Evidence map›Paper›PMID 40739714›Full record

ReviewInternational journal of stem cells2025

Beyond Structure: Next-Generation Electrophysiological Platforms for Functional Brain Organoids.

Ji-Hyoung Cha, Keuntae Kim, Il-Joo Cho

Abstract readReview
In one paragraph

Review in International journal of stem cells, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Ji-Hyoung ChaDepartment of Convergence Medicine, College of Medicine, Korea University, Seoul, Korea.ORCID https://orcid.org/0000-0001-8126-067X
Keuntae KimDepartment of Convergence Medicine, College of Medicine, Korea University, Seoul, Korea.ORCID https://orcid.org/0000-0003-3787-7431
Il-Joo ChoDepartment of Convergence Medicine, College of Medicine, Korea University, Seoul, Korea.ORCID https://orcid.org/0000-0001-9016-6749

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain organoids have emerged as transformative models for studying human neurodevelopment, neurological disorders, and personalized therapeutics. Central to their utility is the ability to monitor neural activity with high spatial and temporal resolution. Traditional electrophysiological tools-such as planar microelectrode arrays and patch-clamp techniques-offer limited access to the three-dimensional and dynamic nature of organoid neural networks. Recent technological advancements have led to the development of next-generation platforms including surface-embedded, flexible, and fully implantable electrodes. Moreover, multifunctional probes incorporating optical, chemical, and mechanical sensing open new avenues for multimodal interrogation of organoid physiology. This review summarizes the current state of electrophysiological technologies applied to brain organoids, highlighting innovations in recording fidelity, spatiotemporal resolution, and device-tissue integration. We also discuss key challenges such as maintaining organoid viability, achieving sufficient electrode density, and enabling non-disruptive, chronic interfacing throughout organoid development. Looking forward, future systems are expected to evolve toward ultra-dense, multimodal, and closed-loop interfaces capable of investigating organoid function throughout extended growth periods. These advances will not only deepen our understanding of brain-like activity in organoids but also support the design of more functionally accurate and translationally relevant neural models.

Indexed as

BrainElectrophysiologyImplantable electrodesNeural interface technologyOrganoids

Identifiers

PMID40739714
PMCPMC12394082

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.