Phase relations of theta oscillations in a computer model of the hippocampal CA1 field: Key role of Schaffer collaterals.

The hippocampal theta rhythm (4-12 Hz) is one of the most important electrophysiological processes in the hippocampus, it participates in cognitive hippocampal functions, such as navigation in space, novelty detection, and declarative memory. We use neural network modeling to study the mechanism of theta rhythm emergence in the CA1 microcircuitry. Our model of the CA1 field includes biophysical representation of major cell types related to the theta rhythm emergence: excitatory pyramidal cells and two types of inhibitory interneurons, PV+ basket cells and oriens lacunosum-moleculare (OLM) cells. The main inputs to the CA1 cells come from the entorhinal cortex via perforant pathway, the CA3 field via Schaffer collaterals, and the medial septum via fimbria-fornix. By computer simulations we investigated the influence of each input, intrinsic parameters of neurons, and connections between neurons on phase coupling between the theta rhythm and the firing of pyramidal, PV+ basket and OLM cells in the CA1. We found that the input from the CA3 field via Schaffercollaterals plays a major role in the formation of phase relations that have been observed in experiments in vivo. The direct input from the medial septum participates in the formation of proper phase relations, but it is not crucial for the production of the theta rhythm in CA1 neural populations.

Oscillatory model of attention-guided object selection and novelty detection.

We develop a new oscillatory model that combines consecutive selection of objects and discrimination between new and familiar objects. The model works with visual information and fulfils the following operations: (1) separation of different objects according to their spatial connectivity; (2) consecutive selection of objects located in the visual field into the attention focus; (3) extraction of features; (4) representation of objects in working memory; (5) novelty detection of objects. The functioning of the model is based on two main principles: the synchronization of oscillators through phase-locking and resonant increase of the amplitudes of oscillators if they work in-phase with other oscillators. The results of computer simulation of the model are described for visual stimuli representing printed words.

Oscillatory neural network model of attention focus formation and control.

A new mechanism to control attention focus formation and switching in the model of selective attention is suggested and studied. The model is based on an oscillatory neural network (ONN) with the star-like architecture and phase shifts in connections between oscillators. Attention is modelled as a dynamical mode of partial synchronisation between a particular subgroup of oscillators and the central oscillator (CO). A new theoretical method to study full and partial synchronisation in the system is presented. Equations for the frequency of synchronisation are derived which allow the programming of the dynamical behaviour of the system depending on the parameters. In particular, we show that phase shifts in connections between oscillators provide an efficient mechanism of attention control.