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Modeling Spatial Representations in Hippocampal Circuits with Attractor Networks| old_uid | 9475 |
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| title | Modeling Spatial Representations in Hippocampal Circuits with Attractor Networks |
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| start_date | 2010/12/20 |
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| schedule | 15h |
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| online | no |
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| summary | The dynamics of hippocampal place cells changes dramatically according to the behavior of the animal. During a run through a cell’s place field, spikes are emitted at progressively earlier phases of the underlying theta rhythm. During awake immobility, rapid orderly activation of place cells expresses a possible or experienced trajectory of the animal. When the animal transiently stops at turning points in a T-maze, sweeps of place cells activity probes possible routes from that point. Common mechanisms underlying these dynamical properties are poorly understood and cannot be accommodated by existing network models. We propose that such a diverse range of behaviors can be explained by endowing a network, storing a map of the environment in its recurrent collaterals, with short-term synaptic depression. When several correlated environments are stored in the same network, there can be a strong interaction between them even when one environment is activated by the external cue.Modeling Spatial Representations in Hippocampal Circuits with Attractor Networks Sandro ROMANI – Dept. of Neurobiology, Weizmann Institute of Science, Rehovot, Israel. The dynamics of hippocampal place cells changes dramatically according to the behavior of the animal. During a run through a cell’s place field, spikes are emitted at progressively earlier phases of the underlying theta rhythm. During awake immobility, rapid orderly activation of place cells expresses a possible or experienced trajectory of the animal. When the animal transiently stops at turning points in a T-maze, sweeps of place cells activity probes possible routes from that point. Common mechanisms underlying these dynamical properties are poorly understood and cannot be accommodated by existing network models. We propose that such a diverse range of behaviors can be explained by endowing a network, storing a map of the environment in its recurrent collaterals, with short-term synaptic depression. When several correlated environments are stored in the same network, there can be a strong interaction between them even when one environment is activated by the external cue. |
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| responsibles | Levenes, Mongillo |
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