Article Synopsis

  • The study investigates potential brain structure differences in individuals with Compulsive Sexual Behavior Disorder (CSBD) compared to healthy controls, focusing on areas linked to reward processing.
  • Research involved MRI scans of 22 CSBD patients and 20 matched controls, measuring cortical thickness and surface area, along with evaluating CSBD symptom severity.
  • Results showed significantly reduced cortical surface area in the right posterior cingulate cortex for CSBD patients, highlighting a possible link between brain structure and CSBD symptoms.

Video Abstracts

WITTY WAVE

July 13, 2024

98 views


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Background And Aims: Compulsive sexual behavior disorder (CSBD) has been included as an impulse control disorder in the International Classification of Diseases (ICD-11). However, the neurobiological mechanisms underlying CSBD remain largely unknown, and given previous indications of addiction-like mechanisms at play, the aim of the present study was to investigate if CSBD is associated with structural brain differences in regions involved in reward processing.

Methods: We analyzed structural MRI data of 22 male CSBD patients (mean = 38.7 years, SD = 11.7) and 20 matched healthy controls (HC; mean = 37.6 years, SD = 8.5). Main outcome measures were regional cortical thickness and surface area. We also tested for case-control differences in subcortical structures and the effects of demographic and clinical variables, such as CSBD symptom severity, on neuroimaging outcomes. Moreover, we explored case-control differences in regions outside our hypothesis including white matter.

Results: CSBD patients had significantly lower cortical surface area in right posterior cingulate cortex than HC. We found negative correlations between right posterior cingulate area and CSBD symptoms scores. There were no group differences in subcortical volume.

Conclusions: Our findings suggest that CSBD is associated with structural brain differences, which contributes to a better understanding of CSBD and encourages further clarifications of the neurobiological mechanisms underlying the disorder.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260207PMC
http://dx.doi.org/10.1556/2006.2023.00008DOI Listing

Publication Analysis

Top Keywords

structural brain
12
brain differences
12
csbd
9
compulsive sexual
8
sexual behavior
8
behavior disorder
8
neurobiological mechanisms
8
mechanisms underlying
8
csbd associated
8
associated structural
8

Similar Publications

Systematic analyses uncover plasma proteins linked to incident cardiovascular diseases.

Protein Cell

August 2025

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China.

Cardiovascular disease (CVD) research is hindered by limited comprehensive analyses of plasma proteome across disease subtypes. Here, we systematically investigated the associations between plasma proteins and cardiovascular outcomes in 53,026 UK Biobank participants over a 14-year follow-up. Association analyses identified 3,089 significant associations involving 892 unique protein analytes across 13 CVD outcomes.

View Article and Find Full Text PDF

Cognitive impairment and dementia, including Alzheimer's disease (AD), pose a global health crisis, necessitating non-invasive biomarkers for early detection. This review highlights the retina, an accessible extension of the central nervous system (CNS), as a window to cerebral pathology through structural, functional, and molecular alterations. By synthesizing interdisciplinary evidence, we identify retinal biomarkers as promising tools for early diagnosis and risk stratification.

View Article and Find Full Text PDF

Neuroimaging Data Informed Mood and Psychosis Diagnosis Using an Ensemble Deep Multimodal Framework.

Hum Brain Mapp

September 2025

Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.

Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.

View Article and Find Full Text PDF

Parasagittal dural space and arachnoid granulations morphology in pre-clinical and early clinical multiple sclerosis.

Mult Scler

September 2025

Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Neurology, VA Medical Center, TN Valley Healthcare System, Nashville, TN, USA.

Background: There is limited knowledge on the post-glymphatic structures such as the parasagittal dural (PSD) space and the arachnoid granulations (AGs) in multiple sclerosis (MS).

Objectives: To evaluate differences in volume and macromolecular content of PSD and AG between people with newly diagnosed MS (pwMS), clinically isolated syndrome (pwCIS), or radiologically isolated syndrome (pwRIS) and healthy controls (HCs) and their associations with clinical and radiological disease measures.

Methods: A total of 69 pwMS, pwCIS, pwRIS, and HCs underwent a 3.

View Article and Find Full Text PDF

Hubs, influencers, and communities of executive functions: a task-based fMRI graph analysis.

Front Hum Neurosci

August 2025

Baptist Medical Center, Department of Behavioral Health, Jacksonville, FL, United States.

Introduction: This study investigates four subdomains of executive functioning-initiation, cognitive inhibition, mental shifting, and working memory-using task-based functional magnetic resonance imaging (fMRI) data and graph analysis.

Methods: We used healthy adults' functional magnetic resonance imaging (fMRI) data to construct brain connectomes and network graphs for each task and analyzed global and node-level graph metrics.

Results: The bilateral precuneus and right medial prefrontal cortex emerged as pivotal hubs and influencers, emphasizing their crucial regulatory role in all four subdomains of executive function.

View Article and Find Full Text PDF