Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Brain Stimul. 2019 Nov-Dec;12(6):1402-1409. doi: 10.1016/j.brs.2019.07.005. Epub 2019 Jul 10.
Deep brain stimulation (DBS) is a successful clinical therapy for a wide range of neurological disorders; however, the physiological mechanisms of DBS remain unresolved. While many different hypotheses currently exist, our analyses suggest that high frequency (∼100 Hz) stimulation-induced synaptic suppression represents the most basic concept that can be directly reconciled with experimental recordings of spiking activity in neurons that are being driven by DBS inputs.
The goal of this project was to develop a simple model system to characterize the excitatory post-synaptic currents (EPSCs) and action potential signaling generated in a neuron that is strongly connected to pre-synaptic glutamatergic inputs that are being directly activated by DBS.
We used the Tsodyks-Markram (TM) phenomenological synapse model to represent depressing, facilitating, and pseudo-linear synapses driven by DBS over a wide range of stimulation frequencies. The EPSCs were then used as inputs to a leaky integrate-and-fire neuron model and we measured the DBS-triggered post-synaptic spiking activity.
Synaptic suppression was a robust feature of high frequency stimulation, independent of the synapse type. As such, the TM equations were used to define alternative DBS pulsing strategies that maximized synaptic suppression with the minimum number of stimuli.
Synaptic suppression provides a biophysical explanation to the intermittent, but still time-locked, post-synaptic firing characteristics commonly seen in DBS experimental recordings. Therefore, network models attempting to analyze or predict the effects of DBS on neural activity patterns should integrate synaptic suppression into their simulations.
深部脑刺激(DBS)是一种成功的临床疗法,适用于广泛的神经疾病;然而,DBS 的生理机制仍未解决。虽然目前存在许多不同的假设,但我们的分析表明,高频(~100 Hz)刺激诱导的突触抑制代表了可以与 DBS 输入驱动的神经元中尖峰活动的实验记录直接协调的最基本概念。
本项目的目标是开发一个简单的模型系统,以表征与直接由 DBS 激活的前谷氨酸能输入强连接的神经元中产生的兴奋性突触后电流(EPSC)和动作电位信号。
我们使用 Tsodyks-Markram(TM)现象学突触模型来表示在广泛的刺激频率范围内由 DBS 驱动的压抑、促进和伪线性突触。然后,将 EPSC 用作漏电积分和放电神经元模型的输入,我们测量了 DBS 触发的突触后尖峰活动。
突触抑制是高频刺激的一个强大特征,与突触类型无关。因此,TM 方程被用于定义替代 DBS 脉冲策略,这些策略以最小的刺激次数最大化突触抑制。
突触抑制为 DBS 实验记录中常见的间歇性但仍时间锁定的突触后放电特征提供了一种生物物理解释。因此,试图分析或预测 DBS 对神经活动模式影响的网络模型应将突触抑制纳入其模拟中。