Neurobiological data sustaining opponent processing operations on self organizing networks as tools for the modeling of hippocampal dynamics

This paper intends to show how the advancement on neurobiological knowledge within an adaptive timing fashion sustains the use of past mathematical described operations such as opponent processing for the modeling of hippocampal dynamics. It is showed that two distinct functional classes of afferents, i.e., excitatory afferents to principal cells and both interneurons and glia acting as either inhibitory or secondarily excitatory afferents to these principal cells form very distinct functional states that sustain a double system for the balanced activity into the hippocampus. We did represent principal cells as dipoles of opponent processing. The last component (node) of each dipole, X5, was considered as the resulting activity of the cell (action potential or null response). Dependent on the oscillations and coherence between the two afferent systems to each dipole, would be created different sets for the processing of hippocampal dynamics. Thus, we could generate very distinct hippocampal electrophysiological states, which would be the correspondent of specific behaviors. We show how this network could, for example, generates place fields when added patterns of self-organization. Our results reproduce the pattern of place cells firing that are dependent on the hippocampal oscillations.