It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear
behaviours. Here we challenge this assumption by leveraging mathematical models derived …

A central challenge in the computational modeling of neural dynamics is the trade-off
between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are …

The neurophysiological processes underlying non-invasive brain activity measurements are
incompletely understood. Here, we developed a connectome-based brain network model …

We considered a large-scale dynamical circuit model of human cerebral cortex with region-
specific microscale properties. The model was inverted using a stochastic optimization …

To provide an effective substrate for cognitive processes, functional brain networks should
be able to reorganize and coordinate on a sub-second temporal scale. We used …

The cortex is a complex system, characterized by its dynamics and architecture, which
underlie many functions such as action, perception, learning, language, and cognition. Its …

In the human brain, spontaneous activity during resting state consists of rapid transitions
between functional network states over time but the underlying mechanisms are not …

Resting state networks (RSNs) are of fundamental importance in human systems
neuroscience with evidence suggesting that they are integral to healthy brain function and …

How a stimulus or a task alters the spontaneous dynamics of the brain remains a
fundamental open question in neuroscience. One of the most robust hallmarks of …

Large-scale brain networks are often described using resting-state functional magnetic
resonance imaging (fMRI). However, the blood oxygenation level-dependent (BOLD) signal …