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Related Experiment Video

Updated: Feb 8, 2026

Soft Lithographic Functionalization and Patterning Oxide-free Silicon and Germanium

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Published on: December 16, 2011

Body mass variability is represented by distinct functional connectivity patterns.

Jennifer R Sadler¹, Grace E Shearrer¹, Kyle S Burger²

¹Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, United States.

|July 4, 2018

Summary

This summary is machine-generated.

Brain connectivity patterns differ based on body mass index (BMI). Lower BMI in twins correlates with stronger prefrontal network connections, while higher BMI is linked to increased cerebellar-insula connectivity, suggesting neurobiological underpinnings of weight regulation.

Keywords:

BMI DMN Default mode network Functional connectivity Insula Obesity Satiation Striatum Twins dlPFC

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Area of Science:

Neuroscience
Obesity Research
Connectomics

Background:

Functional brain connectivity is increasingly recognized as a factor in neurocognitive processes.
Understanding weight-related differences in brain networks offers insights into obesity's underlying mechanisms.
Previous research suggests altered brain activity in individuals with obesity.

Purpose of the Study:

To investigate body mass index (BMI)-dependent differences in functional brain connectivity.
To identify specific brain networks sensitive to weight status.
To explore the relationship between weight discordance within twin pairs and functional connectivity.

Main Methods:

Analysis of Human Connectome Project data from three groups: BMI-discordant twins, BMI-matched unrelated individuals, and BMI-similar twins.
Examined between-network functional connectivity across different BMI categories.
Utilized statistical methods to identify significant differences in connectivity patterns, correcting for multiple comparisons (pFWE).

Main Results:

Three networks were sensitive to weight status: gustatory, visual, and default mode network (DMN).
In BMI-discordant twins, lower BMI was associated with stronger striatal/thalamic-prefrontal connectivity (pFWE=0.04).
Higher BMI in twins correlated with increased cerebellar-insula connectivity (pFWE=0.04).
Connectivity patterns observed in BMI-discordant twins were not present in BMI-similar twins, indicating specificity to weight discordance.

Conclusions:

Distinct functional connectivity patterns are associated with variations in body mass index.
Stronger cortical-striatal-thalamic connectivity in lower-BMI twins may support regulation of motivated behaviors.
Increased cerebellar-insula connectivity in higher-BMI twins could relate to altered satiation signaling.
These findings highlight atypical brain functioning in the accumulation and maintenance of elevated weight.