[原创]论记忆

所谓计算机的记忆模式与神经细胞的自然发生，两者不是名词的区别，而是反映了不同的角度和结果。

计算机模式的特点是，因为我们创造了计算机系统，而且这个系统可以提供类似于我们人类记忆的功能特点，就以为我们大脑的记忆过程也象计算机一样，通过编码、存储、提取来得到记忆，我们的记忆内容也象计算机一样，先把具体内宾存到某一个结构中，把所含的信息不断地转化到不同的结构处理，最后在思维活动时反映出来。于是把神经生理实验中所得到的蛛丝马迹与这个理论去套，建立起一套所谓的记忆理论体系。尽管这个体系在具体环节上无法与大脑的实际生理过程相符。从各种记忆物质的寻找、海马功能的短时记忆库功能假设、前额叶功能的工作记忆库假设等，都反映了这个问题。

但是，如果我们考虑到我们大脑的所有活动都是以神经元为基础，以神经元的网络结构为单元，不同大脑结构之间可能实现的信息传递形式，各种亚细胞结构和物质对神经元活动可能产生的影响，那么关于记忆，甚至是整个思维意识问题，就会完全成另一个模式。

短时记忆与长时记忆方面的文章好像是说记忆是形成了新的蛋白质或突触联系，不知真假？

长时记忆有新的突触产生或旧的突触消失

Modern digital, von Neumann type, parallel computers outperform humans in the domain of
computations and related symbol manipulation. The course of long evolutionary process has provided the human brain with many superior characteristics not present in von Neumann architectures. These include:massive parallelism, distributed representation and computation, learning ability, adaptivity,contextual information processing, fault tolerance, and low energy consumption. Inspired by neuronets, ANNs are massively parallel computing systems consisting of a very large number processors with many interconnections. Thus, ANN models attempt to simul principles present in the human brain. The structure and architecture of biological well formulated in the related literature. To place the state of ANNs in perspective, it is the cerebral cortex contains about 10" neurons. Each neuron is connected to 1 d to 1 total, the human brain contains approximately loi4 to 1015 interconnections. Message train variable frequency of a few to several hundred Hertz, which is a million times slower than switching speeds of modern electronic circuits. However, complex perceptual decisions are typically made by of neurons within a few hundred milliseconds. Thus, the human brain runs parallel programs of steps long (the 1OOstep rule)

我感觉是你偷了我的大脑

最近真忙，一直想抽出点时间写篇关于记忆的文章，可就是没时间。不过看过前面的帖子后觉得有一点应该能达成共识吧：人脑的记忆与电脑的记忆在原理上是一样的只是表现形式不同罢了，如果有问题的话回头我准备在文章里加以详述。