Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 167, Issue 2, Pages 367-375Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2007.08.022
Keywords
Granger causality; coherence; correlation; Parkinson's disease
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Biological systems are usually non-linear and, as a result, the driving signal frequency (say, MHz) is in general not identical with the output frequency (say, NHz). Coherence and causality analysis have been well-developed to measure the (directional) correlation between input and output signals with identical frequencies (N = M), but they are not applicable to the cases with different frequencies (N A M). In this paper, we propose a novel method called frequency-modified causality (coherence) analysis to resolve the issue. The input or output signal is first modulated by up-sampling or down-sampling, coherence and causality analysis are then applied to the frequency modulated and filtered signals. An optimal coherence and causality is found, revealing the true input-output relationship between signals. The method is successfully tested on data generated from a toy model, the van der Pol oscillator and then employed to analyze data recorded from Parkinson's disease (PD) patients. (c) 2007 Elsevier B.V. All rights reserved.
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