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Published in: Cognitive Processing 4/2018

17-05-2018 | Research Report

Topographical assessment of neurocortical connectivity by using directed transfer function and partial directed coherence during meditation

Authors: Laxmi Shaw, Aurobinda Routray

Published in: Cognitive Processing | Issue 4/2018

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Abstract

Due to the presence of nonlinearity and volume conduction in electroencephalography (EEG), sometimes it’s challenging to find out the actual brain network from neurodynamical alteration. In this paper, two well-known time–frequency brain connectivity measures, namely partial directed coherence (PDC) and directed transfer function (DTF), have been applied to evaluate the performance analysis of EEG signals obtained during meditation. These measures are implemented to the multichannel meditation EEG data to get the directed neural information flow. Mostly the assessment of PDC and DTF is entirely subjective and there are probabilities to have erroneous connectivity estimation. To avoid the subjective evaluation, the performance results are compared in terms of absolute energy, signal-to-noise ratio (SNR) and relative SNR (R-SNR) scale. In most of the cases, the PDC result is found to be more efficient than DTF. The limitation of DTF and PDC in terms of the time-varying multivariate autoregressive (MVAR) model is highlighted. The time-varying MVAR model can track the neurodynamical changes better than any other method. In the present study, we would like to show that the PDC-based connectivity gives a better understanding of the non-symmetric relation in EEG obtained during Kriya Yoga meditation in comparison to DTF. However, it needs to be investigated further to warrant this claim.

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Metadata
Title
Topographical assessment of neurocortical connectivity by using directed transfer function and partial directed coherence during meditation
Authors
Laxmi Shaw
Aurobinda Routray
Publication date
17-05-2018
Publisher
Springer Berlin Heidelberg
Published in
Cognitive Processing / Issue 4/2018
Print ISSN: 1612-4782
Electronic ISSN: 1612-4790
DOI
https://doi.org/10.1007/s10339-018-0869-2

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