Evidence map›Paper›PMID 32745989›Full record

ReviewiScience2020

Ultraflexible Neural Electrodes for Long-Lasting Intracortical Recording.

Fei He, Roy Lycke, Mehran Ganji, Chong Xie, Lan Luan

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
–field-weighted citation impact
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

54 citing papers in PubMed.

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  5. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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

5 authors.

Fei HeDepartment of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA; NeuroEngineering Initiative, Rice University, 6500 Main Street, Houston, TX 77005, USA.
Roy LyckeDepartment of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA; NeuroEngineering Initiative, Rice University, 6500 Main Street, Houston, TX 77005, USA; Department of Biomedical Engineering, University of Texas at Austin, 107 Dean Keeton, Austin, TX 78712, USA.
Mehran GanjiDepartment of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA; NeuroEngineering Initiative, Rice University, 6500 Main Street, Houston, TX 77005, USA; Department of Biomedical Engineering, University of Texas at Austin, 107 Dean Keeton, Austin, TX 78712, USA.
Chong XieDepartment of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA; NeuroEngineering Initiative, Rice University, 6500 Main Street, Houston, TX 77005, USA; Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX 77005, USA.
Lan LuanDepartment of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA; NeuroEngineering Initiative, Rice University, 6500 Main Street, Houston, TX 77005, USA; Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX 77005, USA. Electronic address: lan.luan@rice.edu.

Funding

A Nanoelectronic Strategy for Reliable, Large-scale Chronic Neural RecordingR01NS102917 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI Chong Xie · 2017 to 2026
$3.5M
Longitudinal multimodal mapping to decipher the neurovascular impact of microinfarctsR01NS109361 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI LUAN, LAN · 2019 to 2023
$2.9M
Nanoelectronic enabled chronic quantification of neurovascular couplingK25HL140153 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI LUAN, LAN · 2018 to 2022
$890k
Fibrosis-free Glaucoma Drainage ImplantsR21EY028747 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI HAN, YING, XIE, CHONG · 2018 to 2019
$392k
NEI NIH HHS R21 EY028747NHLBI NIH HHS K25 HL140153NINDS NIH HHS R01 NS102917NINDS NIH HHS R01 NS109361
6 · The paper itself

Abstract

Implanted electrodes provide one of the most important neurotechniques for fundamental and translational neurosciences by permitting time-resolved electrical detection of individual neurons in vivo. However, conventional rigid electrodes typically cannot provide stable, long-lasting recordings. Numerous interwoven biotic and abiotic factors at the tissue-electrode interface lead to short- and long-term instability of the recording performance. Making neural electrodes flexible provides a promising approach to mitigate these challenges on the implants and at the tissue-electrode interface. Here we review the recent progress of ultraflexible neural electrodes and discuss the engineering principles, the material properties, and the implantation strategies to achieve stable tissue-electrode interface and reliable unit recordings in living brains.

Indexed as

Bioelectrical EngingeeringBioelectronicsTechniques in Neuroscience

Identifiers

PMID32745989
PMCPMC7398974

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.