Evidence map›Paper›PMID 41766383›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2026

Monolithic 3D Nanoelectrode Arrays on CMOS Circuitry for Scalable, High-Resolution Neural Recording.

Aziliz Lecomte, Laurent Mazenq, Marie-Charline Blatché, Aurélie Lecestre, Guilhem Larrieu

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 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

5 authors.

Aziliz LecomteLAAS-CNRS, Université De Toulouse, CNRS, Toulouse, France.
Laurent MazenqLAAS-CNRS, Université De Toulouse, CNRS, Toulouse, France.
Marie-Charline BlatchéLAAS-CNRS, Université De Toulouse, CNRS, Toulouse, France.
Aurélie LecestreLAAS-CNRS, Université De Toulouse, CNRS, Toulouse, France.
Guilhem LarrieuLAAS-CNRS, Université De Toulouse, CNRS, Toulouse, France.ORCID https://orcid.org/0000-0001-5157-2277

Funding

European Commission 863245
6 · The paper itself

Abstract

Understanding brain function and neurodegenerative disorders, and accelerating preclinical drug development, demand neural interfaces that combine nanoscale sensitivity with high-resolution, large-scale recording capability. Here, we present a monolithically integrated high-density nanoelectrode array (HD-NEA) featuring vertical high-aspect ratio nanowire electrodes embedded within the back-end-of-line of commercial CMOS circuitry. Using a low-temperature (<400 °C), wafer-scale post-fabrication strategy, we decouple nanostructure formation from circuit integration while preserving CMOS functionality. The resulting 3D array, comprising 26,400 electrodes, achieves high yield and uniformity across 4-in. wafers. When interfaced with in vitro cortical neurons, the HD-NEA yields significantly higher spike amplitudes and signal-to-noise ratios than planar microelectrodes, without requiring electroporation. High-resolution spike mapping revealed steeper spatial signal decay, consistent with closer neuron-nanowires coupling, and enabled the detection of distinct waveform morphologies including putative dendritic signals. These results position HD-NEA as a scalable and CMOS-compatible nanobiointerface, enabling high-fidelity neural recording for neuroscience research, brain-machine interfacing, and bioelectronic diagnostics.

Indexed as

NanotechnologyNeuronsSemiconductorsAction PotentialsAnimalsMicroelectrodesNanowiresbioelectronicshigh‐resolution electrophysiologyin vitro neuronal interfacesmonolithic CMOS integrationnanoelectrode arrays

Identifiers

PMID41766383
PMCPMC13089090

What Socratic 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 Socratic graph.