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Reconstruction of effective connectivity in the case of asymmetric phase distributions.
- Source :
-
Journal of Neuroscience Methods . Apr2019, Vol. 317, p94-107. 14p. - Publication Year :
- 2019
-
Abstract
- Highlights • Observables distribution asymmetry can cause false connectivity estimations. • To avoid this error the measured phase should be transformed to an invariant phase. • We extended Dynamic Causal Modelling for phase coupling with such a transformation. • The new extension of Dynamic Causal Modelling can characterize m:n phase coupling. • The proposed new method is able to resolve spurious coupling between brain regions. Abstract Background The interaction of different brain regions is supported by transient synchronization between neural oscillations at different frequencies. Different measures based on synchronization theory are used to assess the strength of the interactions from experimental data. One method of estimating the effective connectivity between brain regions, within the framework of the theory of weakly coupled phase oscillators, was implemented in Dynamic Causal Modelling (DCM) for phase coupling (Penny et al., 2009). However, the results of such an approach strongly depend on the observables used to reconstruct the equations (Kralemann et al., 2008). In particular, an asymmetric distribution of the observables could result in a false estimation of the effective connectivity between the network nodes. New method In this work we built a new modelling part into DCM for phase coupling, and extended it with a distortion function that accommodates departures from purely sinusoidal oscillations. Results By analysing numerically generated data sets with an asymmetric phase distribution, we demonstrated that the extended DCM for phase coupling with the additional modelling component, correctly estimates the coupling functions. Comparison with existing methods The new method allows for different intrinsic frequencies among coupled neuronal populations and provides results that do not depend on the distribution of the observables. Conclusions The proposed method can be used to analyse effective connectivity between brain regions within and between different frequency bands, to characterize m:n phase coupling, and to unravel underlying mechanisms of the transient synchronization. [ABSTRACT FROM AUTHOR]
- Subjects :
- *CAUSAL models
*FREQUENCIES of oscillating systems
*DYNAMIC models
Subjects
Details
- Language :
- English
- ISSN :
- 01650270
- Volume :
- 317
- Database :
- Academic Search Index
- Journal :
- Journal of Neuroscience Methods
- Publication Type :
- Academic Journal
- Accession number :
- 134904539
- Full Text :
- https://doi.org/10.1016/j.jneumeth.2019.02.009