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Nikos Koutsouleris

@koutsouleris.bsky.social

interested in finding ways to prevent severe mental disorders using computational methods.

10 Posts182 Follower203 Folgt
Nikos Koutsouleris@koutsouleris.bsky.social · 3mo ago

New preprint: www.medrxiv.org/content/10.6... We built a mechanistic simulator of youth mental health: the Coupled Stochastic Dynamical System (CSDS) ...and tested whether its synthetic people behave like real ones. They do, more than we expected. 🧵

The Coupled Stochastic Dynamical System: A Generative Model for Simulating and Forecasting Youth Mental Health Trajectories

Mechanism-informed models that can simulate counterfactual mental-health trajectories remain scarce in digital phenotyping. Most existing approaches either predict outcomes from sensor-derived data wi...

medrxiv.org

Nikos Koutsouleris@koutsouleris.bsky.social · last yr.

It matters if we try to predict single snapshot of mental phenotypes or stable outcomes over time. Great new paper from my PhD student, Madalina Buciuman, who used the PRONIA dataset to predict functional outcomes in early psychosis and depression: www.biologicalpsychiatryjournal.com/article/S000...

From Snapshots to Stable Outcomes: rs-fMRI-based Prognosis of Functioning in Patients with Psychosis Risk or Recent-Onset Depression

Early recovery of functioning is critical for favorable outcomes in psychotic and affective disorders. Transdiagnostic brain activity patterns may capture pathways for poor outcomes before clinical ma...

biologicalpsychiatryjournal.com

Nikos Koutsouleris@koutsouleris.bsky.social · 2y ago

Excited to share our new preprint (www.researchsquare.com/article/rs-6...). We show that heterogeneous clinical high-risk criteria impede detection of biomarkers for early psychosis detection. Integrating cognitive basic symptoms and their neural surrogates may help to improve precision.

Refining Schizophrenia Risk Assessment: Machine Learning Delineates a Brain Signature of Cognitive Basic Symptoms

Biological risk signatures could aid the early detection of schizophrenia, but their precision likely depends on the clinical risk definitions they are derived from. Using machine learning, we analyze...

researchsquare.com