Is cortical connectivity optimized for storing information?
Is cortical connectivity optimized for storing information?
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DOI：
10.1038/nn.4286
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发表时间：
2016-05-01
影响因子：
25
通讯作者：
Brunel, Nicolas
中科院分区：
文献类型：
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作者：
Brunel, Nicolas
皮质网络被认为是由经验依赖性突触可塑性形成的。理论研究表明，突触可塑性允许网络存储活动模式的记忆，使它们成为网络动态的吸引子。在这里，我们研究的兴奋性突触连接在一个网络，最大限度地提高存储的活动模式的数量在一个强大的方式的属性。我们发现，由此产生的突触连接矩阵具有以下特性：它是稀疏的，与零突触权重（“潜在”突触）的大部分;双向耦合的神经元对相比，一个随机的网络，并表示过度;和双向连接的对有更强的突触平均比单向连接的对。所有这些功能再现定量可用的数据连接在皮层。这表明皮层中的突触连接被优化为以稳健的方式存储大量吸引子状态。
Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamics of the network. Here we study the properties of the excitatory synaptic connectivity in a network that maximizes the number of stored patterns of activity in a robust fashion. We show that the resulting synaptic connectivity matrix has the following properties: it is sparse, with a large fraction of zero synaptic weights ('potential' synapses); bidirectionally coupled pairs of neurons are over-represented in comparison to a random network; and bidirectionally connected pairs have stronger synapses on average than unidirectionally connected pairs. All these features reproduce quantitatively available data on connectivity in cortex. This suggests synaptic connectivity in cortex is optimized to store a large number of attractor states in a robust fashion.