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Bayesian approaches to the analysis of task related coherent activity in the basal ganglia

机译:Bayesian对基础神经节的任务相关连贯活动分析的方法

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In this paper we outline a suitable methodology for the analysis of nonstationary electrophysiological signals. The methodology is founded on a Bayesian approach to spectral estimation, which offers definite advantages in objectivity as compared to other approaches. The analysis of such signals is important in experimental paradigms where one is interested in tracking changes in spectral power or coherence. We describe how this methodology has been successfully applied to scalp EEG and deep brain local field potentials recorded from Parksinsonian patients, and used to deduce task related changes in power and coherence that are relevant to the understanding of the neural organisation of voluntary movement.
机译:本文概述了一种合适的方法,用于分析非营养的电生理信号。该方法建立在贝叶斯估计的贝叶斯方法上,与其他方法相比,其在客观性方面具有明确的优势。对这种信号的分析在实验范例中是重要的,其中一个人有兴趣跟踪光谱功率或连贯性的变化。我们介绍了该方法如何成功应用于从Parksinsonian患者记录的头皮EEG和深脑当地领域潜力,并用于推导与对自愿运动神经组织的神经组织有关的权力和一致性的任务相关变化。

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