Membrane potential depolarization causes alterations in neuron arrangement and connectivity in cocultures

The disruption of neuron arrangement is associated with several pathologies. In contrast to action potentials, the role of resting potential (Vmem) in regulating connectivity remains unknown.

Neuron assemblies were quantified when their Vmem was depolarized using ivermectin (Ivm), a drug that opens chloride channels, for 24 h in cocultures with astrocytes. Cell aggregation was analyzed using automated cluster analysis methods. Neural connectivity was quantified based on the identification of isolated somas in phase-contrast images using image processing. Vmem was measured using voltage-sensitive dyes and whole-cell patch clamping. Immunocytochemistry and Western blotting were used to detect changes in the distribution and production of the proteins.

Data show that Vmem regulates cortical tissue shape and connectivity. Automated cluster analysis methods revealed that the degree of neural aggregation was significantly increased (0.26 clustering factor vs. 0.21 in controls, P ≤ 0.01). The number of beta-tubulin III positive neural projections was also significantly increased in the neural aggregates in cocultures with Ivm. Hyperpolarized neuron cells formed fewer connections (33% at 24 h, P ≤ 0.05) compared to control cells in 1-day cultures. Glia cell densities increased (33.3%, P ≤ 0.05) under depolarizing conditions.

Vmem can be a useful tool to probe neuronal cells, disease tissues models, and cortical tissue arrangements.

Keywords: Automated cluster analysis, cell resting membrane potential, connectivity, cortical neurons, neuron assemblies

Cortical arrangement, including shape and size at the cellular and tissue levels, relates to neural connectivity associated with normal brain development and function (Anstotz et al. 2013; Comin and da Fontoura Costa 2013; Foxworthy et al. 2013). We have used the term ‘neuron arrangement’ as a general term referring to the positional reorganization of cells in respect to each other. Neural assemblies, as first defined by Donald Hebb, are diffuse structures comprising cells in the cortex and diencephalon. Those structures are also capable of acting briefly as a closed system, delivering facilitation to other such systems. Neural assemblies are implicated in complex brain functions such as learning or planning, and accepted as the smallest representatives of a cognitive concept in the brain, as explained in Hebbian theory (Hebb 1949). Neural assemblies are suggested to constitute neural syntaxes that integrate and parse the fundamental assemblies of neural activities (Buzsaki 2010).

Deficits in neuronal organization and connectivity can result in a range of pathologies. Brains of corticobasal syndrome patients have a common degenerating neural network comprised of the motor circuit and primary motor-cortex (Sudmeyer et al. 2012). Corticostriatal connectivity with a precise arrangement of large scale loops has been suggested to play a critical role in neurodevelopmental, neuropsychiatric, and movement disorders (Shepherd 2013). In autism, altered connectivity due to changes in the ratio of distinct types of inhibitory neurons has been reported (Zikopoulos and Barbas 2013). Similarly, profound alterations have been recorded from cortical and subcortical networks in epileptic seizures (Spencer 2002). Changes in brain functional connectivity are detected in patients with Obsessive-Compulsive Disorder and in social anxiety disorder (Fontenelle et al. 2012; Gimenez et al. 2012).

The deformation or volume change in cortical tissue occurs in several neurological diseases. For example, hippocampal shape and volume can predict the onset of dementia in the elderly (Csernansky et al. 2005). In Amyotropic Lateral Sclerosis, a significant thinning due to reduced gray matter has been detected in multiple motor and extramotor cortical areas (d'Ambrosio et al. 2014). Brain morphometric studies have revealed focal abnormalities in several areas of brain, including the cortex, in schizophrenia patients (Davatzikos et al. 2005; Zierhut et al. 2013). Volume loss and cortical thinning was found in the medial temporal lobe of individuals with schizophrenia when compared with control groups. Also correlations between structural measures and memory performance in schizophrenia subjects were demonstrated (Karnik-Henry et al. 2012). Significant variations in shape have been reported in the frontobasal brain region in Obsessive-Compulsive Disorder (Pujol et al. 2011). Reductions in cortical thickness in the left hemisphere and a lack of integrity of white matter is a main contributor to long-term impairment in declarative memory among patients suffering from severe and diffuse traumatic brain injury (Palacios et al. 2013). A recent study verified that cortical thinning is observable/quantifiable and is functionally relevant in blast-related traumatic brain injury patients (Tate et al. 2014). Interestingly, regardless of the disease-induced cause, a decline in cortex volume has also been identified in elderly (Thomann et al. 2013). However, it is still not known which cell types in number, density, or size in the brain are disturbed related to neurological disorders.

Magnetic resonance imaging of clinical subjects is the most common approach used to assess functional brain anatomy. This analytical approaches provides rapid and general diagnosis for clinical purposes (Bernhardt et al. 2013), but lacks spatial resolution at the cellular level, which is important to elucidate the mechanisms of disease and development. In vitro model systems and automated quantitative analysis tools are needed to achieve insight into disease mechanisms and to implement approaches for disease control and therapy.

Vmem can regulate cell differentiation as undifferentiated cells exhibit relatively depolarized Vmem compared to terminally differentiated cells (Levin 2007). The underlying mechanism for that is the regulation of cell proliferation and differentiation (Sundelacruz et al. 2009). It has long been known that activity of the nervous system during embryogenesis helps regulate differentiation, proliferation, and topology of the nascent CNS (Katz and Shatz 1996; Penn and Shatz 1999; Deisseroth et al. 2004; Young et al. 2012). However, despite the exciting recent data indicating roles for resting potential gradients in embryonic patterning of many organs (Levin et al. 2002; Lange et al. 2011; Levin 2012, 2013; Levin and Stevenson 2012; Beane et al. 2013; Tseng and Levin 2013), the roles of Vmem in neural connectivity remain unknown. The objective of this study was to develop a novel approach to mimic and detect abnormalities in cortical tissue arrangement based on changes in the neuron arrangement, as well as shape and size of neural cell assemblies. Ivm is known to change the cellular chloride content. Ivm can change the Vmem specifically by binding to Glycine Receptor Chloride Channel alpha-1 subunit. That makes Ivm a specifically targeted and a convenient tool to change the Vmem in cells expressing the channel (Sharmeen et al. 2010; Blackiston et al. 2011; Lynagh et al. 2011; Dutertre et al. 2012). We found that Ivm can affect both astrocytes and neurons, as western blot studies revealed that GlyR was produced also in astrocytes. However, the ability of Ivm to affect Vmem was in different time windows for neurons and astrocytes. Ivm caused a relatively hyperpolarized Vmem in astrocytes alone at 2w and 4w where it reversed neuron Vmem (depolarized) at 3 weeks in presence of astrocytes versus the controls (Ozkucur et al., in review).

Using intrinsic chloride-dependent Vmem shift from depolarizing to hyperpolarizing in developing neurons (Ehrlich et al. 1999), cortical shape and connectivity were controlled with a Vmem-specific manner using Ivm. The data reveal that changes in gross cortical anatomy can be recapitulated at the cellular level, and suggest Vmem as a useful tool to establish in vitro models for both normal and diseased cortex.

E18 rat cerebral cortical tissue was kindly provided every week from Gregory Frost from Dr. Steven Moss's laboratory at Tufts Neuroscience Center. The brain tissue isolation protocol was approved by Tufts University Institutional Animal Care and Use Committee and complies with the NIH Guide for the Care and Use of Laboratory Animals (IACUC # B2011-45).

Cortices were removed from Hanks Balanced Salt Solution (HBSS) using a 10 mL pipette, and were placed in a pre-warmed 0.25%/0.3% Trypsin/DNase solution in a new 35-mm dish. Cortices were incubated at 37°C for 20 min for enzymatic dissociation of the tissues. The tissue suspension was mixed with pre-warmed trypsin inhibitor solution (1 mg/mL) at 1:1 ratio in a 15 mL tube. The mixture was pipetted up and down <20 times until the tissues were broken up into a homogeneous cell suspension. Dissociated neurons were centrifuged at 1000 rpm for 5 min. The cell pellet was resuspended in 10 mL dissociation buffer (complete NB media + 1:50 glutamate). Cells were counted using a hemocytometer. Cells were seeded on poly-d-lysine (100 μg/mL) coated plates in Neurobasal Media, supplemented with B27, 1% penicillin/streptomycin and 1% glutamax, all purchased from Invitrogen (Carlsbad, CA). Ivm (1 μmol/L, Tocris Bioscience-R&D Systems, Inc., MN) was added to the culture medium to change Vmem of the cells. Cell culture media were changed once a week. Each series of experiments constituted the same pool of cortical cells isolated from one rat cerebral cortex. Ninety-six-well plates (Nunc, Rochester, NY), 8-well chambers, and 3-cm petri dishes (Ibidi, LLC, Verona, WI) were used for high-throughput measurements, immunocytochemistry, and connectivity assays, respectively.

Each cortex was taken up with a 10 mL pipette and placed into a 15 mL conical tube containing 5 mL warmed 10% FBS DMEM + 1% penicillin/streptomycin media. Cortices were pipetted up and down <20 times. The homogenized cell suspension was passed through a 40 μm cell strainer into a 50 mL tube. The cell strainer was moved to a new tube and 5 mL of cells were pipetted from a 50 mL conical tube into T-25 flasks. The next day after seeding, the media were replaced with prewarmed fresh 10% FBS DMEM + 1% penicillin/streptomycin. This process was repeated 2–5 days after seeding. After 1 week, the media were removed, cells were rinsed with PBS, and new prewarmed 2% FBS DMEM + 1% penicillin/streptomycin media were added to the cells. Neurons and astrocytes were seeded in 3:1 (3 × 105:1 × 105 cells/mL) ratio for cocultures. Each series of experiments constituted the same pool of astrocytes isolated from cerebral cortices of the offspring of one pregnant rat. Cocultures were maintained in astrocyte media combined with complete neurobasal media at 37°C in a humidified incubator with 5% CO2. Medium was changed once in a week. Astrocyte cultures were split 1:5 once a week.

Cell toxicity data were collected from WST-1 assay that measures mitochondrial activity. This assay is based on a tetrazolium salt is cleaved to formazan by the ‘succinate-tetrazolium reductase’ system which belongs to the respiratory chain of the mitochondria and is active only in viable cells (Hoper 1997; Ngamwongsatit et al. 2008). Cultures at 0–4 weeks after plating were incubated for 2 h, at 37°C with WST-1 reagent (1:10 in cell culture medium, Roche). Mitochondrial dehydrogenase activity in vital cells was measured as optical density at 440 nm using multimode multiplate reader (SpectraMax M2, Molecular devices, Sunnyvale, CA) with SoftMax Pro software. After measurement, cells were trypsinized and cell numbers were counted using hemocytometer. Cell viability was represented as optical density (OD) values divided by corresponding cell numbers (Ncell).

Cells were washed once with Ca2+- and Mg2+-containing PBS (pH 7.4), fixed in 4% formaldehyde/PBS for 30 min at room temperature (RT), permeabilized with 0.03% Triton X-100/PBS (Sigma Aldrich) for 5 min. Primary antibodies were added in 10% FBS/PBS and incubated overnight at 4°C. After washing with PBS, cells were further treated with fluorescence-coupled secondary antibodies in 10% FBS/PBS at 37°C for 30 min. Fluoroshield Mounting Medium With DAPI (Abcam, Cambridge, MA) was used as a mounting solution. The following antibodies were used; rabbit polyclonal Vimentin (Sigma-Aldrich Cat# SAB4503083, RRID:AB_10746985), mouse monoclonal Glial Fibrillary Acidic Protein (GFAP, Sigma-Aldrich Cat# G3893 RRID:AB_477010)), rabbit polyclonal Glycine Receptor Alpha 1 (GLRA1, Abcam Cat# ab475, RRID:AB_304586), mouse monoclonal Synaptophysin (Abcam Cat# ab8049 RRID:AB_2198854), rabbit polyclonal beta III-tubulin (Abcam Cat# ab18207 RRID:AB_444319), anti-mouse Alexa Fluor 568 (Life Technologies Cat# A11004 RRID:AB_10562368), anti-rabbit Alexa Fluor 488 (Molecular Probes Cat# A11008 RRID:AB_143165), and Hoechst 33342 (Invitrogen, Cat# H1399). Images were collected using Leica DM, (Wetzlar, Germany) inverted fluorescence microscope, equipped with a mercury lamp, ebq 100 and a monochrome camera. 20X and 40X objectives were used. DAPI (excitation 360 ± 20 nm and emission 470 ± 20 nm), GFP (excitation 470 ± 20 nm and emission 525 ± 25 nm), and TexasRed (excitation 560 ± 20 nm and emission 645 ± 40 nm) filter sets were used.

The samples were reduced and denatured by boiling each cell lysate in sample buffer at 65°C for 5 min. Samples were loaded into the wells of the SDS-PAGE gel, along with molecular weight markers. Ten μg of total protein was loaded from cell lysate. The gel was run at 80V for 30 min, and then switched to 150V and run 1–2 h. The protein was then transferred from the gel to PVDF membrane using 200 mA current for 2 h.

The membrane was blocked in room temperature for 1 h or overnight at 4°C using 5% blocking solution. The membrane was then incubated with the appropriate dilutions of primary antibody in 5% BSA overnight at 4°C or for 2 h at room temperature. The membrane was washed in PBST three times, 5 min each. Membrane was then incubated with the recommended dilution of labeled secondary antibody in 5% blocking buffer in PBST at room temperature for 1 h. After washing the membrane three times in PBST, the membrane was soaked in Pierce ECL western blotting substrate for 1 min for signal development. The membrane was covered in transparent plastic wrap before for imaging.

Ratiometric di-8-ANEPPS dye (Invitrogen, Carlsbad, CA) was used to measure the Vmem of neurons (N), astrocytes (A) and cocultures (NA) from 0–4 weeks (w) after plating. Cells were washed once with HBSS prior to staining. Di-8-ANEPPS dye was diluted in HBSS to a final concentration of 2 μmol/L and added to the cells (100 μL/well). Cells were incubated at 37°C for 30 min in the dark. The uptake of dye was confirmed under a microscope using a red filter. Cells were washed once with HBSS to remove the excessive dye prior to measurement. Fluorescent intensities were measured using a top read fluorescence multimode multiplate reader (SpectraMax M5, Molecular Devices, Sunnyvale, CA). The relative Vmem of the cells was measured as the ratio of readings at two excitation states of the dye (450 nm/510 nm, emission: 640 nm). Plots were generated in excel. P values were calculated using Student's t-test.

Cultured rat embryonic day 18 cortical neurons plated on poly-D-lysine-coated 10-mm glass cover slips with or without astrocytes 4–6 days ago were placed inside a recording chamber (P1, Warner Instruments) that contained extracellular solution (140 mmol/L NaCl, 2.8 mmol/L KCl, 2 mmol/L CaCl2, 2 mmol/L MgCl2, 10 mmol/L HEPES, and 10 mmol/L D-glucose, with pH adjusted to 7.4 with NaOH). Cells were visualized with a Zeiss Axiovert 100 inverted microscope. Membrane potentials were measured at room temperature by whole-cell patch clamp using an Axopatch 1D amplifier (Axon Instruments) in current-clamp mode. Patch electrodes were pulled from 1.5-mm-diameter borosilicate glass capillaries (Sutter) with a Sutter P-87 microelectrode puller, and had 4–6 MΩ resistances when filled with an intracellular solution that contained 140 mmol/L potassium gluconate, 10 mmol/L NaCl, 2 mmol/L MgCl2, 10 mmol/L HEPES, 1 mmol/L EGTA, 4 mmol/L MgATP, and 0.3 mmol/L NaGTP, with pH adjusted to 7.3 with KOH. Membrane potential data were filtered by the amplifier-incorporated 4-pole Bessel filter at 2 KHz, and digitized at 5 KHz by a Molecular Devices digitizer (Digidata 1440A) using a Dell Precision 340 computer, with pClamp 10 software (Molecular Devices). Vmem quantification based on two methods, di-8-ANEPPS and whole-cell patch clamping, revealed that 1% change in ANEPPS ratio corresponds to 1 mV change in Vmem in E18 cortical neurons (Fig.1).

To quantify the extent to which cells clustered, a Fourier-based analysis of image intensities was utilized through the development of a custom-written Matlab code. This method enabled us to analyze large number of cells immune-labeled for three different cellular components in an automated manner. Images that were collected with different objectives and at different digital resolutions were first resampled to a consistent digital resolution (800 × 600 pixels; 1.6 pixels/μm) that exceeded the diffraction-limit optical resolution of all objectives in an effort to standardize the image data prior to cluster analysis. To facilitate Fourier-based cluster analysis, images were further cropped to a 600 × 600 pixel image by taking the center portion of the original image. A two-dimensional (2D) power spectral density (PSD) map was obtained through a discrete Fourier transform, and the 2D PSD was then radially sampled to produce a single PSD-frequency curve for each image as previously described (Xylas et al. 2012). The PSD-frequency data were log transformed, and a PSD-weighted average spatial frequency (f) was then computed using every data point i:

A normalized clustering factor (NCF) was defined from the PSD-weighted average frequency as follows:

where fmin and fmax represent the minimum and maximum spatial frequencies in the PSD curve. In this normalized scale, random (white) noise would produce a NCF = 0, whereas a single large Gaussian distributed clump would correspond to the maximum value of NCF = 1. Of note, PSD-frequency curves demonstrating a power law decay (e.g., a self-similar fractal) would produce an NCF = 0.5. NCF values were obtained from each fluorescence channel in the acquired images.

The number of cells in each image and the average cell area were also approximated through automated image analysis algorithms written in Matlab. Cells were counted by identifying the locations of individual DAPI-stained nuclei. First, pixel intensity values were normalized in the DAPI images to span between 0 and 1. To highlight the location of nuclei, which spanned 12–18 pixels in diameter, two filtered DAPI images were produced through convolutions with 12 and 18 pixel diameter disks. An image of the difference between the two filtered images was produced to highlight nuclei between this 12–18 pixel diameter range. Pixel locations from this filtered image exceeding a value of 0.005 were noted. Next, a Prewitt edge finding filter was applied to the filtered image to identify pixel locations with a high intensity gradient. Objects made of contiguous pixels with intensities exceeding 0.005 and a gradient value exceeding 0.02 were identified, and the locations of individual nuclei were defined by the centroids of each of these objects. These two intensity threshold values for the processed DAPI images were chosen based on their collective ability to provide an accurate identification of nuclei across all image sets. Nuclei were labeled as neurons if the intensity of the green channel (beta III tubulin/Alexa Fluor 488) exceeded the intensity of the red channel (Glial Fibrillary Acidic Protein/Alexa Fluor 568) at that pixel location, whereas astrocytes were defined when the red intensity exceeded the green intensity.

The relative areas covered by astrocytes and neurons were also calculated from the image intensities in each channel. Regions covered by astrocytes were defined by pixel locations that (a) had a red channel intensity that exceeded 10% of the image's maximum intensity and (b) also had a higher red channel intensity than green channel intensity. The neuronal regions were defined by pixel locations at which the green intensity exceeded both 10% of the maximum image intensity and also the red channel intensity at that location. The average area of an individual cell within each image was computed from the total area of a given cell type and the number of nuclei identified and classified as that cell type.

Phase-contrast images collected from control and Ivm-treated cortical neuron cultures were used to analyze Vmem-induced changes in the neural connectivity. 35-mm-petri dishes with low walls and an imprinted 500 μm relocation grid were used for both culturing and imaging (Ibidi, LLC, Verona, WI). Imprinted grids enabled the relocation of the same cells at different time points during imaging. We focused on analyzing phase-contrast images rather than fluorescence images of the labeled cells. The reason for that was a) to avoid the morphological changes due to the staining process, and b) to be able to work on the most natural state of the neurons as possible in vitro. The somas were manually annotated, and then the isolated somas were identified. We categorized somas as ‘connected’ if they were connected to others by a dendrite. In our case, we used 10 pixels as the distance threshold; usually somas closer than 10 pixels shared a common “halo”, which is an artifact of phase-contrast microscopy. Isolated somas were identified as somas that were neither connected with others by a dendrite nor close in proximity to another soma. As an example, there were 43 somas identified in Fig.4C, which shows one 0.5 × 0.5 mm area (a grid) of the entire dish; the somas are numbered as well as the boundaries of the somas. The very bright areas, which were assumed to be dead cells, were omitted. We identified somas that were connected through dendrites as the first condition of connectivity. Although there were no dendrites among some somas, they were very close to each other and thus we also treated these somas as connected.

The total number of projections emerging from single neurons (arrows) was counted manually in the fluorescent (beta III tubulin/AlexaFluor488) images taken from control (Fig.2A) or Ivm-treated 3w cocultures (Fig.2B). Depolarization of neural Vmem was verified by ratiometric measurement of Vmem-specific dye di-8-ANEPPS in control (no Ivm) and in Ivm-treated 3w cocultures. Accuracy of di-8-ANEPPS dye was verified by whole-cell patch clamp measurements as shown in the methods section. When incubated with 1 μmol/L Ivm for 24 h, the di-8-ANEPPS ratio (450 nm/510 nm) signal measured from cocultures was significantly increased (by 29%), indicating a depolarized Vmem (Fig.2C). The Vmem of glial cells in homotypic cultures did not change upon Ivm exposure. Differentiated neurons had a significantly increased (133%, P ≤ 0.01) number of projections when their Vmem was depolarized using 1 μmol/L Ivm for 24 h. Control cells had fewer projections (Fig.2D). Cell toxicity was examined using the WST-1 assay, which measures cell health via readout of mitochondrial activity (Hoper 1997; Ngamwongsatit et al. 2008). We found that 1 μmol/L Ivm was not toxic to E18 cortical cells during 4 weeks in vitro. In contrast, cells treated with the drug exhibited significantly higher mitochondrial activity than cells without the drug (Fig.2E). We conclude that depolarized Vmem causes mature neurons to form more membrane projections.

We used a pharmacological strategy (Blackiston et al. 2011; Adams and Levin 2013) targeting native chloride channels to stably depolarize the Vmem of cells in culture and to ascertain the effects on cell distribution. The distribution of neural cells was quantified by performing automated cluster analysis on the fluorescent images. Images were taken from 3w cocultures labeled with beta III-tubulin and GFAP for visualizing neurons and astrocytes, respectively. The y axis of the plot is power spectral density (PSD), analogous to a histogram frequency count. The PSD was generated by transforming the images to Fourier space as previously described (Xylas et al. 2012). The x axis is spatial frequency, which has units of pixels−1. An image feature, like a clump of cells that is 100 pixels in diameter would correspond to a frequency of 0.01 pixels−1 (Fig.3A). Control cells were distributed mostly sparsely with single cells or very small aggregates of a few cells (Fig.3C). In contrast, mature neurons assembled into aggregates when 3w cocultures were exposed to 1 μmol/L Ivm for 24 h (Fig.3B). A normalized clustering factor was defined based on the PSD-weighted average frequency, in which the largest possible aggregate within the images is equal to 1 and random organization (no aggregation) is 0. Under depolarizing conditions (1 μmol/L Ivm, 24 h), neurons showed significantly greater aggregation by a degree of 0.26 compared to controls (0.21) with no Ivm exposure (Fig.3D). In contrast, glia cell aggregates had no significant difference in their clustering factor between Ivm and control conditions (Fig.3E). We conclude that mature neurons cluster together to form large assemblies when their cell membrane is depolarized.

We also examined these assemblies using a calcium pump (SERCA)-opener Thapsigargin (TG) on cell cultures loaded with 2 μmol/L Fluo4-AM and found that the assemblies were functionally connected to each other. Real-time connectivity was recorded as a calcium wave propagating among Vmem-induced (24 h Ivm) neural assemblies upon TG (20 μmol/L)-induced depolarization. TG was applied on the left side of the dish during recording (Supplementary Movie S1). Glycine receptor (GLR) production increased in cells with depolarized membrane potential, which may be linked to the formation of the assemblies (Fig.3F).

Segmentation analysis was performed to locate and quantify the nuclei in fluorescent images from cells labeled with DAPI (small circles). Cells were labeled as neurons based on a greater intensity of green stain relative to red and are circled in magenta. Those cells labeled as glia are circled in cyan. False-colored masks (Fig.4A and B) showing glia and neuron areas were generated from the corresponding original images (Fig.4C and D). Glial and neural cell areas were identified based on red (GFAP/AlexaFluor 563) and green (Beta-III tubulin/AlexaFluor 488) intensity profiles, respectively. In 3w cocultures treated with Ivm (1 μmol/L, 24 h), both neuron (33.6%) and glia (59.7%) cells had greater numbers than controls with no Ivm exposure (Fig.4E). Similarly, both glial (33.3%, P ≤ 0.05) and neural (20.4%) cell densities were greater in 3w cocultures under depolarizing conditions (1 μmol/L Ivm, 24 h) compared to their densities in control conditions with no Ivm exposure (Fig.4F). In contrast, divergent changes were detected between neural and glial cell area profiles when neural Vmem was depolarized in 3w cocultures. After depolarization, the neurons had an average size of 643 μm2, larger than the controls (521 μm2), whereas glia had a reduced cell size of 1449 μm2 compared to controls (1743 μm2). Data revealed that the average size of the neurons increased by 18.9% whereas that of glia declined by 20.3% when the Vmem of the neurons was depolarized (Fig.4G). Additionally, the ratio of neuron and glia cell counts decreased slightly (10.4%) in 3w cocultures under depolarizing conditions (Fig.4H). We conclude that a depolarized Vmem alters the neuronal microenvironment due to the higher density packing of astrocytes surrounding them.