Data from: Theta-modulation drives the emergence of connectivity patterns underlying replay in a network model of place cells
Data files
Oct 26, 2018 version files 1.94 GB
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A991-20140826-04_BehavElectrDataLFP.mat
202.47 MB
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A991-20140830-01_BehavElectrDataLFP.mat
216.30 MB
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A991-20140830-05_BehavElectrDataLFP.mat
200.28 MB
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A992-20140824-03_BehavElectrDataLFP.mat
190.33 MB
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A992-20140831-01_BehavElectrDataLFP.mat
174.18 MB
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A992-20140831-05_BehavElectrDataLFP.mat
170.98 MB
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Yingxue Wang - A991-20140826-02_BehavElectrDataLFP_muscimol.mat
194.60 MB
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Yingxue Wang - A992-20140824-01_BehavElectrDataLFP_muscimol.mat
217.01 MB
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Yingxue Wang - A991-20140830-03_BehavElectrDataLFP.mat
202.77 MB
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Yingxue Wang - A992-20140831-03_BehavElectrDataLFP.mat
169.16 MB
Abstract
Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in any environment. Therefore for any given trajectory one observes a repeatable sequence of place cell activations. When the animal is quiescent or sleeping, one can observe similar sequences of activation known as replay, which underlie the process of memory consolidation. However, it remains unclear how replay is generated. Here we show how a temporally asymmetric plasticity rule during spatial exploration gives rise to spontaneous replay in a model network by shaping the recurrent connectivity to reflect the topology of the learned environment. Crucially, the rate of this encoding is strongly modulated by ongoing rhythms. Oscillations in the theta range optimize learning by generating repeated pre-post pairings on a time-scale commensurate with the window for plasticity, while lower and higher frequencies generate learning rates which are lower by orders of magnitude.