Neural network model of the primary visual cortex: from functional architecture to lateral connectivity and back.

Neural network model of the primary visual cortex: from functional architecture to lateral connectivity and back.
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DOI:
10.1007/s10827-006-6307-y
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发表时间:
2006-04
影响因子:
1.2
通讯作者:
Tsodyks M
Tsodyks M
中科院分区:
医学4区
文献类型:
--
作者:
Blumenfeld B;Bibitchkov D;Tsodyks M

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内在皮质动力学的作用是一个有争议的问题。最近的光学成像研究(Kenet等人,2003)发现,即使在没有感觉输入的情况下,初级视觉皮层(V1)也会出现类似于方向图(OM)的活动模式,这表明OM激活的内在机制。为了更好地理解这些结果,揭示内在的V1处理,我们建议一个神经网络模型,其中OM是由内在的横向连接编码。建议的连接模式取决于首选的方向,与以前的模型不同,方向的相互连接的神经元的选择性的程度。我们证明了网络有一个环吸引子组成的一个近似版本的OMs。因此,当网络被呈现非结构化的噪声输入时,OM自发地出现。仿真结果表明,该模型可以应用于实验数据,并产生逼真的OM。我们研究了空间限制连接的模型的变化,并表明,它会产生由几个OM组成的状态。我们假设这些状态可以代表视觉场景的局部属性。
The role of intrinsic cortical dynamics is a debatable issue. A recent optical imaging study (Kenet et al., 2003) found that activity patterns similar to orientation maps (OMs), emerge in the primary visual cortex (V1) even in the absence of sensory input, suggesting an intrinsic mechanism of OM activation. To better understand these results and shed light on the intrinsic V1 processing, we suggest a neural network model in which OMs are encoded by the intrinsic lateral connections. The proposed connectivity pattern depends on the preferred orientation and, unlike previous models, on the degree of orientation selectivity of the interconnected neurons. We prove that the network has a ring attractor composed of an approximated version of the OMs. Consequently, OMs emerge spontaneously when the network is presented with an unstructured noisy input. Simulations show that the model can be applied to experimental data and generate realistic OMs. We study a variation of the model with spatially restricted connections, and show that it gives rise to states composed of several OMs. We hypothesize that these states can represent local properties of the visual scene.
DOI: 10.1038/nature02078
发表时间: 2003-10-30
期刊: NATURE
影响因子: 64.8
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