Connelly William M
Neuroscience Division, School of Biosciences, Cardiff University, Life Sciences Building, Cardiff, United Kingdom.
PLoS One. 2014 Feb 28;9(2):e89995. doi: 10.1371/journal.pone.0089995. eCollection 2014.
Computational models of gamma oscillations have helped increase our understanding of the mechanisms that shape these 40-80 Hz cortical rhythms. Evidence suggests that interneurons known as basket cells are responsible for the generation of gamma oscillations. However, current models of gamma oscillations lack the dynamic short term synaptic plasticity seen at basket cell-basket cell synapses as well as the large autaptic synapses basket cells are known to express. Hence, I sought to extend the Wang-Buzsáki model of gamma oscillations to include these features. I found that autapses increased the synchrony of basket cell membrane potentials across the network during neocortical gamma oscillations as well as allowed the network to oscillate over a broader range of depolarizing drive. I also found that including realistic synaptic depression filtered the output of the network. Depression restricted the network to oscillate in the 60-80 Hz range rather than the 40-120 Hz range seen in the standard model. This work shows the importance of including accurate synapses in any future model of gamma oscillations.
γ振荡的计算模型有助于增进我们对塑造这些40-80赫兹皮层节律机制的理解。有证据表明，被称为篮状细胞的中间神经元负责γ振荡的产生。然而，当前的γ振荡模型缺乏在篮状细胞-篮状细胞突触中所见的动态短期突触可塑性，以及篮状细胞已知会表达的大型自突触。因此，我试图扩展γ振荡的王-布扎克模型以纳入这些特征。我发现自突触在新皮层γ振荡期间增加了整个网络中篮状细胞膜电位的同步性，并且使网络能够在更广泛的去极化驱动范围内振荡。我还发现纳入现实的突触抑制会过滤网络的输出。抑制使网络限制在60-80赫兹范围内振荡，而不是标准模型中所见的40-120赫兹范围。这项工作表明在未来任何γ振荡模型中纳入精确突触的重要性。
