Sorbonne University, Pierre et Marie Curie Campus, Paris, France.
Group of Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, PSL University, Paris, France.
PLoS Comput Biol. 2021 Dec 6;17(12):e1009639. doi: 10.1371/journal.pcbi.1009639. eCollection 2021 Dec.
Rhythmic neuronal network activity underlies brain oscillations. To investigate how connected neuronal networks contribute to the emergence of the α-band and to the regulation of Up and Down states, we study a model based on synaptic short-term depression-facilitation with afterhyperpolarization (AHP). We found that the α-band is generated by the network behavior near the attractor of the Up-state. Coupling inhibitory and excitatory networks by reciprocal connections leads to the emergence of a stable α-band during the Up states, as reflected in the spectrogram. To better characterize the emergence and stability of thalamocortical oscillations containing α and δ rhythms during anesthesia, we model the interaction of two excitatory networks with one inhibitory network, showing that this minimal topology underlies the generation of a persistent α-band in the neuronal voltage characterized by dominant Up over Down states. Finally, we show that the emergence of the α-band appears when external inputs are suppressed, while fragmentation occurs at small synaptic noise or with increasing inhibitory inputs. To conclude, α-oscillations could result from the synaptic dynamics of interacting excitatory neuronal networks with and without AHP, a principle that could apply to other rhythms.
节律性神经元网络活动是大脑振荡的基础。为了研究连接的神经元网络如何有助于α 波段的出现以及上、下状态的调节,我们研究了一个基于突触短期抑制-易化与后超极化(AHP)的模型。我们发现,α 波段是由上状态吸引子附近的网络行为产生的。通过相互连接来耦合抑制性和兴奋性网络,导致在上状态期间出现稳定的α 波段,这反映在频谱图中。为了更好地表征麻醉期间包含α 和δ 节律的丘脑皮质振荡的出现和稳定性,我们模拟了两个兴奋性网络与一个抑制性网络的相互作用,表明这种最小拓扑结构是产生神经元电压中持续α 波段的基础,其特征是上状态相对于下状态占主导地位。最后,我们表明,当抑制外部输入时,α 波段的出现,而在小突触噪声或增加抑制性输入时会出现碎片化。总之,α 振荡可能是由具有和不具有 AHP 的相互作用的兴奋性神经元网络的突触动力学引起的,这一原理可能适用于其他节律。