Fernando A. N. Santos

The paper shows metabolic scaling diversity arises from stochastic cellular growth dynamics, not fixed mass-metabolism relationships.

This paper introduces a topological fingerprint using Local Euler Curvature to identify secondary protein structures, achieving accurate classification through unsupervised clustering and supervised learning.

This paper develops a multivariate signal processing pipeline to build high-order brain networks from fMRI data and identifies high-order hubs associated with distinct brain systems.

This study shows that multimodal multilayer network centrality in the frontoparietal network is positively associated with executive functioning, outperforming unilayer centrality.

This tutorial provides computational tools for analyzing neuroimaging data using network and topological neuroscience frameworks, with a focus on resting-state functional MRI data from the 1000 Functional Connectomes Project.

The paper links functional network integration in the default mode network to cellular properties in TLE patients, showing correlations between network centrality and memory performance.

This study identifies topological phase transitions in functional brain networks using TDA, showing they occur when Euler entropy has a singularity and correlate with multidimensional topological holes.