Arrow Research search

Author name cluster

Inga Aarts

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers
1 author row

Possible papers

2

YNICL Journal 2025 Journal Article

Treatment outcome is associated with pre-treatment connectome measures across psychiatric disorders − evidence for connectomic reserve?

  • Chris Vriend
  • Sophie M.D.D. Fitzsimmons
  • Inga Aarts
  • Aniek Broekhuizen
  • Ysbrand D. van der Werf
  • Linda Douw
  • Henny A.D. Visser
  • Kathleen Thomaes

Predicting treatment efficacy in psychiatric disorders remains challenging, despite the availability of effective interventions. Previous studies suggest a link between pre-treatment brain network characteristics and treatment efficacy in individual disorders, but cross-disorder investigations are lacking. We analyzed pre-treatment MRI data from 177 individuals (113 females) with either obsessive-compulsive disorder (OCD) or post-traumatic stress disorder with comorbid personality disorders (PTSD) that received different non-pharmacological treatments. Using diffusion and resting-state MRI, we constructed structural, functional, and multilayer connectomes and calculated network measures for network integration (e.g. global efficiency, eccentricity), segregation (modularity) and their balance (small-worldness). We assessed the relationship between these pre-treatment network measures, and treatment improvement using mixed-model and Bayesian analyses. We also compared psychiatric cases with healthy controls and investigated associations between clinical response and treatment-induced changes in network measures. Across disorders and treatments, psychiatric cases showed a 41.6 ± 29.6 % symptom improvement (62 % response rate) after treatment. They also showed pre-treatment differences in functional and multilayer network topology compared to healthy controls. Symptom improvement was associated with pre-treatment functional (P = 0.04) and structural small-worldness (P = 0.01), and multilayer eccentricity (P = 0.01), while responders had higher functional modularity (P = 0.02). Results were robust across trials and treatments, when adjusting for medication status and showed high credibility in Bayesian analyses. Network change associations with treatment response were only modest. These results show that pre-treatment connectome characteristics are related to treatment response, regardless of treatment and psychiatric disorder, and suggest that individual differences in intrinsic features of the human connectome underlie amenability to treatment.

YNICL Journal 2024 Journal Article

Brain activation during an emotional task in participants with PTSD and borderline and/or cluster C personality disorders

  • Inga Aarts
  • Chris Vriend
  • Odile A. van den Heuvel
  • Kathleen Thomaes

INTRODUCTION: Although comorbidity of post-traumatic stress disorder (PTSD) with borderline personality disorder (BPD) and/or cluster C personality disorders (CPD) is common, neural correlates of this comorbidity are unknown. METHODS: We acquired functional MRI scans during an emotional face task in participants with PTSD + CPD (n = 34), PTSD + BPD (n = 24), PTSD + BPD + CPD (n = 18) and controls (n = 30). We used ANCOVAs and Bayesian analyses on specific ROIs in a fearful vs. scrambled faces contrast. We also investigated associations with clinical measures. RESULTS: There were no robust differences in brain activation between the groups with ANCOVAs. Transdiagnostically, we found a negative association between severity of dissociation and right insula and right dmPFC activation, and emotion regulation problems with right dmPFC activation. Bayesian analyses showed credible evidence for higher activation in all ROIs in the PTSD + BPD + CPD group compared to PTSD + BPD and PTSD + CPD. DISCUSSION: Our Bayesian and correlation analyses support new dimensional conceptualizations of personality disorders.