Single neurons can induce phase transitions of cortical recurrent networks with multiple internal states
Single neurons can induce phase transitions of cortical recurrent networks with multiple internal states
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DOI：
10.1093/cercor/bhj010
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发表时间：
2006-05-01
期刊：
影响因子：
3.7
通讯作者：
Ikegaya, Y
中科院分区：
文献类型：
--
作者：
Fujisawa, S;Matsuki, N;Ikegaya, Y
皮层神经元膜电位的波动，在这里被称为内部状态，对大脑功能至关重要，但人们对这些内部状态如何出现和维持，或者是什么决定了这些状态之间的转换知之甚少。我们从海马CA3锥体细胞离体进行细胞内记录，发现神经元显示多层次的内部状态，这与胆碱能活性和膜电位动力学的几个幂律结构的特点。来自相邻神经元的多个记录显示，神经元之间的内部状态是一致的，这表明局部网络中任何给定细胞的内部状态都可以代表网络的活动状态。随着时间的推移，重复刺激单个神经元会导致受刺激神经元和相邻神经元转变为不同的内部状态。因此，单个小区的激活足以改变整个本地网络的状态。随着状态转移到更活跃的水平，θ和γ频率分量以亚阈值振荡的形式发展。状态转换与膜电导的变化，但不伴随着逆转电位的变化。这些数据表明，循环网络通过平衡的兴奋和抑制的网络活动将单个神经元的内部状态组织成同步，并且这种组织本质上是离散的、异质的和动态的。因此，神经元的状态反映了一个活跃的网络，一个新的动力学和灵活性的皮质微电路演示的“阶段”。
Fluctuations of membrane potential of cortical neurons, referred to here as internal states, are essential for brain function, but little is known about how these internal states emerge and are maintained, or what determines transitions between these states. We performed intracellular recordings from hippocampal CA3 pyramidal cells ex vivo and found that neurons display multiple and hierarchical internal states, which are linked to cholinergic activity and are characterized by several power law structures in membrane potential dynamics. Multiple recordings from adjacent neurons revealed that the internal states were coherent between neurons, indicating that the internal state of any given cell in a local network could represent the network activity state. Repeated stimulation of single neurons led over time to transitions to different internal states in both the stimulated neuron and neighboring neurons. Thus, single-cell activation is sufficient to shift the state of the entire local network. As the states shift to more active levels, theta- and gamma-frequency components developed in the form of subthreshold oscillations. State transitions were associated with changes in membrane conductance but were not accompanied by a change in reversal potential. These data suggest that the recurrent network organizes the internal states of individual neurons into synchronization through network activity with balanced excitation and inhibition, and that this organization is discrete, heterogeneous and dynamic in nature. Thus, neuronal states reflect the 'phase' of an active network, a novel demonstration of the dynamics and flexibility of cortical microcircuitry.