Abstract Traditionally, the electroencephalogram (EEG) has been understood as arising from rhythmic neuronal oscillators with varying degrees of synchronisation. Alternative insights, however, highlight the arrhythmic nature of the EEG, primarily inferred from broadband properties like the ubiquitous 1/ f spectrum. From the analysis of EEG simulations based on stochastic pulse superposition, we identified mathematical relations between the statistical features of the superposition signal and the