Evidence map›Paper›PMID 42473571›Full record

ArticleHardwareX2026

A low-cost, 3D-printed open-source platform for acute brain slice electrophysiology.

Younsoo Byun, Hyunjun Noh, Sung-Han Rhim, Jihyun Noh

Abstract read
In one paragraph

Article in HardwareX, 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

4 authors.

Younsoo ByunDepartment of Science Education, Dankook University, Yongin 16890, Republic of Korea.
Hyunjun NohDepartment of Mechanical Engineering, Dankook University, Yongin 16890, Republic of Korea.
Sung-Han RhimDepartment of Mechanical Engineering, Dankook University, Yongin 16890, Republic of Korea.
Jihyun NohDepartment of Science Education, Dankook University, Yongin 16890, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain slice electrophysiology is a widely used approach for investigating synaptic physiology, network activity, and pharmacological responses. However, the high cost of commercial recording chambers and perfusion systems restricts accessibility in resource-limited laboratories. Here, we describe the design, fabrication, and electrophysiological validation of a fully integrated, open-source field recording platform for acute brain slice electrophysiology. The system comprises three independently assembled modules: a submerged recording chamber, a tissue-positioning stage, and a suction assembly, all fabricated via FDM (Fused Deposition Modeling) 3D printer using PLA (Polylactic Acid) filaments at a total material cost of approximately 1.23 USD. The platform was validated using acute hippocampal slices from adult male C57BL/6N mice. Field excitatory postsynaptic potential recordings from the CA3-CA1 Schaffer collateral pathway demonstrated high-fidelity signals and reproducible stimulus-response relationships, alongside stable 15-minute baselines. Thermal characterization confirmed uniform perfusate distribution and rapid temperature equilibration within the chamber bath. All design files and assembly instructions are openly available, with the hardware design files released under the CERN-OHL-S-2.0 license and the documentation under a CC BY 4.0 license, enabling straightforward replication by the broader neuroscience community.

Indexed as

Additive manufacturingBrain slice electrophysiologyField recordingHippocampusLow-cost instrumentationOpen-source hardware

Identifiers

PMID42473571
PMCPMC13380772

What OpenQuestion 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 OpenQuestion graph.