Kilis D, Gatewood L, Zhuo Z, Hatfield G, Seaholm S, Ackerman E
National Micropopulation Simulation Resource, Health Computer Sciences, University of Minnesota, Minneapolis 55455.
Comput Biol Med. 1993 May;23(3):215-25. doi: 10.1016/0010-4825(93)90022-s.
COGNET, based on a neural network first described by Fukushima, demonstrates the relationship between connectionist and other micropopulation models. Its success and physiological orientation led to an implementation using the SUMMERS simulation shell. After self-supervised learning, COGNET uses forward and backward propagation of signals to recognize partial and noisy patterns, and to reconstruct the originals. Stochastic features include variable thresholds for neuronal firing and occasional cell death. The successful implementation of COGNET demonstrates the generality of the concepts embodied in SUMMERS, which in turn promotes the reusability of software and facilitates the extension of computational models in biomedical research. COGNET itself forms a framework for building other physiologically oriented neural network models.
COGNET基于福岛首次描述的神经网络，展示了联结主义模型与其他微种群模型之间的关系。它的成功及生理导向促使其使用SUMMERS模拟外壳进行实现。经过自监督学习后，COGNET利用信号的前向和反向传播来识别部分和有噪声的模式，并重建原始模式。随机特征包括神经元放电的可变阈值和偶尔的细胞死亡。COGNET的成功实现证明了SUMMERS中所体现概念的通用性，这反过来又促进了软件的可重用性，并便于生物医学研究中计算模型的扩展。COGNET本身构成了构建其他生理导向神经网络模型的框架。
