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无监督形成发声敏感神经元:基于短期和动态平衡可塑性的皮质模型。

Unsupervised formation of vocalization-sensitive neurons: a cortical model based on short-term and homeostatic plasticity.

机构信息

Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA.

出版信息

Neural Comput. 2012 Oct;24(10):2579-603. doi: 10.1162/NECO_a_00345. Epub 2012 Jul 30.

DOI:10.1162/NECO_a_00345
PMID:22845822
Abstract

The discrimination of complex auditory stimuli relies on the spatiotemporal structure of spike patterns arriving in the cortex. While recordings from auditory areas reveal that many neurons are highly selective to specific spatiotemporal stimuli, the mechanisms underlying this selectivity are unknown. Using computer simulations, we show that selectivity can emerge in neurons in an entirely unsupervised manner. The model is based on recurrently connected spiking neurons and synapses that exhibit short-term synaptic plasticity. During a developmental stage, spoken digits were presented to the network; the only type of long-term plasticity present was a form of homeostatic synaptic plasticity. From an initially unresponsive state, training generated a high percentage of neurons that responded selectively to individual digits. Furthermore, units within the network exhibited a cardinal feature of vocalization-sensitive neurons in vivo: differential responses between forward and reverse stimulus presentations. Direction selectivity deteriorated significantly, however, if short-term synaptic plasticity was removed. These results establish that a simple form of homeostatic plasticity is capable of guiding recurrent networks into regimes in which complex stimuli can be discriminated. In addition, one computational function of short-term synaptic plasticity may be to provide an inherent temporal asymmetry, thus contributing to the characteristic forward-reverse selectivity.

摘要

复杂听觉刺激的辨别依赖于到达皮层的尖峰模式的时空结构。虽然来自听觉区域的记录表明许多神经元对特定的时空刺激具有高度选择性,但这种选择性的机制尚不清楚。我们使用计算机模拟表明,选择性可以以完全无监督的方式出现在神经元中。该模型基于具有短期突触可塑性的递归连接的尖峰神经元和突触。在发育阶段,向网络呈现口语数字;唯一存在的长期可塑性形式是一种形式的同型突触可塑性。从最初的无反应状态开始,训练生成了很大比例的对单个数字有选择性反应的神经元。此外,网络中的单元表现出体内发声敏感神经元的一个主要特征:正向和反向刺激呈现之间的差异反应。然而,如果去除短期突触可塑性,方向选择性会显著恶化。这些结果表明,一种简单的同型突触可塑性形式能够引导递归网络进入可以区分复杂刺激的状态。此外,短期突触可塑性的一个计算功能可能是提供内在的时间不对称性,从而有助于特征性的前后选择性。

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