Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding.

IF 2.4 4区 医学 Q3 ENGINEERING, BIOMEDICAL Physical and Engineering Sciences in Medicine Pub Date : 2024-09-01 Epub Date: 2024-05-13 DOI:10.1007/s13246-024-01427-8
Martín Durán-Santos, R Salazar-Varas, Gibran Etcheverry
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Abstract

Regarding motor processes, modeling healthy people's brains is essential to understand the brain activity in people with motor impairments. However, little research has been undertaken when external forces disturb limbs, having limited information on physiological pathways. Therefore, in this paper, a nonlinear delay differential embedding model is used to estimate the brain response elicited by externally controlled wrist movement in healthy individuals. The aim is to improve the understanding of the relationship between a controlled wrist movement and the generated cortical activity of healthy people, helping to disclose the underlying mechanisms and physiological relationships involved in the motor event. To evaluate the model, a public database from the Delft University of Technology is used, which contains electroencephalographic recordings of ten healthy subjects while wrist movement was externally provoked by a robotic system. In this work, the cortical response related to movement is identified via Independent Component Analysis and estimated based on a nonlinear delay differential embedding model. After a cross-validation analysis, the model performance reaches 90.21% ± 4.46% Variance Accounted For, and Correlation 95.14% ± 2.31%. The proposed methodology allows to select the model degree, to estimate a general predominant operation mode of the cortical response elicited by wrist movement. The obtained results revealed two facts that had not previously been reported: the movement's acceleration affects the cortical response, and a common delayed activity is shared among subjects. Going forward, identifying biomarkers related to motor tasks could aid in the evaluation of rehabilitation treatments for patients with upper limbs motor impairments.

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通过非线性延迟微分嵌入模拟手腕操作引起的大脑皮层反应
关于运动过程,健康人的大脑模型对于了解运动障碍患者的大脑活动至关重要。然而,由于有关生理通路的信息有限,在外力干扰肢体时开展的研究很少。因此,本文采用非线性延迟微分嵌入模型来估计健康人在外部控制手腕运动时引起的大脑反应。这样做的目的是为了更好地理解受控手腕运动与健康人大脑皮层活动之间的关系,帮助揭示运动事件的内在机制和生理关系。为了评估该模型,我们使用了代尔夫特理工大学的一个公共数据库,其中包含十名健康受试者在机器人系统外部刺激下进行手腕运动时的脑电记录。在这项工作中,与运动相关的皮层响应通过独立分量分析进行识别,并根据非线性延迟差分嵌入模型进行估计。经过交叉验证分析,该模型的性能达到了 90.21% ± 4.46% 方差占比,相关性为 95.14% ± 2.31%。所提出的方法可以选择模型的程度,从而估算出手腕运动所引起的大脑皮层反应的一般主导运行模式。研究结果揭示了两个以前从未报道过的事实:运动的加速度会影响大脑皮层的反应,而且受试者之间存在共同的延迟活动。展望未来,确定与运动任务相关的生物标志物有助于评估上肢运动障碍患者的康复治疗。
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CiteScore
8.40
自引率
4.50%
发文量
110
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