Growth Dynamics Explain the Development of Spatiotemporal Burst Activity of Young Cultured Neuronal Networks in Detail

A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP) synapses (so, no long-term potentiation, LTP, or depression, LTD, was included). However, elevated pre-phases (burst leaders) and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

解离大鼠皮层细胞的体外分离培养神经元网络的典型特征为同步尖峰放电，该现象被称为爆发式放电（bursting），于细胞铺板后约一周开始出现，此时解离的细胞已伸出足够的神经突并形成充足的突触连接。

本文为体外培养神经元网络仿真模型系列三篇研究的第三篇。此前两项研究[26, 27]已证实，随机循环神经网络活动模型可生成与实验数据高度相似的爆发内与爆发间活动模式。该类网络以噪声或起搏点驱动，采用仅搭载短期可塑性（short-term plastic, STP）突触的Izhikevich神经元单元（Izhikevich-neuronal elements），因此未纳入长时程增强（long-term potentiation, LTP）与长时程抑制（long-term depression, LTD）机制。

但在网络发育过程中通常出现的爆发主波形的前置高放电阶段（爆发先导期，burst leaders）与后置阶段，尚未得到充分细致的仿真。该细节缺失的原因可能在于，随机模型完全未考虑网络拓扑结构与生长模型。

因此，本文首次在活动模型中加入生长模型，赋予网络时变拓扑结构，以更细致地阐释爆发波形。本次研究同样未纳入LTP与LTD机制。

整合的生长-活动模型可生成符合真实生理情况的爆发式放电模式。对各类相互依存的网络参数进行自动调整，是本研究方法的核心优势之一。时空爆发活动已通过实验数据得到验证。

根据网络规模的不同，可在网络边界处观察到波回响机制，该机制或可解释爆发主波形前后的高放电阶段的产生。

综上，研究结果证实，加入拓扑结构与生长模型可详尽细致地阐释爆发波形，并提示年轻的体外培养神经元网络尚未具备/无需LTP与LTD机制。