dorsal/arxiv
View SchemaA learning rule for place fields in a cortical model: theta phase precession as a network effect
| Authors | Silvia Scarpetta, Maria Marinaro |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0507002 |
| URL | https://arxiv.org/abs/q-bio/0507002 |
Abstract
We show that a model of the hippocampus introduced recently by Scarpetta, Zhaoping & Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta phase precession phenomena. In our model, the theta phase precession comes out as a consequence of the associative-memory-like network dynamics, i.e. the network's ability to imprint and recall oscillatory patterns, coded both by phases and amplitudes of oscillation. The learning rule used to imprint the oscillatory states is a natural generalization of that used for static patterns in the Hopfield model, and is based on the spike time dependent synaptic plasticity (STDP), experimentally observed. In agreement with experimental findings, the place cell's activity appears at consistently earlier phases of subsequent cycles of the ongoing theta rhythm during a pass through the place field, while the oscillation amplitude of the place cell's firing rate increases as the animal approaches the center of the place field and decreases as the animal leaves the center. The total phase precession of the place cell is lower than 360 degrees, in agreement with experiments. As the animal enters a receptive field the place cell's activity comes slightly less than 180 degrees after the phase of maximal pyramidal cell population activity, in agreement with the findings of Skaggs et al (1996). Our model predicts that the theta phase is much better correlated with location than with time spent in the receptive field. Finally, in agreement with the recent experimental findings of Zugaro et al (2005), our model predicts that theta phase precession persists after transient intra-hippocampal perturbation.
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"date_created": "2026-03-02T18:01:31.801000Z",
"date_modified": "2026-03-02T18:01:31.801000Z",
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"abstract": "We show that a model of the hippocampus introduced recently by Scarpetta,\nZhaoping \u0026 Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta\nphase precession phenomena. In our model, the theta phase precession comes out\nas a consequence of the associative-memory-like network dynamics, i.e. the\nnetwork\u0027s ability to imprint and recall oscillatory patterns, coded both by\nphases and amplitudes of oscillation. The learning rule used to imprint the\noscillatory states is a natural generalization of that used for static patterns\nin the Hopfield model, and is based on the spike time dependent synaptic\nplasticity (STDP), experimentally observed. In agreement with experimental\nfindings, the place cell\u0027s activity appears at consistently earlier phases of\nsubsequent cycles of the ongoing theta rhythm during a pass through the place\nfield, while the oscillation amplitude of the place cell\u0027s firing rate\nincreases as the animal approaches the center of the place field and decreases\nas the animal leaves the center. The total phase precession of the place cell\nis lower than 360 degrees, in agreement with experiments. As the animal enters\na receptive field the place cell\u0027s activity comes slightly less than 180\ndegrees after the phase of maximal pyramidal cell population activity, in\nagreement with the findings of Skaggs et al (1996). Our model predicts that the\ntheta phase is much better correlated with location than with time spent in the\nreceptive field. Finally, in agreement with the recent experimental findings of\nZugaro et al (2005), our model predicts that theta phase precession persists\nafter transient intra-hippocampal perturbation.",
"arxiv_id": "q-bio/0507002",
"authors": [
"Silvia Scarpetta",
"Maria Marinaro"
],
"categories": [
"q-bio.NC",
"cond-mat.dis-nn"
],
"title": "A learning rule for place fields in a cortical model: theta phase precession as a network effect",
"url": "https://arxiv.org/abs/q-bio/0507002"
},
"schema_id": "dorsal/arxiv",
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