Eirini Messaritaki

Myelin-weighted Core Network Connectivity Supports Trait-Level Future Thinking

The paper links structural brain network properties to individual differences in future thinking abilities using MRI and psychometric data.

From Brain Microstructure to Dynamics: Linking Grey and White Matter Architecture to Propagation Delays

This study links brain microstructure to neural dynamics by showing that white and grey matter properties significantly correlate with propagation delays measured via MEG.

Decoding Brain Structure-Function Dynamics in Health and in Psychosis: A Tale of Two Models

This paper compares two models for mapping brain structure to function in health and psychosis, finding that deep learning outperforms analytical models in predicting functional connectivity in healthy individuals.

The impact of genetic risk for Alzheimers disease on the structural brain networks of young adults

This study examines how genetic risk for Alzheimer's disease affects structural brain networks in young adults using MRI and genotype data.

Increased structural connectivity in high schizotypy

The paper investigates the relationship between structural brain connectivity and schizotypy using diffusion MRI data from two cohorts, finding positive correlations between schizotypy scores and specific graph metrics in sensorimotor and default-mode subnetworks.

The Impact of Graph Construction Scheme and Community Detection Algorithm on the Reliability of Community and Hub Identification in Structural Brain Networks

The paper assesses the repeatability of community detection algorithms and graph construction schemes in structural brain networks using Human Connectome Project data, finding optimal pairings for reliable community and hub identification.

Dementia risk factors modify hubs but leave other connectivity measures unchanged in asymptomatic individuals: a graph theoretical analysis.

This study identifies a structural brain network hub in the right paracentral lobule associated with dementia risk factors in asymptomatic individuals, without affecting other graph theoretical measures.

Predicting MEG resting-state functional connectivity using microstructural information

The paper predicts resting-state functional connectivity using microstructural metrics and finds that streamline count and myelin measures yield the most accurate predictions.

Optimization of graph construction can significantly increase the power of structural brain network studies

This study evaluates 20 graph construction schemes for structural brain networks, finding that scheme choice significantly affects reproducibility and statistical power.