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Dynamic imaging of coherent sources: Studying neural interactions in the human brain

机译:相干源的动态成像:研究人脑中的神经相互作用

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Functional connectivity between cortical areas may appear as correlated time behavior of neural activity. It has been suggested that merging of separate features into a single percept ("binding") is associated with coherent gamma band activity across the cortical areas involved. Therefore. it would be of utmost interest to image cortico-cortical coherence in the working human brain. The fre- quency specificity and transient nature of these interactions re- quires time-sensitive tools such as magneto- or electroencepha- lography (MEG/EEG). Coherence between signals of sensors covering different scalp areas is commonly taken as a measure of functional coupling. However, this approach provides vague in- formation on the actual cortical areas involved, owing to the complex relation between the active brain areas and the sensor recordings. We propose a solution to the crucial issue of proceed- ing beyond the MEG sensor level to estimate coherences between cortical areas. Dynamic imaging of coherent sources (DICS) uses a spatial filter to localize coherent brain regions and provides the time courses of their activity. Reference points for the computation of neural coupling may be based on brain areas of maximum power or other physiologically meaningful information, or they may be estimated starting from sensor coherences. The performance of DICS is evaluated with simulated data and illustrated with record- ings of spontaneous activity in a healthy subject and a parkinso- nian patient. Methods for estimating functional connectivities between brain areas will facilitate characterization of cortical networks involved in sensory, motor, or cognitive tasks and will allow investigation of pathological connectivities in neurological disorders.
机译:皮质区域之间的功能连通性可能表现为神经活动的相关时间行为。已经提出,将单独的特征合并成单个感知(“结合”)与跨越所涉及的皮质区域的相干γ带活性有关。因此。在工作的人脑中成像皮质-皮质相干性将是最大的兴趣。这些相互作用的频率特异性和瞬态性质需要时间敏感的工具,例如磁电图或脑电图(MEG / EEG)。通常将覆盖不同头皮区域的传感器信号之间的相干性作为功能性耦合的量度。然而,由于活跃的大脑区域和传感器记录之间的复杂关系,这种方法在涉及的实际皮质区域上提供了模糊的信息。我们提出了解决这一重要问题的解决方案,该问题超出了MEG传感器水平,以估计皮层区域之间的连贯性。相干源的动态成像(DICS)使用空间滤波器来定位相干脑区域并提供其活动的时程。用于神经耦合计算的参考点可以基于最大功率的大脑区域或其他生理上有意义的信息,或者可以从传感器的一致性开始进行估计。 DICS的性能通过模拟数据进行评估,并以健康受试者和帕金森病患者的自发活动记录来说明。估计大脑区域之间功能连接的方法将有助于表征涉及感觉,运动或认知任务的皮层网络,并将允许调查神经系统疾病中的病理连接。

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