Tupikov Yevhen, Jin Dezhe Z
Departments of Physics and Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America.
PLoS Comput Biol. 2021 Mar 17;17(3):e1008824. doi: 10.1371/journal.pcbi.1008824. eCollection 2021 Mar.
During development, neurons arrive at local brain areas in an extended period of time, but how they form local neural circuits is unknown. Here we computationally model the emergence of a network for precise timing in the premotor nucleus HVC in songbird. We show that new projection neurons, added to HVC post hatch at early stages of song development, are recruited to the end of a growing feedforward network. High spontaneous activity of the new neurons makes them the prime targets for recruitment in a self-organized process via synaptic plasticity. Once recruited, the new neurons fire readily at precise times, and they become mature. Neurons that are not recruited become silent and replaced by new immature neurons. Our model incorporates realistic HVC features such as interneurons, spatial distributions of neurons, and distributed axonal delays. The model predicts that the birth order of the projection neurons correlates with their burst timing during the song.
在发育过程中，神经元会在较长一段时间内到达局部脑区，但它们如何形成局部神经回路尚不清楚。在这里，我们通过计算对鸣禽前运动核HVC中精确计时网络的出现进行建模。我们表明，在歌曲发育早期孵化后添加到HVC的新投射神经元被招募到不断增长的前馈网络的末端。新神经元的高自发活动使它们成为通过突触可塑性在自组织过程中被招募的主要目标。一旦被招募，新神经元会在精确的时间轻易放电，并变得成熟。未被招募的神经元会变得沉默，并被新的未成熟神经元取代。我们的模型纳入了HVC的实际特征，如中间神经元、神经元的空间分布和分布式轴突延迟。该模型预测，投射神经元的出生顺序与其在歌曲中的爆发时间相关。
