Definition
Spectral interdependency methods are a means of statistically quantifying the interrelationship between a pair of dynamic processes as a function of frequency or time period of oscillation. The measures of spectral interdependency are derived from the time series recordings of dynamic systems either by using autoregressive modeling (parametric method) or by using direct Fourier or wavelet transforms (nonparametric method). For a pair of multivariate stationary processes (1 and 2), there are three measures that characterize the spectral interdependency between these processes. They are total interdependence (M 1, 2), Granger causality (one-way effect or directional influence from the first process to the second process, M 1→ 2, or from the second to the first, M 2→ 1), and instantaneous causality (measure of reciprocity, M 1. 2). In general, the...
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Dhamala, M. (2014). Spectral Interdependency Methods. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_420-2
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_420-2
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Spectral Interdependency Methods- Published:
- 13 September 2014
DOI: https://doi.org/10.1007/978-1-4614-7320-6_420-2
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Spectral Interdependency Methods- Published:
- 03 April 2014
DOI: https://doi.org/10.1007/978-1-4614-7320-6_420-1