Sustained synchronized neuronal network activity in a human astrocyte co-culture system.
- Authors
- Kuijlaars, Jacobine; Oyelami, Tutu; Diels, Annick; Rohrbacher, Jutta; Versweyveld, Sofie; Meneghello, Giulia; Tuefferd, Marianne; Verstraelen, Peter; Detrez, Jan R; Verschuuren, Marlies; De Vos, Winnok H; Meert, Theo; Peeters, Pieter J; Cik, Miroslav; Nuydens, Rony; Brône, Bert; Verheyen, An
- Year
- 2016
- Journal
- Scientific reports
- PMID
- 27819315
- DOI
- 10.1038/srep36529
- PMCID
- PMC5098163
Impaired neuronal network function is a hallmark of neurodevelopmental and neurodegenerative disorders such as autism, schizophrenia, and Alzheimer's disease and is typically studied using genetically modified cellular and animal models. Weak predictive capacity and poor translational value of these models urge for better human derived in vitro models. The implementation of human induced pluripotent stem cells (hiPSCs) allows studying pathologies in differentiated disease-relevant and patient-derived neuronal cells. However, the differentiation process and growth conditions of hiPSC-derived neurons are non-trivial. In order to study neuronal network formation and (mal)function in a fully humanized system, we have established an in vitro co-culture model of hiPSC-derived cortical neurons and human primary astrocytes that recapitulates neuronal network synchronization and connectivity within three to four weeks after final plating. Live cell calcium imaging, electrophysiology and high content image analyses revealed an increased maturation of network functionality and synchronicity over time for co-cultures compared to neuronal monocultures. The cells express GABAergic and glutamatergic markers and respond to inhibitors of both neurotransmitter pathways in a functional assay. The combination of this co-culture model with quantitative imaging of network morphofunction is amenable to high throughput screening for lead discovery and drug optimization for neurological diseases.
Characterization of hiPSC (-derived) cells during different steps of the differentiation protocol on laminin coated surface (a) Schematic overview of the differentiation protocol towards hiPSC-derived cortical neuronal cultures. (b) hiPSCs express pluripotency markers OCT4 and NANOG before the start of differentiation. (c) Neural precursor cells express neural stem cell markers PAX6, nestin, and OTX2 at the 25th day of the differentiation protocol. (d) Fully differentiated neurons express neuronal marker class III β-tubulin and cortical markers TBR1, CTIP2, and SATB2. However, due to the heterogeneous nature of the cultures, not all cells are immuno-positive for all markers (also undifferentiated neural precursor cells and potentially some astrocytes are present in the cultures).
LLM interpretation
This figure consists of a schematic diagram and several immunofluorescence microscopy images characterizing the differentiation of hiPSCs into cortical neurons. Panel (a) is a timeline diagram detailing the stages of neural induction, proliferation, purification, and maturation from DIV -1 to DIV 80. Panels (b), (c), and (d) show microscopy images with DAPI nuclear staining (blue) and specific markers: pluripotency markers OCT4 (green) and NANOG (red) in hiPSCs; neural stem cell markers PAX6, Nestin, and OTX2 (green) in precursor cells; and neuronal markers TUBB3 (red) alongside cortical markers TBR1, CTIP2, and SATB2 (green) in mature neurons.
Functional maturation of hiPSC derived cortical neurons in a short time frame via co-culture with astrocytes and treatment with DAPT (a) Cortical neurons are differentiated from NPCs after final plating on top of an astrocyte monolayer. During the first week of differentiation DAPT is added. Functional and morphological assays are performed at 2–8 weeks after final plating. (b) hiPSCs differentiated towards cortical neurons in co-culture with primary human astrocytes are stained with neuronal marker class III β-tubulin, astrocyte marker GFAP and nuclear marker DAPI. (c) Cortical fate of hiPSC-derived neurons grown in human astrocyte co-cultures is confirmed by immunocytochemistry for cortical markers TBR1, CTIP2, and SATB2 in combination with the nuclear marker DAPI. (d) Functional maturation of neurons analyzed using whole cell patch clamp. Traces of evoked potentials (protocol scheme included) show a clear difference between early (wk1 and wk2 respectively firing no action potentials or only one) and later time points (wk4-5 firing repetitive action potentials) of differentiation. The left graph shows a more negative resting membrane potential over time (One-way ANOVA, p = 0.0113). The middle graph shows an increasing maximum action potential frequency over time (One-way ANOVA, p = 0.0187). An increased rheobase is observed as well two and three weeks after final plating (One-way ANOVA, p = 0.0112). n ≥ 9 from ≥1 differentiation, mean + SEM, *p < 0.05.
LLM interpretation
This figure consists of a differentiation timeline (a), immunofluorescence microscopy images (b, c), and electrophysiological data (d). The microscopy images show hiPSC-derived neurons co-cultured with astrocytes, stained for markers including TUBB3, GFAP, TBR1, CTIP2, and SATB2. The patch-clamp data includes voltage traces and bar charts demonstrating that from week 1 to week 5, neurons exhibit a more negative resting membrane potential, an increase in maximum action potential frequency, and a peak in rheobase at weeks 2-3 (all p < 0.05).
Optimization of conditions for synchronized neuronal calcium oscillations (a) Image showing automated identification of FLUO-4 loaded cells by color-coded regions of interest (ROIs) and representative traces (each trace represents fluorescence of one cell) of co-cultures with DAPT two weeks after final plating (left, no synchronicity) and four weeks after final plating (right, highly synchronized calcium influxes). After 250 frames (61 frames per minute) 30 μM glutamate was added, resulting in a large calcium influx and used to distinguish neurons from astrocytes. (b) Co-culturing with primary human astrocytes and treatment with DAPT significantly increases the percentage of active neurons (Two-way ANOVA, p < 0.0001), bursting frequency (Two-way ANOVA, p < 0.0001) and synchronicity (Two-way ANOVA, p < 0.0001) compared to cultures without DAPT and astrocytes. n ≥ 4 from ≥2 differentiations, mean ± SEM, **p < 0.01,***p ≤ 0.0001. (c) Synchronized activity sustains up to 8 weeks after final plating in human astrocyte co-cultures with DAPT. n ≥ 5 from ≥2 differentiations, mean ± SEM. d) Limited FGF2 passaging significantly reduces the percentage of active neurons (Two-way ANOVA, p < 0.0001), bursting frequency (Two-way ANOVA, p < 0.0001) and synchronicity (Two-way ANOVA, p < 0.0001). n ≥ 4 from ≥2 differentiations, mean ± SEM, *p < 0.05, ***p ≤ 0.0001.
LLM interpretation
This figure consists of microscopy images, fluorescence traces, and line graphs analyzing neuronal calcium oscillations. Panel (a) shows color-coded ROIs of cells and corresponding fluorescence traces over time, comparing non-synchronized activity at week 2 to highly synchronized oscillations at week 4. Panels (b), (c), and (d) utilize line graphs to show that the percentage of active neurons, bursting frequency, and correlation scores (synchronicity) increase over time in co-cultures with astrocytes and DAPT (b), sustain up to 8 weeks (c), and decrease with increased FGF2 passaging (d). Statistical significance is indicated by asterisks (*p < 0.05, **p < 0.01, ***p ≤ 0.0001) across the different experimental conditions.
Synchronized calcium oscillations represent neuronal network activity (a) Representative traces of live cell calcium imaging recordings in 5 week old cortical neuronal co-cultures, FLUO-4 intensity is shown over time (61 frames per minute). After 200 frames cells are exposed to tetrodotoxin (0.1 μM) followed by addition of glutamate (30 μM) after 200 frames, resulting in a large calcium influx. (b) Representative traces of patch clamp recordings of sPSCs showing sparse sPSCs (upper trace), sparse bursts of sPSCs (middle trace) and frequent bursting (lower trace). (c) Co-culture with primary human astrocytes + DAPT increases the percentage of cells with sPSC bursts compared to control (no DAPT, no astrocytes). “No activity” represents up to five single sPCSs per minute, “sparse activity” reflects 5 or more single events or less than one burst per minute and cells bursting at a frequency higher than one burst per minute are labeled with “frequently bursting”. Number of cells per cell culture condition n ≥ 22, from ≥2 differentiations. (d) Frequency of sPSC bursts per minute in co-cultures with primary human astrocytes + DAPT or neuron-only cultures equals the calcium oscillation frequency (Two-way ANOVA, p = NS for the respective cell culture conditions), while culture conditions induce significantly different bursting frequencies (Two-way ANOVA, p ≤ 0.0001). sPSC frequency: number of patched cells per cell culture condition ≥ 22, from ≥2 differentiations, calcium oscillation frequency: n ≥ 6 from ≥2 differentiations. Mean + SEM, ***p ≤ 0.0001.
LLM interpretation
This figure consists of four panels analyzing neuronal network activity. Panel (a) shows live-cell calcium imaging traces (FLUO-4 intensity over time) exhibiting oscillations that are suppressed by tetrodotoxin and triggered by glutamate, while panel (b) displays patch clamp recordings of spontaneous postsynaptic currents (sPSCs) with varying bursting patterns. Panel (c) is a stacked bar chart showing a higher percentage of "frequently bursting" cells in co-cultures with astrocytes and DAPT compared to control. Panel (d) is a bar chart comparing sPSC bursting frequency and calcium oscillation frequency across conditions, indicating a significant increase in bursting frequency for the astrocyte + DAPT group (***p ≤ 0.0001).
GABAergic and glutamatergic contribution to neuronal network function for cortical neurons in co-culture (a) Graphs showing a clear contribution of glutamatergic transmission to the calcium signal. Percentage of active neurons (One-way ANOVA, p < 0.0001), frequency (One-way ANOVA, p = 0.0002) and synchronicity (One-way ANOVA, p = 0.0004) significantly change compared to baseline. Mean + SEM, n ≥ 3, from 3 differentiations. *p < 0.05, ***p ≤ 0.0001 on the different time points. (b) Representative traces of live cell calcium imaging recordings in 5 week old cortical neuronal co-cultures, FLUO-4 intensity is shown over time (61 frames per minute). After 200 frames cells are exposed to DAP5 (50 μM) and CNQX (20 μM) followed by exposure to glutamate (30 μM) after 200 frames, resulting in a large calcium influx. (c) Graphs showing the contribution of GABAergic transmission to the calcium signal. The percentage of active neurons (One-way ANOVA, p = 0.0015), bursting frequency (One-way ANOVA, p = 0.0302) and burst amplitude (One-way ANOVA, p = 0.0125) are significantly changed after addition of picrotoxin. Mean + SEM, n ≥ 3, from 3 differentiations. *p < 0.05, **p < 0.01 on the different time points (d) Representative traces of calcium imaging. After 200 frames, the cells are exposed to the GABAergic inhibitor picrotoxin (50 μM), followed by glutamate exposure (30 μM) after 200 frames.
LLM interpretation
This figure consists of bar charts and calcium imaging traces analyzing the effects of glutamatergic and GABAergic inhibition on cortical neuronal co-cultures over 3, 5, and 7 weeks. Panels (a) and (b) show that glutamatergic inhibition significantly reduces the percentage of active neurons, bursting frequency, and correlation score compared to baseline (p < 0.0001 to p = 0.0004). Panels (c) and (d) demonstrate that GABAergic inhibition via picrotoxin significantly alters the percentage of active neurons at 3 weeks and bursting amplitude at 5 weeks. The imaging traces in (b) and (d) show FLUO-4 intensity over time, illustrating the response to inhibitors followed by a large calcium influx upon glutamate exposure.
Astrocyte co-cultures are suitable for HCI and analyses (a) hiPSCs differentiated towards cortical neurons in co-culture with primary human astrocytes show expression of glutamatergic marker vGLUT1, GABAergic marker GAD65, and neuronal marker MAP2. (b) Image analysis based on raw data files from a plate scanner. Masks (in yellow) are drawn per channel to identify the number of nuclei (based on DAPI staining), neurite area (based on MAP2 staining) and the number of puncta per marker (either based on vGLUT1 or GAD65). (c) Quantification of glutamatergic marker vGLUT1 and GABAergic marker GAD65 per neurite area in human astrocyte co-cultures. Mean + SEM, n ≥ 4, from 3 differentiations.
LLM interpretation
This figure consists of immunofluorescence images and a bar chart evaluating hiPSC-derived neurons in astrocyte co-cultures. Panel (a) shows microscopy images staining for MAP2 (green), GAD65 (green/yellow), and vGLUT1 (red), with DAPI (blue) marking nuclei. Panel (b) demonstrates the image analysis process using yellow masks to quantify nuclei, neurite area, and synaptic puncta. Panel (c) is a bar chart showing the spot density of vGLUT1 and GAD65 puncta per $\text{mm}^2$ of neurite area across 3, 5, and 7 weeks in culture, with vGLUT1 consistently showing higher density than GAD65.
| Name | Type |
|---|---|
| 2-mercaptoethanol | drug |
| accutase | drug |
| action potential firing | phenotype |
| Active cells local | phenotype |
| active neurons | phenotype |
| active neurons (percentage) local | phenotype |
| Alexa secondary antibodies local | drug |
| Alzheimer's disease | phenotype |
| AMPA | drug |
| AMPA/kainate receptor local | drug |
| AMPA/kainate receptor local | gene |
| anti-CTIP2 local | drug |
| anti-GAD65 local | drug |
| anti-GFAP local | drug |
| anti-GS1 local | drug |
| anti-HuCHuD local | drug |
| anti-MAP2 local | drug |
| anti-NANOG local | drug |
| anti-Nestin local | drug |
| anti-OCT4 local | drug |
| anti-OTX2 local | drug |
| anti-PAX6 local | drug |
| anti-S100B local | drug |
| anti-SATB2 local | drug |
| anti-TBR1 local | drug |
| anti-vGLUT1 local | drug |
| anti-β3 tubulin local | drug |
| astrocyte-induced calcium oscillations local | phenotype |
| astrocytes | phenotype |
| autism | phenotype |
| B27 supplement | drug |
| Bcl11b | gene |
| Bdnf | gene |
| bursting amplitude local | phenotype |
| Bursting amplitude local | phenotype |
| bursting frequency local | phenotype |
| Bursting frequency local | phenotype |
| burst per minute local | phenotype |
| bursts of postsynaptic events local | phenotype |
| C7000 High Content Imaging System local | drug |
| CaCl2 | drug |
| calcium | drug |
| Calcium burst local | phenotype |
| calcium oscillations local | phenotype |
| Calcium oscillations local | phenotype |
| Calcium oscillation synchronization local | phenotype |
| ChiPSC6b_m1 local | cohort |
| CNQX | drug |
| CO2 | drug |
| co-cultures local | cohort |
| compounds | drug |
| control | cohort |
| correlation score local | phenotype |
| cortex | anatomy |
| cortical fate local | phenotype |
| Cortical neuron phenotype local | phenotype |
| cortical neurons | anatomy |
| CTIP2 | gene |
| DAP5 local | drug |
| DAPI | drug |
| DAPT | drug |
| depolarizing spike local | phenotype |
| dibutyryl cAMP local | drug |
| dispase | drug |
| d/l AP-5 | drug |
| DMEM:F12 Glutamax local | drug |
| donkey serum | drug |
| dorsomorphin | drug |
| dysregulation of network function local | phenotype |
| early cortical development local | anatomy |
| EDTA | drug |
| epilepsy | phenotype |
| extracellular solution local | drug |
| Faster kinetics local | phenotype |
| FGF2 | drug |
| Fitmaster software local | drug |
| Fluo-4-AM local | drug |
| frequently bursting local | phenotype |
| frontotemporal dementia | phenotype |
| fully human co-cultures local | cohort |
| Fully human co-cultures local | cohort |
| GABA | phenotype |
| GABAA receptor | drug |
| GABAergic pathway local | phenotype |
| GAD2 | gene |
| GAD65 local | drug |
| GDNF | drug |
| gene editing technologies local | drug |
| GFAP | gene |
| glucose | drug |
| glutamate | drug |
| glutamatergic pathway | phenotype |
| Glutamax | drug |
| GS1 local | gene |
| healthy controls | cohort |
| HEPES | drug |
| heterogeneous neuronal identities local | phenotype |
| hippocampus | anatomy |
| hiPSC | cohort |
| hiPSC-derived cortical neurons local | cohort |
| hiPSC-derived neuronal networks local | phenotype |
| hiPSC-derived neurons | cohort |
| hiPSC lines | cohort |
| HuC/HuD local | gene |
| human astrocyte co-cultures local | cohort |
| Human astrocyte co-culture system local | cohort |
| human astrocyte medium local | drug |
| human iPSC-derived astrocytes local | anatomy |
| human iPSC-derived neurons local | anatomy |
| human primary astrocytes (passage ≤3) local | cohort |
| impaired functional networks local | phenotype |
| Increased activity local | phenotype |
| insulin | drug |
| intracellular solution local | drug |
| iPSC0028 local | cohort |
| iPSC-derived neuronal co-culture network local | cohort |
| KCl | drug |
| K-gluconate | drug |
| laminin | drug |
| Leica DMI 4000B microscope local | drug |
| MAP2 | gene |
| MAP2-positive surface local | phenotype |
| matrigel | drug |
| MEM NEAA local | drug |
| MgCl2 | drug |
| Mixed co-cultures local | cohort |
| mixed rat/human co-cultures local | cohort |
| monoculture local | phenotype |
| monocultures local | cohort |
| Monocultures local | cohort |
| mTesR1 | drug |
| mTeSR1 medium | drug |
| N2B27 local | drug |
| N2B27 medium | drug |
| N2 supplement | drug |
| Na2ATP | drug |
| Na2GTP local | drug |
| NaH2PO4 | drug |
| NaHCO3 | drug |
| Nanog | gene |
| Negative resting membrane potential local | phenotype |
| NES | gene |
| network activity | phenotype |
| network development local | phenotype |
| network functionality local | phenotype |
| network maturity local | phenotype |
| neural precursor cells local | phenotype |
| Neural progenitor phenotype local | phenotype |
| neural synchronicity local | phenotype |
| neurite outgrowth | phenotype |
| neurobasal medium | drug |
| neurogenesis | phenotype |
| neuro-inflammation local | phenotype |
| neuronal activity | phenotype |
| neuronal clumping local | phenotype |
| neuronal co-cultures local | cohort |
| Neuronal culture local | cohort |
| neuronal detachment local | phenotype |
| neuronal differentiation | phenotype |
| neuronal maturation | phenotype |
| neuronal network function local | phenotype |
| neuronal network functionality local | phenotype |
| neuronal pathologies local | phenotype |
| neuronal_subtype local | phenotype |
| neuron/astrocyte co-cultures local | cohort |
| neurons | phenotype |
| neurotoxicity | phenotype |
| NMDA | drug |
| NMDA receptor | drug |
| no activity local | phenotype |
| non-neuronal cells | phenotype |
| NPC | drug |
| NPCs | cohort |
| Opera Phenix High Content Screening System local | drug |
| OTX2 | gene |
| oxygen | drug |
| p0 NPCs local | cohort |
| paraformaldehyde | drug |
| Parkinson's disease | phenotype |
| Pax6 | gene |
| pen/strep | drug |
| picrotoxin | drug |
| poly-l-ornithine | drug |
| POU5F1 | gene |
| primary microglia | anatomy |
| progenitor proliferation local | phenotype |
| proper network function local | phenotype |
| pyruvic acid local | drug |
| quasi rhythmic events local | phenotype |
| rat primary astrocytes local | cohort |
| resting membrane potential | phenotype |
| rheobase local | phenotype |
| Rock inhibitor | drug |
| Rodent astrocytes local | cohort |
| S100B local | gene |
| SATB2 local | gene |
| SB431542 | drug |
| schizophrenia | phenotype |
| Slc17a7 | gene |
| Sodium | drug |
| sodium pyruvate local | drug |
| sparse activity local | phenotype |
| Species-specific clock local | phenotype |
| spontaneous postsynaptic currents | phenotype |
| spontaneous synaptic currents local | phenotype |
| sPSC bursts local | phenotype |
| sucrose | drug |
| synaptic network activity local | phenotype |
| synaptic puncta local | phenotype |
| synchronicity local | phenotype |
| Synchronicity local | phenotype |
| Synchronicity of calcium signals local | phenotype |
| Synchronization of calcium oscillations local | phenotype |
| synchronization of neuronal calcium oscillations local | phenotype |
| synchronized oscillations local | phenotype |
| Tbr1 | gene |
| tetrodotoxin | drug |
| triple co-culture model local | cohort |
| Triton-X100 | drug |
| TUBB3 | gene |
| vGLUT1 local | drug |
| vGLUT1 | gene |
| voltage-gated sodium channel local | gene |
| Voltage-gated sodium channel local | drug |
| Zeiss LSM 510 local | drug |
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Genetics of Alcohol Use Disorder: A Role for Induced Pluripotent Stem Cells? | 2018 | 29897633 |
External
| Title | Authors | Journal | Year | Link |
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| Early-stage quality-late-stage confidence: Neural induction quality control as a key to reproducible MEA-based neurotoxicity assays. | Scharkin I et al. | — | 2026 | → |
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| Basal activation of astrocytic Nrf2 in neuronal culture media: Challenges and implications for neuron-astrocyte modelling. | Elsharkasi MMO et al. | — | 2025 | → |
| Co-cultures of Human-Induced Pluripotent Stem Cell-Derived Neurons, Astrocytes, and Microglia for Modeling Neurodegenerative Diseases. | Roewe J et al. | — | 2025 | → |
| <i>MAPT</i>-A152T mutation drives neuronal hyperactivity through Fyn-NMDAR signaling in human iPSC-Derived neurons: Insights into Alzheimer's pathogenesis. | Itsuno M et al. | — | 2025 | → |
| Increasing hexokinase 1 expression improves mitochondrial and glycolytic functional deficits seen in sporadic Alzheimer's disease astrocytes. | Bell SM et al. | — | 2025 | → |
| Neuroglia in neurodegeneration: Alzheimer, Parkinson, and Huntington disease. | Lim D et al. | — | 2025 | → |
| The Effect of Intracellular Calcium Buffer Bapta on Epileptiform Activity of Hippocampal Neurons. | Zinchenko VP et al. | — | 2025 | → |
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| Assembling a Coculture System to Prepare Highly Pure Induced Pluripotent Stem Cell-Derived Neurons at Late Maturation Stages. | Akter M et al. | — | 2024 | → |
| Astrocytes induce desynchronization and reduce predictability in neuron-astrocyte networks cultured on microelectrode arrays. | Genocchi B et al. | — | 2024 | → |
| Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders. | Yang Z et al. | — | 2024 | → |
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| Modulation of Ca<sup>2+</sup> oscillation following ischemia and nicotinic acetylcholine receptors in primary cortical neurons by high-throughput analysis. | Sasaki T et al. | — | 2024 | → |
| Participation of calcium-permeable AMPA receptors in the regulation of epileptiform activity of hippocampal neurons. | Zinchenko VP et al. | — | 2024 | → |
| Polyethyleneimine facilitates the growth and electrophysiological characterization of iPSC-derived motor neurons. | Yang M et al. | — | 2024 | → |
| Study of the Synchronization and Transmission of Intracellular Signaling Oscillations in Cells Using Bispectral Analysis. | Astashev ME et al. | — | 2024 | → |
| Unbiased identification of cell identity in dense mixed neural cultures | De Beuckeleer S et al. | — | 2024 | — |
| 5. Collaborative Study on the Genetics of Alcoholism: Functional genomics. | Gameiro-Ros I et al. | — | 2023 | → |
| A Human Neuron/Astrocyte Co-culture to Model Seeded and Spontaneous Intraneuronal Tau Aggregation. | Batenburg KL et al. | — | 2023 | → |
| ANDA: an open-source tool for automated image analysis of in vitro neuronal cells. | Wæhler HA et al. | — | 2023 | → |
| A robust and reliable methodology to perform GECI-based multi-time point neuronal calcium imaging within mixed cultures of human iPSC-derived cortical neurons. | Patel N et al. | — | 2023 | → |
| A Robust Pipeline for the Multi-Stage Accelerated Differentiation of Functional 3D Cortical Organoids from Human Pluripotent Stem Cells. | Whye D et al. | — | 2023 | → |
| Decoding Natural Astrocyte Rhythms: Dynamic Actin Waves Result from Environmental Sensing by Primary Rodent Astrocytes. | O'Neill KM et al. | — | 2023 | → |
| Emerging strategies of engineering retinal organoids and organoid-on-a-chip in modeling intraocular drug delivery: Current progress and future perspectives. | Yu J et al. | — | 2023 | → |
| Immortalized hippocampal astrocytes from 3xTg-AD mice, a new model to study disease-related astrocytic dysfunction: a comparative review. | Tapella L et al. | — | 2023 | → |
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| Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array. | Lam D et al. | — | 2023 | → |
| ST2-Conditioned Medium Fosters Dorsal Horn Cell Excitability and Synaptic Transmission in Cultured Mouse Spinal Cord. | Juárez EH et al. | — | 2023 | → |
| Astrocytes derived from ASD individuals alter behavior and destabilize neuronal activity through aberrant Ca<sup>2+</sup> signaling. | Allen M et al. | — | 2022 | → |
| Cross Talk proposal: Human-derived brain tissue is a better epilepsy model than animal-based approaches. | Cunningham MO | — | 2022 | → |
| Developmental neurotoxicity induced by glutaraldehyde in neuron/astrocyte co-cultured cells and zebrafish. | Oh HN et al. | — | 2022 | → |
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| In vitro neurotoxicity evaluation of biocidal disinfectants in a human neuron-astrocyte co-culture model. | Oh HN et al. | — | 2022 | → |
| Is the forming of neuronal network activity in human-induced pluripotent stem cells important for the detection of drug-induced seizure risks? | Kreir M et al. | — | 2022 | → |
| NPFF Decreases Activity of Human Arcuate NPY Neurons: A Study in Embryonic-Stem-Cell-Derived Model. | Torz L et al. | — | 2022 | → |
| Optimization of Long-Term Human iPSC-Derived Spinal Motor Neuron Culture Using a Dendritic Polyglycerol Amine-Based Substrate. | Thiry L et al. | — | 2022 | → |
| Promising Strategies for the Development of Advanced In Vitro Models with High Predictive Power in Ischaemic Stroke Research. | Van Breedam E et al. | — | 2022 | → |
| The implication of a diversity of non-neuronal cells in disorders affecting brain networks. | Carrier M et al. | — | 2022 | → |
| Tracking connectivity maps in human stem cell-derived neuronal networks by holographic optogenetics. | Schmieder F et al. | — | 2022 | → |
| Advancing models of neural development with biomaterials. | Roth JG et al. | — | 2021 | → |
| Building on a Solid Foundation: Adding Relevance and Reproducibility to Neurological Modeling Using Human Pluripotent Stem Cells. | Knock E et al. | — | 2021 | → |
| Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology. | Forro C et al. | — | 2021 | → |
| Emerging Opportunities in Human Pluripotent Stem-Cells Based Assays to Explore the Diversity of Botulinum Neurotoxins as Future Therapeutics. | Duchesne de Lamotte J et al. | — | 2021 | → |
| Live Viral Vaccine Neurovirulence Screening: Current and Future Models. | May Fulton C et al. | — | 2021 | → |
| Modelling epilepsy in the mouse: challenges and solutions. | Marshall GF et al. | — | 2021 | → |
| Novel test strategies for in vitro seizure liability assessment. | Tukker AM et al. | — | 2021 | → |
| PDE inhibition in distinct cell types to reclaim the balance of synaptic plasticity. | Rombaut B et al. | — | 2021 | → |
| Phenotyping Neurodegeneration in Human iPSCs. | Li J et al. | — | 2021 | → |
| SOX9-induced Generation of Functional Astrocytes Supporting Neuronal Maturation in an All-human System. | Neyrinck K et al. | — | 2021 | → |
| Ubisol-Q<sub>10</sub>, a Nanomicellar and Water-Dispersible Formulation of Coenzyme-Q<sub>10</sub> as a Potential Treatment for Alzheimer's and Parkinson's Disease. | Wear D et al. | — | 2021 | → |
| A flexible 3-dimensional microelectrode array for in vitro brain models. | Soscia DA et al. | — | 2020 | → |
| Alzheimer's disease risk gene <i>BIN1</i> induces Tau-dependent network hyperexcitability. | Voskobiynyk Y et al. | — | 2020 | → |
| Applicability of hiPSC-Derived Neuronal Cocultures and Rodent Primary Cortical Cultures for In Vitro Seizure Liability Assessment. | Tukker AM et al. | — | 2020 | → |
| Electrophysiological Maturation of Cerebral Organoids Correlates with Dynamic Morphological and Cellular Development. | Fair SR et al. | — | 2020 | → |
| Investigation of Schizophrenia with Human Induced Pluripotent Stem Cells. | Powell SK et al. | — | 2020 | → |
| Mapping regulators of cell fate determination: Approaches and challenges. | Kumar A et al. | — | 2020 | → |
| Modeling Alzheimer's disease with iPSC-derived brain cells. | Penney J et al. | — | 2020 | → |
| Modeling the complex genetic architectures of brain disease. | Fernando MB et al. | — | 2020 | → |
| Neurodegeneration in a dish: advancing human stem-cell-based models of Alzheimer's disease. | Klimmt J et al. | — | 2020 | → |
| Review: <i>In vitro</i> Cell Platform for Understanding Developmental Toxicity. | Xie J et al. | — | 2020 | → |
| Three-dimensional differentiation of human pluripotent stem cell-derived neural precursor cells using tailored porous polymer scaffolds. | Murphy AR et al. | — | 2020 | → |
| Astrocyte lineage cells are essential for functional neuronal differentiation and synapse maturation in human iPSC-derived neural networks. | Klapper SD et al. | — | 2019 | → |
| CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data. | Wegmann R et al. | — | 2019 | → |
| Concepts toward directing human astroplasticity to promote neuroregeneration. | Patel R et al. | — | 2019 | → |
| Differentiation of lymphoblastoid-derived iPSCs into functional cardiomyocytes, neurons and myoblasts. | Poulin H et al. | — | 2019 | → |
| Early glioma is associated with abnormal electrical events in cortical cultures. | Savarraj JP et al. | — | 2019 | → |
| Examining the fundamental biology of a novel population of directly reprogrammed human neural precursor cells. | Ahlfors JE et al. | — | 2019 | → |
| Functional and Mechanistic Neurotoxicity Profiling Using Human iPSC-Derived Neural 3D Cultures. | Sirenko O et al. | — | 2019 | → |
| High-throughput microscopy exposes a pharmacological window in which dual leucine zipper kinase inhibition preserves neuronal network connectivity. | Verschuuren M et al. | — | 2019 | → |
| Human iPS Cell-Derived Patient Tissues and 3D Cell Culture Part 1: Target Identification and Lead Optimization. | Eglen RM et al. | — | 2019 | → |
| In Vivo Phenotyping of Familial Parkinson's Disease with Human Induced Pluripotent Stem Cells: A Proof-of-Concept Study. | Zygogianni O et al. | — | 2019 | → |
| Neurotoxicity of pesticides. | Richardson JR et al. | — | 2019 | → |
| One Step Into the Future: New iPSC Tools to Advance Research in Parkinson's Disease and Neurological Disorders. | Mohamed NV et al. | — | 2019 | → |
| Robust Generation of Person-Specific, Synchronously Active Neuronal Networks Using Purely Isogenic Human iPSC-3D Neural Aggregate Cultures. | Izsak J et al. | — | 2019 | → |
| Role of Human-Induced Pluripotent Stem Cell-Derived Spinal Cord Astrocytes in the Functional Maturation of Motor Neurons in a Multielectrode Array System. | Taga A et al. | — | 2019 | → |
| Systems-Wide Approaches in Induced Pluripotent Stem Cell Models. | Lau E et al. | — | 2019 | → |
| The effect of rho kinase inhibition on morphological and electrophysiological maturity in iPSC-derived neurons. | Harbom LJ et al. | — | 2019 | → |
| Tissue-specific extracellular matrix accelerates the formation of neural networks and communities in a neuron-glia co-culture on a multi-electrode array. | Lam D et al. | — | 2019 | → |
| Altered glutamate response and calcium dynamics in iPSC-derived striatal neurons from XDP patients. | Capetian P et al. | — | 2018 | → |
| Brain Organoids and the Study of Neurodevelopment. | Trujillo CA et al. | — | 2018 | → |
| Effects of Passage Number and Differentiation Protocol on the Generation of Dopaminergic Neurons from Rat Bone Marrow-Derived Mesenchymal Stem Cells. | Shall G et al. | — | 2018 | → |
| GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks. | Mäkinen ME et al. | — | 2018 | → |
| Genetically Engineered iPSC-Derived FTDP-17 MAPT Neurons Display Mutation-Specific Neurodegenerative and Neurodevelopmental Phenotypes. | Verheyen A et al. | — | 2018 | → |
| Genetics of Alcohol Use Disorder: A Role for Induced Pluripotent Stem Cells? | Prytkova I et al. | — | 2018 | → |
| Human iPSC-derived neuronal models for in vitro neurotoxicity assessment. | Tukker AM et al. | — | 2018 | → |
| <i>In vitro</i> Models for Seizure-Liability Testing Using Induced Pluripotent Stem Cells. | Grainger AI et al. | — | 2018 | → |
| Image-Based Profiling of Synaptic Connectivity in Primary Neuronal Cell Culture. | Verstraelen P et al. | — | 2018 | → |
| Improved Generation of Induced Pluripotent Stem Cells From Hair Derived Keratinocytes - A Tool to Study Neurodevelopmental Disorders as ADHD. | Re S et al. | — | 2018 | → |
| Modeling Neuropsychiatric and Neurodegenerative Diseases With Induced Pluripotent Stem Cells. | LaMarca EA et al. | — | 2018 | → |
| Modelling Sporadic Alzheimer's Disease Using Induced Pluripotent Stem Cells. | Rowland HA et al. | — | 2018 | → |
| Simple and Inexpensive Paper-Based Astrocyte Co-culture to Improve Survival of Low-Density Neuronal Networks. | Aebersold MJ et al. | — | 2018 | → |
| Single-cell analysis of diversity in human stem cell-derived neurons. | Harbom LJ et al. | — | 2018 | → |
| Decreased calcium flux in Niemann-Pick type C1 patient-specific iPSC-derived neurons due to higher amount of calcium-impermeable AMPA receptors. | Rabenstein M et al. | — | 2017 | → |
| Dysregulation of Microtubule Stability Impairs Morphofunctional Connectivity in Primary Neuronal Networks. | Verstraelen P et al. | — | 2017 | → |
| Human induced pluripotent stem cell (hiPSC)-derived neurons respond to convulsant drugs when co-cultured with hiPSC-derived astrocytes. | Ishii MN et al. | — | 2017 | → |
| Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells. | Nadadhur AG et al. | — | 2017 | → |
| Prospects for Modeling Abnormal Neuronal Function in Schizophrenia Using Human Induced Pluripotent Stem Cells. | Prytkova I et al. | — | 2017 | → |
| Rod-Shaped Neural Units for Aligned 3D Neural Network Connection. | Kato-Negishi M et al. | — | 2017 | → |