Washington University in St. Louis, St. Louis, USA.
University of California, Berkeley, Berkeley, USA.
Sci Rep. 2020 Sep 29;10(1):15997. doi: 10.1038/s41598-020-72936-1.
Neurons in sensory cortices are more naturally and deeply integrated than any current neural population recording tools (e.g. electrode arrays, fluorescence imaging). Two concepts facilitate efforts to observe population neural code with single-cell recordings. First, even the highest quality single-cell recording studies find a fraction of the stimulus information in high-dimensional population recordings. Finding any of this missing information provides proof of principle. Second, neurons and neural populations are understood as coupled nonlinear differential equations. Therefore, fitted ordinary differential equations provide a basis for single-trial single-cell stimulus decoding. We obtained intracellular recordings of fluctuating transmembrane current and potential in mouse visual cortex during stimulation with drifting gratings. We use mean deflection from baseline when comparing to prior single-cell studies because action potentials are too sparse and the deflection response to drifting grating stimuli (e.g. tuning curves) are well studied. Equation-based decoders allowed more precise single-trial stimulus discrimination than tuning-curve-base decoders. Performance varied across recorded signal types in a manner consistent with population recording studies and both classification bases evinced distinct stimulus-evoked phases of population dynamics, providing further corroboration. Naturally and deeply integrated observations of population dynamics would be invaluable. We offer proof of principle and a versatile framework.
感觉皮层中的神经元比任何当前的神经群体记录工具（例如电极阵列、荧光成像）更自然、更深入地融合在一起。有两个概念可以帮助我们通过单细胞记录来观察群体神经编码。首先，即使是最高质量的单细胞记录研究也只能在高维群体记录中找到一部分刺激信息。找到任何缺失的信息都提供了原理证明。其次，神经元和神经群体被理解为耦合的非线性微分方程。因此，拟合的常微分方程为单次试验单细胞刺激解码提供了基础。我们在小鼠视觉皮层中用漂移光栅刺激时获得了波动跨膜电流和电位的细胞内记录。我们使用与之前的单细胞研究相比时的基线平均偏差，因为动作电位太稀疏，并且漂移光栅刺激的偏转响应（例如调谐曲线）已经得到了很好的研究。基于方程的解码器比基于调谐曲线的解码器能够更精确地进行单次试验刺激分类。记录信号类型的性能变化方式与群体记录研究一致，并且两种分类基础都表现出明显的群体动力学诱发阶段，提供了进一步的证实。对群体动态的自然而深入的观察将是非常宝贵的。我们提供了原理证明和一个通用的框架。
