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Spike-timing patterns-crucial for synaptic plasticity and neural computation-are 22 often modeled as Poisson-like random processes, log-normal distribution or gamma-23 distribution patterns, each with different underlying assumptions that may or may not be 24 biologically true. However, it is not entirely clear whether (and how well) these different 25 models would or would not capture spike-timing statistical patterns across different 26 neurons, regions, animal species and cognitive states. Here, we examine statistical patterns 27 of spike-timing irregularity in 13 different cortical and subcortical regions from mouse, 28 hamster, cat and monkey brains. In contrast to the widely-assumed Poisson or log-normal 29 distribution patterns, we show that spike-timing patterns of various projection neurons-30 including cortical excitatory principal cells, hippocampal pyramidal cells, inhibitory 31 striatal medium spiny neurons and dopaminergic neurons, as well as fast-spiking 32 interneurons–all invariantly conform to the gamma-distribution model. While higher 33 regularity in spike-timing patterns are observed in a few cases, such as mouse DA neurons 34 and monkey motor cortical neurons, there is no clear tendency in increased firing regularity 35 from the sensory and subcortical neurons to prefrontal or motor cortices, as previously 36 entertained. Moreover, gamma shapes of spike-timing patterns remain robust over various 37 natural cognitive states, such as sleep, awake periods, or during fearful episodic 38 experiences. Interestingly, ketamine-induced general anesthesia or unconsciousness is 39 associated with the breakdown of forebrain spike …