Leading eigenvector decomposition (LEiDA)

Extract the leading eigenvector from a series of instantaneous phase-locking matrices. The sign of each eigenvector is normalised so that its sum is non-positive, following the LEiDA convention.

Usage

get_leida(sync_conn)

Arguments

sync_conn

Numeric array [N, N, Tmax]. Instantaneous phase-locking matrices, as returned by dyn_phase_lock().

Value

Numeric matrix [Tmax × N]. Leading eigenvectors, one per timepoint.

References

Cabral, J. et al. (2017). Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest. Scientific Reports, 7(1), 5135. doi:10.1038/s41598-017-05425-7

Lord, L.-D. et al. (2019). Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin. NeuroImage, 199, 127–142. doi:10.1016/j.neuroimage.2019.05.060