Markus Helmer

QuNex Recipes provide a framework for creating executable, human-readable workflows to ensure reproducibility in neuroimaging research.

The paper evaluates the stability of CCA and PLS in high-dimensional datasets, finding instability in small samples and proposing a power calculator for reliable multivariate analysis.

QuNex provides a platform for reproducible neuroimaging analytics, integrating multi-modal tools and enabling scalable, high-throughput processing across species and datasets.

The paper develops a stable brain-behavior space mapping for psychosis-spectrum disorders using symptom and brain data, showing univariate approaches outperform multivariate ones for individualized prediction.

The paper introduces a generative null model to create spatially autocorrelated surrogate brain maps for hypothesis testing in brain organization studies.

The paper develops a dynamical circuit model of human cortex incorporating hierarchical heterogeneity to better explain large-scale neural dynamics and functional connectivity.