Evidence map›Paper›PMID 40125335›Full record

ArticleJournal of Alzheimer's disease reports

Study on cognitive impairment evaluation based on photoelectric neural information.

Zehua Wang, Ye Zhang, Ning Ma, Huiting Qiao, Meiyun Xia, Deyu Li

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease reports. 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

6 authors.

Zehua WangSchool of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0009-0003-2183-4274
Ye ZhangSchool of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0009-0009-1937-4815
Ning MaSchool of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0009-0000-0986-7354
Huiting QiaoSchool of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0000-0001-8772-069X
Meiyun XiaInnovation Center for Medical Engineering &Engineering Medicine, Hangzhou International Innovation Institute, Beihang University, Hangzhou, China.ORCID https://orcid.org/0000-0001-9587-6686
Deyu LiSchool of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0000-0001-7465-7433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Whether there is a cognitive load-dependent brain activation pattern in the pre-Alzheimer's disease phase is unknown. Multimodal system provides a powerful technical tool. Objective: We evaluated brain activity patterns under different cognitive loads in patients with mild cognitive impairment. Methods: Functional near-infrared spectroscopy signals and electroencephalography signals were acquired from the mild cognitive impairment group (MCI, n = 20) and the healthy control group (HC, n = 24) under four cognitive loads. We analyzed the respective brain activity features and performed correlation analyses. Results: (1) During the encoding phase, both the left occipital ( Conclusions: The pattern of brain activity in MCI depends on cognitive load. Left occipital and left temporal may be important brain regions for evaluating MCI and need to be focused on in the future.

Indexed as

Alzheimer's diseasebrain networkelectroencephalographyfunctional near-infrared spectroscopy

Identifiers

PMID40125335
PMCPMC11930469

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.