Moving from phenomenological to predictive modelling: Pitfalls of modeling brain stimulation in-silico

Brain stimulation is an increasingly popular tool for both research and clinical use. However, the effects of brain stimulation are not entirely known, and neither are the mechanisms by which brain stimulation changes brain activity. One way to efficiently study the relationship between the brain and neuromodulation is to use computational models. Computational models allow researchers to run realistic simulations that show how the brain is influenced by neuromodulation or predict what brain stimulation will change in brain activity and/or behaviour. This talk will introduce how Wilson Cowan, Kuramoto, and Stuart Landau oscillators can form models that can simulate the relationship between the brain and brain stimulation. These models are described in the context of state-of-the-art research studies, to provide examples of how they are used. Finally, this talk will introduce three suggested phases to improve phenomenological models and how they can be used to form testable predictions. We hope that this review makes computational modelling more accessible by showing researchers how the math underpinning the models and their behavior relates to brain structure and function.