Christian Bick

The paper studies how neuronal activity influences the spread of toxic proteins in neurodegenerative diseases through a multi-timescale model of spreading on adaptive networks.

The paper uses a whole-brain model to show glioma patients have altered neuronal dynamics compared to healthy controls, with changes in interregional coupling and excitability.

The paper develops mean-field approximations for neural networks with STDP to provide low-dimensional descriptions of their dynamics and improve computational efficiency.

The paper shows that metastable oscillatory modes in the brain emerge from synchronization in the spacetime connectome, matching MEG data from healthy individuals.

This paper models the spread of amyloid-β and tau in the human brain to explain Alzheimer's disease-related neuronal hyperactivation, frequency slowing, and hypoactivation.

This paper develops an algorithm for optimal closed-loop deep brain stimulation using multi-contact electrodes to maximize desynchronization of brain activity.

This paper shows that average beta burst duration profiles reflect changes in the dynamics of beta oscillations between ON and OFF medication states in Parkinson's disease, linking them to motor impairment.

The paper uses a Wilson-Cowan model to analyze phase-dependent effects of deep brain stimulation in essential tremor patients, showing the model can predict tremor responses and fit patient data.

This paper predicts the effects of deep brain stimulation using a reduced coupled oscillator model and proposes a hybrid strategy for closed-loop DBS in essential tremor patients.