EEG Functional Network Resilience During VR-Induced Emotional States

Min Jae Lee's research data, uploaded to figshare in April 2026, examines the topological resilience of brain networks. The dataset likely contains graph-theoretical measures of EEG-based functional connectivity across six frequency bands, derived from participants experiencing negative, neutral, and positive emotional states induced by virtual reality. Resilience was assessed by simulating targeted attacks and random failures on the networks.

Use Cases

• Analyzing emotion-specific resilience profiles in brain networks based on graph-theoretical measures mentioned in the description
• Training models to classify emotional states based on EEG functional connectivity features across six frequency bands
• Benchmarking network robustness algorithms using simulated targeted attacks and random failures on functional architectures
• Investigating the relationship between high gamma band activity and network robustness during negative emotional states

Strengths

• Data is derived from a controlled experimental framework using VR for emotion induction
• Analysis includes six distinct EEG frequency bands from delta to high gamma
• Network resilience is quantified using two complementary simulation approaches: targeted attacks and random failures

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The primary data file is a 3.1 MB DOCX document, which may not be a standard data format for direct analysis

Provenance

Source

figshare, author Min Jae Lee

Collection Method

EEG data collected during VR-induced emotional states, with functional connectivity computed using coherence and graph-theoretical measures applied.

Time Range

null

Freshness

Last updated 2026-04-10 05:29:19

Geography

null