Generation and control of septo-hippocampal oscillations

Behavioral, vigilance and emotional or affective states are thought to be reflected in the electrical brain patterns of mammals. Macroscopically measurable population activities are in the lime-light since the early 1900s, the invention of electroencephalography (EEG). From EEG recordings of brain activity several brainwave types were identified. In our present research the so called theta and often related gamma activities of the septo-hippocampal system are studied.

Theta oscillation of the septo-hippocampal system has been considered as a prominent activity associated with cognitive function and affective processes. It occures for example when a rat is learning how to navigate in a maze or during navigation but prominent theta activity can also be found during REM sleep. Much less is known about the functional role of hippocampal gamma oscillation. In the neocortex gamma rhythm was proposed to play a role in binding perceived and recalled attributes of events (Gray et al, 1989) or memory formation in the hippocampus (Jensen and Lisman, 1996). Recently, hippocampal gamma oscillation was proposed to play a role in behavioral regulation (Ma and Leung, 2000) as well.

Our computational modeling work aims at providing a theoretical background for the understanding of the generation of hippocampal theta and gamma oscillations, particularly in areas CA3 and CA1. We use the compartmental modeling technic and the Hodgkin-Huxley framework to build biologically realistic neural networks. By studying the properties of these models we can ask questions on how action potentials propagate and synchronize in a neural system to build up a coherent population activity. These modeling studies help us understanding basic mechanisms that might take place in neural systems underlying rhythm generation.

Recently, our model system was used to study effect of pharmacological agents in the generation of theta rhythm in area CA1. Computer models that integrate anatomical, physiological, biophysical and mathematical knowledge are proposed as a possible future tool in drug design and discovery. Using computer simulations several experiments otherwise hard or impossible to perform can be executed. For example, using the skeleton network shown in figure 1 we were able to identify GABAA pathways in the CA1 that were especially suitable for the modification of theta rhythm (figure 2).

Figure 1. The skeleton network showing cell types and connections among them. Pyramidal cells (pyr), septal GABAergic neurons (MS-GABA), basket cells (i(b)) and horizontal interneurons (O-LM (i(o/a)) cells and hippocampo-septal cells (i(h))) were taken into account.
Figure 2. Selective modification of specific GABAA pathways of the skeleton network. Unselective effect of pharmacological agents would affect several components of a large, complex system to achieve the goal of changing the population activity into the desired pattern. Using computer simulations and selectively modulating designated pathways of the system we could identify those connections to which the rhythm is most sensitive. We found that theta oscillation is easiest to modify via connections among basket cells. (Legend: control - connection strengths are set as reported in control situation; total reduction - connection strengths are decreased at all synaptic sites; h2m, m2h - connections between horizontal cells and septal GABAergic cells are decreased selectively and in both directions; m2m, b2b - similarly, connections between septal and septal and basket and basket cells are decreased, respectively; b2b - connection strengths only within the basket cell network was decreased; m2m - connection strengths only within the septal GABAergic cell network was decreased.)

Selected articles documenting this project:

Also, please visit the homepage, which contains details of our computer model.

Presently, Péter Érdi, Balázs Ujfalussy, Gergő Orbán and Tamás Kiss are working on this project.

This project is supported by the Hungarian National Research Fund (OTKA) Grant T038140.