Evidence map›Paper›PMID 41133115›Full record

ArticleJournal of biomedical optics2025

Optogenetically enhanced physical reservoir computing with

Yin Deng, Jie Li, Yarong Lin, Zeying Lu, Lili Gui, Longze Sha, Xiaojuan Sun, Yueheng Lan, Qi Xu, Kun Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of biomedical optics, 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. Online supervised learning of temporal patterns in biological neural networks under feedback control.Proceedings of the National Academy of Sciences of the United States of America · 2026
    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

10 authors.

Yin DengBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.
Jie LiBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.
Yarong LinChinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Beijing, China.
Zeying LuBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.
Lili GuiBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.ORCID https://orcid.org/0000-0002-3710-6330
Longze ShaChinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Beijing, China.
Xiaojuan SunBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.
Yueheng LanBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.
Qi XuChinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Beijing, China.
Kun XuBeijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: The effects of optogenetic stimulation (OS) on Aim: We aim to utilize optogenetically controlled Approach: We presented an all-optical biological reservoir computing framework that leverages optogenetics and calcium imaging to precisely regulate and record neuronal activities. A closed-loop system was developed incorporating the FORCE learning algorithm, which guided a virtual car through obstacle avoidance tasks. Results: The system demonstrated high accuracy and efficiency in navigating obstacles, achieving optimal performance after Conclusions: The results highlight the potential of optogenetically controlled biological neural networks in neuro-robotic systems, showcasing their capability to achieve accurate and efficient obstacle avoidance through physical reservoir computing.

Indexed as

Neural Networks, ComputerOptogeneticsAlgorithmsAnimalsNeuronsRoboticsneural networksoptogenetic stimulationreservoir computing

Identifiers

PMID41133115
PMCPMC12543164

What OpenQuestion holds

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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.