School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran.
PLoS Comput Biol. 2023 Feb 1;19(2):e1010853. doi: 10.1371/journal.pcbi.1010853. eCollection 2023 Feb.
The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.
大脑的突触组织通过活动依赖性突触可塑性不断改变。在几种神经疾病中，异常的神经元活动和病理性的突触连接可能会严重损害正常的大脑功能。通过治疗性刺激对神经元回路进行重组有可能恢复正常的大脑动态。越来越多的证据表明，时间刺激模式对刺激的持久治疗效果起着至关重要的作用。在这里，我们测试了一种特定的脑刺激模式是否可以通过尖峰时间依赖性可塑性（STDP）来抑制病理性强的群体间突触连接。更具体地说，我们测试了向两个相互作用的神经元群体施加刺激时引入时间延迟如何有效地将它们解耦。为此，我们首先使用了一个可处理的模型，即两个双向耦合的漏积分和放电（LIF）神经元，从理论上分析了用于解耦的最佳刺激频率和时间延迟范围。然后，我们将结果扩展到两个相互连接的神经元群体（模块），其中群体间的延迟连接通过 STDP 进行修改。正如理论结果所预测的，适当的时间延迟刺激通过 STDP 导致两个模块系统解耦，即通过忘记两个群体之间的病理性强突触相互作用。基于连接的整体拓扑结构，两个模块的解耦继而导致种群的去同步，这种去同步会持续到刺激停止之后。时间延迟刺激的解耦效应可以通过时间延迟的爆发刺激以及时间延迟的连续模拟来实现。我们的研究结果为进一步优化各种多通道刺激方案提供了思路，这些方案旨在对患病的大脑网络进行治疗性重塑。
