Parks R W, Long D L, Levine D S, Crockett D J, McGeer E G, McGeer P L, Dalton I E, Zec R F, Becker R E, Coburn K L
Laboratory of Clinical Science and Neuropsychology, National Institute of Mental Health, Bethesda, Maryland.
Int J Neurosci. 1991 Oct;60(3-4):195-214. doi: 10.3109/00207459109167033.
Parallel Distributed Processing (PDP), a computational methodology with origins in Associationism, is used to provide empirical information regarding neurobiological systems. Recently, supercomputers have enabled neuroscientists to model brain behavior-relationships. An overview of supercomputer architecture demonstrates the advantages of parallel over serial processing. Histological data provide physical evidence of the parallel distributed nature of certain aspects of the human brain, as do corresponding computer simulations. Whereas sensory networks follow more sequential neural network pathways, in vivo brain imaging studies of attention and rudimentary language tasks appear to involve multiple cortical and subcortical areas. Controversy remains as to whether associative models or Artificial Intelligence symbolic models better reflect neural networks of cognitive functions; however, considerable interest has shifted towards associative models.
并行分布式处理（PDP）是一种起源于联想主义的计算方法，用于提供有关神经生物学系统的实证信息。最近，超级计算机使神经科学家能够对大脑行为关系进行建模。超级计算机架构的概述展示了并行处理相对于串行处理的优势。组织学数据以及相应的计算机模拟都为人类大脑某些方面的并行分布式性质提供了物理证据。虽然感觉网络遵循更多的顺序神经网络通路，但对注意力和基本语言任务的活体脑成像研究似乎涉及多个皮质和皮质下区域。关于联想模型或人工智能符号模型是否能更好地反映认知功能的神经网络仍存在争议；然而，相当多的兴趣已转向联想模型。
