Reciprocity of structure-function relations in developing neural networks: the Odyssey of a self-organizing brain through research fads, fallacies and prospects

Abstract

This chapter explores the empirical and theoretical studies for analyzing complex, dynamic non-linear interactions in neural system. The design of crucial experiments can be accomplished by simulating the consequences of all plausible mechanisms by means of appropriate mathematical models because only in exceptionally simple situations will deductive logic suffice to generate the required truth tables. The author emphasized not only the importance of network models for understanding how the nervous system operates, but also the reciprocal question of how neural function can feed back upon the structure generating it so as to modify its organization, often in a long-lasting way. The chapter also presents few of the arguments for regarding intrinsically generated bioelectric activity as a key variable in understanding many features of plasticity and self-organization in the developing nervous system. It is concluded that guidance by systems-analytical techniques would be an excellent precedent also for experimental studies at intra and supra-cellular levels, i.e. the molecular and the histological, respectively.