Ruijter B J, Hofmeijer J, Meijer H G E, van Putten M J A M
Clinical Neurophysiology, MIRA - Institute for Biomedical Technology and Technical Medicine, University of Twente, Hallenweg 15, 7522NB Enschede, The Netherlands.
Clinical Neurophysiology, MIRA - Institute for Biomedical Technology and Technical Medicine, University of Twente, Hallenweg 15, 7522NB Enschede, The Netherlands; Department of Neurology, Rijnstate Hospital, Wagnerlaan 55, 6815AD Arnhem, The Netherlands.
Clin Neurophysiol. 2017 Sep;128(9):1682-1695. doi: 10.1016/j.clinph.2017.06.245. Epub 2017 Jul 8.
In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically evolve in time. We aim to improve the understanding of pathophysiological mechanisms underlying these EEG abnormalities.
We used a mean field model comprising excitatory and inhibitory neurons, local synaptic connections, and input from thalamic afferents. Anoxic damage is modeled as aggravated short-term synaptic depression, with gradual recovery over many hours. Additionally, excitatory neurotransmission is potentiated, scaling with the severity of anoxic encephalopathy. Simulations were compared with continuous EEG recordings of 155 comatose patients after cardiac arrest.
The simulations agree well with six common categories of EEG rhythms in postanoxic encephalopathy, including typical transitions in time. Plausible results were only obtained if excitatory synapses were more severely affected by short-term synaptic depression than inhibitory synapses.
In postanoxic encephalopathy, the evolution of EEG patterns presumably results from gradual improvement of complete synaptic failure, where excitatory synapses are more severely affected than inhibitory synapses. The range of EEG patterns depends on the excitation-inhibition imbalance, probably resulting from long-term potentiation of excitatory neurotransmission.
Our study is the first to relate microscopic synaptic dynamics in anoxic brain injury to both typical EEG observations and their evolution in time.
在缺氧后昏迷中,脑电图模式可表明脑病的严重程度,且通常会随时间演变。我们旨在加深对这些脑电图异常背后病理生理机制的理解。
我们使用了一个平均场模型,该模型包含兴奋性和抑制性神经元、局部突触连接以及来自丘脑传入神经的输入。缺氧损伤被模拟为加重的短期突触抑制,并在数小时内逐渐恢复。此外,兴奋性神经传递增强,与缺氧性脑病的严重程度成比例。将模拟结果与155名心脏骤停后昏迷患者的连续脑电图记录进行比较。
模拟结果与缺氧后脑病中六种常见的脑电图节律类别吻合良好,包括随时间的典型转变。只有当兴奋性突触比抑制性突触更严重地受到短期突触抑制的影响时,才能获得合理的结果。
在缺氧后脑病中,脑电图模式的演变可能是由于完全性突触功能衰竭的逐渐改善所致,其中兴奋性突触比抑制性突触受到的影响更严重。脑电图模式的范围取决于兴奋 - 抑制失衡,这可能是由于兴奋性神经传递的长期增强所致。
我们的研究首次将缺氧性脑损伤中的微观突触动力学与典型的脑电图观察结果及其随时间的演变联系起来。