Griffiths John D, McIntosh Anthony Randal, Lefebvre Jeremie
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
Front Comput Neurosci. 2020 Dec 21;14:575143. doi: 10.3389/fncom.2020.575143. eCollection 2020.
Rhythmic activity in the brain fluctuates with behaviour and cognitive state, through a combination of coexisting and interacting frequencies. At large spatial scales such as those studied in human M/EEG, measured oscillatory dynamics are believed to arise primarily from a combination of cortical (intracolumnar) and corticothalamic rhythmogenic mechanisms. Whilst considerable progress has been made in characterizing these two types of neural circuit separately, relatively little work has been done that attempts to unify them into a single consistent picture. This is the aim of the present paper. We present and examine a whole-brain, connectome-based neural mass model with detailed long-range cortico-cortical connectivity and strong, recurrent corticothalamic circuitry. This system reproduces a variety of known features of human M/EEG recordings, including spectral peaks at canonical frequencies, and functional connectivity structure that is shaped by the underlying anatomical connectivity. Importantly, our model is able to capture state- (e.g., idling/active) dependent fluctuations in oscillatory activity and the coexistence of multiple oscillatory phenomena, as well as frequency-specific modulation of functional connectivity. We find that increasing the level of sensory drive to the thalamus triggers a suppression of the dominant low frequency rhythms generated by corticothalamic loops, and subsequent disinhibition of higher frequency endogenous rhythmic behaviour of intracolumnar microcircuits. These combine to yield simultaneous decreases in lower frequency and increases in higher frequency components of the M/EEG power spectrum during states of high sensory or cognitive drive. Building on this, we also explored the effect of pulsatile brain stimulation on ongoing oscillatory activity, and evaluated the impact of coexistent frequencies and state-dependent fluctuations on the response of cortical networks. Our results provide new insight into the role played by cortical and corticothalamic circuits in shaping intrinsic brain rhythms, and suggest new directions for brain stimulation therapies aimed at state-and frequency-specific control of oscillatory brain activity.
大脑中的节律性活动会随着行为和认知状态而波动，这是通过共存和相互作用的频率组合实现的。在诸如人类脑磁图（M/EEG）研究的大空间尺度上，测量到的振荡动力学被认为主要源于皮质（柱内）和皮质丘脑节律生成机制的组合。虽然在分别表征这两种类型的神经回路方面已经取得了相当大的进展，但将它们统一成一个连贯的整体的工作相对较少。这就是本文的目的。我们提出并研究了一个基于全脑连接组的神经团块模型，该模型具有详细的远程皮质-皮质连接以及强大的、循环的皮质丘脑回路。该系统再现了人类M/EEG记录的各种已知特征，包括在标准频率处的频谱峰值，以及由潜在解剖连接塑造的功能连接结构。重要的是，我们的模型能够捕捉振荡活动中与状态（例如，空闲/活跃）相关的波动以及多种振荡现象的共存，以及功能连接的频率特异性调制。我们发现，增加对丘脑的感觉驱动水平会触发对皮质丘脑回路产生的主导低频节律的抑制，随后解除对柱内微回路高频内源性节律行为的抑制。这些共同作用导致在高感觉或认知驱动状态下，M/EEG功率谱的低频成分同时降低，高频成分增加。在此基础上，我们还探讨了脉动性脑刺激对正在进行的振荡活动的影响，并评估了共存频率和状态依赖性波动对皮质网络反应的影响。我们的结果为皮质和皮质丘脑回路在塑造内在脑节律中所起的作用提供了新的见解，并为旨在对振荡性脑活动进行状态和频率特异性控制的脑刺激疗法提出了新的方向。
