Evidence map›Paper›PMID 42345861›Full record

ReviewBiosensors2026

Microelectrode Arrays Technology for Brain-on-a-Chip Applications.

Mingda Zhao, Yuxing Zhang, Yibo Wang, Hui Liu, Mingxiao Li, Yang Zhao, Lingqian Zhang, Chengjun Huang

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mingda ZhaoInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.ORCID 0009-0004-3368-3490
Yuxing ZhangInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
Yibo WangInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
Hui LiuInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.
Mingxiao LiInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0002-4150-3080
Yang ZhaoInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0002-5616-7809
Lingqian ZhangInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0003-1922-834X
Chengjun HuangInstitute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0003-4942-5432

Funding

National Natural Science Foundation of China No. 62574217
6 · The paper itself

Abstract

Brain-on-a-chip (BOC) refers to a miniaturized in vitro platform that integrates living neuronal networks on a micro-engineered chip, enabling the simulation of brain functions, neural activities and physiological responses. BOC technology is an advanced evolution of microphysiological systems (MPS) and Lab-on-a-Chip platforms, providing novel paradigms for in vitro modeling and exploring early-stage biocomputing by interfacing living neural networks with engineered electronics. Microelectrode arrays (MEAs) serve as the critical physical interface for bidirectional communication in these systems. In this review, we systematically examine the technological landscape and engineering requirements of MEAs tailored for BOC applications, evaluating them across electrical characteristics, structural properties, and biocompatibility. Two primary classes of current MEA technologies, including planar arrays for 2D neural cultures and 3D flexible arrays for brain organoids, are discussed in detail. We highlight the transition from passive planar electrodes to high-density active CMOS and TFT-based arrays, and detail how 3D flexible MEAs utilize endogenous integration and exogenous wrapping strategies to overcome tissue-mechanics mismatches. Furthermore, the integration of MEAs with microfluidics, optoelectronics, and electrochemical sensors to enable multimodal monitoring is explored. With the advantages of the various MEAs, the application of MEAs for BOC, particularly in biological computing and network plasticity research, is discussed. Finally, future technological developments in scalability bottlenecks, chronic stability, and the incorporation of artificial intelligence for MEAs of BOC are prospected.

Indexed as

Biosensing TechniquesBrainLab-On-A-Chip DevicesAnimalsHumansMicroelectrodesMicrophysiological SystemsNeuronsbioelectronicsbiosensorsbrain-on-a-chip (BOC)microelectrode arrays (MEAs)organoid intelligence

Identifiers

PMID42345861
PMCPMC13296383

What Socratic holds

Textmetadata
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 Socratic graph.