The digital twin in neuroscience: from theory to tailored therapy - Fekonja, Lucius Samo; Schenk, Robert; Schröder, Emily; Tomasello, Rosario; Tomšič, Samo; Picht, Thomas (Frontiers in Neuroscience, 2024)
Digital twins enable simulation, comprehensive analysis and predictions, as virtual representations of physical systems. They are also finding increasing interest and application in the healthcare sector, with a particular focus on digital twins of the brain. We discuss how digital twins in neuroscience enable the modeling of brain functions and pathology as they offer an in-silico approach to studying the brain and illustrating the complex relationships between brain network dynamics and related functions. To showcase the capabilities of digital twinning in neuroscience we demonstrate how the impact of brain tumors on the brain’s physical structures and functioning can be modeled in relation to the philosophical concept of plasticity. Against this technically derived backdrop, which assumes that the brain’s nonlinear behavior toward improvement and repair can be modeled and predicted based on MRI data, we further explore the philosophical insights of Catherine Malabou. Malabou emphasizes the brain’s dual capacity for adaptive and destructive plasticity. We will discuss in how far Malabou’s ideas provide a more holistic theoretical framework for understanding how digital twins can model the brain’s response to injury and pathology, embracing Malabou’s concept of both adaptive and destructive plasticity which provides a framework to address such yet incomputable aspects of neuroscience and the sometimes seemingly unfavorable dynamics of neuroplasticity helping to bridge the gap between theoretical research and clinical practice.