Department of Neuroinformatics, Donders Institute, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands.
School of Psychology, University of Birmingham, Edgbaston, B15 2TT, UK.
Biol Cybern. 2021 Oct;115(5):487-517. doi: 10.1007/s00422-021-00894-6. Epub 2021 Oct 9.
Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be differentially involved in many cognitive functions. These cell types also show different relationships with the power and phase of oscillations in local field potentials. The mechanisms that underlie the emergence of different oscillatory rhythms in neural circuits with more than one interneuron subtype, and the roles specific interneurons play in those mechanisms, are not fully understood. Here, we present a comprehensive analysis of all possible circuit motifs and input regimes that can be achieved in circuits comprised of excitatory cells, PV-like fast-spiking interneurons and SOM-like low-threshold spiking interneurons. We identify 18 unique motifs and simulate their dynamics over a range of input strengths. Using several characteristics, such as oscillation frequency, firing rates, phase of firing and burst fraction, we cluster the resulting circuit dynamics across motifs in order to identify patterns of activity and compare these patterns to behaviors that were generated in circuits with one interneuron type. In addition to the well-known PING and ING gamma oscillations and an asynchronous state, our analysis identified three oscillatory behaviors that were generated by the three-cell-type motifs only: theta-nested gamma oscillations, stable beta oscillations and theta-locked bursting behavior, which have also been observed in experiments. Our characterization provides a map to interpret experimental activity patterns and suggests pharmacological manipulations or optogenetics approaches to validate these conclusions.
神经回路包含多种不同类型的中间神经元，这些中间神经元在其生理特性和连接模式上存在差异。两种最常见的中间神经元类型，即表达 parvalbumin 和 somatostatin 的细胞，已被证明在许多认知功能中具有不同的作用。这些细胞类型还表现出与局部场电位的功率和相位振荡不同的关系。在具有多种中间神经元亚型的神经回路中，不同的振荡节律是如何出现的，以及特定的中间神经元在这些机制中扮演什么角色，这些机制还不完全清楚。在这里，我们对由兴奋性细胞、PV 样快速放电中间神经元和 SOM 样低阈值放电中间神经元组成的回路中所有可能的回路模式和输入状态进行了全面分析。我们确定了 18 种独特的模式，并在一系列输入强度下模拟了它们的动力学。使用几种特征，如振荡频率、放电率、放电相位和爆发分数，我们对不同模式的回路动力学进行聚类，以识别活动模式，并将这些模式与由一种中间神经元类型产生的行为进行比较。除了众所周知的 PING 和 ING 伽马振荡以及异步状态外，我们的分析还确定了仅由三细胞类型模式产生的三种振荡行为：theta 嵌套的 gamma 振荡、稳定的 beta 振荡和 theta 锁定的爆发行为，这些行为也在实验中观察到。我们的特征描述提供了一个解释实验活动模式的图谱，并提出了药理学干预或光遗传学方法来验证这些结论。
