Fast dynamics of brain regional networks underlying cognition

认知过程在大脑中由区域网络实现，这些区域网络基于遗传编程和环境导向可塑性（学习）衍生的复杂连接，对传入（感觉）和存储（记忆）信息进行各种计算。很明显，在每个认知“操作”过程中，信息和控制信号必须在这些大脑区域之间传递，例如，新感觉信息的前馈扫描、错误反馈、对传入刺激的准备程度提高或降低的注意信号等。一些区域网络正变得相当容易理解，至少在它们可能进行的计算方面是这样。我们已经开始使用先进的技术来描述这些网络的快速动态，例如阅读网络和注意力导向网络。通过“快速动力学”，我指的是信息和控制信号的传输，在不同的振荡频率下，在网络中涉及的区域之间以几十到几百毫秒的时间尺度进行。我将在几个重要的方向上扩展这项工作。首先，我打算研究各种各样的干扰对快速动态网络的影响，这两个网络都是我们过去看到的，例如阅读、注意力、知觉意识，以及一些对我们来说是新的网络，例如工作记忆、视觉和听觉图像。干扰的类型包括自然干扰，如阅读障碍、习惯性大麻使用、死亡和经颅刺激，包括阴极直流电刺激（tDCS）和噪音（tRNS）。其次，我打算研究大脑刺激如何影响这些网络的快速动态，包括正常的和挑战的。在正常网络的情况下，可能会提高时间精度和性能，而对于挑战网络，可能会部分恢复正常的时间动态。第三，我将开始描述皮质-皮质下回路的快速动态。我将采用直接涉及特定皮层下回路的技术，如杏仁核、枕核和丘脑MD，它们可能有可靠的皮层镜像（例如，杏仁核的前额叶，枕核的PPC）。我将进行fMRI-EEG联合注册研究，通过fMRI验证皮层下受累，绘制功能性和有效的连通性，从而识别皮层镜像区域，EEG研究该网络的快速动态。最后，我将继续对振荡大脑网络的计算建模进行理论研究，目的是描述支持认知的振荡大脑区域之间的相互作用。我希望这项工作不仅会对大脑区域神经网络如何实现认知过程的基本理解产生成果，而且最终会在改善大脑挑战（如阅读障碍）方面找到应用。衰老和吸毒。

Cognitive processes are implemented in the brain by regional networks that perform a variety of computations on incoming (sensory) and stored (memory) information based on intricate connectivity derived from both genetic programming and environmentally-directed plasticity (learning). It is clear that during each cognitive “operation” information and control signals must be passed among these brain regions, e.g., the feedforward sweep of new sensory information, error feedback, attentional signals turning up or down readiness for incoming stimuli, etc. Some of the regional networks are becoming fairly well understood, at least in terms of the sort of computations they might be doing. We have begun to characterize the fast dynamics of these networks using advanced techniques, for example the reading network and the attention orienting network. By “fast dynamics” I mean the transfer of information and control signals, at various oscillatory frequencies, between the regions involved in the network on a time scale of tens to hundreds of ms. I will expand this work in several important directions. First, I intend to investigate the effects of disruptions of various sorts on the fast dynamics both of the networks we have looked at in the past, e.g. reading, attention, perceptual consciousness, and of some that are new to us, e.g., working memory, visual and auditory imagery. The types of disruptions include natural ones, such as dyslexia, habitual cannabis use, dying, and transcranial stimulation, both cathodal direct current stimulation (tDCS) and noise (tRNS). Second I intend to investigate how brain stimulation might affect the fast dynamics in these networks, both normal and challenged. In the case of normal networks there might be improved temporal precision as well as improved performance, and for challenged networks there might be partial restoration of normal temporal dynamics. Third, I will begin to characterize the fast dynamics of cortico-subcortical circuits. I will employ techniques that directly involve particular subcortical circuits, such as amygdala and pulvinar and MD thalamus and that might have reliable cortical mirrors (e.g., prefrontal for amygdala, PPC for pulvinar). I will do co-registered fMRI-EEG studies, using fMRI to verify the subcortical involvement and to map out the functional and effective connectivity so as to identify cortical mirror regions, and EEG to study the fast dynamics of this network. Finally, I will continue theoretical studies of computational modeling of oscillatory brain networks with the goal of characterizing the interactions between oscillating brain regions that support cognition. I expect this work will not only be fruitful for a fundamental understanding of how brain-regional neural networks implement cognitive processes, but also will eventually find application in ameliorating brain challenges such as dyslexia. aging and drug use.