ABSTRACT
On neural activity, several of the earliest theoretical papers appearing from the 1940's into the 1970's dealt mostly with random network models of interconnected cells. In 1954, Cragg and Temperley were perhaps the first to elaborate and examine qualitatively the possible analogy between the organization of neurons and the kind of interaction among atoms which leads to the cooperative processes in physics. A more pragmatic method of analyzing neural activity via statistical physics was portrayed by Peretto who considered the collective properties of neural networks by extending Hopfield's model to little’s model. The synaptic activity, manifesting as the competition between the excitatory and inhibitory processes is regarded as equitable to the competition between the ferromagnetic and antiferromagnetic exchange interactions in spin-glass systems. The formal theory of stochastic neural network is based heavily on statistical mechanics considerations. The inconsistencies blossom from the asymmetric synaptic coupling of the real neurons as against the inherently symmetric attributes of magnetic spin connection strengths.
