TY - JOUR T1 - Spike-Timing Patterns Conform to Gamma Distribution with Regional and Cell Type-Specific Characteristics JF - bioRxiv DO - 10.1101/145813 SP - 145813 AU - Meng Li AU - Kun Xie AU - Hui Kuang AU - Jun Liu AU - Deheng Wang AU - Grace E. Fox AU - Xiaojian Li AU - Yuhui Li AU - Fang Zhao AU - He Cui AU - Joe Z. Tsien Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/06/03/145813.abstract N2 - Spike-timing patterns are crucial for synaptic plasticity and neural computation, yet their statistical patterns in various brain regions which cross different mammalian species have not been examined in a systematic manner. Neurons in vivo discharge spikes with enormous variability; this irregularity is widely viewed as noise and thus often model as a Poisson-like random process. Here, we systematically examine statistical behaviors of spike-time irregularity in 13 different cortical and subcortical regions from mouse, hamster, cat and monkey brains. We show that spike-timing patterns of various projection neurons - including cortical excitatory principal cells, hippocampal pyramidal cells, inhibitory striatal medium spiny neurons, as well as dopaminergic neurons – all conform to the gamma distribution model. Moreover, gamma shapes of spike-timing patterns remain robust over different states, such as sleep vs. awake periods. Interestingly, there are significant regional variations with DA neurons, the somatosensory cortex and motor cortices showing increased regularity, whereas the V1 cortex, retrosplenial cortex, anterior cingulate cortex, striatum, amygdala and hippocampus tend to exhibit greater irregularity. Such a conserved Gamma-distribution pattern, coupled with characteristic regional variations, may influence how spike-timing patterns exert dynamic actions on neural coding and network-level plasticity.Significance Statement: Spike-timing patterns are crucial for synaptic plasticity and neural computation, yet their statistical patterns in various brain regions which cross different mammalian species have not been examined in a systematic manner. We have examine statistical behaviors of spike-time irregularity in 13 different cortical and subcortical regions from mouse, hamster, cat and monkey brains. We show that spike-timing patterns of various projection neurons all conform to the gamma distribution model. Furthermore, there are significant regional variations of the spike-timing’s regularities. In coupling with different NMDA receptor compositions across different regions, such intrinsic statistical characteristics of spiking-time distribution will likely influence not only how spike-timing patterns drive synaptic plasticity but also how cell assemblies in various circuits perform neural computation. ER -