Evidence mapPaperPMID 41345143Full record

ArticleScientific reports2025

Revealing neural resonance in neuronal ensembles through frequency response tests.

Peng Zhang, Liuye Yao, Tianyi Yang, Yajun Lou, Wei Xu, Wei Jiang, Weitao Li, Xiaofei Ji, Fan Gao, Zhiyu Qian

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

10 authors.

Peng ZhangDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Liuye YaoDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Tianyi YangDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Yajun LouDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Wei XuDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Wei JiangDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Weitao LiDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Xiaofei JiDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China. jinxiaofei@nuaa.edu.cn.
Fan GaoDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China. gfbme@nuaa.edu.cn.
Zhiyu QianDepartment of Biomedical Engineering, Key Laboratory of Multi-modal Brain-Computer Precision Drive Ministry of Industry and Information Technology, Key Laboratory of Digital Medical Equipment and Technology of Jiangsu Province, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China. zhiyubme@163.com.

Funding

Fundamental Research Funds for the Central Universities NZ2024032Jiangsu Funding Program for Excellent Postdoctoral Talent 2024ZB661Key Project of Nanjing Health Science and Technology Development Special Fund ZKX24043National Natural Science Foundation of China 82151311Natural Science Foundation of Jiangsu Province BK20210531
6 · The paper itself

Abstract

Photobiomodulation emerges as a novel method to boost neuronal activities and brain function, with notable implications for treating brain disorders. Yet, the mechanisms and optimal frequency parameters of transcranial photobiomodulation are still unclear, which highlights a research gap in understanding how different stimulation frequencies affect neural responses. This study proposes a hypothesis that the nervous system exhibits resonance phenomena, suggesting that external stimuli near the system's resonant frequency trigger the strongest responses. We tested this by performing frequency response tests with pulsed transcranial near-infrared light (10-200 Hz) on mouse brains, monitoring neural responses across frequencies by analyzing cerebral blood flow, concentration of oxygenated hemoglobin, and neurophysiological activity in both cortical and deep brain regions. Our results reveal pronounced neural responses in cortical and deep brain areas at 60-80 Hz and 120-140 Hz, suggesting the potential existence of neural system resonance. Conceptually, the neural system appears to be modulatable by external stimuli, reaching maximal neural response when the stimulation frequency aligns with the system's resonant frequency, leading to neural resonance. These findings will expect to become guide new theoretical frameworks and strategies for neural modulation and therapeutic interventions.

Indexed as

BrainNeuronsAnimalsCerebrovascular CirculationMaleMiceMice, Inbred C57BLNear-infrared lightNeural resonanceNeuromodulationPhotobiomodulation

Identifiers

PMID41345143
PMCPMC12680619

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.