Shaping Intrinsic Neural Oscillations with Periodic Stimulation
Shaping Intrinsic Neural Oscillations with Periodic Stimulation
复制标题
DOI：
10.1523/jneurosci.0236-16.2016
复制
发表时间：
2016-05-11
影响因子：
5.3
通讯作者：
Lefebvre, Jeremie
中科院分区：
文献类型：
--
作者：
Herrmann, Christoph S.;Murray, Micah M.;Lefebvre, Jeremie
节律性脑活动在神经处理和行为中起着重要作用。这些振荡的特征，包括幅度、相位和频谱，可能会受到内部状态(例如，唤醒、注意力或认知能力的变化)或外部刺激的影响。电磁刺激技术，如经颅磁刺激、经颅直流电刺激、经颅交流电刺激，在研究和临床环境中的应用越来越多。目前，依赖时间的外部刺激影响人口规模振荡的机制仍然知之甚少。在这里，我们提供了关于周期性脉动刺激参数(如幅度和频率)与递归的非线性尖峰神经网络的响应动力学之间的映射的计算见解。使用由兴奋性神经元和抑制性神经元组成的大脑皮层模型，我们系统地探索了广泛的刺激强度和频率。我们的结果表明，节律性刺激可以形成一种控制范式的基础，在这种范式中，人们可以通过多种输入驱动机制来操纵驱动网络的内在振荡特性。我们的结果表明，除了共振和夹带，非线性加速也参与了我们所建模网络的节奏响应的形成。神经网络中自发和同步振荡活动的这种非线性加速发生在强烈、高频节奏刺激的区域中。这些结果为基础和临床研究开辟了操纵同步神经活动的新视角。
Rhythmic brain activity plays an important role in neural processing and behavior. Features of these oscillations, including amplitude, phase, and spectrum, can be influenced by internal states (e.g., shifts in arousal, attention or cognitive ability) or external stimulation. Electromagnetic stimulation techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, and transcranial alternating current stimulation are used increasingly in both research and clinical settings. Currently, the mechanisms whereby time-dependent external stimuli influence population-scale oscillations remain poorly understood. Here, we provide computational insights regarding the mapping between periodic pulsatile stimulation parameters such as amplitude and frequency and the response dynamics of recurrent, nonlinear spiking neural networks. Using a cortical model built of excitatory and inhibitory neurons, we explored a wide range of stimulation intensities and frequencies systematically. Our results suggest that rhythmic stimulation can form the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven mechanisms. Our results show that, in addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network. Such nonlinear acceleration of spontaneous and synchronous oscillatory activity in a neural network occurs in regimes of intense, high-frequency rhythmic stimulation. These results open new perspectives on the manipulation of synchronous neural activity for basic and clinical research.