Evidence map›Paper›PMID 34890232›Full record

ArticleScience advances2021

Organic neuromorphic electronics for sensorimotor integration and learning in robotics.

Imke Krauhausen, Dimitrios A Koutsouras, Armantas Melianas, Scott T Keene, Katharina Lieberth, Hadrien Ledanseur, Rajendar Sheelamanthula, Alexander Giovannitti, Fabrizio Torricelli, Iain Mcculloch and 4 more

Abstract read
In one paragraph

Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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  5. Review
  6. Article
  7. Article
  8. Article
  9. Performance-Recoverable Closed-Loop Neuroprosthetic System.Advanced materials (Deerfield Beach, Fla.) · 2025
    Article
  10. Brain-Inspired Polymer Dendrite Networks for Morphology-Dependent Computing Hardware.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  20. Article
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

14 authors.

Imke KrauhausenMax Planck Institute for Polymer Research, Mainz, Germany.ORCID 0000-0001-5633-389X
Dimitrios A KoutsourasMax Planck Institute for Polymer Research, Mainz, Germany.ORCID 0000-0002-9456-9630
Armantas MelianasDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-3443-0987
Scott T KeeneDepartment of Engineering, University of Cambridge, Cambridge, UK.ORCID 0000-0002-6635-670X
Katharina LieberthMax Planck Institute for Polymer Research, Mainz, Germany.ORCID 0000-0001-6160-7162
Hadrien LedanseurMax Planck Institute for Polymer Research, Mainz, Germany.
Rajendar SheelamanthulaKAUST Solar Center, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.ORCID 0000-0001-5223-9580
Alexander GiovannittiDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-4778-3615
Fabrizio TorricelliDepartment of Information Engineering, University of Brescia, 25123 Brescia, Italy.ORCID 0000-0002-7932-0677
Iain MccullochKAUST Solar Center, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.ORCID 0000-0002-6340-7217
Paul W M BlomMax Planck Institute for Polymer Research, Mainz, Germany.ORCID 0000-0002-6474-9497
Alberto SalleoDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-7448-9123
Yoeri van de BurgtMicrosystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0003-3472-0148
Paschalis GkoupidenisMax Planck Institute for Polymer Research, Mainz, Germany.ORCID 0000-0002-0139-0851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In living organisms, sensory and motor processes are distributed, locally merged, and capable of forming dynamic sensorimotor associations. We introduce a simple and efficient organic neuromorphic circuit for local sensorimotor merging and processing on a robot that is placed in a maze. While the robot is exposed to external environmental stimuli, visuomotor associations are formed on the adaptable neuromorphic circuit. With this on-chip sensorimotor integration, the robot learns to follow a path to the exit of a maze, while being guided by visually indicated paths. The ease of processability of organic neuromorphic electronics and their unconventional form factors, in combination with education-purpose robotics, showcase a promising approach of an affordable, versatile, and readily accessible platform for exploring, designing, and evaluating behavioral intelligence through decentralized sensorimotor integration.

Identifiers

PMID34890232
PMCPMC8664264

What OpenQuestion 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 OpenQuestion graph.