Bennett Maxwell R, Farnell Les, Gibson William G, Lagopoulos Jim
The Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia.
Mathematical Biology, University of Sydney, Sydney, NSW, Australia.
Neurobiol Stress. 2019 Apr 1;10:100159. doi: 10.1016/j.ynstr.2019.100159. eCollection 2019 Feb.
The synaptic networks in the amygdala have been the subject of intense interest in recent times, primarily because of the role of this structure in emotion. Fear and its extinction depend on the workings of these networks, with particular interest in extinction because of its potential to ameliorate adverse symptoms associated with post-traumatic stress disorder. Here we place emphasis on the extinction networks revealed by recent techniques, and on the probable plasticity properties of their synaptic connections. We use modules of neurons representing each of the principal components identified as involved in extinction. Each of these modules consists of neural networks, containing specific ratios of excitatory and specialized inhibitory neurons as well as synaptic plasticity mechanisms appropriate for the component of the amygdala they represent. While these models can produce dynamic output, here we concentrate on the equilibrium outputs and do not model the details of the plasticity mechanisms. Pavlovian fear conditioning generates a fear memory in the lateral amygdala module that leads to activation of neurons in the basal nucleus fear module but not in the basal nucleus extinction module. Extinction protocols excite infralimbic medial prefrontal cortex neurons (IL) which in turn excite so-called extinction neurons in the amygdala, leading to the release of endocannabinoids from them and an increase in efficacy of synapses formed by lateral amygdala neurons on them. The model simulations show how such a mechanism could explain experimental observations involving the role of IL as well as endocannabinoids in different temporal phases of extinction.
杏仁核中的突触网络近来一直是人们密切关注的对象,主要是因为该结构在情绪方面所起的作用。恐惧及其消退取决于这些网络的运作,消退尤其受到关注,因为它有可能改善与创伤后应激障碍相关的不良症状。在此,我们重点关注近期技术所揭示的消退网络,以及其突触连接可能具有的可塑性特性。我们使用代表确定参与消退过程的每个主要成分的神经元模块。这些模块中的每一个都由神经网络组成,包含特定比例的兴奋性神经元和特殊的抑制性神经元,以及适合它们所代表的杏仁核成分的突触可塑性机制。虽然这些模型可以产生动态输出,但在此我们专注于平衡输出,并未对可塑性机制的细节进行建模。经典条件恐惧训练在杏仁核外侧模块中产生恐惧记忆,该记忆会导致基底核恐惧模块中的神经元激活,但不会导致基底核消退模块中的神经元激活。消退训练会激发眶下内侧前额叶皮质神经元(IL),这些神经元进而会激发杏仁核中所谓的消退神经元,导致它们释放内源性大麻素,并增强杏仁核外侧神经元在其上形成的突触的效能。模型模拟展示了这样一种机制如何能够解释涉及IL以及内源性大麻素在消退不同时间阶段作用的实验观察结果。