Kim D, Samarth P, Feng F, Pare D, Nair Satish S
Electrical and Computer Engineering, University of Missouri, Columbia, MO, 65211, USA.
Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, 197 University Avenue, Newark, NJ, 07102, USA.
Brain Struct Funct. 2016 May;221(4):2163-82. doi: 10.1007/s00429-015-1037-4. Epub 2015 Apr 10.
Competitive synaptic interactions between principal neurons (PNs) with differing intrinsic excitability were recently shown to determine which dorsal lateral amygdala (LAd) neurons are recruited into a fear memory trace. Here, we explored the contribution of these competitive interactions in determining the stimulus specificity of conditioned fear associations. To this end, we used a realistic biophysical computational model of LAd that included multi-compartment conductance-based models of 800 PNs and 200 interneurons. To reproduce the continuum of spike frequency adaptation displayed by PNs, the model included three subtypes of PNs with high, intermediate, and low spike frequency adaptation. In addition, the model network integrated spatially differentiated patterns of excitatory and inhibitory connections within LA, dopaminergic and noradrenergic inputs, extrinsic thalamic and cortical tone afferents to simulate conditioned stimuli as well as shock inputs for the unconditioned stimulus. Last, glutamatergic synapses in the model could undergo activity-dependent plasticity. Our results suggest that plasticity at both excitatory (PN-PN) and di-synaptic inhibitory (PN-ITN and, particularly, ITN-PN) connections are major determinants of the synaptic competition governing the assignment of PNs to the memory trace. The model also revealed that training-induced potentiation of PN-PN synapses promotes, whereas that of ITN-PN synapses opposes, stimulus generalization. Indeed, suppressing plasticity of PN-PN synapses increased, whereas preventing plasticity of interneuronal synapses decreased the CS specificity of PN recruitment. Overall, our results indicate that the plasticity configuration imprinted in the network by synaptic competition ensures memory specificity. Given that anxiety disorders are characterized by tendency to generalize learned fear to safe stimuli or situations, understanding how plasticity of intrinsic LAd synapses regulates the specificity of learned fear is an important challenge for future experimental studies.
最近研究表明，具有不同内在兴奋性的主要神经元（PNs）之间的竞争性突触相互作用决定了哪些背外侧杏仁核（LAd）神经元会被纳入恐惧记忆痕迹。在此，我们探讨了这些竞争性相互作用在决定条件性恐惧关联的刺激特异性方面的作用。为此，我们使用了一个逼真的LAd生物物理计算模型，该模型包括基于多隔室电导的800个PNs和200个中间神经元的模型。为了再现PNs显示的连续的动作电位频率适应性，该模型包括具有高、中、低动作电位频率适应性的三种PNs亚型。此外，模型网络整合了LA内兴奋性和抑制性连接的空间差异模式、多巴胺能和去甲肾上腺素能输入、外在丘脑和皮质紧张传入，以模拟条件刺激以及无条件刺激的电击输入。最后，模型中的谷氨酸能突触可发生依赖活动的可塑性变化。我们的结果表明，兴奋性（PN-PN）和双突触抑制性（PN-ITN，特别是ITN-PN）连接的可塑性是决定将PNs分配到记忆痕迹的突触竞争的主要决定因素。该模型还表明，训练诱导的PN-PN突触增强促进刺激泛化，而ITN-PN突触增强则相反。事实上，抑制PN-PN突触的可塑性增加，而防止中间神经元突触的可塑性降低了PN募集的条件刺激特异性。总体而言，我们的结果表明，突触竞争在网络中留下的可塑性配置确保了记忆特异性。鉴于焦虑症的特征是倾向于将习得的恐惧泛化到安全刺激或情境中，了解LAd内在突触的可塑性如何调节习得恐惧的特异性是未来实验研究的一项重要挑战。
