Resting-State fMRI Data for Emotional Intelligence Analysis

Data from Weigang Pan's 2020 study uses resting-state fMRI to investigate associations between emotional intelligence (EI) and the amplitude of low-frequency fluctuations (ALFFs) in a large sample of young, healthy adults. The dataset provides neuroimaging evidence linking EI to activity in the social emotional processing and cognitive control brain networks.

Use Cases

• Correlate amplitude of low-frequency fluctuations (ALFFs) with emotional intelligence scores to identify neural substrates.
• Analyze ALFF patterns in specific brain regions like the fusiform gyrus and bilateral pre-SMA to model emotion perception and control components.
• Use resting-state fMRI data from a large sample of young adults to validate network models of social emotional processing.

Strengths

• Data originates from a peer-reviewed study published in 2020, providing a scientific foundation.
• Focuses on a large sample of young, healthy adults, offering a specific demographic cohort.
• Investigates associations between EI and ALFFs in key nodes of two distinct brain networks.

Limitations

• Specific data structure, row count, column count, and file formats are unknown from the input.
• The dataset is temporally static with a last update in 2020, lacking ongoing updates.
• Geographic and demographic coverage is limited to a specific sample of young, healthy adults.

Provenance

Source

Weigang Pan via Dryad.

Collection Method

Resting-state fMRI scans used to measure amplitude of low-frequency fluctuations (ALFFs) in a large sample of young, healthy adults.

Freshness

Last updated 2020-06-24.