ArticleComputational intelligence and neuroscience2015
A low-noise, modular, and versatile analog front-end intended for processing in vitro neuronal signals detected by microelectrode arrays.
Article in Computational intelligence and neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Nanogroove-Induced Enhancement of Neural Spike Activity in Stem Cell-Derived Networks.Micromachines · 2026Article
- Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.Journal of neural engineering · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The collection of good quality extracellular neuronal spikes from neuronal cultures coupled to Microelectrode Arrays (MEAs) is a binding requirement to gather reliable data. Due to physical constraints, low power requirement, or the need of customizability, commercial recording platforms are not fully adequate for the development of experimental setups integrating MEA technology with other equipment needed to perform experiments under climate controlled conditions, like environmental chambers or cell culture incubators. To address this issue, we developed a custom MEA interfacing system featuring low noise, low power, and the capability to be readily integrated inside an incubator-like environment. Two stages, a preamplifier and a filter amplifier, were designed, implemented on printed circuit boards, and tested. The system is characterized by a low input-referred noise (<1 μV RMS), a high channel separation (>70 dB), and signal-to-noise ratio values of neuronal recordings comparable to those obtained with the benchmark commercial MEA system. In addition, the system was successfully integrated with an environmental MEA chamber, without harming cell cultures during experiments and without being damaged by the high humidity level. The devised system is of practical value in the development of in vitro platforms to study temporally extended neuronal network dynamics by means of MEAs.
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Registered trials
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