Introduction
Understanding links between (clinical) measures of brain function and their underlying molecular, synaptic constraints is essential for developing and utilizing personalised interventions. We developed a flexible approach to integrate multi-modal datasets of different spatial scales and test hypotheses on how micro-/mesoscale properties shape macroscale brain dynamics. Here, we...
Introduction
Long-range temporal correlations (LRTC) are a ubiquitous property of healthy brain activity and, under the Critical Brain Hypothesis, reflect proximity to critical states. In line with this, these scale-free dynamics diminish during loss of consciousness - signaling a departure from criticality - and rebound upon recovery. Yet their implications for individual-level metabolic...
Comparing whole-brain dynamics across individuals and modalities remains challenging, particularly when seeking interpretable, cohort-scale metrics that respect the discrete, metastable nature of brain activity. We introduce a two-part framework that combines energy landscape analysis with a multi-subject dimensionality reduction stage to yield bias-minimal, scale-invariant, and...
We present a scalable computational framework for simulating brain dynamics within structurally complex regions such as the hippocampus, integrating high-resolution multimodal data—including BigBrain-derived surface meshes and diffusion MRI tractography—into The Virtual Brain simulator. This Region Brain Network Model (RBNM) framework enables vertex-level placement of neural mass models (NMMs)...
