Resting-State EEG Microstates and Cognitive Scores for 60 MCI and Healthy Control Subjects

A dataset of 60 adults (30 with Mild Cognitive Impairment and 30 healthy controls) with resting-state EEG microstate parameters and cognitive test scores. The data includes Global Explained Variance, duration, occurrence, and coverage for seven canonical microstate classes (A–G) and scores from the MMSE, MoCA, Raven’s Progressive Matrices, and Benton Facial Recognition Test. It was authored by Ceyhun Sayman and last updated in May 2026.

Use Cases

• Correlating EEG microstate dynamics with fluid intelligence scores based on Raven's Progressive Matrices.
• Comparing neural network activity between MCI patients and healthy controls based on microstate Global Explained Variance.
• Investigating associations between specific microstate classes (e.g., B and C) and executive function based on MoCA scores.
• Developing predictive models for cognitive status using temporal microstate parameters like occurrence and coverage.

Strengths

• Includes data from 60 subjects with a balanced case-control design (30 MCI, 30 HC).
• Provides multiple validated cognitive assessments (MMSE, MoCA, RPM, BFRT) per subject.
• Reports statistically significant group differences in microstate parameters (e.g., GEV for microstate B: ≈11.3% vs. 7.9%).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (18.0 KB), indicating limited scope, likely containing summary statistics rather than raw time-series data.

Provenance

Source

Ceyhun Sayman via figshare.

Collection Method

Resting-state, eyes-closed EEG recordings analyzed with Metamaps2023 templates to derive microstate parameters; cognitive assessments administered clinically.

Freshness

Last updated 2026-05-20 05:50:18; freshness should be verified.