Molkov Yaroslav I, Borgmann Anke, Koizumi Hidehiko, Hama Noriyuki, Zhang Ruli, Smith Jeffrey C
Department of Mathematics and Statistics, Neuroscience Institute, Georgia State University, Atlanta, GA.
Cellular and Systems Neurobiology Section, NINDS, NIH, Bethesda, MD.
bioRxiv. 2025 Jan 17:2024.08.12.607656. doi: 10.1101/2024.08.12.607656.
Unraveling synaptic interactions between excitatory and inhibitory interneurons within rhythmic neural circuits, such as central pattern generation (CPG) circuits for rhythmic motor behaviors, is critical for deciphering circuit interactions and functional architecture, which is a major problem for understanding how neural circuits operate. Here we present a general method for extracting and separating patterns of inhibitory and excitatory synaptic conductances at high temporal resolution from single neuronal intracellular recordings in rhythmically active networks. These post-synaptic conductances reflect the combined synaptic inputs from the key interacting neuronal populations and can reveal the functional connectome of the active circuits. To illustrate the applicability of our analytic technique, we employ our method to infer the synaptic conductance profiles in identified rhythmically active interneurons within key microcircuits of the mammalian (mature rat) brainstem respiratory CPG and provide a perspective on how our approach can resolve the functional interactions and circuit organization of these interneuron populations. We demonstrate the versatility of our approach, which can be applied to any other rhythmic circuits where conditions allow for neuronal intracellular recordings.
解析节律性神经回路（如用于节律性运动行为的中枢模式发生器（CPG）回路）中兴奋性和抑制性中间神经元之间的突触相互作用，对于解读回路相互作用和功能架构至关重要，而这是理解神经回路如何运作的一个主要问题。在此，我们提出了一种通用方法，可从节律性活动网络中的单个神经元细胞内记录中，以高时间分辨率提取和分离抑制性和兴奋性突触电导模式。这些突触后电导反映了关键相互作用神经元群体的综合突触输入，并且能够揭示活动回路的功能连接组。为了说明我们分析技术的适用性，我们运用该方法推断哺乳动物（成年大鼠）脑干呼吸CPG关键微回路中已识别的节律性活动中间神经元的突触电导分布，并就我们的方法如何解析这些中间神经元群体的功能相互作用和回路组织提供一个视角。我们展示了我们方法的通用性，该方法可应用于条件允许进行神经元细胞内记录的任何其他节律性回路。
