Evidence map›Paper›PMID 30424378›Full record

ArticleMicromachines2018

The History and Horizons of Microscale Neural Interfaces.

Takashi D Y Kozai

Abstract read
In one paragraph

Article in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

1 author.

Takashi D Y KozaiDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15261, USA. tdk18@pitt.edu.ORCID 0000-0002-2507-3295

Funding

Improving chronic neural recording performance through biomaterial strategiesR01NS062019 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CUI, XINYAN TRACY · 2008 to 2018
$4.4M
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
Exploring the role of Oligodendrocytes and progenitors on chronic brain implantsR21NS108098 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KOZAI, TAKASHI DANIEL YOSHIDA · 2018 to 2019
$387k
Defense Sciences Office, DARPA DARPA-BAA-16-09-NESD-FP-001National Institutes of Health R01NS062019, R01NS094396, R01NS089688, R21NS108098NINDS NIH HHS R01 NS062019NINDS NIH HHS R01 NS089688NINDS NIH HHS R01 NS094396NINDS NIH HHS R21 NS108098
6 · The paper itself

Abstract

Microscale neural technologies interface with the nervous system to record and stimulate brain tissue with high spatial and temporal resolution. These devices are being developed to understand the mechanisms that govern brain function, plasticity and cognitive learning, treat neurological diseases, or monitor and restore functions over the lifetime of the patient. Despite decades of use in basic research over days to months, and the growing prevalence of neuromodulation therapies, in many cases the lack of knowledge regarding the fundamental mechanisms driving activation has dramatically limited our ability to interpret data or fine-tune design parameters to improve long-term performance. While advances in materials, microfabrication techniques, packaging, and understanding of the nervous system has enabled tremendous innovation in the field of neural engineering, many challenges and opportunities remain at the frontiers of the neural interface in terms of both neurobiology and engineering. In this short-communication, we explore critical needs in the neural engineering field to overcome these challenges. Disentangling the complexities involved in the chronic neural interface problem requires simultaneous proficiency in multiple scientific and engineering disciplines. The critical component of advancing neural interface knowledge is to prepare the next wave of investigators who have simultaneous multi-disciplinary proficiencies with a diverse set of perspectives necessary to solve the chronic neural interface challenge.

Indexed as

biasbiocompatibilityBRAIN Initiativediversityeducationmicro-electromechanical systems (MEMS)micromachinemulti-disciplinaryneurosciencetraining

Identifiers

PMID30424378
PMCPMC6187275

What OpenQuestion holds

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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.