ArticleThe International journal of eating disorders2018
Using person-specific neural networks to characterize heterogeneity in eating disorders: Illustrative links between emotional eating and ovarian hormones.
Article in The International journal of eating disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 21 citations in OpenAlex.
- Changes in Brain Network Connections After Exposure and Response Prevention Therapy for Obsessive-Compulsive Disorder in Adolescents and Adults.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2024Trial
- Perceptual Dysfunction in Eating Disorders.Current topics in behavioral neurosciences · 2025Review
- Ovarian hormones reduce the negative association between worry and cognitive control: A combined neural and behavioral investigation.Psychoneuroendocrinology · 2024Article
- Determining menstrual cycle phase: An empirical examination of methodologies and recommendations for improvement in behavioral and brain sciences.Hormones and behavior · 2023Article
- Prenatal androgen influences on the brain: A review, critique, and illustration of research on congenital adrenal hyperplasia.Journal of neuroscience research · 2023Review
- Personalized Neural Networks Underlie Individual Differences in Ethnic Identity Exploration and Resolution.Journal of research on adolescence : the official journal of the Society for Research on Adolescence · 2023Article
- Assessment and Disruption of Ruminative Episodes to Enhance Mobile Cognitive Behavioral Therapy Just-in-Time Adaptive Interventions in Clinical Depression: Pilot Randomized Controlled Trial.JMIR formative research · 2023Article
- A network approach can improve eating disorder conceptualization and treatment.Nature reviews psychology · 2022Article
- Changes in cognitive and behavioral control after lamotrigine and intensive dialectical behavioral therapy for severe, multi-impulsive bulimia nervosa: an fMRI case study.Eating and weight disorders : EWD · 2022Article
- Intrauterine Device Use: A New Frontier for Behavioral Neuroendocrinology.Frontiers in endocrinology · 2022Article
- Resting state functional connectivity subtypes predict discrete patterns of cognitive-affective functioning across levels of analysis among patients with treatment-resistant depression.Behaviour research and therapy · 2021Article
- Detecting Task-Dependent Functional Connectivity in Group Iterative Multiple Model Estimation with Person-Specific Hemodynamic Response Functions.Brain connectivity · 2021Article
- Neural Connectivity Subtypes Predict Discrete Attentional Bias Profiles Among Heterogeneous Anxiety Patients.Clinical psychological science : a journal of the Association for Psychological Science · 2020Article
- Connections that characterize callousness: Affective features of psychopathy are associated with personalized patterns of resting-state network connectivity.NeuroImage. Clinical · 2020Article
- Ovarian Hormones and Reward Processes in Palatable Food Intake and Binge Eating.Physiology (Bethesda, Md.) · 2020Review
- Gonadal hormone contributions to individual differences in eating disorder risk.Current opinion in psychiatry · 2019Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveEmotional eating has been linked to ovarian hormone functioning, but no studies to-date have considered the role of brain function. This knowledge gap may stem from methodological challenges: Data are heterogeneous, violating assumptions of homogeneity made by between-subjects analyses. The primary aim of this paper is to describe an innovative within-subjects analysis that models heterogeneity and has potential for filling knowledge gaps in eating disorder research. We illustrate its utility in an application to pilot neuroimaging, hormone, and emotional eating data across the menstrual cycle.
methodGroup iterative multiple model estimation (GIMME) is a person-specific network approach for estimating sample-, subgroup-, and individual-level connections between brain regions. To illustrate its potential for eating disorder research, we apply it to pilot data from 10 female twins (N = 5 pairs) discordant for emotional eating and/or anxiety, who provided two resting state fMRI scans and hormone assays. We then demonstrate how the multimodal data can be linked in multilevel models.
resultsGIMME generated person-specific neural networks that contained connections common across the sample, shared between co-twins, and unique to individuals. Illustrative analyses revealed positive relations between hormones and default mode connectivity strength for control twins, but no relations for their co-twins who engage in emotional eating or who had anxiety. DISCUSSION: This paper showcases the value of person-specific neuroimaging network analysis and its multimodal associations in the study of heterogeneous biopsychosocial phenomena, such as eating behavior.
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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.