Computation and brain processes, with special reference to neuroendocrin systems

The development of neural networks and brain automata has made neuroscientists aware that the performance limits of these devices lies, at least in part, in their computational power. The computational basis of standard cybernetic design, in fact, refers to that of a discrete and finite state machine or Turing Machine (TM). In contrast, it has been suggested that a number of human cerebral activites, from feeback control to mental processes, rely on a mixing of both finitary, digital-like and infinitary, continuous-like procedures. The human central nervous system (CNS) would thus exploit a form of computation going beyond that of a TM. This non conventional computation is called hybrid computation. Some basic structures for hybrid brain computation are believed to be the brain computational maps, in which both Turing-like (digital) computation and continuous (analog) forms of calculus would occur. Current theories on neural activit suggest a cooperation between discrete and continuous forms of communication in the CNS. The recent realization of neuromorphic chips suggests that assumption of a discrete-continuum polarity in designing biocompatible neural circuitries is crucial for their ensueing performance. In these bionic structures, in fact, a correspondence exists between the original anatomical architecture and the synthetic wiring of the chip, resulting in a correspondence between natural and cybernetic neural activity. Chip “form” thus provides a continuum essential to chip “function”. We conclude that it is reasonable to predict the existence of hybrid computational processes in the course of many human, brain integrating activities, urging the development of cybernetic approaches for a more adequate reproduction of the highest cerebral performances.