The neural system is believed to have such a capacity for self-organization that it can modify its structures or behavior in adapting to the information structures of the environment. We have constructed a mathematical theory of self-organizing nerve nets, with the aim of elucidating the modes and capabilities of this peculiar information processing in nerve nets.
We first present a unified theoretical framework for analyzing learning and selforganization of a system of neurons with modifiable synapses, which receive signals from a stationary information source. We consider the dynamics of self-organization, which shows how the synaptic weights are modified, together with the dynamics of neural excitation patterns. It is proved that a neural system has the ability automatically to form, by selforganization, detectors or processors for every signal included in the information source of the environment.
A model of self-organization in nerve fields is then presented, and the dynamics of pattern formation is analyzed in nerve fields. The theory is applied to the formation of topographic maps between two nerve fields. It is shown that under certain conditions columnar microstructures are formed in nerve fields by self-organization.

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It is generally believed that myosin subfragment-1 (S-1) is the segment of the myosin molecule that catalyzes the hydrolysis of ATP and thereby impels actin. So the structure and "internal mechanics" of S-1 assume great importance in clarifying the molecular mechanism of the sliding theory of muscle contraction, Group with various suggestive functionalities (reactive thiols, a reactive lysine, reactive arginines, certain tryptophans, etc.) reside on S-1. The limited tryptic digestion of the heavy chain of S-1 results in three major peptides with approximate molecular weight of 50K, 27K, and 20K, without much additional protolysis. This method opens a new line of ilvestigation. Locating known functionalities and their proximities among the peptides are eafly step in this line.
In the tryptic digestion of S-1, 27 K-peptide is generated by two parallel routes: directly from the 75K-peptide, and through a 29.5K-peptide precursor. A reactive lysyl residue is present in both the 27K-and 29.5K-peptides. However, the reactivity of these lysyl residue differ. This indicates that the two routes of generating the 27K-peptide correspond to the proteolysis of two different heavy chains of S-1.

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