Synaptic scaling stabilizes persistent activity driven by asynchronous neurotransmitter release.
Synaptic scaling stabilizes persistent activity driven by asynchronous neurotransmitter release.
复制标题
突触缩放可稳定由异步神经递质释放驱动的持续活动。
DOI：
10.1162/neco_a_00098
复制
发表时间：
2011
影响因子：
2.9
通讯作者：
Gerkin,RichardC
中科院分区：
文献类型：
--
作者：
Volman,Vladislav;Gerkin,RichardC
培养的海马神经元的小网络响应于瞬时刺激，具有持续数秒的有节奏的网络活动（混响），构成了同步性，工作记忆和癫痫发作的体外模型。这种活动模式在理论上和实验上都被证明依赖于神经递质的异步释放（发育中海马的一个基本特征），并且得到了各种发育中神经元网络的支持，尽管群体大小（10-200个神经元）和突触连接模式存在差异。以前在计算模型中已经报道过，“小世界”连接拓扑对于类似模式的网络活动的传播是理想的，尽管这仅针对利用同步（相位）突触传递的神经元。我们研究了突触连接的拓扑约束如何影响也使用异步突触传输的小型网络中混响的稳定性。我们发现，混响持续时间在这样的网络是耐拓扑结构的变化和规模与网络的大小不佳。然而，通过减少神经元之间突触输入的方差，突触驱动的正常化稳定了这种网络中的混响。因此，我们的研究结果表明，在发展中的网络的正常和病理状态的稳定性可能是由方差归一化突触驱动的约束。我们提供了一个实验预测的后果，这种监管的行为的小网络。
Small networks of cultured hippocampal neurons respond to transient stimulation with rhythmic network activity (reverberation) that persists for several seconds, constituting anin vitromodel of synchrony, working memory, and seizure. This mode of activity has been shown theoretically and experimentally to depend on asynchronous neurotransmitter release (an essential feature of the developing hippocampus) and is supported by a variety of developing neuronal networks despite variability in the size of populations (10–200 neurons) and in patterns of synaptic connectivity. It has previously been reported in computational models that “small-world” connection topology is ideal for the propagation of similar modes of network activity, although this has been shown only for neurons utilizing synchronous (phasic) synaptic transmission. We investigated how topological constraints on synaptic connectivity could shape the stability of reverberations in small networks that also use asynchronous synaptic transmission. We found that reverberation duration in such networks was resistant to changes in topology and scaled poorly with network size. However, normalization of synaptic drive, by reducing the variance of synaptic input across neurons, stabilized reverberation in such networks. Our results thus suggest that the stability of both normal and pathological states in developing networks might be shaped by variance-normalizing constraints on synaptic drive. We offer an experimental prediction for the consequences of such regulation on the behavior of small networks.