Isaev Mikhail, Bobrov Pavel, Mokienko Olesya, Fedotova Irina, Lyukmanov Roman, Ikonnikova Ekaterina, Cherkasova Anastasiia, Suponeva Natalia, Piradov Michael, Ustinova Ksenia
Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow 117485, Russia.
Department of Neuro-Computer Interfaces, Pirogov Russian National Research Medical University, Moscow 117513, Russia.
Sensors (Basel). 2025 Aug 14;25(16):5040. doi: 10.3390/s25165040.
Understanding patterns of interhemispheric asymmetry is crucial for monitoring neuroplastic changes during post-stroke motor rehabilitation. However, conventional laterality indices often pose computational challenges when applied to functional near-infrared spectroscopy (fNIRS) data due to the bidirectional hemodynamic responses. In this study, we analyze fNIRS recordings from 15 post-stroke patients undergoing motor imagery brain-computer interface training across multiple sessions. We compare traditional laterality coefficients with a novel task response asymmetry coefficient (TRAC), which quantifies differential hemispheric involvement during motor imagery tasks. Both indices are calculated for oxygenated and deoxygenated hemoglobin responses using general linear model coefficients, and their day-to-day dynamics are assessed with linear regression. The proposed TRAC demonstrates greater sensitivity than conventional measures, revealing significantly higher oxygenated hemoglobin TRAC values (0.18 ± 0.19 vs. -0.05 ± 0.20, < 0.05) and lower deoxygenated hemoglobin TRAC values (-0.15 ± 0.27 vs. 0.04 ± 0.23, < 0.05) in lesioned compared to intact hemispheres. Among patients who exhibit substantial motor recovery, distinct daily TRAC dynamics were observed, with statistically significant temporal trends. Overall, the novel TRAC metric offers enhanced discrimination of interhemispheric asymmetry patterns and captures temporal neuroplastic changes not detected by conventional indices, providing a more sensitive biomarker for tracking rehabilitation progress in post-stroke brain-computer interface applications.
了解半球间不对称模式对于监测中风后运动康复过程中的神经可塑性变化至关重要。然而，由于双向血流动力学反应，传统的偏侧性指数在应用于功能性近红外光谱（fNIRS）数据时常常带来计算挑战。在本研究中，我们分析了15名中风后患者在多个疗程中进行运动想象脑机接口训练时的fNIRS记录。我们将传统的偏侧性系数与一种新的任务反应不对称系数（TRAC）进行比较，该系数量化了运动想象任务期间不同半球的参与情况。使用一般线性模型系数计算含氧血红蛋白和脱氧血红蛋白反应的这两个指数，并通过线性回归评估它们的每日动态变化。所提出的TRAC显示出比传统测量方法更高的敏感性，与未受损半球相比，受损半球的含氧血红蛋白TRAC值显著更高（0.18±0.19对-0.05±0.20，<0.05），脱氧血红蛋白TRAC值更低（-0.15±0.27对0.04±0.23，<0.05）。在表现出显著运动恢复的患者中，观察到了明显的每日TRAC动态变化，具有统计学上显著的时间趋势。总体而言，新的TRAC指标能够更好地区分半球间不对称模式，并捕捉到传统指数未检测到的时间性神经可塑性变化，为追踪中风后脑机接口应用中的康复进展提供了一个更敏感的生物标志物。
