Section on Critical Brain Dynamics, Laboratory of Systems Neuroscience, National Institutes of Mental Health, Bethesda, Maryland 20892, USA.
J Neurosci. 2012 Jan 18;32(3):1061-72. doi: 10.1523/JNEUROSCI.2771-11.2012.
Ongoing interactions among cortical neurons often manifest as network-level synchrony. Understanding the spatiotemporal dynamics of such spontaneous synchrony is important because it may (1) influence network response to input, (2) shape activity-dependent microcircuit structure, and (3) reveal fundamental network properties, such as an imbalance of excitation (E) and inhibition (I). Here we delineate the spatiotemporal character of spontaneous synchrony in rat cortex slice cultures and a computational model over a range of different E-I conditions including disfacilitated (antagonized AMPA, NMDA receptors), unperturbed, and disinhibited (antagonized GABA(A) receptors). Local field potential was recorded with multielectrode arrays during spontaneous burst activity. Synchrony among neuronal groups was quantified based on phase-locking among recording sites. As network excitability was increased from low to high, we discovered three phenomena at an intermediate excitability level: (1) onset of synchrony, (2) maximized variability of synchrony, and (3) neuronal avalanches. Our computational model predicted that these three features occur when the network operates near a unique balanced E-I condition called "criticality." These results were invariant to changes in the measurement spatial extent, spatial resolution, and frequency bands. Our findings indicate that moderate average synchrony, which is required to avoid pathology, occurs over a limited range of E-I conditions and emerges together with maximally variable synchrony. If variable synchrony is detrimental to cortical function, this is a cost paid for moderate average synchrony. However, if variable synchrony is beneficial, then by operating near criticality the cortex may doubly benefit from moderate mean and maximized variability of synchrony.
皮质神经元之间的持续相互作用通常表现为网络级别的同步。理解这种自发同步的时空动态非常重要,因为它可能 (1) 影响网络对输入的响应,(2) 塑造活动依赖性微电路结构,和 (3) 揭示基本的网络特性,例如兴奋性 (E) 和抑制性 (I) 的不平衡。在这里,我们描绘了在不同 E-I 条件下(包括去激活(对抗 AMPA、NMDA 受体)、未受干扰和去抑制(对抗 GABA(A) 受体))大鼠皮质切片培养物和计算模型中的自发同步的时空特征。在自发爆发活动期间,使用多电极阵列记录局部场电位。基于记录位点之间的相位锁定来量化神经元群体之间的同步性。随着网络兴奋性从低到高增加,我们在中间兴奋性水平发现了三种现象:(1) 同步的开始,(2) 同步的最大可变性,和 (3) 神经元雪崩。我们的计算模型预测,当网络在称为“临界性”的独特平衡 E-I 条件附近运行时,会出现这三个特征。这些结果与测量空间范围、空间分辨率和频带的变化无关。我们的发现表明,为了避免病理学,适度的平均同步性发生在有限的 E-I 条件范围内,并与最大可变性的同步性一起出现。如果可变同步性对皮质功能有害,这是为适度平均同步性付出的代价。然而,如果可变同步性是有益的,那么通过在临界性附近操作,皮质可能会从适度的平均同步性和最大可变性同步性中双重受益。