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Medical & Biological Engineering & Computing

, Volume 55, Issue 11, pp 1915–1926 | Cite as

Use of phase-locking value in sensorimotor rhythm-based brain–computer interface: zero-phase coupling and effects of spatial filters

  • Wenjuan JianEmail author
  • Minyou Chen
  • Dennis J. McFarland
Original Article

Abstract

Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain–computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10–15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.

Keywords

Brain–computer interface (BCI) Phase-locking value (PLV) Spatial filters Zero phase 

Notes

Acknowledgements

This work was supported in part by the National Institutes of Health (NIH) (Grants HD30146 46) (NCMRR/NICHD), EB00856 (NIBIB &NINDS), National “111” Project (B08036) and in part by the China Scholarship Council. The authors would like to thank Jonathan Carp and Li Zhang for their helpful comments on an earlier version of this paper.

Supplementary material

11517_2017_1641_MOESM1_ESM.doc (142 kb)
Supplementary material 1 (DOC 142 kb)

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Copyright information

© International Federation for Medical and Biological Engineering 2017

Authors and Affiliations

  1. 1.State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical EngineeringChongqing UniversityChongqingChina
  2. 2.National Center for Adaptive Neurotechnologies, Wadsworth CenterNew York State Department of HealthAlbanyUSA

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