RT Journal Article
T1 Phase locking value revisited: teaching new tricks to an old dog
A1 Bruña Fernández, Ricardo
A1 Maestu Unturbe, Fernando
A1 Pereda, Ernesto
AB Objective. Despite the increase in calculation power over the last few 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. Approach. We start from the original implementation of phase locking value (PLV) and re-formulated it in a computationally very efficient way. What is more, 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). Main results. The new implementation of PLV avoids some highly CPU-expensive operations and achieves a 100-fold speedup over the original algorithm. The new derived metrics were highly robust in the presence of volume conduction. Moreover, ciPLV proved capable of ignoring zero-lag connectivity, while correctly estimating nonzero-lag connectivity. Significance. Our implementation of PLV makes it possible to calculate whole-brain connectivity in much shorter times. The results of the simulations using ciPLV suggest that this metric is ideal to measure synchronization in the presence of volume conduction or source leakage effects.
PB IOP Publishing
SN 1741-2552
YR 2018
FD 2018-07-28
LK https://hdl.handle.net/20.500.14352/100167
UL https://hdl.handle.net/20.500.14352/100167
LA eng
NO Ricardo Bruña et al 2018 J. Neural Eng. 15 056011 DOI 10.1088/1741-2552/aacfe4
NO Ministerio de Economía y Competitivida
DS Docta Complutense
RD 17 ago 2024