Evidence map›Paper›PMID 36010801›Full record

ArticleEntropy (Basel, Switzerland)2022

Spatio-Temporal Dynamics of Entropy in EEGS during Music Stimulation of Alzheimer's Disease Patients with Different Degrees of Dementia.

Tingting Wu, Fangfang Sun, Yiwei Guo, Mingwei Zhai, Shanen Yu, Jiantao Chu, Chenhao Yu, Yong Yang

Open access · goldAbstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 24% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Is EEG Entropy a Useful Measure for Alzheimer's Disease?Actas espanolas de psiquiatria · 2024
    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

8 authors at 1 institution in 1 country.

Tingting WuSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Fangfang SunSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-6005-1104
Yiwei GuoSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Mingwei ZhaiSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-4876-0362
Shanen YuSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Jiantao ChuSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Chenhao YuSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Yong YangSchool of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Hangzhou Dianzi University · CN

Funding

Fundamental Research Funds for the Provincial Universities of Zhejiang GK209907299001-005National Natural Science Foundation of China no.81671038,81171251 and 81871071
6 · The paper itself

Abstract

Music has become a common adjunctive treatment for Alzheimer’s disease (AD) in recent years. Because Alzheimer’s disease can be classified into different degrees of dementia according to its severity (mild, moderate, severe), this study is to investigate whether there are differences in brain response to music stimulation in AD patients with different degrees of dementia. Seventeen patients with mild-to-moderate dementia, sixteen patients with severe dementia, and sixteen healthy elderly participants were selected as experimental subjects. The nonlinear characteristics of electroencephalogram (EEG) signals were extracted from 64-channel EEG signals acquired before, during, and after music stimulation. The results showed the following. (1) At the temporal level, both at the whole brain area and sub-brain area levels, the EEG responses of the mild-to-moderate patients showed statistical differences from those of the severe patients (p < 0.05). The nonlinear characteristics during music stimulus, including permutation entropy (PmEn), sample entropy (SampEn), and Lempel−Ziv complexity (LZC), were significantly higher in both mild-to-moderate patients and healthy controls compared to pre-stimulation, while it was significantly lower in severe patients. (2) At the spatial level, the EEG responses of the mild-to-moderate patients and the severe patients showed statistical differences (p < 0.05), showing that as the degree of dementia progressed, fewer pairs of EEG characteristic showed significant differences among brain regions under music stimulation. In this paper, we found that AD patients with different degrees of dementia had different EEG responses to music stimulation. Our study provides a possible explanation for this discrepancy in terms of the pathological progression of AD and music cognitive hierarchy theory. Our study has adjunctive implications for clinical music therapy in AD., potentially allowing for more targeted treatment. Meanwhile, the variations in the brains of Alzheimer’s patients in response to music stimulation might be a model for investigating the neural mechanism of music perception.

Indexed as

Alzheimer’s diseasedifferent degree of dementiaEEGmusic stimulationpermutation entropy

Identifiers

PMID36010801
PMCPMC9407451
OpenAlexW4292265099

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.