Local and interareal alpha and low-beta band oscillation dynamics underlie the bilateral field advantage in visual working memory.

Visual working memory has a limited maximum capacity, which can be larger if stimuli are presented bilaterally vs. unilaterally. However, the neuronal mechanisms underlying this bilateral field advantage are not known.

Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture.

Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or 'oscillatoriness' per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantification of rhythmicity. We applied pACF to human intracerebral stereoelectroencephalography (SEEG) and magnetoencephalography (MEG) data and uncovered a spectrally and anatomically fine-grained cortical architecture in the rhythmicity of single- and multi-frequency neuronal oscillations.