A microcircuit model of the frontal eye fields
A microcircuit model of the frontal eye fields
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DOI：
10.1523/jneurosci.0974-07.2007
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发表时间：
2007-08-29
影响因子：
5.3
通讯作者：
Martin, Kevan A. C.
中科院分区：
文献类型：
--
作者：
Heinzle, Jakob;Hepp, Klaus;Martin, Kevan A. C.
大脑皮层对眼球运动的控制是非常复杂的。眼球运动不仅可以指向视觉场景中最显著的目标，而且还可以通过视觉搜索或阅读所需的自上而下的规则来控制。被称为额叶眼场（FEF）的皮层区域已被证明在需要眼球运动模式的任务中的视觉到眼动转换中起关键作用，该眼球运动模式不是完全反应性的，而是遵循先前学习的规则。在初级感觉皮层中，分层的局部皮层回路为所有皮层计算提供了解剖学基础，已经被广泛研究。这些研究产生了新皮质“典型回路”的概念（道格拉斯等人，1989;道格拉斯和马丁，1991），提出新皮层的所有区域共享一个共同的基本电路。然而，还没有探索原则上是否从猫区17导出详细的规范电路（Binzegger等人，2004）可以实现前额叶皮层的完全不同的功能。在这里，我们表明，典型的电路，与一些修改，模型的灵长类动物FEF。整合和激发神经元的基于尖峰的网络在用于行为猕猴的电生理实验的任务中进行了测试。该模型的动力学与FEF中观察到的神经元动力学相匹配，行为结果与心理物理实验中观察到的结果相匹配。模型和皮质结构之间的密切关系允许与生理数据的模拟结果的详细比较，并预测FEF的解剖电路的细节。
The cortical control of eye movements is highly sophisticated. Not only can eye movements be made to the most salient target in a visual scene, but they can also be controlled by top-down rules as is required for visual search or reading. The cortical area called frontal eye fields ( FEF) has been shown to play a key role in the visual to oculomotor transformations in tasks requiring an eye movement pattern that is not completely reactive, but follows a previously learned rule. The layered, local cortical circuit, which provides the anatomical substrate for all cortical computation, has been studied extensively in primary sensory cortex. These studies led to the concept of a "canonical circuit" for neocortex ( Douglas et al., 1989; Douglas and Martin, 1991), which proposes that all areas of neocortex share a common basic circuit. However, it has not ever been explored whether in principle the detailed canonical circuit derived from cat area 17 ( Binzegger et al., 2004) could implement the quite different functions of prefrontal cortex. Here, we show that the canonical circuit can, with a few modifications, model the primate FEF. The spike-based network of integrate-and-fire neurons was tested in tasks that were used in electrophysiological experiments in behaving macaque monkeys. The dynamics of the model matched those of neurons observed in the FEF, and the behavioral results matched those observed in psychophysical experiments. The close relationship between the model and the cortical architecture allows a detailed comparison of the simulation results with physiological data and predicts details of the anatomical circuit of the FEF.