Dynamic changes in the direction of the theta rhythmic drive between supramammillary nucleus and the septohippocampal system

✍ Scribed by Bernat Kocsis; Maciej Kaminski

• Publisher: John Wiley and Sons
• Year: 2006
• Tongue: English
• Weight: 457 KB
• Volume: 16
• Category: Article
• ISSN: 1050-9631
• DOI: 10.1002/hipo.20180

✦ Synopsis

Abstract

Neurons in the supramammillary nucleus (SUM) of urethane‐anesthetized rats fire rhythmically in synchrony with hippocampal theta rhythm. As these neurons project to the septum and hippocampus, it is generally assumed that their role is to mediate ascending activation, leading to the hippocampal theta rhythm. However, the connections between SUM and the septohippocampal system are reciprocal; there is strong evidence that theta remains in the hippocampus after SUM lesions and in the SUM after lesioning the medial septum. The present study examines the dynamics of coupling between rhythmic discharge in the SUM and hippocampal field potential oscillations, using the directionality information carried by the two signals. Using directed transfer function analysis, we demonstrate that during sensory‐elicited theta rhythm and also during short episodes of theta acceleration of spontaneous oscillations, the spike train of a subpopulation of SUM neurons contains information predicting future variations in rhythmic field potentials in the hippocampus. In contrast, during slow spontaneous theta rhythm, it is the SUM spike signal that can be predicted from the preceding segment of the electrical signal recorded in the hippocampus. These findings indicate that, in the anesthetized rat, SUM neurons effectively drive theta oscillations in the hippocampus during epochs of sensory‐elicited theta rhythm and short episodes of theta acceleration, whereas spontaneous slow theta in the SUM is controlled by descending input from the septohippocampal system. Thus, in certain states, rhythmically firing SUM neurons function to accelerate the septal theta oscillator, and in others, they are entrained by a superordinate oscillatory network. © 2006 Wiley‐Liss Inc.