Evidence map›Paper›PMID 38846893›Full record

ReviewAnnals of medicine and surgery (2012)2024

Microengineered neuronal networks: enhancing brain-machine interfaces.

Burhan Kantawala, Ali Emir Hamitoglu, Lea Nohra, Hassan Abdullahi Yusuf, Kirumira Jonathan Isaac, Sanobar Shariff, Abubakar Nazir, Kevin Soju, Konstantin Yenkoyan, Magda Wojtara and 1 more

Abstract readReview
In one paragraph

Review in Annals of medicine and surgery (2012), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Burhan KantawalaOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Ali Emir HamitogluOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Lea NohraOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Hassan Abdullahi YusufOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Kirumira Jonathan IsaacOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Sanobar ShariffOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Abubakar NazirOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Kevin SojuOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Konstantin YenkoyanNeuroscience Laboratory, Cobrain Centre, Yerevan State Medical University named after Mkhitar Heratsi, Yerevan, Armenia.
Magda WojtaraOli Health Magazine Organization, Research and Education, Kigali, Rwanda.
Olivier UwishemaOli Health Magazine Organization, Research and Education, Kigali, Rwanda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain-machine interface (BMI), a crucial conduit between the human brain and computers, holds transformative potential for various applications in neuroscience. This manuscript explores the role of micro-engineered neuronal networks (MNNs) in advancing BMI technologies and their therapeutic applications. As the interdisciplinary collaboration intensifies, the need for innovative and user-friendly BMI technologies becomes paramount. A comprehensive literature review sourced from reputable databases (PubMed Central, Medline, EBSCOhost, and Google Scholar) aided in the foundation of the manuscript, emphasizing the pivotal role of MNNs. This study aims to synthesize and analyze the diverse facets of MNNs in the context of BMI technologies, contributing insights into neural processes, technological advancements, therapeutic potentials, and ethical considerations surrounding BMIs. MNNs, exemplified by dual-mode neural microelectrodes, offer a controlled platform for understanding complex neural processes. Through case studies, we showcase the pivotal role of MNNs in BMI innovation, addressing challenges, and paving the way for therapeutic applications. The integration of MNNs with BMI technologies marks a revolutionary stride in neuroscience, refining brain-computer interactions and offering therapeutic avenues for neurological disorders. Challenges, ethical considerations, and future trends in BMI research necessitate a balanced approach, leveraging interdisciplinary collaboration to ensure responsible and ethical advancements. Embracing the potential of MNNs is paramount for the betterment of individuals with neurological conditions and the broader community.

Indexed as

brain–machine interface (BMI)devicesdisordersethicsmicroengineered neuronal networks (MNNs)neurologytherapeutics

Identifiers

PMID38846893
PMCPMC11152794

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.