publications
publications by categories in reversed chronological order.
2026
- Nabila Siregar, Phong Le, and Raquel G AlhamaIn International Conference on the Evolution of Language, 2026
We present a computational framework to investigate whether artificial agents in a foraging environment develop a communication protocol with features of the honeybee waggle dance. Analyzing communicative success, compositionality, and emergent semantics, we find that (i) agents tend to use directional signals for communication, especially when they have the freedom to explore the environment, (ii) in the absence of direct distance representations, agents develop a system based on shortest-path routes when their mental map representations overlap, and (iii) constraining their communication channel to simulate kinematic properties of honeybees provides a slight positive benefit. Overall, we find that, under certain constraints, agents develop a (relatively) compositional communication system reminiscent of the waggle dance.
2025
- Angela Koloi, Nabila P.R. Siregar, Rick Quax, and 7 more authorsBiological Psychiatry Global Open Science, 2025
Background: Major depressive disorder (MDD) and cardiovascular diseases (CVD) often co-occur whereby comorbidity results in poorer clinical outcomes, presumably due to shared immune-metabolic pathways. Identifying shared biomarkers for MDD-CVD comorbidity may provide targets for prevention or treatment. Methods: Using data from the Netherlands Study of Depression and Anxiety (NESDA: N=2,256, 66.3% female, mean age 41.75 ± 13.11 years), validated with the UK Biobank data (UKB, N=35,668, 56.14% female, mean age 63.95 ± 7.74 years), this study aimed to identify (i) biomarkers, closely associated with current MDD, and (ii) longitudinal pathways linking MDD and atherosclerotic CVD. Plasma metabolites (NMR, Nightingale) and inflammatory markers were used as exposures within a Machine Learning framework. Influential biomarkers were integrated into a temporal network analysis linking MDD to subsequent CVD, exploring longitudinal pathways through Causal Discovery, validated by sensitivity analysis and centrality assessment. External validation included mediation and regression analysis adjusting for covariates. Results: Network analysis identified stable direct paths from MDD to CVD via TNF-α, tyrosine, and fatty acids, and indirect paths via acetate, HDL diameter, IL-6, alpha-1-acid glycoprotein (AGP), hs-CRP, and LDL triglycerides. Among these, acetate, tyrosine, AGP, and HDL diameter potentially mediate the MDD-CVD connection, as these were identified as key nodes within the network. UKB validation confirmed HDL diameter (β = 0.004) and AGP (β = 0.003) as significant depression-CVD mediators (both p < .001), after adjusting for age, sex, deprivation index, alcohol consumption, smoking status, physical activity, and BMI. Conclusions: These analyses identified biomarkers shared in MDD and CVD and may drive comorbid pathology risk.