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Published on: August 7, 2017
Partial event coincidence analysis for distinguishing direct and indirect coupling in functional network construction
Jiamin Lu1, Reik V Donner2, Dazhi Yin3
1School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China.
This study introduces partial event coincidence analysis to accurately identify direct and indirect interactions in complex systems. The method improves functional network construction by distinguishing true connections from spurious ones, enhancing brain activity analysis.
Area of Science:
- Neuroscience
- Complex Systems Analysis
- Time Series Analysis
Background:
- Functional network construction relies on accurate interaction pattern identification from multivariate time series.
- Bivariate association measures often yield false links due to indirect interactions mediated by common drivers.
- Distinguishing direct from indirect links is crucial for reliable network analysis.
Purpose of the Study:
- To generalize event coincidence analysis to a partial version for distinguishing direct and indirect interactions in event-like data.
- To apply the partial event coincidence analysis to electroencephalography (EEG) data for investigating brain connectivity.
- To understand differences in coordinated alpha band activity between eyes open (EO) and eyes closed (EC) resting states.
Main Methods:
- Developed a partial event coincidence analysis to exclude transitive effects of indirect couplings.
- Validated the methodology using coupled chaotic systems and stochastic processes on star and chain topologies.
- Applied the partial event coincidence analysis to multi-channel EEG recordings.
Main Results:
- The proposed methodology correctly identifies indirect interactions in simulated systems.
- Direct connections in EEG data typically link spatially close brain regions, while indirect connections often span longer distances.
- The eyes closed (EC) state shows enhanced frontal brain connectivity compared to the eyes open (EO) state, with reduced posterior connectivity.
- A significant reduction in identified indirect connections was observed.
Conclusions:
- Partial event coincidence analysis effectively distinguishes direct and indirect interactions, improving functional network construction.
- The findings provide insights into brain region coordination during different resting states (EO vs. EC).
- The method aids in understanding the alpha band desynchronization phenomenon observed in the EO state.
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