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multi-electrode arrays  (MicroFluidic Systems)

 
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    MicroFluidic Systems multi-electrode arrays
    Multi Electrode Arrays, supplied by MicroFluidic Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/multi-array+system/multi+electrode+arrays/pmc05459496-157-0-7
    Average 90 stars, based on 1 article reviews
    multi-electrode arrays - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Microelectrode Array:

    Article Title: Microelectrode array architecture
    Article Snippet: .. It is believed that the Microelectrode Array Architecture can provide solutions to the needs mentioned above with a number of advantages over the conventional digital microfluidic systems. ..

    Article Title: Microelectrode array architecture
    Article Snippet: .. The present invention, Microelectrode Array Architecture, relates to the manipulation of the independently controllable discrete droplets; including but not limited to the electrowetting-on-dielectric (EWOD) based microfluidic systems and methods. .. This invention offers scalable system architecture based on an array of identical basic microfluidic unit cells called microelectrodes.

    other:

    Article Title: Innovations in 3-Dimensional Tissue Models of Human Brain Physiology and Diseases
    Article Snippet: For microfluidic systems, this is typically achieved through the integration of multi-electrode arrays (MEA) that are capable of recording electrical activity with high spatial and temporal resolution.

    Article Title: FIDELITY: A quality control system for droplet microfluidics
    Article Snippet: Interdigitated electrode (IDE) arrays are widely used in microfluidic systems in general to perform functions such as particle manipulation ( ) and cell separation ( , , ) and have also been used in droplet microfluidic systems, mostly for droplet merging purposes ( – ).

    Article Title: Shear and AC Field Enhanced Carbon Nanotube Impedance Assay for Rapid, Sensitive, and Mismatch-Discriminating DNA Hybridization.
    Article Snippet: R apid and highly sensitive RNA/DNA hybridization assays have attracted enormous attention in a wide variety of applications ranging from genotyping to molecular diagnosis.. Conventional labbased optical detection methods for hybridization assays, such as microarray and realtime PCR, involve expensive detection protocols based on fluorescent tagging, thus requiring qualified professionals and limiting their potential use.. Furthermore, DNA hybridization reactions in microarray analyses are time-consuming due to ratelimiting diffusion kinetics, making the technique difficult for point-of-need and highthroughput applications.

    Article Title: An Oscillation-Based Technique for Degradation Monitoring of Sensing and Actuation Electrodes Within Microfluidic Systems
    Article Snippet: There is significant interest in the use of electrodes for sensing or actuation in bio-fluidic microsystems.. Within these systems high levels of reliability are crucial and complimented by requirements for extremely low probabilities of false positive and false negatives.. This paper extends previous work on impedance and oscillation based condition monitoring of electrode arrays by investigating the application of oscillation built-in self-test to a microfluidic based electrodes for conductance measurements and a system level implementation for monitoring multiple electrodes on-line.

    Article Title: Multiplex Immunosensor Arrays for Electrochemical Detection of Cancer Biomarker Proteins
    Article Snippet: Multi-electrode arrays can also be integrated to microfluidic systems to reduce sample volume, automate the assay process and increase throughput.



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    (A) Representative image of multi-unit recordings setup of ex vivo thalamic horizontal slices in a humidified, oxygenated interface chamber. (B) Schematic of multi-unit activity recordings with a <t>Neuronexus</t> <t>16-channel</t> recording electrode positioned in the thalamus following electrical stimulation of the internal capsule. (C) Representative 3-second recording of intrathalamic multi-unit activity evoked by stimulation of the internal capsule (black dot indicates time of stimulation). Only 12 of 16 channels are shown for clarity. (D) Collapsed activity from 12 recording channels in (C). Black dot indicates time of stimulation. (E) Post-stimulus time histogram of instantaneous spiking frequency from multi-unit activity recorded across 16 channels (all 16 channels were analyzed, 12 representative channels are displayed in (C) from 15 slices from 9 hCSF1 (WT) mice, 8 slices from 7 hCSF1-Grn −/− +KOxMG mice, and 12 slices from 9 hCSF1-Grn −/− +WTxMG mice. The grey box denotes early response (0–1.5 s), and the white box denotes delayed response (1.5–3 s) after stimulation. (F) Enlarged instantaneous frequency of the delayed response (1.5–3 s) from (D). (G) Relative probability of eliciting spiking during the direct response (0–1.5 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (* p = 0.0024). (H) Instantaneous frequency of spiking during the early response (0–1.5 s) after stimulation; Kruskal–Wallis test, H(3) = 6.767, p = 0.0797. (I) Relative probability of eliciting spiking during the delayed response (1.5–3 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (**** p < 0.0001). (J) Instantaneous frequency of spiking during the delayed response (1.5–3 s) after stimulation; Kruskal-Wallis test, H(3)=56.6, **** p < 0.0001, and Dunn’s multiple comparisons test (**** p < 0.0001). Data are presented as mean ± SEM. Comparisons not shown are not significant.
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    (A) Representative image of multi-unit recordings setup of ex vivo thalamic horizontal slices in a humidified, oxygenated interface chamber. (B) Schematic of multi-unit activity recordings with a <t>Neuronexus</t> <t>16-channel</t> recording electrode positioned in the thalamus following electrical stimulation of the internal capsule. (C) Representative 3-second recording of intrathalamic multi-unit activity evoked by stimulation of the internal capsule (black dot indicates time of stimulation). Only 12 of 16 channels are shown for clarity. (D) Collapsed activity from 12 recording channels in (C). Black dot indicates time of stimulation. (E) Post-stimulus time histogram of instantaneous spiking frequency from multi-unit activity recorded across 16 channels (all 16 channels were analyzed, 12 representative channels are displayed in (C) from 15 slices from 9 hCSF1 (WT) mice, 8 slices from 7 hCSF1-Grn −/− +KOxMG mice, and 12 slices from 9 hCSF1-Grn −/− +WTxMG mice. The grey box denotes early response (0–1.5 s), and the white box denotes delayed response (1.5–3 s) after stimulation. (F) Enlarged instantaneous frequency of the delayed response (1.5–3 s) from (D). (G) Relative probability of eliciting spiking during the direct response (0–1.5 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (* p = 0.0024). (H) Instantaneous frequency of spiking during the early response (0–1.5 s) after stimulation; Kruskal–Wallis test, H(3) = 6.767, p = 0.0797. (I) Relative probability of eliciting spiking during the delayed response (1.5–3 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (**** p < 0.0001). (J) Instantaneous frequency of spiking during the delayed response (1.5–3 s) after stimulation; Kruskal-Wallis test, H(3)=56.6, **** p < 0.0001, and Dunn’s multiple comparisons test (**** p < 0.0001). Data are presented as mean ± SEM. Comparisons not shown are not significant.
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    Image Search Results


    (A) Representative image of multi-unit recordings setup of ex vivo thalamic horizontal slices in a humidified, oxygenated interface chamber. (B) Schematic of multi-unit activity recordings with a Neuronexus 16-channel recording electrode positioned in the thalamus following electrical stimulation of the internal capsule. (C) Representative 3-second recording of intrathalamic multi-unit activity evoked by stimulation of the internal capsule (black dot indicates time of stimulation). Only 12 of 16 channels are shown for clarity. (D) Collapsed activity from 12 recording channels in (C). Black dot indicates time of stimulation. (E) Post-stimulus time histogram of instantaneous spiking frequency from multi-unit activity recorded across 16 channels (all 16 channels were analyzed, 12 representative channels are displayed in (C) from 15 slices from 9 hCSF1 (WT) mice, 8 slices from 7 hCSF1-Grn −/− +KOxMG mice, and 12 slices from 9 hCSF1-Grn −/− +WTxMG mice. The grey box denotes early response (0–1.5 s), and the white box denotes delayed response (1.5–3 s) after stimulation. (F) Enlarged instantaneous frequency of the delayed response (1.5–3 s) from (D). (G) Relative probability of eliciting spiking during the direct response (0–1.5 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (* p = 0.0024). (H) Instantaneous frequency of spiking during the early response (0–1.5 s) after stimulation; Kruskal–Wallis test, H(3) = 6.767, p = 0.0797. (I) Relative probability of eliciting spiking during the delayed response (1.5–3 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (**** p < 0.0001). (J) Instantaneous frequency of spiking during the delayed response (1.5–3 s) after stimulation; Kruskal-Wallis test, H(3)=56.6, **** p < 0.0001, and Dunn’s multiple comparisons test (**** p < 0.0001). Data are presented as mean ± SEM. Comparisons not shown are not significant.

    Journal: bioRxiv

    Article Title: Transplantation of Human IPSC-derived Microglia Ameliorates Neuropathology and Circuit Dysfunction in Progranulin-Deficient Mice

    doi: 10.64898/2026.01.13.699312

    Figure Lengend Snippet: (A) Representative image of multi-unit recordings setup of ex vivo thalamic horizontal slices in a humidified, oxygenated interface chamber. (B) Schematic of multi-unit activity recordings with a Neuronexus 16-channel recording electrode positioned in the thalamus following electrical stimulation of the internal capsule. (C) Representative 3-second recording of intrathalamic multi-unit activity evoked by stimulation of the internal capsule (black dot indicates time of stimulation). Only 12 of 16 channels are shown for clarity. (D) Collapsed activity from 12 recording channels in (C). Black dot indicates time of stimulation. (E) Post-stimulus time histogram of instantaneous spiking frequency from multi-unit activity recorded across 16 channels (all 16 channels were analyzed, 12 representative channels are displayed in (C) from 15 slices from 9 hCSF1 (WT) mice, 8 slices from 7 hCSF1-Grn −/− +KOxMG mice, and 12 slices from 9 hCSF1-Grn −/− +WTxMG mice. The grey box denotes early response (0–1.5 s), and the white box denotes delayed response (1.5–3 s) after stimulation. (F) Enlarged instantaneous frequency of the delayed response (1.5–3 s) from (D). (G) Relative probability of eliciting spiking during the direct response (0–1.5 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (* p = 0.0024). (H) Instantaneous frequency of spiking during the early response (0–1.5 s) after stimulation; Kruskal–Wallis test, H(3) = 6.767, p = 0.0797. (I) Relative probability of eliciting spiking during the delayed response (1.5–3 s) after stimulation; p values from Kolmogorov-Smirnov test with Bonferroni correction (**** p < 0.0001). (J) Instantaneous frequency of spiking during the delayed response (1.5–3 s) after stimulation; Kruskal-Wallis test, H(3)=56.6, **** p < 0.0001, and Dunn’s multiple comparisons test (**** p < 0.0001). Data are presented as mean ± SEM. Comparisons not shown are not significant.

    Article Snippet: Extracellular multi-unit activity (MUA) recordings were obtained with a linear 16-channel multi-electrode array (Neuronexus) that spanned the nRT and VB thalamic regions.

    Techniques: Ex Vivo, Activity Assay