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首页> 外文期刊>Journal of Neuroscience Methods >Data-driven approach to the estimation of connectivity and time delays in the coupling of interacting neuronal subsystems.
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Data-driven approach to the estimation of connectivity and time delays in the coupling of interacting neuronal subsystems.

机译：数据驱动的方法来估计相互作用的神经元子系统之间的连通性和时延。

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摘要

One of the challenges in neuroscience is the detection of directionality between signals reflecting neural activity. To reveal the directionality of coupling and time delays between interacting multi-scale signals, we use a combination of a data-driven technique called empirical mode decomposition (EMD) and partial directed coherence (PDC) together with the instantaneous causality test (ICT). EMD is used to separate multiple processes associated with different frequency bands, while PDC and ICT allow to explore directionality and characteristic time delays, respectively. We computationally validate our approach for the cases of both stochastic and chaotic oscillatory systems with different types of coupling. Moreover, we apply our approach to the analysis of the connectivity in different frequency bands between local field potentials (LFPs) bilaterally recorded from the left and right of subthalamic nucleus (STN) in patients with Parkinson's disease (PD). We reveal a bidirectional coupling between the left and right STN in the beta-band (10-30 Hz) for an akinetic PD patient and in the tremor band (3-5 Hz) for a tremor-dominant PD patient. We detect a short time delay, most probably reflecting the inter-hemispheric transmission time. Additionally, in both patients we observe a long time delay of approximately a mean period of the beta-band activity in the akinetic PD patient or the tremor band activity in the tremor-dominant PD patient. These long delays may emerge in subcortico-thalamic loops or longer pathways, comprising reflex loops, respectively. We show that the replacement of EMD by conventional bandpass filtering complicates the detection of directionality and leads to a spurious detection of time delays.
机译：神经科学的挑战之一是检测反映神经活动的信号之间的方向性。为了揭示相互作用的多尺度信号之间的耦合方向性和时间延迟，我们使用了一种称为经验模式分解（EMD）和部分有向相干性（PDC）的数据驱动技术以及瞬时因果关系测试（ICT）的组合。 EMD用于分离与不同频带相关的多个过程，而PDC和ICT分别允许探索方向性和特征性时延。我们通过计算验证了我们的方法对于具有不同耦合类型的随机和混沌振动系统的情况。此外，我们将我们的方法用于分析从帕金森病（PD）患者的丘脑底下核（STN）的左右两侧双边记录的局部场电势（LFP）在不同频段之间的连通性。我们揭示了在β波段（10-30 Hz）对于运动性PD患者和在震颤波段（3-5 Hz）对于以震颤为主的PD患者的左STN和右STN之间的双向耦合。我们检测到较短的时间延迟，很可能反映了半球之间的传输时间。此外，在这两名患者中，我们观察到了运动性PD患者中β谱带活动的平均时间或震颤占优势的PD患者的震颤带活动的平均时间的长时间延迟。这些较长的延迟可能出现在皮层-丘脑下环或更长的路径中，分别包括反射环。我们表明，用常规的带通滤波代替EMD会使方向性的检测复杂化，并导致时间延迟的虚假检测。

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