↓ Skip to main content

Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult

Overview of attention for article published in Frontiers in Aging Neuroscience, May 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
10 X users

Readers on

mendeley
68 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult
Published in
Frontiers in Aging Neuroscience, May 2015
DOI 10.3389/fnagi.2015.00070
Pubmed ID
Authors

Brielle M. Paolini, Paul J. Laurienti, Sean L. Simpson, Jonathan H. Burdette, Robert G. Lyday, W. Jack Rejeski

Abstract

Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of WL.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Netherlands 1 1%
United States 1 1%
Unknown 65 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 15%
Student > Doctoral Student 9 13%
Researcher 8 12%
Student > Bachelor 5 7%
Student > Master 5 7%
Other 13 19%
Unknown 18 26%
Readers by discipline Count As %
Psychology 13 19%
Medicine and Dentistry 8 12%
Neuroscience 6 9%
Sports and Recreations 4 6%
Nursing and Health Professions 3 4%
Other 10 15%
Unknown 24 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 July 2015.
All research outputs
#5,212,748
of 25,182,110 outputs
Outputs from Frontiers in Aging Neuroscience
#2,662
of 5,439 outputs
Outputs of similar age
#60,823
of 270,426 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#40
of 64 outputs
Altmetric has tracked 25,182,110 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,439 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 270,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.