Trends in Neurosciences
Review
INMED/TINS special issueNetwork and intrinsic cellular mechanisms underlying theta phase precession of hippocampal neurons
INMED/TINS special issue
Introduction
The hippocampus of rodents and many other mammals shows an oscillation of its local field potential in the range of ∼6–8 Hz, while animals are actively locomoting, attending to external stimuli or in REM sleep, and the total spike activity of ensembles of hippocampal principal neurons (pyramidal and granule cells) is phase-locked to this rhythm 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11; however, the behavior of individual neurons is more complex. It is now well established that hippocampal principal cells fire in a manner that is consistent both with a ‘cognitive mapping’ system (e.g. ‘place cells’; [12]), much as originally envisaged by O’Keefe and Nadel [11], and with an episodic memory indexing system (e.g. see Ref. [13]; but the role of the theta rhythm in these (or other) hippocampal functions has been much less clear.
Section snippets
Theta phase precession
Speculation as to the function of the theta rhythm 7, 11, 14, 15, 16, 17, 18 entered a new era with the discovery [19] that hippocampal pyramidal cells, when they show spatially correlated activity, systematically vary their firing phase relative to the theta frequency local field oscillation as a function of spatial location (Figure 1). As an animal enters a ‘place field’ of a given cell, the first spikes occur late in the theta cycle. As the animal leaves the field, they occur near the
Functions of theta phase precession
Since the initial discovery of theta phase precession, it was recognized that a downstream network that can respond to both relative phase and firing rate could generate a more accurate estimate of the location of the animal than firing rate alone 17, 19. The plausibility of this proposal was confirmed [20] using neural ensemble-based reconstruction methods [21] with data from rats running on linear tracks; however, the usefulness of phase information for position encoding during normal
Mechanism of phase precession
As mentioned earlier, phase precession necessarily implies that the burst frequency of the neuron must be somewhat higher than the local field oscillation. O’Keefe and Recce [19] suggested that the mechanism of precession itself might actually be based on interference effects from two oscillators of slightly different frequencies; a slower oscillating input, presumably from the medial septum, which generates the hippocampal theta rhythm, and a slightly faster oscillation that arises from a
Strengths and weaknesses of the two classes of model
Phase precession could be generated by a network mechanism, an intrinsic oscillator mechanism, or possibly by a combination of these. Some recent findings, however, are difficult to reconcile with the intrinsic oscillator model, at least as an explanation for phase precession in CA1. Perhaps the most difficult problem for the intrinsic oscillator model is that CA1 place cells can participate in multiple assemblies within the same theta cycle. For the majority of place fields, phase precession
Hybrid models
The intrinsic oscillation model and the asymmetric connection model both encounter significant difficulties when used to explain phase precession in the hippocampus proper. Skaggs et al. [17] demonstrated that cells in the dentate gyrus also showed phase precession and had their peak firing ∼90° earlier than CA1 pyramidal cells and suggested on this basis that phase precession does not originate in CA1, but rather is inherited from either the dentate gyrus or even the superficial layers of the
Conclusion
The study of the neural mechanisms underlying the spatio-temporal dynamics of the rodent entorhinal–hippocampal system is at an exciting crossroads. It seems clear that there is a deep relationship between the precise ordering of action potentials in relation to the phase of the theta rhythm and the position of the rat in space, and the mechanisms underlying the equally striking, regularly repeating grid fields of neurons in medial entorhinal cortex. Two very different classes of model seem to
Acknowledgements
This work was supported by US PHS Grant NS020331.
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