1. Lp (p ≤ 1) Norm Partial Directed Coherence for Directed Network Analysis of Scalp EEGs
- Author
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Peiyang Li, Dezhong Yao, Huan Liu, Peng Xu, Xiaoye Huang, Xuyang Zhu, and Weiwei Zhou
- Subjects
Adult ,Male ,Computer science ,0206 medical engineering ,02 engineering and technology ,Electroencephalography ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,medicine ,Humans ,Computer Simulation ,Radiology, Nuclear Medicine and imaging ,Lp space ,Ocular Physiological Phenomena ,Scalp ,Network construction ,Radiological and Ultrasound Technology ,medicine.diagnostic_test ,business.industry ,Pattern recognition ,Models, Theoretical ,020601 biomedical engineering ,Neurology ,Frequency domain ,Norm (mathematics) ,Outlier ,Neurology (clinical) ,Artificial intelligence ,Anatomy ,Artifacts ,business ,Functional magnetic resonance imaging ,Algorithms ,030217 neurology & neurosurgery ,Network analysis - Abstract
Partial directed coherence (PDC), which is capable of estimating directed brain networks in the frequency domain, has been widely used in various physiological recordings such as electroencephalograms (EEGs) and functional magnetic resonance imaging. However, clinical data from EEGs are inevitably contaminated with unexpected outlier artifacts. This will result in biased networks, which are different from the original physiological mechanism because of the L2 norm structure utilized in PDC to estimate the directed links. In this work, we define a new PDC model in the Lp norm (p ≤ 1) space to restrict outlier influence and use a feasible iteration procedure to solve this model for directed network construction. The quantitative evaluation using a predefined simulation network demonstrates that Lp-PDC is more consistent with the predefined networks than LS-PDC and Lasso-PDC under various simulated outlier conditions. Applying the Lp-PDC model to resting-state EEGs with ocular artifacts also show that the proposed PDC can effectively restrict the ocular artifacts to recover the networks, which is also more consistent with the physiological basis. Both simulation and real-life EEG applications demonstrate the efficiency of the proposed PDC in suppressing the influence of outliers in EEG signals, and the proposed Lp-PDC may be helpful to capture reliable causal relationships for related studies contaminated with outlier artifacts.
- Published
- 2018
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