Heterogeneity of timescales in random networks with bistable units

Recent experiments reveal that neural circuits operate in a regime with simultaneous presence of multiple timescales. Such heterogeneity of timescales was observed not only across different brain areas (Murray JD et al 2014) but also across neurons within the same circuit (Cavanagh SE et al 2016) during periods of ongoing activity, suggesting that it may be an intrinsic dynamical property of recurrent circuits. Here we investigate which neural mechanisms may support this heterogeneous distribution of timescales. We show that random neural networks with bistable units (Stern M et al 2014) naturally exhibit large heterogeneity of timescales across neurons in the presence of a distribution of self-couplings. We provide a biophysical interpretation for the bistable units in our rate network in terms of Hebbian assemblies. We show that, in recurrent spiking networks where excitatory and inhibitory neurons are arranged in assemblies, one can achieve a heterogeneous distribution of timescales when assembly sizes are unequal. We thus interpret the rate network self-couplings as potentiated synaptic couplings between neurons within the same assembly. Our results establish a novel theoretical framework to investigate the observed heterogeneity of intrinsic neuronal timescales.