Brain functions and neural dynamics.

Anatomical and physiological evidence is cited for the existence in the CNS of more or less discrete populations of interconnected neurons. These are given the term netlets. A model based on these observations is presented, in which it is assumed that the netlets are the fundamental building blocks out of which nets of considerable complexity may be as embled. The connectivity within each netlet is assumed to be random. Neuronal macrostates are defined in which the fractions of neurons active in each netlet are the dynamical variables. Thus the temporal and spatial fine structure of neuronal activity are considered to be of secondary significance and are disregarded. These assumptions bring about an enormous reduction in complexity. Thus calculations and computer simulation studies become possible for systems hitherto inaccessible to quantitative description. It is hoped that the features retained in the model play a sufficiently significant role in the functioning of real neural nets to make these results meaningful. The mathematical formalism and detailed numerical results appear in another paper of this issue ( Anninos, 1970 ). Some of these results are anticipated in this paper and their implications for our model are discussed. The study proceeds from a treatment of isolated probabilistic netlets to the dynamics of interacting netlets. Of particular interest are the conditions under which a netlet will go into sustained activity and the often extremely delicate control exerted by afferent excitatory or inhibitory biases. Hysteresis effects are common and may represent a type of short-term memory. A variety of neural functions are listed to which some of these mechanisms may be applied. Among these are the modulating effects of the brain stem reticular formation on cortical and spinal neuron populations and the “energizing” of cortical centers by spontaneous activity in sensory systems. Finally the concepts of netlet interaction are applied in conjunction with the principle of synaptic facilitation to information processing in the cortex. Examples given are sensory-sensory cortical conditioning and the formation of the classical conditioned reflex.