Cortical reactivations of recent sensory experiences predict bidirectional network changes during learning
Autor: | Andrew Lutas, Christian R. Burgess, Kristian Kinden Lensjø, Arthur U. Sugden, Osama Alturkistani, Jeffrey D. Zaremba, Rohan N. Ramesh, Lauren Alpert Sugden, Mark L. Andermann, Kelly L. McGuire |
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Rok vydání: | 2019 |
Předmět: |
0301 basic medicine
Sensory system Article Discrimination Learning 03 medical and health sciences Mice 0302 clinical medicine Neuroimaging Reward Cortex (anatomy) medicine Animals Association (psychology) Sensory cue Visual Cortex Neurons Neuronal Plasticity General Neuroscience Functional connectivity 030104 developmental biology medicine.anatomical_structure Food Visual discrimination QUIET Visual Perception Cues Psychology Food Deprivation Neuroscience 030217 neurology & neurosurgery psychological phenomena and processes |
Zdroj: | Nature neuroscience |
ISSN: | 1546-1726 |
Popis: | Salient experiences are often relived in the mind. Human neuroimaging studies suggest that such experiences drive activity patterns in visual association cortex that are subsequently reactivated during quiet waking. Nevertheless, the circuit-level consequences of such reactivations remain unclear. Here, we imaged hundreds of neurons in visual association cortex across days as mice learned a visual discrimination task. Distinct patterns of neurons were activated by different visual cues. These same patterns were subsequently reactivated during quiet waking in darkness, with higher reactivation rates during early learning and for food-predicting versus neutral cues. Reactivations involving ensembles of neurons encoding both the food cue and the reward predicted strengthening of next-day functional connectivity of participating neurons, while the converse was observed for reactivations involving ensembles encoding only the food cue. We propose that task-relevant neurons strengthen while task-irrelevant neurons weaken their dialog with the network via participation in distinct flavors of reactivation. |
Databáze: | OpenAIRE |
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