Cortical Microcircuits from a Generative Vision Model
Cortical Microcircuits from a Generative Vision Model
复制标题
来自生成视觉模型的皮质微电路
DOI：
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
M. Lázaro
中科院分区：
文献类型：
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作者：
Dileep George;Alexander Lavin;J. S. Guntupalli;David A. Mély;Nick J. Hay;M. Lázaro
了解皮质回路的信息处理作用是神经科学和人工智能中的一个突出问题。贝叶斯推理的理论设置已被建议作为理解皮质计算的框架。基于最近发布的视觉推理生成模型（George et al., 2017），我们推导出一系列解剖实例化和功能性皮层回路模型。与贝叶斯推理的简单模型相比，底层生成模型的表征选择是通过需要高效推理和强泛化的现实世界任务进行验证的。皮层回路模型是通过系统地比较该模型的计算要求与已知的解剖学约束而得出的。导出的模型提出了在不同层和柱中观察到的前馈、反馈和横向连接的精确功能作用，并为通过丘脑的路径分配了计算作用。
Understanding the information processing roles of cortical circuits is an outstanding problem in neuroscience and artificial intelligence. The theoretical setting of Bayesian inference has been suggested as a framework for understanding cortical computation. Based on a recently published generative model for visual inference (George et al., 2017), we derive a family of anatomically instantiated and functional cortical circuit models. In contrast to simplistic models of Bayesian inference, the underlying generative model’s representational choices are validated with real-world tasks that required efficient inference and strong generalization. The cortical circuit model is derived by systematically comparing the computational requirements of this model with known anatomical constraints. The derived model suggests precise functional roles for the feedforward, feedback and lateral connections observed in different laminae and columns, and assigns a computational role for the path through the thalamus.
影响因子：
56.9
作者：
Martin B. Stemmler;Marius Usher;Marius Usher;Marius Usher;E. Niebur
通讯作者：
Martin B. Stemmler;Marius Usher;Marius Usher;Marius Usher;E. Niebur
DOI：
10.1364/josaa.20.001434
发表时间：
2003-07-01
影响因子：
1.9
作者：
Lee, TS;Mumford, D
通讯作者：
Mumford, D