Reproducible sequence generation in random neural ensembles
Reproducible sequence generation in random neural ensembles
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DOI：
10.1103/physrevlett.93.238104
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发表时间：
2004-12-03
影响因子：
8.6
通讯作者：
Rabinovich, M
中科院分区：
文献类型：
--
作者：
Huerta, R;Rabinovich, M
我们对神经回路产生可重复序列所必须满足的条件知之甚少。显然，遗传密码无法控制大脑中复杂回路的所有细节。在这封信中，我们给出了连接度的条件，导致可重复的和强大的序列中的随机耦合的兴奋性和抑制性神经元的神经种群。与传统的理论观点相反，我们表明序列不需要学习。在这里提出的框架中，随机电路的平均特性必须受到遗传控制。我们发现，如果随机网络是在附近的兴奋抑制突触平衡的节奏序列可以产生。另一方面，可复制的瞬时序列被发现远离突触平衡。
Little is known about the conditions that neural circuits have to satisfy to generate reproducible sequences. Evidently, the genetic code cannot control all the details of the complex circuits in the brain. In this Letter, we give the conditions on the connectivity degree that lead to reproducible and robust sequences in a neural population of randomly coupled excitatory and inhibitory neurons. In contrast to the traditional theoretical view we show that the sequences do not need to be learned. In the framework proposed here just the averaged characteristics of the random circuits have to be under genetic control. We found that rhythmic sequences can be generated if random networks are in the vicinity of an excitatory-inhibitory synaptic balance. Reproducible transient sequences, on the other hand, are found far from a synaptic balance.