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Developing neuronal networks: Self-organized criticality predicts the future

机译:发展神经网络:自组织的关键性预测未来

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Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and “aging” process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.
机译:神经活动中出现的自组织临界性是描述发展中的神经元网络的形成和功能的关键概念之一。临界动力学与神经发育之间的关系在理论上和实验上都很有吸引力。然而,尽管众所周知,在体外成熟过程中,皮质网络在不同阶段表现出丰富的活动模式,但整个神经发育过程中的动态活动模式仍然不清楚。在这里,我们显示了在从离体大鼠神经元培养的海马网络的发展和“衰老”过程中出现了一系列亚稳态网络状态。状态转换的单向序列只能在显示分布式神经元雪崩的幂律定标的网络中观察到。我们的数据表明,自组织的临界度可能将自发活动引导为发育过程中稳态调控的瞬态模式的连续序列,这可能有助于预测未来早期神经发育的趋势。

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