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首页> 外文期刊>Neuron >Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.
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Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.

机译：依赖于峰值时间的可塑性和异突触竞争组织了网络，以产生无标度的长序列神经活动。

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摘要

Sequential neural activity patterns are as ubiquitous as the outputs they drive, which include motor gestures and sequential cognitive processes. Neural sequences are long, compared to the activation durations of participating neurons, and sequence coding is sparse. Numerous studies demonstrate that spike-time-dependent plasticity (STDP), the primary known mechanism for temporal order learning in neurons, cannot organize networks to generate long sequences, raising the question of how such networks are formed. We show that heterosynaptic competition within single neurons, when combined with STDP, organizes networks to generate long unary activity sequences even without sequential training inputs. The network produces a diversity of sequences with a power law length distribution and exponent -1, independent of cellular time constants. We show evidence for a similar distribution of sequence lengths in the recorded premotor song activity of songbirds. These results suggest that neural sequences may be shaped by synaptic constraints and network circuitry rather than cellular time constants.
机译：顺序神经活动模式与其驱动的输出一样普遍，包括运动手势和顺序认知过程。与参与神经元的激活持续时间相比，神经序列较长，并且序列编码稀疏。大量研究表明，依赖于尖峰时间的可塑性（STDP）是神经元中时间顺序学习的主要已知机制，它无法组织网络以生成长序列，从而引发了如何形成此类网络的问题。我们显示，当与STDP结合时，单个神经元内的异突触竞争会组织网络以生成长的一元活动序列，即使没有顺序训练输入也是如此。网络产生具有幂律长度分布和指数-1的各种序列，与细胞时间常数无关。我们显示出在记录的鸣禽运动前歌曲活动中序列长度的相似分布的证据。这些结果表明，神经序列可能受突触约束和网络电路的影响，而不是细胞时间常数的影响。

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