Phase Locking Value revisited: teaching new tricks to an old dog
Ricardo Bru\~na, Fernando Maest\'u, Ernesto Pereda

TL;DR
This paper introduces a highly efficient reformulation of the Phase Locking Value algorithm, enabling fast whole-brain connectivity estimation and proposing new metrics insensitive to zero-lag synchronization, improving robustness against volume conduction.
Contribution
Reformulates PLV for 100-fold speedup and introduces ciPLV and iPLV metrics that are robust to volume conduction and zero-lag connectivity effects.
Findings
Achieved 100-fold speedup over original PLV implementation.
Proposed ciPLV effectively ignores zero-lag connectivity.
Metrics are robust in presence of volume conduction.
Abstract
Despite the increase in calculation power in the last decades, the estimation of brain connectivity is still a tedious task. The high computational cost of the algorithms escalates with the square of the number of signals evaluated, usually in the range of thousands. In this work we propose a re-formulation of a widely used algorithm that allows the estimation of whole brain connectivity in much smaller times. We start from the original implementation of Phase Locking Value (PLV) and re-formulated it in a highly computational efficient way. Besides, this formulation stresses its strong similarity with coherence, which we used to introduce two new metrics insensitive to zero lag synchronization, the imaginary part of PLV (iPLV) and its corrected counterpart (ciPLV). The new implementation of PLV avoids some highly CPU-expensive operations, and achieved a 100-fold speedup over the…
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