The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex.
Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Although there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
Hu
Hong
H
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, China. huhong@ics.ict.ac.cn
Li
Su
S
Wang
YunJiu
Y
Qi
XiangLin
X
Shi
ZhongZhi
Z
D017143:Fuzzy Logic; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*