Goldman Jennifer S, Kusch Lionel, Aquilue David, Yalçınkaya Bahar Hazal, Depannemaecker Damien, Ancourt Kevin, Nghiem Trang-Anh E, Jirsa Viktor, Destexhe Alain
CNRS, Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Saclay, France.
Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France.
Front Comput Neurosci. 2023 Jan 13;16:1058957. doi: 10.3389/fncom.2022.1058957. eCollection 2022.
Hallmarks of neural dynamics during healthy human brain states span spatial scales from neuromodulators acting on microscopic ion channels to macroscopic changes in communication between brain regions. Developing a scale-integrated understanding of neural dynamics has therefore remained challenging. Here, we perform the integration across scales using mean-field modeling of Adaptive Exponential (AdEx) neurons, explicitly incorporating intrinsic properties of excitatory and inhibitory neurons. The model was run using The Virtual Brain (TVB) simulator, and is open-access in EBRAINS. We report that when AdEx mean-field neural populations are connected structural tracts defined by the human connectome, macroscopic dynamics resembling human brain activity emerge. Importantly, the model can qualitatively and quantitatively account for properties of empirically observed spontaneous and stimulus-evoked dynamics in space, time, phase, and frequency domains. Large-scale properties of cortical dynamics are shown to emerge from both microscopic-scale adaptation that control transitions between wake-like to sleep-like activity, and the organization of the human structural connectome; together, they shape the spatial extent of synchrony and phase coherence across brain regions consistent with the propagation of sleep-like spontaneous traveling waves at intermediate scales. Remarkably, the model also reproduces brain-wide, enhanced responsiveness and capacity to encode information particularly during wake-like states, as quantified using the perturbational complexity index. The model was run using The Virtual Brain (TVB) simulator, and is open-access in EBRAINS. This approach not only provides a scale-integrated understanding of brain states and their underlying mechanisms, but also open access tools to investigate brain responsiveness, toward producing a more unified, formal understanding of experimental data from conscious and unconscious states, as well as their associated pathologies.
健康人类大脑状态下神经动力学的特征跨越了从作用于微观离子通道的神经调质到脑区之间宏观通信变化的空间尺度。因此,对神经动力学进行跨尺度的综合理解仍然具有挑战性。在这里,我们使用自适应指数(AdEx)神经元的平均场模型进行跨尺度整合,明确纳入了兴奋性和抑制性神经元的内在特性。该模型使用虚拟大脑(TVB)模拟器运行,并且在EBRAINS上是开放获取的。我们报告称,当AdEx平均场神经群体通过人类连接组定义的结构束连接时,类似于人类大脑活动的宏观动力学就会出现。重要的是,该模型可以在空间、时间、相位和频域中定性和定量地解释经验观察到的自发和刺激诱发动力学的特性。皮质动力学的大规模特性显示出既源于控制从觉醒样活动到睡眠样活动转变的微观尺度适应性,也源于人类结构连接组的组织;它们共同塑造了跨脑区同步和相位相干的空间范围,这与中等尺度上睡眠样自发行波的传播一致。值得注意的是,该模型还再现了全脑范围内增强的反应性和编码信息的能力,特别是在觉醒样状态下,这是使用微扰复杂性指数量化的。该模型使用虚拟大脑(TVB)模拟器运行,并且在EBRAINS上是开放获取的。这种方法不仅提供了对大脑状态及其潜在机制的跨尺度综合理解,还提供了用于研究大脑反应性的开放获取工具,以更统一、正式地理解来自有意识和无意识状态的实验数据及其相关病理学。