Blumenfeld Barak, Bibitchkov Dmitri, Tsodyks Misha
Department of Neurobiology, Weizmann Institute of Science, Rehovot, 76100, Israel.
J Comput Neurosci. 2006 Apr;20(2):219-41. doi: 10.1007/s10827-006-6307-y. Epub 2006 Apr 22.
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.
大脑皮质内在动力学的作用是一个有争议的问题。最近的一项光学成像研究（凯内特等人，2003年）发现，即使在没有感觉输入的情况下，初级视觉皮层（V1）中也会出现类似于方位图（OMs）的活动模式，这表明存在一种激活方位图的内在机制。为了更好地理解这些结果并阐明V1的内在处理过程，我们提出了一种神经网络模型，其中方位图由内在横向连接进行编码。所提出的连接模式取决于偏好方位，并且与先前的模型不同，还取决于相互连接神经元的方位选择性程度。我们证明该网络具有由方位图的近似版本组成的环形吸引子。因此，当网络接收到无结构的噪声输入时，方位图会自发出现。模拟结果表明，该模型可以应用于实验数据并生成逼真的方位图。我们研究了具有空间受限连接的模型变体，并表明它会产生由多个方位图组成的状态。我们假设这些状态可以代表视觉场景的局部属性。
