Peter A. Robinson

This study applies neural field theory to EEG data to identify correlations between model parameters and consciousness states, highlighting potential biomarkers and physiological bases.

This paper shows that brain function can be understood through geometric resonant modes rather than connectivity, revealing brain-wide dynamics in task-evoked activity.

The paper develops a 3D hemodynamic model to predict BOLD responses across cortical depth, showing it matches experimental data with fewer assumptions than prior 2D models.

The paper uses neural field theory to analyze gamma-band oscillations in V1, reproducing experimental results on correlation properties under different conditions.

This paper investigates how changes in physiological connection strength parameters affect the dynamics of tonic-clonic seizures using a neural field model.

The paper unifies global and focal aspects of absence epilepsy using a corticothalamic model, showing how seizure localization and generalization relate to observed dynamics in humans and rats.

NFTsim is a software package for simulating neural field dynamics across multiple scales, enabling the study of brain activity and comparison with experimental data.

This paper reviews TMS paradigms and develops biophysically-based models to understand how LTP/LTD modulate population-level neuronal activity in response to TMS.