Evidence map›Paper›PMID 30787389›Full record

ArticleScientific reports2019

A softening laminar electrode for recording single unit activity from the rat hippocampus.

A Zátonyi, G Orbán, R Modi, G Márton, D Meszéna, I Ulbert, A Pongrácz, M Ecker, W E Voit, A Joshi-Imre and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  4. Review
  5. Article
  6. Review
  7. Commonly Overlooked Factors in Biocompatibility Studies of Neural Implants.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. A Parylene Neural Probe Array for Multi-Region Deep Brain Recordings.Journal of microelectromechanical systems : a joint IEEE and ASME publication on microstructures, microactuators, microsensors, and microsystems · 2020
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

A ZátonyiResearch Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
G OrbánÓbuda University Doctoral School on Materials Sciences & Technologies, Budapest, Hungary.
R ModiAdvanced Polymer Research Laboratory, The University of Texas at Dallas, Richardson, TX, USA.
G MártonInstitute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
D MeszénaInstitute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
I UlbertResearch Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
A PongráczResearch Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
M EckerAdvanced Polymer Research Laboratory, The University of Texas at Dallas, Richardson, TX, USA.ORCID 0000-0002-0603-6683
W E VoitAdvanced Polymer Research Laboratory, The University of Texas at Dallas, Richardson, TX, USA.
A Joshi-ImreAdvanced Polymer Research Laboratory, The University of Texas at Dallas, Richardson, TX, USA. alexandra.joshi-imre@utdallas.edu.ORCID 0000-0002-4271-1623
Z FeketeResearch Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary. fekete.zoltan@itk.ppke.hu.ORCID 0000-0002-6718-4022
The University of Texas at Dallas · USPázmány Péter Catholic University · HUInstitute of Cognitive Neuroscience and Psychology · HUObuda University · HUUniversity of Pannonia · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Softening neural implants that change their elastic modulus under physiological conditions are promising candidates to mitigate neuroinflammatory response due to the reduced mechanical mismatch between the artificial interface and the brain tissue. Intracortical neural probes have been used to demonstrate the viability of this material engineering approach. In our paper, we present a robust technology of softening neural microelectrode and demonstrate its recording performance in the hippocampus of rat subjects. The 5 mm long, single shank, multi-channel probes are composed of a custom thiol-ene/acrylate thermoset polymer substrate, and were micromachined by standard MEMS processes. A special packaging technique is also developed, which guarantees the stable functionality and longevity of the device, which were tested under in vitro conditions prior to animal studies. The 60 micron thick device was successfully implanted to 4.5 mm deep in the hippocampus without the aid of any insertion shuttle. Spike amplitudes of 84 µV peak-to-peak and signal-to-noise ratio of 6.24 were achieved in acute experiments. Our study demonstrates that softening neural probes may be used to investigate deep layers of the rat brain.

Indexed as

Electrodes, ImplantedAction PotentialsAnimalsElectric ImpedanceHippocampusPolymersRats, WistarSignal Processing, Computer-AssistedTemperaturePolymers

Identifiers

PMID30787389
PMCPMC6382803
OpenAlexW2939621317

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.