Lisitsyn Dmitriy, Ernst Udo A
Computational Neuroscience Lab, Institute for Theoretical Physics, Department of Physics, University of Bremen, Bremen, Germany.
Front Comput Neurosci. 2019 Feb 19;13:7. doi: 10.3389/fncom.2019.00007. eCollection 2019.
Electrical stimulation is a promising tool for interacting with neuronal dynamics to identify neural mechanisms that underlie cognitive function. Since effects of a single short stimulation pulse typically vary greatly and depend on the current network state, many experimental paradigms have rather resorted to continuous or periodic stimulation in order to establish and maintain a desired effect. However, such an approach explicitly leads to forced and "unnatural" brain activity. Further, continuous stimulation can make it hard to parse the recorded activity and separate neural signal from stimulation artifacts. In this study we propose an alternate strategy: by monitoring a system in realtime, we use the existing preferred states or attractors of the network and apply short and precise pulses in order to switch between those states. When pushed into one of its attractors, one can use the natural tendency of the system to remain in such a state to prolong the effect of a stimulation pulse, opening a larger window of opportunity to observe the consequences on cognitive processing. To elaborate on this idea, we consider flexible information routing in the visual cortex as a prototypical example. When processing a stimulus, neural populations in the visual cortex have been found to engage in synchronized gamma activity. In this context, selective signal routing is achieved by changing the relative phase between oscillatory activity in sending and receiving populations (communication through coherence, CTC). In order to explore how perturbations interact with CTC, we investigate a network of interneuronal gamma (ING) oscillators composed of integrate-and-fire neurons exhibiting similar synchronization and signal routing phenomena. We develop a closed-loop stimulation paradigm based on the phase-response characteristics of the network and demonstrate its ability to establish desired synchronization states. By measuring information content throughout the model, we evaluate the effect of signal contamination caused by the stimulation in relation to the magnitude of the injected pulses and intrinsic noise in the system. Finally, we demonstrate that, up to a critical noise level, precisely timed perturbations can be used to artificially induce the effect of attention by selectively routing visual signals to higher cortical areas.
电刺激是一种很有前景的工具，可用于与神经元动力学相互作用，以识别认知功能背后的神经机制。由于单个短刺激脉冲的效应通常差异很大，并且取决于当前的网络状态，许多实验范式更倾向于采用连续或周期性刺激，以便建立和维持所需的效果。然而，这种方法明显会导致强迫性和“不自然”的大脑活动。此外，连续刺激可能会使解析记录的活动并将神经信号与刺激伪迹区分开来变得困难。在本研究中，我们提出了一种替代策略：通过实时监测系统，我们利用网络现有的偏好状态或吸引子，并施加短而精确的脉冲，以便在这些状态之间切换。当系统被推向其吸引子之一时，可以利用系统保持在这种状态的自然趋势来延长刺激脉冲的效果，从而打开一个更大的机会窗口来观察对认知处理的影响。为了详细阐述这一想法，我们将视觉皮层中的灵活信息路由作为一个典型例子。在处理刺激时，已发现视觉皮层中的神经群体参与同步伽马活动。在这种情况下，选择性信号路由是通过改变发送和接收群体中振荡活动之间的相对相位（通过相干性进行通信，CTC）来实现的。为了探索扰动如何与CTC相互作用，我们研究了一个由积分发放神经元组成的抑制性神经元伽马（ING）振荡器网络，该网络表现出类似的同步和信号路由现象。我们基于网络的相位响应特性开发了一种闭环刺激范式，并证明了其建立所需同步状态的能力。通过测量整个模型中的信息内容，我们评估了与注入脉冲的幅度和系统中的固有噪声相关的刺激引起的信号污染的影响。最后，我们证明，在达到临界噪声水平之前，精确计时的扰动可用于通过将视觉信号选择性地路由到更高皮层区域来人工诱导注意力效应。
