ArticleAIMS neuroscience2023
Electroencephalography and mild cognitive impairment research: A scoping review and bibliometric analysis (ScoRBA).
Article in AIMS neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Functional and effective EEG connectivity patterns in Alzheimer's disease and mild cognitive impairment: a systematic review.Frontiers in aging neuroscience · 2025Pooled it
- [Advances in research on neuroelectrophysiological characteristics of post-stroke cognitive impairment based on quantitative electroencephalography and acupuncture interventions].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Review
- A Precision Computational Framework for sLORETA Neurofeedback in Mild Cognitive Impairment: Integration of qEEG Biomarkers and Neuropsychological Metrics.International journal of environmental research and public health · 2026Article
- Resting-state EEG microstates link neural dynamics to fluid intelligence in mild cognitive impairment.Frontiers in aging neuroscience · 2026Article
- The application of traditional machine learning and deep learning with EEG for mild cognitive impairment: a bibliometric analysis.Frontiers in aging neuroscience · 2026Article
- Alzheimer's Disease and Epilepsy: Exploring Shared Pathways and Promising Biomarkers for Future Treatments.Journal of clinical medicine · 2024Review
- From Gut Microbiota to Brain Waves: The Potential of the Microbiome and EEG as Biomarkers for Cognitive Impairment.International journal of molecular sciences · 2024Review
- Neurophysiological markers of early cognitive decline in older adults: a mini-review of electroencephalography studies for precursors of dementia.Frontiers in aging neuroscience · 2024Review
- An EEG-based framework for automated discrimination of conversion to Alzheimer's disease in patients with amnestic mild cognitive impairment: an 18-month longitudinal study.Frontiers in aging neuroscience · 2024Article
- Can auditory processing dysfunction indicate early cognitive decline?Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) and early diagnosis may help improve treatment effectiveness. To identify accurate MCI biomarkers, researchers have utilized various neuroscience techniques, with electroencephalography (EEG) being a popular choice due to its low cost and better temporal resolution. In this scoping review, we analyzed 2310 peer-reviewed articles on EEG and MCI between 2012 and 2022 to track the research progress in this field. Our data analysis involved co-occurrence analysis using VOSviewer and a Patterns, Advances, Gaps, Evidence of Practice, and Research Recommendations (PAGER) framework. We found that event-related potentials (ERP), EEG, epilepsy, quantitative EEG (QEEG), and EEG-based machine learning were the primary research themes. The study showed that ERP/EEG, QEEG, and EEG-based machine learning frameworks provide high-accuracy detection of seizure and MCI. These findings identify the main research themes in EEG and MCI and suggest promising avenues for future research in this field.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.