In this project, we aim to understand the network interactions underlying intact and lesion impaired brain function by pursuing and integrating two approaches for identifying higher-order interactions in the brain. We will use the game theoretical approach of Multi-perturbation Shapley Value Analysis and information theoretical approaches to determine higher-order network interactions from the activity patterns and the causal interactions of brain nodes. Our goal is to apply these approaches to synthetic data and a suitable clinical dataset that comprises both lesion perturbation data and data on the activity of brain nodes, so that the outcomes for determining higher order interactions from the two approaches can be compared directly. The work will be performed in close collaboration between the two teams investigating the frameworks of game theory-based (Hilgetag) and information theory-based (Marinazzo) higher-order network interactions. With this project, we aim to derive a better understanding of the functionally relevant interactions in complex brain networks and to apply these insights to the interpretation of lesion deficits in a clinical context.