Orientation Selectivity from Very Sparse LGN Inputs in a Comprehensive Model of Macaque V1 Cortex
Orientation Selectivity from Very Sparse LGN Inputs in a Comprehensive Model of Macaque V1 Cortex
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DOI：
10.1523/jneurosci.2603-16.2016
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发表时间：
2016-12-07
影响因子：
5.3
通讯作者：
Young, Lai-Sang
中科院分区：
文献类型：
--
作者：
Chariker, Logan;Shapley, Robert;Young, Lai-Sang
建立了一个新的猕猴初级视皮层（V1）的计算模型，以协调V1的视觉功能与其LGN输入的解剖数据，其极端稀疏性对皮层功能的理论合理解释提出了严重挑战。我们证明，即使有这样的稀疏输入，它是可能产生强大的方向选择性，以及在方向图的连续性。我们超越了这一点，找到合理的动态制度，我们的新模型，同时模拟实验数据的范围广泛的V1现象，开始与方向选择性，但也包括多样性的神经元反应，双峰分布的调制比（简单/复杂的分类），和动态签名，如伽马波段振荡。皮质内相互作用在模型视觉功能的各个方面都起着重要作用。
A new computational model of the primary visual cortex (V1) of the macaque monkey was constructed to reconcile the visual functions of V1 with anatomical data on its LGN input, the extreme sparseness of which presented serious challenges to theoretically sound explanations of cortical function. We demonstrate that, even with such sparse input, it is possible to produce robust orientation selectivity, as well as continuity in the orientation map. We went beyond that to find plausible dynamic regimes of our new model that emulate simultaneously experimental data for a wide range of V1 phenomena, beginning with orientation selectivity but also including diversity in neuronal responses, bimodal distributions of the modulation ratio (the simple/complex classification), and dynamic signatures, such as gamma-band oscillations. Intracortical interactions play a major role in all aspects of the visual functions of the model.