ArticleFrontiers in neuroscience2017
Recording Spikes Activity in Cultured Hippocampal Neurons Using Flexible or Transparent Graphene Transistors.
Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Predicting upper limb motor dysfunction after ischemic stroke: a functional near-infrared spectroscopy-based nomogram model.Frontiers in neurology · 2025Article
- Flexible Graphene Field-Effect Transistors and Their Application in Flexible Biomedical Sensing.Nano-micro letters · 2024Review
- Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording.Nano-micro letters · 2024Review
- Recent Advancements in Graphene-Based Implantable Electrodes for Neural Recording/Stimulation.Sensors (Basel, Switzerland) · 2023Review
- Living-Neuron-Based Autogenerator.Sensors (Basel, Switzerland) · 2023Article
- Graphene-Based Field-Effect Transistors in Biosensing and Neural Interfacing Applications: Recent Advances and Prospects.Analytical chemistry · 2023Review
- Manufacturing Processes of Implantable Microelectrode Array for In Vivo Neural Electrophysiological Recordings and Stimulation: A State-Of-the-Art Review.Journal of micro- and nano-manufacturing · 2022Article
- Graphene-Based Electrode Materials for Neural Activity Detection.Materials (Basel, Switzerland) · 2021Review
- Interactions Between 2D Materials and Living Matter: A Review on Graphene and Hexagonal Boron Nitride Coatings.Frontiers in bioengineering and biotechnology · 2021Review
- A Review: Electrode and Packaging Materials for Neurophysiology Recording Implants.Frontiers in bioengineering and biotechnology · 2020Review
- Transistors for Chemical Monitoring of Living Cells.Biosensors · 2018Review
- Interfacing Graphene-Based Materials With Neural Cells.Frontiers in systems neuroscience · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of nanoelectronics applied to neural interfaces has started few decades ago, and aims to provide new tools for replacing or restoring disabled functions of the nervous systems as well as further understanding the evolution of such complex organization. As the same time, graphene and other 2D materials have offered new possibilities for integrating micro and nano-devices on flexible, transparent, and biocompatible substrates, promising for bio and neuro-electronics. In addition to many bio-suitable features of graphene interface, such as, chemical inertness and anti-corrosive properties, its optical transparency enables multimodal approach of neuronal based systems, the electrical layer being compatible with additional microfluidics and optical manipulation ports. The convergence of these fields will provide a next generation of neural interfaces for the reliable detection of single spike and record with high fidelity activity patterns of neural networks. Here, we report on the fabrication of graphene field effect transistors (G-FETs) on various substrates (silicon, sapphire, glass coverslips, and polyimide deposited onto
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.