  The temporal activity of many biological systems, including neural circuits,
exhibits fluctuations simultaneously varying over a large range of timescales.
The mechanisms leading to this temporal heterogeneity are yet unknown. Here we
show that random neural networks endowed with a distribution of self-couplings,
representing functional neural clusters of different sizes, generate multiple
timescales activity spanning several orders of magnitude. When driven by a
time-dependent broadband input, slow and fast neural clusters preferentially
entrain slow and fast spectral components of the input, respectively,
suggesting a potential mechanism for spectral demixing in cortical circuits.
