Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095-1763.
Department of Physics & Astronomy, University of California, Los Angeles, Los Angeles, California 90095-1596.
J Neurosci. 2023 Jan 11;43(2):240-260. doi: 10.1523/JNEUROSCI.1195-22.2022. Epub 2022 Nov 18.
The preBötzinger Complex (preBötC) encodes inspiratory time as rhythmic bursts of activity underlying each breath. Spike synchronization throughout a sparsely connected preBötC microcircuit initiates bursts that ultimately drive the inspiratory motor patterns. Using minimal microcircuit models to explore burst initiation dynamics, we examined the variability in probability and latency to burst following exogenous stimulation of a small subset of neurons, mimicking experiments. Among various physiologically plausible graphs of 1000 excitatory neurons constructed using experimentally determined synaptic and connectivity parameters, directed Erdős-Rényi graphs with a broad (lognormal) distribution of synaptic weights best captured the experimentally observed dynamics. preBötC synchronization leading to bursts was regulated by the efferent connectivity of spiking neurons that are optimally tuned to amplify modest preinspiratory activity through input convergence. Using graph-theoretic and machine learning-based analyses, we found that input convergence of efferent connectivity at the next-nearest neighbor order was a strong predictor of incipient synchronization. Our analyses revealed a crucial role of synaptic heterogeneity in imparting exceptionally robust yet flexible preBötC attractor dynamics. Given the pervasiveness of lognormally distributed synaptic strengths throughout the nervous system, we postulate that these mechanisms represent a ubiquitous template for temporal processing and decision-making computational motifs. Mammalian breathing is robust, virtually continuous throughout life, yet is inherently labile: to adapt to rapid metabolic shifts (e.g., fleeing a predator or chasing prey); for airway reflexes; and to enable nonventilatory behaviors (e.g., vocalization, breathholding, laughing). Canonical theoretical frameworks-based on pacemakers and intrinsic bursting-cannot account for the observed robustness and flexibility of the preBötzinger Complex rhythm. Experiments reveal that network synchronization is the key to initiate inspiratory bursts in each breathing cycle. We investigated preBötC synchronization dynamics using network models constructed with experimentally determined neuronal and synaptic parameters. We discovered that a fat-tailed (non-Gaussian) synaptic weight distribution-a manifestation of synaptic heterogeneity-augments neuronal synchronization and attractor dynamics in this vital rhythmogenic network, contributing to its extraordinary reliability and responsiveness.
preBötzinger 复合体(preBötC)将吸气时间编码为每个呼吸的节律性爆发活动。稀疏连接的 preBötC 微电路中的尖峰同步会引发爆发,最终驱动吸气运动模式。使用最小的微电路模型来探索爆发起始动力学,我们研究了在外源性刺激一小部分神经元(模拟实验)后,爆发的概率和潜伏期的变化。在所构建的 1000 个兴奋性神经元的各种具有生理意义的图中,使用实验确定的突触和连接参数构建的具有广泛(对数正态)突触权重分布的有向 Erdős-Rényi 图最好地捕捉到了实验观察到的动力学。导致爆发的 preBötC 同步受放电神经元传出连接的调节,这些神经元的传出连接通过输入汇聚被最佳地调整以放大适度的预吸气活动。使用图论和基于机器学习的分析,我们发现下一个最近邻阶的传出连接的输入汇聚是同步开始的强有力预测指标。我们的分析揭示了突触异质性在赋予异常稳健但灵活的 preBötC 吸引子动力学方面的关键作用。鉴于整个神经系统中普遍存在对数正态分布的突触强度,我们假设这些机制代表了时间处理和决策计算基元的普遍模板。哺乳动物呼吸稳健,几乎在整个生命周期中都是连续的,但本质上是不稳定的:为了适应快速的代谢变化(例如,逃避捕食者或追逐猎物);为了气道反射;并为了实现非通气行为(例如,发声、屏息、大笑)。基于起搏器和内在爆发的经典理论框架不能解释 preBötzinger 复合体节律所观察到的稳健性和灵活性。实验表明,网络同步是启动每个呼吸周期吸气爆发的关键。我们使用实验确定的神经元和突触参数构建的网络模型来研究 preBötC 同步动力学。我们发现,胖尾(非高斯)突触权重分布——突触异质性的表现——增强了这个重要节律生成网络中的神经元同步和吸引子动力学,使其具有非凡的可靠性和响应能力。