts; a supralinearity is the situation where the response when the identified synapses are activated sequentially is greater than the sum of the voltage responses from the same synapses activated in isolation. Regenerative events in dendrites are responsible for non-linearities in pyramidal neurons (Schaeffer, 2003); the axonal AP is back-propagating into the dendrites and long-lasting, mainly Ca2+ mediated depolarizations are initiated in the distal regions of apical dendrites. The distal depolarizations are an example of forward propagation (Vetter, 2001). The ability of thin dendritic branches of pyramidal neurons to support forward propagation called a ‘dendritic spike’ has been known for some time. These dendritic spikes are carried by Na+, Ca2+ and predominantly by special glutamate conductances mediated by NMDA receptors (Judkewitz, 2006). In this study, the voltage responses at the cell body were supralinear, meaning if you add together the individual synaptic responses from spines that are activated in isolation, the amplitude is smaller than if the same spines are activated sequentially. Something is boosting the signal to cause the supralinearity. This effect develops gradually with increasing numbers of recruited synapses. When the NMDA Glutamate receptor was blocked, the supralinearity disappeared, and furthermore, direction sensitivity, velocity sensitivity, and detectable dendritic calcium signals were abolished. This evidence points to amplification via NMDA-dependent regenenerative signal boosting and NMDA dendritic spikes.

Where does our program, Neurolucida, come in? The best research uses multiple techniques; and the authors decided to use Neuron, an electrophysiological modeling program, to study the conductances that have been implicated in creating the voltage non-linearities. The neurons were traced using Neurolucida. Neuron has a feature to import Neurolucida tracings. This way the anatomical arrangement of the dendrites is used in the electrophysiological modeling program; the authors could pick one dendritic branch, virtually activate its synapses either in isolation or in sequence, and look at the response at the cell body. Direction sensitivity could be reproduced with a simple model using dendrites with passive electrical properties and synapses containing AMPA and NMDA conductances. The NMDA conductance starts out small and gets bigger over time for the OUT direction and starts out large and gets smaller over time for the IN direction. Direction and velocity sensitivity are abolished by leaving only AMPA receptors and removing the NMDA receptors. There is asymmetric recruitment of NMDA receptors when activating synapses in the different directions. This is due to the smaller input resistance at the tip of the dendrite combined with the highly nonlinear voltage dependence of the NMDA receptor conductance.

So picture it this way. A pyramidal neuron in the sensory cortex is firing axonal APs in response to some sensory stimulus. These APs back propagate into the dendrites. Along with the back propagation the dendrite also experiences forward propagation as a result of active conductances that create a dendritic spike. The back propagation will be maintained or attenuated by the nature of the geometry of the dendritic tree (Schaefer, 2003; Vetter, 2001). Now what if one sensory stimulus sequentially activates the spines along a dendritic branch in the IN direction and another activates it in the OUT direction. For the IN direction, the first synapse activated is at the tip of the dendrite. How is this different than when the first synapse is at the base of the dendrite? First of all, due to differences in location along the geometry of the dendritic tree, the back-propagation voltage signal will be different. Also the dendrites taper, so the tip will have less radius and a greater input resistance than the base. Therefore, the history of what happened to each synapse is different depending on the IN or OUT direction. The NMDA receptors on the dendrites have a non-linear voltage dependence, so the different history or the differences in what just happened to the neighboring synapse, causes a larger signal for the IN than for the OUT direction. The dendrite itself can detect the difference between the two sensory stimuli. The evidence gathered from this work supports the exciting and important conclusion that these cortical neurons use their dendrites to not just pass the signal on, but to change the signal; and furthermore to change the signal based on the time and space pattern of the input to its synapses.

Branco T., Clark B. A., & Häusser M., 2010, Dendritic discrimination of temporal input sequences in cortical        neurons. Science, 329, pp. 1671 – 1675.

Euler T, Detwiler, P.B., & Denk W., 2002, Directionally selective calcium signals in dendrites of Starburst Amacrine Cells. Nature, 418, pp. 845 – 852.

Häusser M. & Mel B., 2003, Dendrites: bug or feature? Current Opinion in Neurobiology, 13, pp. 372 – 383.

Judkewitz B., Roth A., & Häusser M., 2006, Dendritic enlightenment: using patterned two-photon uncaging to reveal the secrets of the brain’s smallest dendrites. Neuron, 50, pp. 180 – 183.

Larkum M.E., Waters J., Sakmann B., & Helmchen, F., 2007, Dendritic spikes in apical dendrites of neocortical layer 2/3 pyramidal neurons. Journal of Neuroscience, 27, pp. 8999 – 9008.

Losonczy A. & Magee J.C., 2006, Integrative properties of radial oblique dendrites in Hippocampal CA1 Pyramidal Neurons. Neuron, 50, pp. 291 – 307.

Schaefer A.T., Larkum M.E., Sakmann B., & Roth A., 2003, Coincidence detection in pyramidal neurons is tuned by their dendritic branching pattern. Journal of Neurophysiology, 89, pp. 3143 – 3154.

Vetter P., Roth A., & Häusser M. 2001, Propagation of action potentials in dendrites depends on dendritic morphology. Journal of Neurophysiology, 85, pp. 926 – 937.

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It’s Not You, It’s Your Hormones. Scientists Study Estrogen’s Role in Stress.

Scientific research shows that women are twice as likely as men to develop stress disorders. Why are women more sensitive than men to stress? A recent research study presents new evidence that estrogen could play a role.

The symptoms of disorders like major depressive disorder and post traumatic stress disorder lead neuroscientists to speculate that a dysfunction occurs in the way the medial prefrontal cortex connects to the amygdala–regions of the brain associated with the regulation of memory and behavior. Following research published in 2009 determining resilience against changes in dendritic morphology in this region in male rats, scientists at the Mount Sinai School of Medicine turned their focus to female rats. They discovered unexpected changes in dendritic length and spine density to the neurons in this region when both estrogen and stress are present.

After removing the ovaries from all subjects and implanting half of the rats with estrogen, the researchers exposed them to ten days of either immobilization stress (two hours in a rodent immobilization bag) or home cage rest. They then sectioned the rats’ brains and examined the neurons in question.

“We used Neurolucida and Neurolucida Explorer to measure dendritic length and branch point number in a set of pyramidal neurons that had been filled with the fluorescent dye Lucifer Yellow,” said lead author Dr. Rebecca Shansky. “The software was very user-friendly, and we were easily able to customize the settings to get just the analyses we wanted,” Dr. Shansky added.

What they found was increased dendritic arborization and spine density in the females treated with estrogen, “indicating that estrogen and stress can interact at the level of this circuit to produce a unique response to stress in females,” according to the paper “Estrogen Promotes Stress Sensitivity in a Prefrontal Cortex–Amygdala Pathway,” published earlier this year in Cerebral Cortex.

Read the free abstract, or download the full paper at Cerebral Cortex.

Rebecca M. Shansky, Carine Hamo, Patrick R. Hof, Wendy Lou, Bruce S. McEwen, and John H. Morrison, “Estrogen Promotes Stress Sensitivity in a Prefrontal Cortex–Amygdala Pathway” (Cereb Cortex 2010; 20: 2560-2567)

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Brain Inflammation May Cause Autoimmune Disease Stress

When your mouth is dry, your joints are stiff, or your heart is inflamed because your immune system is attacking your own body, chances are you’re suffering from a little stress. A recent study shows that there may be physiological reasons why patients with autoimmune diseases experience increased levels of anxiety.

Scientists at the City University of New York Medical School, Columbia University, and the University of Messina suggest it may be brain inflammation that leads to elevated stress in patients with autoimmune diseases like systemic lupus erythematosus, rheumatoid arthritis, and Sjögren’s syndrome.

After modeling these diseases in a population of mice by introducing cytokine B-cell activating factor (BAFF), the research group examined their emotional behavior. They also checked for brain inflammation, stress-induced c-Fos protein, and the proliferation of progenitor cells in the hippocampus, using Neurolucida Explorer.

They found that the older mice produced anxiety-like characteristics associated with brain inflammation. These anxious mice responded to mild stress-inducing stimuli by displaying abnormal activity within the limbic system — the region of the brain that controls basic emotions.

During the course of the study, Neurolucida Explorer was used to calculate dendritic length. “I was very pleased with Neurolucida Explorer,” said Dr. Fortunato Battaglia. “I find the software very friendly and the quantitative data were crucial for our work. I am looking forward to using it again in future experiments.”

Read the free abstract or download the complete paper “Reduced Adult Neurogenesis and Altered Emotional Behaviors in Autoimmune-Prone B-Cell Activating Factor Transgenic Mice” at Biological Psychiatry.

Rosalia Crupi, Marco Cambiaghi, Linda Spatz, Rene Hen, Mitchell Thorn, Eitan Friedman, Giuseppe Vita, Fortunato Battaglia, “Reduced Adult Neurogenesis and Altered Emotional Behaviors in Autoimmune-Prone B-Cell Activating Factor Transgenic Mice” (Biological Psychiatry (2010) 67 6, 558-566)

{Illustration of a human brain and skull licensed under the Creative Commons Attribution 2.5 Generic license}

Multiple Sclerosis and Schizophrenia Research May Benefit From New Findings

Myelin, which insulates axons in the central nervous system is produced by oligodendrocytes. But not all oligodendrocytes are equal.

Led by Dr. Jonathan Vinet of the Université Laval in Quebec, scientists have identified three different types of oligodendrocytes in the mouse hippocampus: “ramified,” “stellar,” and “smooth.”

Each type displayed varying morphological characteristics, mainly in shape, volume, and branching behavior, which led the researchers to believe that the three types represent different stages of maturation.

As described in the paper, “Subclasses of oligodendrocytes populate the mouse hippocampus,” published in the European Journal of Neuroscience, the “smooth,” or most simple type possibly morphs into the “stellar,” which eventually develops into the most complex of the three, the “ramified” oligodendrocyte.

The identification of these morphologically distinct oligodendrocyte populations in the hippocampus may help researchers determine which specific types of oligodendrocytes are affected in diseases such as schizophrenia and multiple sclerosis.

Using a Neurolucida system with an Olympus AX-50 microscope, the scientists formed 3D reconstructions of the hippocampal oligodendrocytes integral to their study. They then analyzed their tracings with Neurolucida Explorer.

“Without Neurolucida we couldn’t have carried out this study,” said Dr. Attila Sik, “it was an essential component. Nice piece of equipment, for sure.”

Read the free abstract, or access the full article (by subscription), at the European Journal of Neuroscience.

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University of Maryland Scientists Reconstruct Neuronal Processes in 3D with Neurolucida

University of Maryland School of Medicine researchers have used Neurolucida since it was in its embryonic stages in the 1960s. Now, nearly a half-century later, the Department of Anatomy and Neurobiology continues using Neurolucida in their research, as outlined in a recent study concerning the organization of the olfactory system.

Dr. Michael Shipley and his team collaborated with scientists from Hungary and Japan on the paper “Molecular Identity of Periglomerular and Short Axon Cells,” published in the January 20 issue of The Journal of Neuroscience. The study involved the examination of the olfactory systems—including the olfactory sensory axons and juxtaglomerular neurons— of TH transgenic mice expressing green fluorescent protein.

“Neurolucida was essential for the tracing and derivation of basic morphometric parameters (length, etc.),” said co-author Dr. Adam C. Puche. The research team used Neurolucida to create 3D reconstructions of interglomerular connections, a process which aided in the determination that “different JG cell chemotypes contribute to distinct microcircuits within or between glomeruli.”

Access the article abstract and full text (by subscription) at jneurosci.org

{Image courtesy of Adam C. Puche, Ph.D., University of Maryland, School of Medicine}

Emi Kiyokage, Yu-Zhen Pan, Zuoyi Shao, Kazuto Kobayashi, Gabor Szabo, Yuchio Yanagawa, Kunihiko Obata, Hideyuki Okano, Kazunori Toida, Adam C. Puche, and Michael T. Shipley (2010), “Molecular Identity of Periglomerular and Short Axon Cells” The Journal of Neuroscience, 30(3):1185-1196

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Neurolucida Helps Scientists Better Understand Sound Localization

Birds and mammals hear binaurally, hearing sounds through two ears. Binaural hearing allows them to determine which direction a sound came from—a pivotal element of survival.

Doctors Armin H. Seidl, Edwin W. Rubel, and David M. Harris of Seattle’s Virginia Merrill Bloedel Hearing Research Center at the University of Washington recently published a study in the Journal of Neuroscience that may encourage scientists to think in new ways about the sound localization process.

The research involved the sectioning and 3D reconstruction of the brains and brainstems of over 50 white leghorn chickens.  By analyzing the part of the brain responsible for computing the interaural time difference (ITD)—the difference in the arrival time of a sound between two ears—the scientists determined that the length of the axons in the chicken sound localization circuit alone cannot compensate for external ITDs, as previously thought. Instead, it seems that the axon diameter and the distances between Nodes of Ranvier are also vital to the process.

Dr. Seidl explained that his team used Neurolucida in the study for two reasons:

“Neurolucida allowed us to trace and reconstruct labeled axon over several 3D images. Hence, we could record labeled axons at high magnification and stitch them together over several Z-stacks of images. Pivotal was also the possibility of introducing branch points to the 3D trace.”

“Neurolocida Explorer allowed us to measure the reconstructed axon and to measure specific segments, i.e., from a certain branch point or to a certain ending.”

“We found Neurolucida very user friendly and we always got great help from your online support department. We are planning on using it in future,” Seidl said.

Read “Mechanisms for Adjusting Interaural Time Differences to Achieve Binaural Coincidence Detection” at The Journal of Neuroscience Online.

{Image: Nuclei outlined with the contour function in Neurolucida. Courtesy of Dr. Armin Seidl}

Armin H. Seidl, Edwin W. Rubel, and David M. Harris (2010), “Mechanisms for Adjusting Interaural Time Differences to Achieve Binaural Coincidence Detection.” Journal of Neuroscience, 30(1):70-80