کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5738984 | 1615265 | 2017 | 18 صفحه PDF | دانلود رایگان |
- Information flow in the hippocampal-entorhinal loop is regulated by brain state.
- Waking theta states and REM sleep involve distinct information processing.
- Firing rate distributions of individual neurons are skewed in all brain states.
- Firing rates of individual neurons are preserved across brain states and situations.
- Firing rates of high- and low-firing neurons are distinctly regulated by sleep.
According to a two-stage memory consolidation model, during waking theta states, afferent activity from the neocortex to the hippocampus induces transient synaptic modification in the hippocampus, where the information is deposited as a labile form of memory trace. During subsequent sharp-wave ripples (SPW-Rs), the newly acquired hippocampal information is transferred to the neocortex and stored as a long-lasting memory trace. Consistent with this hypothesis, waking theta states and SPW-Rs distinctly control information flow in the hippocampal-entorhinal loop. Although both waking theta states and rapid eye movement (REM) sleep are characterized by prominent hippocampal theta oscillations, the two brain states involve distinct temporal coordination and oscillatory coupling in the hippocampal-entorhinal circuit. While distinct brain states have distinct network dynamics, firing rates of individual neurons in the hippocampal-entorhinal circuitry follow lognormal-like distributions in all states. Firing rates of the same neurons are positively correlated across brain states and testing environments, suggesting that memory is allocated in preconfigured, rather than tabula rasa-type, skewed neuronal networks. The fast-firing minority and slow-firing majority neurons, which can support network stability and flexibility, are under distinct homeostatic regulations that are initiated by spindles and SPW-Rs during slow wave sleep and implemented during subsequent REM sleep.
Journal: Neuroscience Research - Volume 118, May 2017, Pages 30-47