Neural Graphs and Category of Memory States

Abstract

The brain as an astonishingly remarkable device has been studied from various angles. It is now well known that neurons are the seat of all activities of the brain function. The dynamical properties pertaining to a single neuron and a collection of neurons may be widely different owing to the clustering properties of a group of neurons. As it can be clearly understood theory of complex physical systems has been more and more employed to study the behaviour of neurons and neuronal circuits. We here mainly discuss neural correlates of memory and cognitive functions utilizing graph theory and ideas from geometry. It has been suggested that stochastic processes being at the helm of affairs in the neuronal level there may exist surfaces to some extent like a hologram for the existence of memory functions.It is also instructive to mention that Amari's developments \cite{amari} as regards information geometry has acted as an important inspiration. Unlike some previous analysis categorization of memory from neural perspectives have been reconsidered at the neuronal level. In essence the main point of discussion here has been to give an alternative model of memory where stochastic geometry and algebraic surfaces is an important ingredient.