Fig. 1.

KS model schematic, computational workflow, and event detection. (A) SC weight and length matrix. (B) Node pair $(i,j)$ linked by an edge $ij$ and its corresponding phases $\mathit{\theta }(t)$. (C) Oscillator time series $\text{sin}(\theta \left(t\right))$. (D) HRF used for convolving oscillator time series to yield BOLD time series (E). (F) Elementwise product of normalized BOLD time series yields edge time series. (G) RSS of all edge time series yields RSS amplitude time series. The null model consists of a distribution of null RSS amplitudes computed from randomly shifted node time series. Gray dots show amplitudes from 100 null models, stippled line indicates the $P<0.001$ cutoff derived from 1,000 permutation nulls. Peaks exceeding the cutoff indicated by inverted triangles correspond to events. Data shown here computed from a representative run ($k=280$, 12 events detected).