Name: analyzing the size, shape, and directionality of networks of coupled astrocytes
Uploaded: 2018-10-04T13:00:00
Description: Watch this Scientific Journal Video about Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes at JoVE.com

This work is funded by the Canadian Institutes of Health Research, Grant/Award Number: 14392.

All procedures abode by the Canadian Institutes of Health Research rules and were approved by the University of Montreal Animal Care and Use Committee.
1. Preparation of Rat Brain Slices
<ol>
	<li>Prepare 1 L of a sucrose-based solution (Table 1) and 1 L of standard artificial cerebral-spinal fluid (aCSF) (Table 2).</li>
	<li>Bubble the sucrose-based solution with a mix of 95% O2 and 5% CO2 (carbogen) for 30 min before placing it in -80...

<ol>
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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+hemichannels+in+astrocytes:+a+novel+mechanism+of+glutamate+release.">Functional hemichannels in astrocytes: a novel mechanism of glutamate release.</a> Journal of Neuroscience. 23 (9), 3588-3596 (2003).</li><li>Ma, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gap+junction+coupling+confers+isopotentiality+on+astrocyte+syncytium.">Gap junction coupling confers isopotentiality on astrocyte syncytium.</a> Glia. 64 (2), 214-226 (2016).</li><li>Meme, W., Vandecasteele, M., Giaume, C., Venance, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrical+coupling+between+hippocampal+astrocytes+in+rat+brain+slices.">Electrical coupling between hippocampal astrocytes in rat brain slices.</a> Neuroscience Research. 63 (4), 236-243 (2009).</li><li>Ransom, B. 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A number of electrophysiological methods exist to assess functional coupling between astrocytes23,24. However, these methods do not provide information about the anatomical arrangement of astrocytic networks. A number of studies have already shown that &#34;dye- or tracer-coupling&#34;, as done here, occurs only in a fraction of coupled cells that are detected by electrophysiological methods25,26,</s...

Many studies have described how the neuron-astrocyte dialogue at a sub-cellular or synaptic level can have implications in neuronal functions and synaptic transmission. It is well established that astrocytes are sensitive to surrounding neuronal activity; in fact, they have receptors for many neurotransmitters including glutamate, GABA, acetylcholine, and ATP (see previously published reviews2,3,4). In return, astrocytic processes ensheath synaptic elements and influence neuronal activity both there and at extrasynaptic sites by regulating extracellular ionic homeostasis and releasing several factors or transmitters such as glutamate, D-serine, and ATP5,6,7.
The idea that astrocytes can also modulate neuronal function at the network level has emerged, with evidence that astrocytic coupling is spatially regulated and corresponds to neuronal segmentation in areas characterized by a clear anatomical compartmentalization (like areas with sensory representations), indicating that astrocytes will couple to other astrocytes serving the same function rather than just those that are close by. In the lateral superior olive, for instance, most astrocytic networks are oriented orthogonally to the tonotopic axis8, whereas in the barrel cortex or olfactoty glomeruli, communication between astrocytes is much stronger within barrels or glomeruli and weaker between adjacent ones9,10. In both cases, the astrocytic networks are oriented towards the center of the glomerule or barrel9,10.
We recently showed that astrocytic activity modulates neuronal firing by decreasing the concentration of extracellular Ca2+ ([Ca2+]e), presumably through the release of S100&#946;, a Ca2+-binding protein11. This effect, which was demonstrated in a population of trigeminal rhythmogenic neurons in the dorsal part of the trigeminal main sensory nucleus (NVsnpr, thought to play an important role in the generation of masticatory movements), results from the fact that rhythmic firing in these neurons depends on a persistent Na+ current that is promoted by decreases of [Ca2+]e11,12. Rhythmic firing in these neurons can be elicited &#34;physiologically&#34; by stimulation of their inputs or artificial decrease of [Ca2+]e. We further showed that astrocytic coupling was required for neuronal rhythmic firing1. This raised the possibility that astrocytic networks may form circumscribed functional domains where neuronal activity can be synchronized and coordinated. To assess this hypothesis, we first needed to develop a method to rigorously document the organization of these networks within NVsnpr.
Previous studies on astrocytic networks have mostly described the extent of coupling in terms of cell number and the density and area covered. Attempts to evaluate the shape of astrocytic networks and the direction of dye-coupling were mostly performed by comparing the size of networks along two axes (x and y) in the barrel cortex9, hippocampus13,14,15, barreloid fields of the thalamus16, lateral superior olive8, olfactory glomeruli10, and cortex14. The methods described here enable unbiased counts of labeled cells in a network and an estimation of the area they cover. We also developed tools to define the preferred orientation of coupling within a network and to assess whether the preferred orientation is towards the center of the nucleus or in a different direction. In comparison to previously used methods, this protocol provides a means to describe the organization and orientation of astrocytic networks in structures like the dorsal trigeminal main sensory nucleus that do not have a known clear anatomical compartmentalization. In the above studies, the network orientation is described as a relationship to the shape of the structure itself which is already documented (e.g., the barreloid in the thalamus, barrels in the cortex, layers in the hippocampus and cortex, glomeruli in the olfactory bulb, etc.). In addition, vectorial analysis allows for comparisons of coupling orientations revealed under different conditions. To analyze whether these parameters changed according to the position of the network within the nucleus, we also developed a method to replace each network in reference to the boundaries of the nucleus. These tools can be easily adapted to other areas for investigating networks of coupled cells.

<table>
	<tbody>
		<tr>
			<td>NaCl</td>
			<td>Fisher Chemicals</td>
			<td>S671-3</td>
			<td></td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>Fisher Chemicals</td>
			<td>P217-500</td>
			<td></td>
		</tr>
		<tr>
			<td>KH2PO4</td>
			<td>Fisher Chemicals</td>
			<td>P285-500</td>
			<td></td>
		</tr>
		<tr>
			<td>MgSO4</td>
			<td>Fisher Chemicals</td>
			<td>M65-500</td>
			<td></td>
		</tr>
		<tr>
			<td>NaHCO3</td>
			<td>Fisher Chemicals</td>
			<td>S233-500</td>
			<td></td>
		</tr>
		<tr>
			<td>C6H12O6 Dextrose anhydrous</td>
			<td>Fisher Chemicals</td>
			<td>D16-500</td>
			<td></td>
		</tr>
		<tr>
			<td>CaCl2 dihydrated</td>
			<td>Sigma</td>
			<td>C70-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>Sigma</td>
			<td>S9378</td>
			<td></td>
		</tr>
		<tr>
			<td>D-gluconic acid potassium salt</td>
			<td>Sigma</td>
			<td>G45001</td>
			<td></td>
		</tr>
		<tr>
			<td>MgCl2 anhydrous</td>
			<td>Sigma</td>
			<td>M8266</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma</td>
			<td>H3375</td>
			<td></td>
		</tr>
		<tr>
			<td>EGTA</td>
			<td>Sigma</td>
			<td>E4378</td>
			<td></td>
		</tr>
		<tr>
			<td>ATPTris Salt</td>
			<td>Sigma</td>
			<td>A9062</td>
			<td></td>
		</tr>
		<tr>
			<td>GTPTris Salt</td>
			<td>Sigma</td>
			<td>G9002</td>
			<td></td>
		</tr>
		<tr>
			<td>Biocytin</td>
			<td>Sigma</td>
			<td>B4261</td>
			<td></td>
		</tr>
		<tr>
			<td>Carbenoxolone disodium salt</td>
			<td>Sigma</td>
			<td>C4790</td>
			<td></td>
		</tr>
		<tr>
			<td>avidin-biotin complex : ABC kit</td>
			<td>Vestor laboratories</td>
			<td>PK-4000</td>
			<td></td>
		</tr>
		<tr>
			<td>Streptavidine-alexa 594</td>
			<td>Molecular Probes</td>
			<td>S11227</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton</td>
			<td>Fisher Chemicals</td>
			<td>BP151-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Xylene</td>
			<td>Fisher Chemicals</td>
			<td>X5-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Aqueous mounting medium 1 : Fluoromount-G</td>
			<td>SouthernBiotech</td>
			<td>0100-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Toluen-based synthetic resin mounting medium : Permount</td>
			<td>Fisher Chemicals</td>
			<td>SP15-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Slide Drying Bench</td>
			<td>Fisherbrand</td>
			<td>11-474-470</td>
			<td></td>
		</tr>
		<tr>
			<td>Vibratome</td>
			<td>Leica</td>
			<td>VT 1000S</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope cover glass</td>
			<td>Fisherbrand</td>
			<td>12-544A</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope slide ColorFrost</td>
			<td>Fisherbrand</td>
			<td>12-550-413</td>
			<td></td>
		</tr>
		<tr>
			<td>PFA</td>
			<td>Fisherchemicals</td>
			<td>04042-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Olympus FluoView FV 1000 Confocal microscope</td>
			<td>Olympus</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>40X water-immersion lens</td>
			<td>Olympus</td>
			<td>LUMPLFLN40XW</td>
			<td></td>
		</tr>
		<tr>
			<td>20X water-immersion lens</td>
			<td>Olympus</td>
			<td>XLUMPLFL20XW</td>
			<td></td>
		</tr>
		<tr>
			<td>4X water-immersion lens</td>
			<td>Olympus</td>
			<td>XLFLUOR4X/340</td>
			<td></td>
		</tr>
		<tr>
			<td>Micropipette puller</td>
			<td>Sutter Instrument</td>
			<td>P97</td>
			<td></td>
		</tr>
		<tr>
			<td>Micromanipulator</td>
			<td>Sutter Instrument</td>
			<td>MP 225</td>
			<td></td>
		</tr>
		<tr>
			<td>Camera CCD</td>
			<td>Sony</td>
			<td>CX-ST50</td>
			<td></td>
		</tr>
		<tr>
			<td>Black and white monitor</td>
			<td>Sony</td>
			<td>SSM-125</td>
			<td></td>
		</tr>
		<tr>
			<td>Digidata</td>
			<td>Molecular devices</td>
			<td>1322A</td>
			<td></td>
		</tr>
		<tr>
			<td>Patch Clamp amplifier</td>
			<td>Axon instrument</td>
			<td>Mulitclamp 700A</td>
			<td></td>
		</tr>
		<tr>
			<td>Electrophysiology acquisition software</td>
			<td>Molecular devices</td>
			<td>pClamp 8</td>
			<td></td>
		</tr>
		<tr>
			<td>Electrophysiology analysis software</td>
			<td>Molecular devices</td>
			<td>Clampfit 8</td>
			<td></td>
		</tr>
		<tr>
			<td>Imaging analysis software</td>
			<td>ImageJFIJI</td>
			<td>Open source software. FIJI version including plug in package.</td>
			<td></td>
		</tr>
		<tr>
			<td>Vector image editor</td>
			<td>Adobe</td>
			<td>Illustrator CS4</td>
			<td></td>
		</tr>
		<tr>
			<td>Spreadsheet application</td>
			<td>Microsoft Office</td>
			<td>Excel 2010</td>
			<td></td>
		</tr>
	</tbody>
</table>

analyzing the size, shape, and directionality of networks of coupled astrocytes

It has become increasingly clear that astrocytes modulate neuronal function not only at the synaptic and single-cell levels, but also at the network level. Astrocytes are strongly connected to each other through gap junctions and coupling through these junctions is dynamic and highly regulated. An emerging concept is that astrocytic functions are specialized and adapted to the functions of the neuronal circuit with which they are associated. Therefore, methods to measure various parameters of astrocytic networks are needed to better describe the rules governing their communication and coupling and to further understand their functions.
Here, using the image analysis software (e.g., ImageJFIJI), we describe a method to analyze confocal images of astrocytic networks revealed by dye-coupling. These methods allow for 1) an automated and unbiased detection of labeled cells, 2) calculation of the size of the network, 3) computation of the preferential orientation of dye spread within the network, and 4) repositioning of the network within the area of interest.
This analysis can be used to characterize astrocytic networks of a particular area, compare networks of different areas associated to different functions, or compare networks obtained under different conditions that have different effects on coupling. These observations may lead to important functional considerations. For instance, we analyze the astrocytic networks of a trigeminal nucleus, where we have previously shown that astrocytic coupling is essential for the ability of neurons to switch their firing patterns from tonic to rhythmic bursting1. By measuring the size, confinement, and preferential orientation of astrocytic networks in this nucleus, we can build hypotheses about functional domains that they circumscribe. Several studies suggest that several other brain areas, including the barrel cortex, lateral superior olive, olfactory glomeruli, and sensory nuclei in the thalamus and visual cortex, to name a few, may benefit from a similar analysis.

Coupling between cells in the brain is not static but rather dynamically regulated by many factors. The methods described were developed to analyze astrocytic networks revealed under different conditions and to understand their organization in NVsnpr. These results have been already published1. We performed biocytin filling of single astrocytes in the dorsal part of the NVsnpr in three different conditions: at rest (in control conditions in the absence of any stimu...

Watch this Scientific Journal Video about Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes at JoVE.com

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Here we present a protocol to assess the organization of astrocytic networks. The described method minimizes bias to provide descriptive measures of these networks such as cell count, size, area, and position within a nucleus. Anisotropy is assessed with a vectorial analysis.

It has become increasingly clear that astrocytes modulate neuronal function not only at the synaptic and single-cell levels, but also at the network ...

This method can help answer key questions regarding the organization of astrocytic networks in brain structures. The main advantage of this technique is that it proposes an unbiased method to count label cells and document their anatomical organization within a defined structure. Open ImageJFIJI, select the desired file, and click OK in the bio-format's import options window.To redefine a Z stack that will contain only the optical slices needed for the final Z stack, first select STK and Z project, and then click on the stack knob in the tool bar. Select max intensity in the projection type setting. Save the file, and name it stack file.If the imaging file contains several channels, use image color and split channels to show only the channel with the image of the astrocytic network. Check the pixel settings of the image by selecting image, properties, pixel, with one for pixel dimension. Then use the subtract background tool by opening process and subtract background to remove background biocytin labeling.Use the preview function to set the rolling ball radius, which is generally set at 50 pixels. If further noise reduction is required following the subtract background step, select process, noise, and remove outliers. Select bright in the which outliers setting, and use the preview function to set the radius and threshold.Be careful using the remove outlier tool, since it may blur the data, as shown here. Adjust the threshold using image, adjust, threshold. Select default and B and W mode.Click on apply. Convert the image into a binary image with the binary process tool by selecting process, binary, and make binary. Save the file as a tiff file and name it binary file.To count cells, first set the measurement type by clicking analyze and set measurement. Then select the centroid option. Ensure that the binary file is open onscreen.Again, open the analyze menu, and this time select analyze particles. Next, select show and outlines. This generates a new file that shows the result of the detection.Optimize the parameters to refine the detection. To detect cells only, use a size value between 30 and 6000, and circularity between zero to one, where one defines a perfect circle and zero a random shape. Run the detection by clicking OK.Two tables will appear, a table titled summary that provides the number of detected cells, and a table titled results that provides the X and Y coordinates of each cell.Copy the values and paste them into a spreadsheet application. Save this table under the name detection table. A file with a plot of detected cells will also appear.Save this file as a tiff file under the name detection file. If a group of two or more labeled cells are detected as a single cell with the analyze particles tool, use the watershed tool on the binary image by selecting process, binary, and watershed before applying the analyze particles tool. To measure the surface area of the networks, use the detection file in ImageJ.Left click the mouse to select the polygon selection tool in the toolbar. Left click again to begin tracing a region of interest, or ROI, that connects all the cells located in the external periphery of the network. Right click to close the polygon.Open the set measurement window and select the area option. Then open the ROI manager and add the traced polygon in the ROI manager by clicking add. Run the measurement by clicking measure in the ROI manager.The area measurement will appear in a table and be expressed in pixels. Don't forget to convert this value with a conversion factor for the microscope used to obtain the value in square micrometers. Open the stack file in ImageJFIJI and identify the patched cell with its stronger labeling intensity.Then open the file named detection table in a spreadsheet application, and find the number associated with the patched cell and its corresponding coordinates. If unable to accurately determine the patched cell, use the polygon tool to surround the area where the deposit of biocytin is denser, and refer to this position as that of the patched cell. Use the ROI manager as before to draw an ROI at the patched cell location and add it to the ROI manager.Next, set the measurement and select the centroid option. In the RIO manager, click on measure to obtain the coordinates of the centroid of the traced area. Use these coordinates as the reference point for this specific network.Use this formula to calculate the coordinates of each cell in reference to the patched astrocyte. Expressing the coordinates of each cell in reference to the patched astrocyte is an important step to calculate vector from the patched astrocytes. Use this formula to calculate the coordinates of the main vector of preferential orientation.The main vector of preferential orientation of the network is the sum of all the previously calculated vectors for each cell comprised in the network. Divide the length of the main vector by the number of the cells in the network, minus one to exclude the patched cell, to normalize the values and enable comparisons between networks. To determine the position of each network in the nucleus of interest, first open the four x image with a vector image editor.Multiply the dimensions in the dimension window by five to increase the size of the four x image. Here, the image was sampled at 800 by 800 pixels, and so the sampling resolution is changed to 4000 by 4000 pixels. Export the file in tiff format and name it resized four x.Align the top left corner of the resized four x image with the bottom left corner of the Adobe Illustrator document. The software provides coordinates from a bottom left corner referential point. Open the 20 x image of the network.Use the binary file or detection file because they are easier to align. Then, play with the opacity tool on the binary file of the 20 x image to align it with the resized four x image. When the alignment is done, select and hold the pipette tool so the measure tool appears, and select it in the left toolbar.Use the measure tool to click on the top left corner of the 20 x image to get the coordinates of the 20 x referential point onto the resized four x image. This 20 x referential coordinates are useful for expressing the position of each network on a schematic drawing of the nucleus. To sum up the data, normalization of the nucleus as a rectangle is used.To do this, use the polygon tool to surround the nucleus in the resized four x image. Then open the ROI manager and add the drawn ROI. Use image with transparent lights if the borders of the nucleus cannot be seen, in which case remember to resize it first.In set measurement, select the bounding rectangle option to calculate the smallest rectangle within the drawn nucleus. Finally, click measure, then follow the steps in the written protocol to express the labeled cells coordinates in a normalized nucleus represented by the bounding rectangle. A single astrocyte in the dorsal part of the trigeminal main sensory nucleus, labeled by SR101, was targeted for whole-cell recording and filled with 0.2%biocytin.Electrical stimulation of the fifth tract increased biocytin labeling in the dorsal part of the trigeminal main sensory nucleus, representing an increase in the number of coupled cells. Astrocytic networks remain confined within the dorsal part of the trigeminal main sensory nucleus and their main orientation. This technique was developed to position astrocytic networks within a defined structure, but can be used to express the position of population of labeled cell in any structure.

analyzing-size-shape-directionality-networks-coupled

Research

JoVE Journal

Neuroscience

Isolation and Culture of Mouse Cortical Astrocytes

Astrocytes are an abundant cell type in the mammalian brain, yet much remains to be learned about their molecular and functional characteristics. In vitro astrocyte cell culture systems can be used to study the biological functions of these glial cells in detail. This video protocol shows how to obtain pure astrocytes by isolation and culture of mixed cortical cells of mouse pups. The method is based on the absence of viable neurons and the separation of astrocytes, oligodendrocytes and microglia, the three main glial cell populations of the central nervous system, in culture. Representative images during the first days of culture demonstrate the presence of a mixed cell population and indicate the timepoint, when astrocytes become confluent and should be separated from microglia and oligodendrocytes. Moreover, we demonstrate purity and astrocytic morphology of cultured astrocytes using immunocytochemical stainings for well established and newly described astrocyte markers. This culture system can be easily used to obtain pure mouse astrocytes and astrocyte-conditioned medium for studying various aspects of astrocyte biology.

Astrocytes have been recognized to be versatile cells participating in fundamental biological processes that are essential for normal brain development and function, and central nervous system repair. Here we present a rapid procedure to obtain pure mouse astrocyte cultures to study the biology of this major class of central nervous system cells.

Astrocytes  are an abundant cell type in the mammalian brain, yet much remains to be  learned about their molecular and functional characteristics. In ...

Fast Micro-iontophoresis of Glutamate and GABA: A Useful Tool to Investigate Synaptic Integration

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of the dendritic tree, which eventually leads to neuronal output of action potentials at the axon. The influence of diverse spatial and temporal parameters of specific synaptic input on neuronal output is currently under investigation, e.g. the distance-dependent attenuation of dendritic inputs, the location-dependent interaction of spatially segregated inputs, the influence of GABAergig inhibition on excitatory integration, linear and non-linear integration modes, and many more.
With fast micro-iontophoresis of glutamate and GABA it is possible to precisely investigate the spatial and temporal integration of glutamatergic excitation and GABAergic inhibition. Critical technical requirements are either a triggered fluorescent lamp, light-emitting diode (LED), or a two-photon scanning microscope to visualize dendritic branches without introducing significant photo-damage of the tissue. Furthermore, it is very important to have a micro-iontophoresis amplifier that allows for fast capacitance compensation of high resistance pipettes. Another crucial point is that no transmitter is involuntarily released by the pipette during the experiment.
Once established, this technique will give reliable and reproducible signals with a high neurotransmitter and location specificity. Compared to glutamate and GABA uncaging, fast iontophoresis allows using both transmitters at the same time but at very distant locations without limitation to the field of view. There are also advantages compared to focal electrical stimulation of axons: with micro-iontophoresis the location of the input site is definitely known and it is sure that only the neurotransmitter of interest is released. However it has to be considered that with micro-iontophoresis only the postsynapse is activated and presynaptic aspects of neurotransmitter release are not resolved. In this article we demonstrate how to set up micro-iontophoresis in brain slice experiments.

In this article we introduce fast micro-iontophoresis of neurotransmitters as a technique to investigate integration of postsynaptic signals with high spatial and temporal precision.

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of ...

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

In vivo electrophysiological recordings in the awake, behaving animal provide a powerful method for understanding neural signaling at the single-cell level. The technique allows experimenters to examine temporally and regionally specific firing patterns in order to correlate recorded action potentials with ongoing behavior. Moreover, single-unit recordings can be combined with a plethora of other techniques in order to produce comprehensive explanations of neural function. In this article, we describe the anesthesia and preparation for microwire implantation. Subsequently, we enumerate the necessary equipment and surgical steps to accurately insert a microwire array into a target structure. Lastly, we briefly describe the equipment used to record from each individual electrode in the array. The fixed microwire arrays described are well-suited for chronic implantation and allow for longitudinal recordings of neural data in almost any behavioral preparation. We discuss tracing electrode tracks to triangulate microwire positions as well as ways to combine microwire implantation with immunohistochemical techniques in order to increase the anatomical specificity of recorded results.

Implanting organized arrays of microwires for use in single-unit electrophysiological recordings presents a number of technical challenges.&#160;Methods for performing this technique and the equipment necessary are described.&#160;Also, the beneficial use of organized microwire arrays to record from distinct neural subregions with high spatial selectivity is discussed.

In vivo electrophysiological recordings in the awake, behaving animal provide a powerful method for understanding neural signaling at the single-cell ...

Protocol for Three-dimensional Confocal Morphometric Analysis of Astrocytes

As glial cells in the brain, astrocytes have diverse functional roles in the central nervous system. In the presence of harmful stimuli, astrocytes modify their functional and structural properties, a condition called reactive astrogliosis. Here, a protocol for assessment of the morphological properties of astrocytes is presented. This protocol includes quantification of 12 different parameters i.e. the surface area and volume of the tissue covered by an astrocyte (astrocyte territory), the entire astrocyte including branches, cell body, and nucleus, as well as total length and number of branches, the intensity of fluorescence immunoreactivity of antibodies used for astrocyte detection, and astrocyte density (number/1,000 &#181;m2). For this purpose three-dimensional (3D) confocal microscopic images were created, and 3D image analysis software such as Volocity 6.3 was used for measurements. Rat brain tissue exposed to amyloid beta1-40 (A&#946;1-40) with or without a therapeutic&#160;intervention was used to present the method. This protocol can also be used for 3D morphometric analysis of other cells from either in vivo or in vitro conditions.

Astrocytes in the CNS change their functional and structural properties in response to harmful stimuli. This report presents a protocol for assessment of three-dimensional astrocyte morphology in diseased conditions or after therapeutic interventions.

As glial cells in the brain, astrocytes have diverse functional roles in the central nervous system. In the presence of harmful stimuli, astrocytes modify ...

Quadruple Immunostaining of the Olfactory Bulb for Visualization of Olfactory Sensory Axon Molecular Identity Codes

The mouse olfactory system is often used to study mechanisms of neural circuit formation&#12288;because of its simple anatomical structure. An Olfactory Sensory Neuron (OSN) is a bipolar cell with a single dendrite and a single unbranched axon. An OSN expresses only one Olfactory Receptor (OR) gene, OSNs expressing a given type of OR converge their axons to a few sets of invariant glomeruli in the Olfactory Bulb (OB). A remarkable feature of OSN projection is that the expressed ORs play instructive roles in axonal projection. ORs regulate the expression of multiple axon-sorting molecules and generate the combinatorial molecular code of axon-sorting molecules at the OSN axon termini. Thus, to understand the molecular mechanisms of OR-specific axon guidance mechanisms, it is vital to characterize their expression profiles at the OSN axon termini within the same glomerulus. The aim of this article was to introduce methods for collecting as many glomeruli as possible on a single OB section and for performing immunostaining using multiple antibodies. This would allow the comparison and analysis of the expression patterns of axon-sorting molecules without staining variation between OB sections.

Olfactory sensory neurons express a wide variety of axon-sorting molecules to establish proper neural circuitry. This protocol describes an immunohistochemical staining method to visualize combinatorial expressions of axon-sorting molecules at the axon termini of olfactory sensory neurons.

The mouse olfactory system is often used to study mechanisms of neural circuit formation&#12288;because of its simple anatomical structure. An Olfactory ...

Simultaneous Recordings of Cortical Local Field Potentials, Electrocardiogram, Electromyogram, and Breathing Rhythm from a Freely Moving Rat

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls body functions and internal organ rhythms when animals are exposed to emotional challenges and changes in their living environments. In general experiments, signals from different organs, such as the brain and the heart, are recorded by independent recording systems that require multiple recording devices and different procedures for processing the data files. This study describes a new method that can simultaneously monitor electrical biosignals, including tens of local field potentials in multiple brain regions, electrocardiograms that represent the cardiac rhythm, electromyograms that represent awake/sleep-related muscle contraction, and breathing signals, in a freely moving rat. The recording configuration of this method is based on a conventional micro-drive array for cortical local field potential recordings in which tens of electrodes are accommodated, and the signals obtained from these electrodes are integrated into a single electrical board mounted on the animal's head. Here, this recording system was improved so that signals from the peripheral organs are also transferred to an electrical interface board. In a single surgery, electrodes are first separately implanted into the appropriate body parts and the target brain areas. The open ends of all of these electrodes are then soldered to individual channels of the electrical board above the animal's head so that all of the signals can be integrated into the single electrical board. Connecting this board to a recording device allows for the collection of all of the signals into a single device, which reduces experimental costs and simplifies data processing, because all data can be handled in the same data file. This technique will aid the understanding of the neurophysiological correlates of the associations between central and peripheral organs.

This study introduces a method for the simultaneous recording of local field potentials in the brain, electrocardiograms, electromyograms, and breathing signals of a freely moving rat. This technique, which reduces experimental costs and simplifies data analysis, will contribute to the understanding of the interactions between the brain and peripheral organs.

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls ...

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Statistical shape analysis of brain structures has been used to investigate the association between their structural changes and pathological processes. We have developed a software package for accurate and robust shape modeling and group-wise analysis. Here, we introduce an pipeline for the shape analysis, from individual 3D shape modeling to quantitative group shape analysis. We also describe the pre-processing and segmentation steps using open software packages. This practical guide would help researchers save time and effort in 3D shape analysis on brain structures.

We introduce a semi-automatic protocol for shape analysis on brain structures, including image segmentation using open software, and further group-wise shape analysis using an automated modeling package. Here, we demonstrate each step of the 3D shape analysis protocol with hippocampal segmentation from brain MR images.

Statistical shape analysis of brain structures has been used to investigate the association between their structural changes and pathological processes. ...

Visualizing and Analyzing Intracellular Transport of Organelles and Other Cargos in Astrocytes

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in brain homeostasis, astrocytes supply neurons with vital metabolites and buffer extracellular water, ions, and glutamate. An integral component of the &#8220;tri-partite&#8221; synapse, astrocytes are also critical in the formation, pruning, maintenance, and modulation of synapses. To enable these highly interactive functions, astrocytes communicate among themselves and with other glial cells, neurons, the brain vasculature, and the extracellular environment through a multitude of specialized membrane proteins that include cell adhesion molecules, aquaporins, ion channels, neurotransmitter transporters, and gap junction molecules. To support this dynamic flux, astrocytes, like neurons, rely on tightly coordinated and efficient intracellular transport. Unlike neurons,&#160;where intracellular trafficking has been extensively delineated, microtubule-based transport in astrocytes has been less studied. Nonetheless, exo- and endocytic trafficking of cell membrane proteins and intracellular organelle transport orchestrates astrocytes&#8217; normal biology, and these processes are often affected in disease or in response to injury. Here we present a straightforward protocol to culture high quality murine astrocytes, to fluorescently label astrocytic proteins and organelles of interest, and to record their intracellular transport dynamics using time-lapse confocal microscopy. We also demonstrate how to extract and quantify relevant transport parameters from the acquired movies using available image analysis software (i.e., ImageJ/FIJI) plugins.

Here we describe an in vitro live-imaging method to visualize intracellular transport of organelles and trafficking of plasma membrane proteins in murine astrocytes. This protocol also presents an image analysis methodology to determine cargo transport itineraries and kinetics.

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in ...

In vitro Modeling for Neurological Diseases using Direct Conversion from Fibroblasts to Neuronal Progenitor Cells and Differentiation into Astrocytes

Research on neurological disorders focuses primarily on the impact of neurons on disease mechanisms. Limited availability of animal models severely impacts the study of cell type specific contributions to disease. Moreover, animal models usually do not reflect variability in mutations and disease courses seen in human patients. Reprogramming methods for generation of induced pluripotent stem cells (iPSCs) have revolutionized patient specific research and created valuable tools for studying disease mechanisms. However, iPSC technology has disadvantages such as time, labor commitment, clonal selectivity and loss of epigenetic markers. Recent modifications of these methods allow more direct generation of cell lineages or specific cell types, bypassing clonal isolation or a pluripotent stem cell state. We have developed a rapid direct conversion method to generate induced Neuronal Progenitor Cells (iNPCs) from skin fibroblasts utilizing retroviral vectors in combination with neuralizing media. The iNPCs can be differentiated into neurons (iNs) oligodendrocytes (iOs) and astrocytes (iAs). iAs production facilitates rapid drug and disease mechanism testing as differentiation from iNPCs only takes 5 days. Moreover, iAs are easy to work with and are generated in pure populations at large numbers. We developed a highly reproducible co-culture assay using mouse GFP+ neurons and patient derived iAs to evaluate potential therapeutic strategies for numerous neurological and neurodegenerative disorders. Importantly, the iA assays are scalable to 384-well format facilitating the evaluation of multiple small molecules in one plate. This approach allows simultaneous therapeutic evaluation of multiple patient cell lines with diverse genetic background. Easy production and storage of iAs and capacity to screen multiple compounds in one assay renders this methodology adaptable for personalized medicine.

We describe a protocol to reprogram human skin-derived fibroblasts into induced Neuronal Progenitor Cells (iNPCs), and their subsequent differentiation into induced Astrocytes (iAs). This method leads to fast and reproducible generation of iNPCs and iAs in large quantities.

Research on neurological disorders focuses primarily on the impact of neurons on disease mechanisms. Limited availability of animal models severely ...

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.

This article provides a straightforward protocol for acquiring good quality electroencephalography (EEG) data during simultaneous EEG and functional magnetic resonance imaging by utilizing readily available medical products.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG ...