Alterations of the salience network in obesity: A resting‐state fMRI study
Open accessAbstract
Obesity is a major health problem in modern societies. It has been related to abnormal functional organization of brain networks believed to process homeostatic (internal) and/or salience (external) information. This study used resting‐state functional magnetic resonance imaging analysis to delineate possible functional changes in brain networks related to obesity. A group of 18 healthy adult participants with obesity were compared with a group of 16 lean participants while performing a resting‐state task, with the data being evaluated by independent component analysis. Participants also completed a neuropsychological assessment. Results showed that the functional connectivity strength of the putamen nucleus in the salience network was increased in the obese group. We speculate that this abnormal activation may contribute to overeating through an imbalance between autonomic processing and reward processing of food stimuli. A correlation was also observed in obesity between activation of the putamen nucleus in the salience network and mental slowness, which is consistent with the notion that basal ganglia circuits modulate rapid processing of information. Hum Brain Mapp 34:2786–2797, 2013. © 2012 Wiley Periodicals, Inc.
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In obesity, the salience network integrates salient information to make decisions regarding food intake and, together with the executive control network, inhibits reward impulses.
“In obesity, the salience network integrates salient information to make decisions regarding food intake 92, 93, 94, 95 and, together with the executive control network, inhibits reward impulses 96, 97.”
From History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity (2019) · cites this paper as [93]
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- Authors
- García‐García, I., Jurado, M. Á., Garolera, M., Segura, B., Sala‐Llonch, R., Marqués‐Iturria, I., Pueyo, R., Sender‐Palacios, M. J., Vernet‐Vernet, M., Narberhaus, A., Ariza, M., & Junqué, C.
- Affiliations
- Universitat de Barcelona (ES)
- Department of Psychiatry and Clinical Psychobiology University of Barcelona Barcelona Spain
- Hospital Terrassa (ES)
- CAP Terrassa Nord Consorci Sanitari de Terrassa Terrassa Spain
- Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES)
- ORCID
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2012-04-21
- Volume
- 34
- Issue
- 11
- Pages
- 2786-2797
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- PMC
- PMC6870073
- OpenAlex
- W1529341520
- Cited by
- 200
- References
- 79
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 12 · 2023: 11 · 2022: 19 · 2021: 16 · 2020: 18 · 2019: 15 · 2018: 16 · 2017: 17 · 2016: 15 · 2015: 20 · 2014: 11 · 2013: 8 · 2012: 5
- FWCI
- 7.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Human Brain Mapping (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Generalitat de Catalunya (FI-DGR 2011)
- Ministerio de Ciencia e Innovación
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
- Keywords
- obesity, salience network, putamen, functional connectivity, resting-state brain networks, overeating, basal ganglia, independent component analysis
- MeSH terms
- Adolescent, Adult, Body Composition, Brain Mapping, Cognition, Data Interpretation, Statistical, Female, Homeostasis, Humans, Hunger, Image Processing, Computer-Assisted, Limbic System, Magnetic Resonance Imaging, Male, Memory, Mental Processes, Nerve Net, Neural Pathways, Neuropsychological Tests, Obesity, Psychomotor Performance, Putamen, Regression Analysis, Verbal Learning, Body Mass Index, Principal Component Analysis, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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