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Some eating patterns, such as restrained eating and uncontrolled eating, are risk factors for eating disorders. However, it is not yet clear whether they are associated with neurocognitive differences. In the current study, we analyzed whether eating patterns can be used to classify participants into meaningful clusters, and we examined whether there are neurocognitive differences between the clusters. Adolescents ( = 108; 12 to 17 years old) and adults ( = 175, 18 to 40 years old) completed the Three Factor Eating Questionnaire, which was used to classify participants according to their eating profile using k means clustering. Participants also completed personality questionnaires and a neuropsychological examination. A subsample of participants underwent a brain MRI acquisition. In both samples, we obtained a cluster characterized by high uncontrolled eating patterns, a cluster with high scores in restrictive eating, and a cluster with low scores in problematic eating behaviors. The clusters were equivalent with regards to personality and performance in executive functions. In adolescents, the cluster with high restrictive eating showed lower cortical thickness in the inferior frontal gyrus compared to the other two clusters. We hypothesize that this difference in cortical thickness represents an adaptive neural mechanism that facilitates inhibition processes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394556 | PMC |
http://dx.doi.org/10.3390/brainsci11080978 | DOI Listing |
Br J Psychiatry
September 2025
Neuroscience Research Australia, Randwick, New South Wales, Australia.
Background: Individuals with a family history of bipolar disorder are at increased risk of developing affective psychopathology. Longitudinal imaging studies in young people with familial risk have been limited, and cortical developmental trajectories in the progression towards illness remain obscure.
Aims: To establish high-resolution longitudinal differences in cortical structure that are associated with risk of bipolar disorder.
Brain Behav
September 2025
The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Background: Diverse correlations between structural brain abnormalities and the clinical feature of bulimia nervosa (BN) have been identified in previous observational studies.
Objective: To explore the bidirectional causality between BN and brain structural magnetic resonance imaging (MRI) phenotypes.
Methods: Genome-wide association studies (GWAS) of 2441 participants identified genetic variants associated with disordered eating and predicted BN, whereas UK Biobank 3D-T1 MRI data were used to analyze brain structural phenotypes.
Brain Behav
September 2025
Radiology Department, Yantaishan Hospital, Yantai, Shandong, China.
Objective: To investigate the characteristics of brain structures in patients with noise-induced hearing loss (NIHL) using source-based morphometry (SBM) and to evaluate the correlation between abnormal brain regions and clinical data.
Methods: High-resolution 3D T1 structural images were acquired from 81 patients with NIHL and 74 age- and education level-matched healthy controls (HCs). The clinical data of all subjects were collected, including noise exposure time, monaural hearing threshold weighted values (MTWVs), Mini-Mental State Examination (MMSE), and Hamilton Anxiety Scale (HAMA) scores.
Brain Res Bull
September 2025
Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, 230601, He Fei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, 230032, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, 230032, Hefei,
Background: The relationships between white matter microstructure, cortical atrophy, and cognitive function in cerebral small vessel disease (CSVD)-related white matter hyperintensities (WMHs) patients are unclear.
Methods: 71 right-handed WMHs patients (mild, n=23; moderate, n=27; severe, n=21) and 35 healthy controls were included. Tract-based spatial statistics (TBSS) assessed microstructure via fractional anisotropy (FA) and mean diffusivity (MD).
Neuroimage Clin
September 2025
Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Objectives: To examine associations between low cognitive-performance and regional-and network-level brain changes at ages 9-10 in very-preterm, moderately-preterm, and full-term children, and explore whether these alterations predict ASD/ADHD symptoms at age 12.
Methods: This longitudinal population-based study included 9-10-year-old U.S.