Evidence map›Paper›PMID 29805350›Full record

ArticleAdvanced functional materials2018

A Materials Roadmap to Functional Neural Interface Design.

Steven M Wellman, James R Eles, Kip A Ludwig, John P Seymour, Nicholas J Michelson, William E McFadden, Alberto L Vazquez, Takashi D Y Kozai

Abstract read
In one paragraph

Article in Advanced functional materials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers.

0numbers the graph read from it
0cells of the map it votes in
150citing 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

150 citing papers in PubMed.

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90 more citing papers are in PubMed but not listed here.

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

8 authors.

Steven M WellmanDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.
James R ElesDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.
Kip A LudwigDepartment of Neurologic Surgery, 200 First St. SW, Rochester, MN 55905.
John P SeymourElectrical & Computer Engineering, 1301 Beal Ave., 2227 EECS, Ann Arbor, MI 48109.
Nicholas J MichelsonDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.
William E McFaddenDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.
Alberto L VazquezDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.
Takashi D Y KozaiDepartment of Bioengineering, Center for the Basis of Neural Cognition, McGowan Institute of Regenerative Medicine, NeuroTech Center, University of Pittsburgh Brain Institute, Center for Neuroscience at the University of Pittsburgh, University of Pittsburgh, 208 Center for Biotechnology, 300 Technology Dr., Pittsburgh, PA 15219, United States.

Funding

Inhibition of Neural Electrode-mediated Inflammation and Neuronal Cell DeathR01NS089688 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CUI, XINYAN TRACY · 2015 to 2019
$3.1M
Mechanisms behind Electrode Induced BBB damage's impact on neural recordingR01NS094396 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KOZAI, TAKASHI DANIEL YOSHIDA · 2015 to 2019
$2.2M
Modular High-Density Optoelectrodes for Local Circuit Analysis - Administrative SupplementU01NS090526 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BUZSAKI, GYORGY, WISE, KENSALL DAVID · 2014 to 2016
$2.0M
Excitatory and Inhibitory Activity Contributions to Hemodynamic SignalsR01NS094404 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI VAZQUEZ, ALBERTO L · 2016 to 2020
$1.7M
NINDS NIH HHS R01 NS089688NINDS NIH HHS R01 NS094396NINDS NIH HHS R01 NS094404NINDS NIH HHS U01 NS090526
6 · The paper itself

Abstract

Advancement in neurotechnologies for electrophysiology, neurochemical sensing, neuromodulation, and optogenetics are revolutionizing scientific understanding of the brain while enabling treatments, cures, and preventative measures for a variety of neurological disorders. The grand challenge in neural interface engineering is to seamlessly integrate the interface between neurobiology and engineered technology, to record from and modulate neurons over chronic timescales. However, the biological inflammatory response to implants, neural degeneration, and long-term material stability diminish the quality of interface overtime. Recent advances in functional materials have been aimed at engineering solutions for chronic neural interfaces. Yet, the development and deployment of neural interfaces designed from novel materials have introduced new challenges that have largely avoided being addressed. Many engineering efforts that solely focus on optimizing individual probe design parameters, such as softness or flexibility, downplay critical multi-dimensional interactions between different physical properties of the device that contribute to overall performance and biocompatibility. Moreover, the use of these new materials present substantial new difficulties that must be addressed before regulatory approval for use in human patients will be achievable. In this review, the interdependence of different electrode components are highlighted to demonstrate the current materials-based challenges facing the field of neural interface engineering.

Indexed as

BioelectronicsElectrodesMicroelectromechanical SystemsPhotonicsSensors/Biosensors

Identifiers

PMID29805350
PMCPMC5963731

What OpenQuestion holds

Textmetadata
LicenceTDM
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.