ArticleSocial cognitive and affective neuroscience2020
Multivariate neural signatures for health neuroscience: assessing spontaneous regulation during food choice.
Article in Social cognitive and affective neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06263452 (Beta-Blocker Influences on Inflammatory and Neural Responses to Stress), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Beta-Blocker Influences on Inflammatory and Neural Responses to Stress
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Cognitive reappraisal of food craving and emotions: a coordinate-based meta-analysis of fMRI studies.Social cognitive and affective neuroscience · 2024Pooled it
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- A longitudinal neuroimaging study of adolescent girls' mentalizing and perspective-taking tendencies.Developmental cognitive neuroscience · 2025Article
- Enhancing task fMRI individual difference research with neural signatures.medRxiv : the preprint server for health sciences · 2025Article
- Leveraging normative personality data and machine learning to examine the brain structure correlates of obsessive-compulsive personality disorder traits.Journal of psychopathology and clinical science · 2024Article
- Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- What Is Food Noise? A Conceptual Model of Food Cue Reactivity.Nutrients · 2023Review
- Value-based neural representations predict social decision preferences.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- The promises and pitfalls of functional magnetic resonance imaging hyperscanning for social interaction research.Social and personality psychology compass · 2022Review
- A Neuroeconomics Approach to Obesity.Biological psychiatry · 2022Review
- Functional MRI Can Be Highly Reliable, but It Depends on What You Measure: A Commentary on Elliott et al. (2020).Psychological science · 2021Article
- Opportunities for increased reproducibility and replicability of developmental neuroimaging.Developmental cognitive neuroscience · 2021Review
- Neural Indicators Of Food Cue Reactivity, Regulation, And Valuation And Their Associations With Body Composition And Daily Eating Behavior.Social cognitive and affective neuroscience · 2020Article
- Health neuroscience 2.0: integration with social, cognitive and affective neuroscience.Social cognitive and affective neuroscience · 2020Article
- Improving practices and inferences in developmental cognitive neuroscience.Developmental cognitive neuroscience · 2020Review
- Brain Activity Associated With Regulating Food Cravings Predicts Changes in Self-Reported Food Craving and Consumption Over Time.Frontiers in human neuroscience · 2020Article
- The Effectiveness of Online Messages for Promoting Smoking Cessation Resources: Predicting Nationwide Campaign Effects From Neural Responses in the EX Campaign.Frontiers in human neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Establishing links between neural systems and health can be challenging since there is not a one-to-one mapping between brain regions and psychological states. Building sensitive and specific predictive models of health-relevant constructs using multivariate activation patterns of brain activation is a promising new direction. We illustrate the potential of this approach by building two 'neural signatures' of food craving regulation (CR) using multivariate machine learning and, for comparison, a univariate contrast. We applied the signatures to two large validation samples of overweight adults who completed tasks measuring CR ability and valuation during food choice. Across these samples, the machine learning signature was more reliable. This signature decoded CR from food viewing and higher signature expression was associated with less craving. During food choice, expression of the regulation signature was stronger for unhealthy foods and inversely related to subjective value, indicating that participants engaged in CR despite never being instructed to control their cravings. Neural signatures thus have the potential to measure spontaneous engagement of mental processes in the absence of explicit instruction, affording greater ecological validity. We close by discussing the opportunities and challenges of this approach, emphasizing what machine learning tools bring to the field of health neuroscience.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.