B. Z. (Boglarka) Kovacs, PhD

I am a PhD candidate at Erasmus MC within the FAMILY consortium, where I focus on identifying and validating neurobiological markers that predict mental health outcomes and resilience in children of parents with severe mental illness. My work integrates structural and diffusion neuroimaging data with psychosocial and genetic risk factors from both population-based and high-risk cohorts, with a special interest for the perinatal period and the earliest markers of risk and resilience.

• Intergenerational transmission of mental illness
• Brain imaging (MRI, DTI, brain-PAD)
• Early-life risk and resilience factors
• Polygenic risk scores and genetic nurture
• Trio modeling
• Digital phenotyping
• Prenatal psychosocial determinants of brain structure
• Developmental trajectories

• MSc (Psychology/Neuroscience), Lund University 
• Research Intern, Erasmus MC 
• PhD Candidate, Erasmus MC (2023–present) 

Currently supervising my first 2 master’s students.

Trainee committee member in Flux Society.

NICHD Young Investigator Awards in FIT’NG (Fetal, Infant, Toddler Neuroimaging Group).

FAMILY – WP5 (Main PhD Project)

Analyzing neuroimaging data to identify neurobiological predictors of mental health and resilience in children of parents with severe mental illness.

FAMILY – WP2

Contributing to cross-cohort harmonization (questionnaire FAIRification, anatomical scan pipelines).

FinnBrain Cohort Project

Investigating prenatal psychosocial determinants of neonatal brain structure using latent constructs from both parents.

ICV Review

Umbrella review on intracranial volume as a marker for neurodevelopment.

DWI Review

Systematic review on diffusion-weighted imaging markers in offspring of parents with severe mental illness.

GenR – FAMILY Brain-PAD Project

Calculating polygenic risk scores (PRS) and conducting trio modeling to assess direct and indirect genetic effects on brain-predicted age difference (brain-PAD) and aging-related traits.

Digital Phenotyping Project

Review on the application of smartphone-based digital behavior data to predict peripartum depression risk in mothers.

PANDA

Testing fetal and neonatal neuroimaging processing pipelines, data processing, and later analysis in a high-risk offspring study.

BRIDGE

Running DTI pipelines, overseeing scan quality and supervising master’s students.

• FAMILY Consortium 
• BRIDGE – Brain Imaging, Development & Genetics 
• PANDA Study 
• GenR Study 
• FinnBrain