Evidence map›Paper›PMID 37383823›Full record

ArticleData in brief2023

Brain electrophysiological recording during olfactory stimulation in mild cognitive impairment and Alzheimer disease patients: An EEG dataset.

Mohammad Javad Sedghizadeh, Hamid Aghajan, Zahra Vahabi

Open access · goldAbstract read
In one paragraph

Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Mohammad Javad SedghizadehDepartment of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
Hamid AghajanDepartment of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
Zahra VahabiDepartment of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Sharif University of Technology · IRRoozbeh Hospital · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dataset presented in this article contains preprocessed cleaned electroencephalography (EEG) recording from 35 participants including 13 Alzheimer's disease (AD) patients, 7 amnestic mild cognitive impairment (aMCI) patients, and 15 healthy elderly. All participants performed the same olfactory task which consisted of 120 trials of 2 s olfactory stimulation and 8 s rest (no odorant). The olfactory stimulation consisted of rose and lemon odorants. Odor trials were presented randomly with a probability of 0.75 presenting lemon and 0.25 presenting rose. The impedance of the electrodes was kept under 15 KΩ during the experiment. The data was filtered from 0.5 to 40 Hz using a bandpass filter and epoched from 1 s pre-stimulus to 2 s post-stimulus. Artifacts related to eye blinks were removed by running independent component analysis (ICA) and the remaining noisy trials were identified by eye and removed from further analysis. Mini Mental State Examination (MMSE) test scores for all participants are also provided in the dataset. Olfactory dysfunction has been shown to be associated with neurodegenerative diseases such as dementia and Alzheimer's disease. Therefore, studying the response of the olfactory system may lead to identifying early biomarkers for related brain disorders.

Indexed as

Alzheimer's diseaseBrain oscillationsElectroencephalogramMild cognitive impairmentNeurodegenerative diseaseOdorantOlfactory stimulationSensory system

Identifiers

PMID37383823
PMCPMC10294047
OpenAlexW4379260156

What OpenQuestion 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 OpenQuestion graph.