Brain Functional Network Dynamics and BMI in 776 Young Adults

Resting-state fMRI data from 776 healthy young adults, analyzed to characterize the relationship between body mass index (BMI) and dynamic brain network properties. The dataset includes derived metrics on recurring functional connectivity states and the temporal variability of topological properties. It was authored by Xiaoyang Xin and last updated on April 14, 2026.

Use Cases

• Modeling the relationship between BMI and whole-brain functional connectivity state dynamics based on fractional window and mean dwell time metrics.
• Analyzing regional brain network efficiency in relation to BMI based on temporal variability of nodal and local efficiency.
• Investigating visual network connectivity patterns as a potential biomarker for higher BMI based on the described state characteristics.

Strengths

• Data from 776 healthy young adults provides a substantial sample size for analysis.
• Includes derived dynamic functional connectivity metrics, such as recurring states and temporal variability of topological properties.
• Released under a permissive CC-BY-4.0 license.

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 2.8 MB DOCX document, which may not be a standard format for structured data analysis.

Provenance

Source

figshare, author Xiaoyang Xin

Collection Method

Analysis of resting-state fMRI data using independent component analysis and a sliding-window approach.

Time Range

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Freshness

Last updated 2026-04-14 04:20:52; freshness should be verified.

Geography

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