Evidence map›Paper›PMID 40987603›Full record

ReviewChemical reviews2025

Neural vs Neuromorphic Interfaces: Where Are We Standing?

Daniela Rana, Natalia Babushkina, Martina Gini, Alejandra Flores Cáceres, Hangyu Li, Vanessa Maybeck, Valeria Criscuolo, Dirk Mayer, Marcello Ienca, Simon Musall and 3 more

Abstract readReview
In one paragraph

Review in Chemical reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

13 authors.

Daniela RanaInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Natalia BabushkinaInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Martina GiniInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Alejandra Flores CáceresInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Hangyu LiInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Vanessa MaybeckInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Valeria CriscuoloInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.ORCID 0000-0001-5756-9757
Dirk MayerInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.ORCID 0000-0003-1296-8265
Marcello IencaInstitute for History and Ethics of Medicine, Technical University of Munich (TUM), Ismaniger Str. 22, Munich 81675, Germany.
Simon MusallInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Viviana Rincon MontesInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.
Andreas OffenhäusserInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.ORCID 0000-0001-6143-2702
Francesca SantoroInstitute for Biological Information Processing-Bioelectronics, IBI-3 Forschungszentrum Juelich, 52428, Germany.ORCID 0000-0001-7323-9504

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuromorphic interfaces represent a transformative frontier in neural engineering, enabling seamless communication between the nervous system and external devices through biologically inspired computing architectures. These systems offer promising avenues for diagnosing and treating neurological disorders by emulating the brain's computational strategies. Neural devices, including sensors and stimulators, monitor or modulate neural activity, playing a pivotal role in deciphering brain function and neuropathologies. Yet, clinical translation remains limited due to persistent challenges such as foreign body responses, low signal-to-noise ratios, and constraints in real-time data processing. Recent breakthroughs in neuromorphic hardware, neural recording, and stimulation technologies are addressing these challenges, paving the way for more adaptive and efficient brain-machine interfaces and neuroprosthetics. This review highlights the emerging class of neurohybrid interfaces, where neuromorphic systems might be integrated to enhance bidirectional neural communication. It emphasizes novel material strategies engineered for seamless neural interfacing and their incorporation into advanced neuromorphic chip architectures capable of real-time signal processing and closed-loop feedback. Furthermore, this review explores cutting-edge neuromorphic biointerfaces and evaluates the technological, biological, and ethical challenges involved in their clinical deployment. By bridging materials science, neuroscience, and neuromorphic engineering, these systems hold the potential to redefine the landscape of neurotechnology.

Indexed as

Brain-Computer InterfacesNeuronsAnimalsBrainHumans

Identifiers

PMID40987603
PMCPMC12512108

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.