Evidence map›Paper›PMID 30636899›Full record

ReviewExperimental neurobiology2018

Implantable Neural Probes for Brain-Machine Interfaces - Current Developments and Future Prospects.

Jong-Ryul Choi, Seong-Min Kim, Rae-Hyung Ryu, Sung-Phil Kim, Jeong-Woo Sohn

Abstract readReview
In one paragraph

Review in Experimental neurobiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026
    Review
  4. Review
  5. Review
  6. Aerosol Jet Printing for Neuroprosthetic Device Development.Bioengineering (Basel, Switzerland) · 2025
    Review
  7. Review
  8. Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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.

Jong-Ryul ChoiMedical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (DGMIF), Daegu 41061, Korea.
Seong-Min KimDepartment of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung 25601, Korea.
Rae-Hyung RyuLaboratory Animal Center, Daegu-Gyeongbuk Medical Innovation Foundation (DGMIF), Daegu 41061, Korea.
Sung-Phil KimDepartment of Human Factors Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea.
Jeong-Woo SohnDepartment of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung 25601, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings. Specifically, we focus on three key topics: (1) novel implantable neural probes that decrease the level of invasiveness without sacrificing performance, (2) multi-modal neural probes that measure both electrical and optical signals, (3) and neural probes developed using advanced materials. Because safety and precision are critical for practical applications of BMI systems, future studies should aim to enhance these properties when developing next-generation neural probes.

Indexed as

Brain-machine interfaceImplantable neural probesMulti-channel electrodesNeural probes with advanced materials

Identifiers

PMID30636899
PMCPMC6318554

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.