Ursino Mauro, Ricci Giulia, Astolfi Laura, Pichiorri Floriana, Petti Manuela, Magosso Elisa
Department of Electrical, Electronic and Information Engineering Guglielmo Marconi, Campus of Cesena, University of Bologna, Via Dell'Università 50, 47521 Cesena, Italy.
Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto, 25, 00185 Roma, Italy.
Brain Sci. 2021 Nov 8;11(11):1479. doi: 10.3390/brainsci11111479.
Knowledge of motor cortex connectivity is of great value in cognitive neuroscience, in order to provide a better understanding of motor organization and its alterations in pathological conditions. Traditional methods provide connectivity estimations which may vary depending on the task. This work aims to propose a new method for motor connectivity assessment based on the hypothesis of a task-independent connectivity network, assuming nonlinear behavior. The model considers six cortical regions of interest (ROIs) involved in hand movement. The dynamics of each region is simulated using a neural mass model, which reproduces the oscillatory activity through the interaction among four neural populations. Parameters of the model have been assigned to simulate both power spectral densities and coherences of a patient with left-hemisphere stroke during resting condition, movement of the affected, and movement of the unaffected hand. The presented model can simulate the three conditions using a single set of connectivity parameters, assuming that only inputs to the ROIs change from one condition to the other. The proposed procedure represents an innovative method to assess a brain circuit, which does not rely on a task-dependent connectivity network and allows brain rhythms and desynchronization to be assessed on a quantitative basis.
了解运动皮层的连接性在认知神经科学中具有重要价值，以便更好地理解运动组织及其在病理状态下的改变。传统方法提供的连接性估计可能因任务而异。这项工作旨在基于任务独立连接网络的假设，提出一种新的运动连接性评估方法，假设存在非线性行为。该模型考虑了与手部运动相关的六个皮质感兴趣区域（ROI）。使用神经群体模型模拟每个区域的动态，该模型通过四个神经群体之间的相互作用再现振荡活动。已分配模型参数以模拟左半球中风患者在静息状态、患侧手运动和健侧手运动期间的功率谱密度和相干性。所提出的模型可以使用一组单一的连接性参数模拟这三种情况，假设从一种情况到另一种情况仅ROI的输入发生变化。所提出的程序是一种评估脑回路的创新方法，它不依赖于任务相关的连接网络，并允许在定量基础上评估脑节律和去同步化。
