Salience and default networks predict borderline personality traits and affective symptoms: a dynamic functional connectivity analysis
These findings indicate that abnormalities in resting state networks are visible in subclinical populations with varying degrees of borderline traits, with impaired DMN and SN. These insights may pave the way for designing interventions to prevent the development of the full disorder.
Authors
- Davide Rivolta (ORCID: https://orcid.org/0000-0002-9969-9135)
- Parisa Ahmadi Ghomroudi (ORCID: https://orcid.org/0000-0002-0120-3921)
- Xiaoping Yi (ORCID: https://orcid.org/0000-0002-4220-1981)
- Alessandro Grecucci (ORCID: https://orcid.org/0000-0001-6043-2196)
- Irene Messina (ORCID: https://orcid.org/0000-0002-5720-5782)
- Miriam Langerbeck
- Richard Bakiaj (ORCID: https://orcid.org/0009-0007-3601-6978)
Institutions
- Chongqing University (CN)
- University of Trento (IT)
- Maastricht University (NL)
- Chongqing Three Gorges Central Hospital (CN)
- Mercatorum University (IT)
- Chongqing Cancer Hospital (CN)
- Chongqing Three Gorges University (CN)
- University of Bari Aldo Moro (IT)
Publication Details
- Journal
- Frontiers in Human Neuroscience
- Published
- 2025-07-01
- DOI
- https://doi.org/10.3389/fnhum.2025.1589440
- Citations
- 3
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.29