Evidence map›Paper›PMID 30705750›Full record

ReviewF1000Research2018

Silicon Valley new focus on brain computer interface: hype or hope for new applications?

Stefan Mitrasinovic, Alexander P Y Brown, Andreas T Schaefer, Steven D Chang, Geoff Appelboom

Abstract readReview
In one paragraph

Review in F1000Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Identifying Thematics in a Brain-Computer Interface Research.Computational intelligence and neuroscience · 2023
    Review
  2. Article
  3. Review
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.

Stefan MitrasinovicUniversity College London Medical School, London, UK.ORCID 0000-0001-9681-8808
Alexander P Y BrownUniversity College London Medical School, London, UK.
Andreas T SchaeferThe Francis Crick Institute, London, UK.
Steven D ChangDepartment of Neurosurgery, Stanford University Medical Center, Brighton, USA.
Geoff AppelboomDepartment of Neurosurgery, Stanford University Medical Center, Brighton, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last year there has been increasing interest and investment into developing devices to interact with the central nervous system, in particular developing a robust brain-computer interface (BCI). In this article, we review the most recent research advances and the current host of engineering and neurological challenges that must be overcome for clinical application. In particular, space limitations, isolation of targeted structures, replacement of probes following failure, delivery of nanomaterials and processing and understanding recorded data. Neural engineering has developed greatly over the past half-century, which has allowed for the development of better neural recording techniques and clinical translation of neural interfaces. Implementation of general purpose BCIs face a number of constraints arising from engineering, computational, ethical and neuroscientific factors that still have to be addressed. Electronics have become orders of magnitude smaller and computationally faster than neurons, however there is much work to be done in decoding the neural circuits. New interest and funding from the non-medical community may be a welcome catalyst for focused research and development; playing an important role in future advancements in the neuroscience community.

Indexed as

Brain-Computer InterfacesNeurosciencesBrainElectroencephalographyNeuronsBrain computer interfacebrain machine interfaceneuralace

Identifiers

PMID30705750
PMCPMC6343225

What OpenQuestion holds

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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.