Social Brain Volume and In-Degree Network Size in Older Adults

Neuroimaging and social network data from a study of older adults in a village-wide global network. It was used to investigate associations between regional brain volumes (e.g., orbitofrontal cortex, dorsomedial prefrontal cortex) and in-degree social network size, a measure of social ties identified by others. The dataset was authored by Seyul Kwak and published in 2020.

Use Cases

• Analyze the correlation between in-degree network size and regional gray matter volume in the orbitofrontal cortex.
• Compare brain volume patterns associated with in-degree size versus out-degree size to study self-perceived versus peer-reported social connectedness.
• Use meta-analytic reverse inference to explore how the regional volume pattern for in-degree size relates to social inference ability.
• Investigate the social brain hypothesis by examining associations between social network metrics and volumes of the dorsomedial prefrontal cortex and lingual gyrus.

Strengths

• Data is derived from a global social network of an entire village, providing a complete sociocentric context.
• Study findings were published in 2020, offering relatively recent neuroimaging and social network data.
• Dataset includes specific brain region volumes (e.g., orbitofrontal cortex) linked to a defined social metric (in-degree size).

Limitations

• Sample size and number of rows are unknown, limiting assessment of statistical power.
• Specific columns, file formats, and data size are not provided, complicating usability evaluation.
• Geographic and demographic scope is limited to a single village of older adults, reducing generalizability.

Provenance

Source

dryad

Collection Method

Data collected from neuroimaging and social network analysis of an entire village population.

Freshness

Last updated on 2020-06-24.

Geography

A single village (specific location unknown).