Visually evoked neuronal ensembles reactivate during sleep
Lines, J.; Yuste, R.
Show abstract
Neuronal ensembles, defined as groups of coactive neurons, dominate cortical activity and are causally related to perceptual states and behavior. Interestingly, ensembles occur spontaneously in the absence of sensory stimulation. To better understand the function of ensembles in spontaneous activity, we explored if ensembles also occur during different brain states, including sleep, using two-photon calcium imaging from mouse primary visual cortex. We find that ensembles are present during all wake and sleep states, with different characteristics depending on the exact sleep stage. Moreover, visually evoked ensembles are reactivated during subsequent slow wave sleep cycles. Our results are consistent with the hypothesis that repeated sensory stimulation can reconfigure cortical circuits and imprint neuronal ensembles that are reactivated during sleep for potential processing or memory consolidation. One-Sentence SummaryCortical neuronal ensembles are present across wake and sleep states, and visually evoked ensembles are reactivated in subsequent slow-wave sleep.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex 97%
- Recognition of distinct sleep states in Drosophila uncovers previously obscured homeostatic and circadian control of sleep. 96%
- Sleep spindles track cortical learning patterns for memory consolidation 96%
Similar papers in this journal
Similar papers in this journal
- Sleep differentially affects early and late neuronal responses to sounds in auditory and perirhinal cortices 97%
- Dynamic respiration-neural coupling in substantia nigra across sleep and anesthesia 96%
- Relating pupil diameter and blinking to cortical activity and hemodynamics across arousal states 96%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.