Modeling goal-directed spatial navigation in the rat based on physiological data from the hippocampal formation

Koene, Randal A.; Gorchetchnikov, Anatoli; Cannon, Robert C.; Hasselmo, Michael E.

doi:10.1016/s0893-6080(03)00106-0

Cited by 84 publications

(109 citation statements)

References 31 publications

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“…Several explanations for the place-phase relationship were put forward (4)(5)(6)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). To confront these models, we examined the relationship among running speed, oscillation frequency of place cells and LFP , and timing of spikes within the cycle.…”

mentioning

confidence: 99%

Hippocampal place cell assemblies are speed-controlled oscillators

Geisler

Robbe

Zugaro

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

253

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The phase of spikes of hippocampal pyramidal cells relative to the local field oscillation shifts forward (''phase precession'') over a full cycle as the animal crosses the cell's receptive field (''place field''). The linear relationship between the phase of the spikes and the travel distance within the place field is independent of the animal's running speed. This invariance of the phase-distance relationship is likely to be important for coordinated activity of hippocampal cells and space coding, yet the mechanism responsible for it is not known. Here we show that at faster running speeds place cells are active for fewer cycles but oscillate at a higher frequency and emit more spikes per cycle. As a result, the phase shift of spikes from cycle to cycle (i.e., temporal precession slope) is faster, yet spatial-phase precession stays unchanged. Interneurons can also show transient-phase precession and contribute to the formation of coherently precessing assemblies. We hypothesize that the speed-correlated acceleration of place cell assembly oscillation is responsible for the phase-distance invariance of hippocampal place cells.cell assembly ͉ interneurons ͉ phase locking ͉ phase precession ͉ oscillations W hile animals navigate in an environment, the hippocampal local field potential (LFP) is characterized by a highly regular oscillation (8-10 Hz). Principal cells in the hippocampus show place-specific firing by two criteria. First, the firing is tuned to a particular location (''place field''), showing a bellshaped tuning curve centered around its preferred location (1). Second, the timing of spikes within subsequent cycles systematically shifts forward (''phase precession''), Ϸ1 full cycle in total, as the rat runs through the place field of the neuron (2, 3) (see also Fig. 1 A and B). Both the firing rate and discharge phase within a cycle are correlated with the rat's position. However, how the rate change and -phase precession of spikes are related is poorly understood. The available experiments support both a rate-phase interdependence (4-6) and independence (7).Several explanations for the place-phase relationship were put forward (4)(5)(6)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). To confront these models, we examined the relationship among running speed, oscillation frequency of place cells and LFP , and timing of spikes within the cycle. We show that principal cells oscillate at a frequency faster than the simultaneously recorded LFP oscillation, and that this oscillation frequency depends on the rat's running speed. Together with the place-and speed-dependent oscillation frequencies of interneurons, the findings support the hypothesis that place coding results from coordinated network activity. We propose that the locomotion speed-dependent oscillation of place cell assemblies may underlie the mechanisms responsible for distance encoding in the hippocampus. ResultsWe recorded the firing patterns of pyramidal cells, interneurons, and the LFP from the CA1 pyramidal layer of rats as they ran on a U-shap...

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mentioning

confidence: 99%

Hippocampal place cell assemblies are speed-controlled oscillators

Geisler

Robbe

Zugaro

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

253

321

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“…Some of these network models suggest the origin of phase precession to be in CA3 (Tsodyks et al, 1996;Wallenstein & Hasselmo, 1997;Bose & Recce, 2001;Booth & Bose, 2001;Scarpetta & Marinaro, 2005) and others in the entorhinal cortex (Yamaguchi, 2003;Hasselmo & Eichenbaum, 2005). Finally, Jensen and Lisman (1996), Hasselmo et al (2002), Koene et al (2003), and Lisman et al (2005) predict phase precession to be generated through an interplay of the entorhinal cortex and CA3.…”

Section: Comparison With Other Modelsmentioning

confidence: 99%

“…Mechanisms used to explain the generation of phase precession include (1) the interaction of two oscillators with slightly different frequencies (O'Keefe & Recce, 1993;Kamondi et al, 1998;Bose & Recce, 2001;Booth & Bose, 2001;Lengyel et al, 2003;Yamaguchi, 2003;Huhn et al, 2005), (2) the asymmetry of place fields (Mehta et al, 2000(Mehta et al, , 2002, (3) the adaptation of the spiking activity of pyramidal cells in response to sustained excitatory input (Kamondi et al, 1998;Magee, 2001;Harris et al, 2002;Mehta et al, 2002;Mehta, Quirk, & Wilson, 2000) and (4) the use of a short-term memory buffer (Hasselmo et al, 2002;Koene et al, 2003); see, for example, Zugaro et al (2005), Maurer and McNaughton (2007), and Yamaguchi et al (2007) for a discussion of phase precession models. It is also conceivable that phase precession is generated through an interaction of two or more mechanisms.…”

Section: Comparison With Other Modelsmentioning

confidence: 99%

“…Mechanistic models of phase precession can also be divided into models that explain this phenomenon as the result of (sequence) learning (Tsodyks et al, 1996;Jensen & Lisman, 1996;Wallenstein & Hasselmo, 1997;Hasselmo et al, 2002;Koene et al, 2003;Mehta et al, 2002;Scarpetta & Marinaro, 2005;Hasselmo & Eichenbaum, 2005;Jensen & Lisman, 2005), and models, including ours, that do not require previous (sequence) learning (O'Keefe & Recce, 1993;Magee, 2001;Harris et al, 2002;Lengyel et al, 2003;Yamaguchi, 2003;Huhn et al, 2005). The latter retrospective models have the advantage that phase precession in CA1 can occur in the first exposure to a new environment, which is in accordance with the observations of Rosenzweig, Ekstrom, Redish, McNaughton, and Barnes (2000), Mehta et al (2002), and Chen and Frank (2007).…”

Section: Comparison With Other Modelsmentioning

confidence: 99%

“…Recently phase precession has been reported in layer II of the medial entorhinal cortex (Fyhn, Hafting, Moser, & Moser, 2006), which provides input to the hippocampus. The origin of phase precession is still unknown, despite elegant experiments that aimed at unraveling underlying mechanisms (Ekstrom, Meltzer, McNaughton, & Barnes, 2001;Huxter et al, 2003;Zugaro, Monconduit, & Buzsáki, 2005), and despite reasonable effort to put forth mechanistic models (O'Keefe & Recce, 1993;Tsodyks, Skaggs, Sejnowski, & McNaughton, 1996;Jensen & Lisman, 1996;Wallenstein & Hasselmo, 1997;Bose & Recce, 2001;Harris et al, 2002;Hasselmo, Canon, & Koene, 2002;Mehta et al, 2002;Koene, Gorchetchnikov, Cannon, & Hasslemo, 2003;Lengyel, Szatmary, & Erdi, 2003;Yamaguchi, 2003;Huhn, Orban, Erdi, & Lengyel, 2005;Scarpetta & Marinaro, 2005;Lisman, Talamini, & Raffone, 2005;Hasselmo & Eichenbaum, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Phase Precession Through Synaptic Facilitation

et al. 2008

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Phase precession is a relational code that is thought to be important for episodic-like memory, for instance, the learning of a sequence of places. In the hippocampus, places are encoded through bursting activity of socalled place cells. The spikes in such a burst exhibit a precession of their firing phases relative to field potential theta oscillations (4-12 Hz); the theta phase of action potentials in successive theta cycles progressively decreases toward earlier phases. The mechanisms underlying the generation of phase precession are, however, unknown. In this letter, we show * Kay Thurley is now at the Institute of Physiology, University of Bern, 3012 Bern, Switzerland. Christian Leibold is now at the Department of Biology II, LudwigMaximilians-Universität München, 82152 Planegg-Martinsried, Germany. through mathematical analysis and numerical simulations that synaptic facilitation in combination with membrane potential oscillations of a neuron gives rise to phase precession. This biologically plausible model reproduces experimentally observed features of phase precession, such as (1) the progressive decrease of spike phases, (2) the nonlinear and often also bimodal relation between spike phases and the animal's place, (3) the range of phase precession being smaller than one theta cycle, and (4) the dependence of phase jitter on the animal's location within the place field. The model suggests that the peculiar features of the hippocampal mossy fiber synapse, such as its large efficacy, long-lasting and strong facilitation, and its phase-locked activation, are essential for phase precession in the CA3 region of the hippocampus. Neural Computation

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Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior

et al. 2005

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Both the hippocampus and the medial prefrontal cortex are essential for successful performance in learning- and memory-related tasks. Within the hippocampus the theta rhythm plays an integral role in the timing of action potentials of hippocampal neurons responding to elements of any given task. Medial prefrontal cortex (mPFC) neurons display firing rate changes to specific facets of behavioral tasks (Jung et al., 1998. Cereb Cortex 8:437--450). We recorded units in the mPFC and field potentials in the hippocampus to determine whether behaviorally correlated mPFC cells fired with phase relationships to the hippocampal theta rhythm. In two different behavioral tasks (running a linear track and foraging in two distinct environments) we found mPFC cells that alternated between theta entrained firing and nonphasic firing depending on the ongoing behavior, while other cells were modulated during all conditions in both tasks. The majority of the mPFC cells with a significant correlation of firing rate changes with behavior were entrained to hippocampal theta. Cells that fired to specific events during only one direction of running were predisposed to theta modulation only in that direction. mPFC neurons have the capability to respond to behaviorally relevant elements by dynamically alternating between hippocampal theta entrained and nonphasic firing.

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Modeling goal-directed spatial navigation in the rat based on physiological data from the hippocampal formation

Cited by 84 publications

References 31 publications

Hippocampal place cell assemblies are speed-controlled oscillators

Hippocampal place cell assemblies are speed-controlled oscillators

Phase Precession Through Synaptic Facilitation

Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior

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