Lionel Kusch

Spatiotemporal brain complexity quantifies consciousness outside of perturbation paradigms

The paper quantifies consciousness using spatiotemporal brain complexity metrics from resting-state and stimulation data, showing agreement with perturbational complexity in a more accessible paradigm.

Magnetoencephalography dimensionality reduction informed by dynamic brain states

This study uses PHATE to reduce the dimensionality of resting-state MEG data, revealing dynamic brain states and their transitions in a low-dimensional space.

Dynamics and bifurcation structure of a mean-field model of adaptive exponential integrate-and-fire networks

The paper systematically investigates the dynamics and bifurcation structure of a mean-field model of Adaptive Exponential integrate-and-fire networks to aid in interpreting results.

Asynchronous and slow-wave oscillatory states in connectome-based models of mouse, monkey and human cerebral cortex

The paper builds brain-wide models of mouse, macaque, and human cerebral cortex using connectome data and mean-field techniques, showing species differences in slow-wave synchrony due to axonal propagation delays.

A comprehensive neural simulation of slow-wave sleep and highly responsive wakefulness dynamics

This paper develops a mean-field neural model of brain states that reproduces empirical dynamics across scales and brain states, using the human connectome and the Virtual Brain simulator.

Multiscale cosimulation design template for neuroscience applications

The paper introduces a design template for multiscale cosimulation in neuroscience, enabling integration of cellular and population-level models to enhance computational modeling capabilities.

Brain-scale emergence of slow-wave synchrony and highly responsive asynchronous states based on biologically realistic population models simulated in The Virtual Brain

The paper develops a brain-wide model using biologically realistic population dynamics to simulate slow-wave synchrony and asynchronous states, showing their distinct responses to stimulation.