Ly Cheng, Barreiro Andrea K, Gautam Shree Hari, Shew Woodrow L
Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA.
Department of Mathematics, Southern Methodist University, Dallas, TX 75275, USA.
iScience. 2021 Aug 4;24(9):102946. doi: 10.1016/j.isci.2021.102946. eCollection 2021 Sep 24.
The spiking variability of neural networks has important implications for how information is encoded to higher brain regions. It has been well documented by numerous labs in many cortical and motor regions that spiking variability decreases with stimulus onset, yet whether this principle holds in the OB has not been tested. In stark contrast to this common view, we demonstrate that the onset of sensory input can cause an increase in the variability of neural activity in the mammalian OB. We show this in both anesthetized and awake rodents. Furthermore, we use computational models to describe the mechanisms of this phenomenon. Our findings establish sensory evoked increases in spiking variability as a viable alternative coding strategy.
神经网络的脉冲发放变异性对于信息如何编码至更高脑区具有重要意义。众多实验室已在许多皮质和运动区域充分证明，随着刺激开始，脉冲发放变异性会降低，但这一原理在嗅球（OB）中是否成立尚未得到验证。与这一普遍观点形成鲜明对比的是，我们证明感觉输入的开始会导致哺乳动物嗅球中神经活动变异性增加。我们在麻醉和清醒的啮齿动物中均证实了这一点。此外，我们使用计算模型来描述这一现象的机制。我们的研究结果确立了感觉诱发的脉冲发放变异性增加作为一种可行的替代编码策略。
