Fekonja Lucius Samo, Schenk Robert, Schröder Emily, Tomasello Rosario, Tomšič Samo, Picht Thomas
Cluster of Excellence Matters of Activity, Image Space Material, Humboldt-Universität zu Berlin, Berlin, Germany.
Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Front Neurosci. 2024 Sep 17;18:1454856. doi: 10.3389/fnins.2024.1454856. eCollection 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.
数字孪生作为物理系统的虚拟表示,能够实现模拟、全面分析和预测。它们在医疗保健领域也越来越受到关注和应用,尤其聚焦于大脑的数字孪生。我们将探讨神经科学中的数字孪生如何实现大脑功能和病理的建模,因为它们提供了一种在计算机上研究大脑并阐明脑网络动态与相关功能之间复杂关系的方法。为了展示神经科学中数字孪生的能力,我们将说明如何根据可塑性的哲学概念,对脑肿瘤对大脑物理结构和功能的影响进行建模。在这种基于技术推导的背景下,即假设大脑在改善和修复方面的非线性行为可以根据磁共振成像(MRI)数据进行建模和预测,我们进一步探讨凯瑟琳·马拉布的哲学见解。马拉布强调大脑具有适应性和破坏性可塑性的双重能力。我们将讨论马拉布的观点在多大程度上为理解数字孪生如何模拟大脑对损伤和病理的反应提供了一个更全面的理论框架,接受马拉布关于适应性和破坏性可塑性的概念,这为解决神经科学中此类难以计算的方面以及神经可塑性有时看似不利的动态变化提供了一个框架,有助于弥合理论研究与临床实践之间的差距。