REM Sleep Reorganizes Hippocampal Excitability

Grosmark, Andres; Mizuseki, Kenji; Pastalkova, Eva; Diba, Kamran; Buzsáki, György

doi:10.1016/j.neuron.2012.08.015

Cited by 295 publications

(344 citation statements)

References 43 publications

(75 reference statements)

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“…Specifically we first segregated the WAKE state from the two sleep states based on the 3-D accelerometer data. Next SWS and REM sleep stages were determined by the theta (5-10 Hz)/delta (1-5 Hz) ratio extracted from the power spectrum of the LFP from VC, according to generally accepted practice (Grosmark et al, 2012;de Lavilléon et al, 2015).…”

Section: Methodsmentioning

confidence: 99%

Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states

Nair

Klaassen

Poirot

et al. 2016

Journal of Physiology-Paris

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The basal forebrain (BF) is an important regulator of cortical excitability and responsivity to sensory stimuli, and plays a major role in wake-sleep regulation. While the impact of BF on cortical EEG or LFP signals has been extensively documented, surprisingly little is known about LFP activity within BF. Based on bilateral recordings from rats in their home cage, we describe endogenous LFP oscillations in the BF during quiet wakefulness, rapid eye movement (REM) and slow wave sleep (SWS) states. Using coherence and Granger causality methods, we characterize directional influences between BF and visual cortex (VC) during each of these states. We observed pronounced BF gamma activity particularly during wakefulness, as well as to a lesser extent during SWS and REM. During wakefulness, this BF gamma activity exerted a directional influence on VC that was associated with cortical excitation. During SWS but not REM, there was also a robust directional gamma band influence of BF on VC. In all three states, directional influence in the gamma band was only present in BF to VC direction and tended to be regulated specifically within each brain hemisphere. Locality of gamma band LFPs to the BF was confirmed by demonstration of phase locking of local spiking activity to the gamma cycle. We report novel aspects of endogenous BF LFP oscillations and their relationship to cortical LFP signals during sleep and wakefulness. We link our findings to known aspects of GABAergic BF networks that likely underlie gamma band LFP activations, and show that the Granger causality analyses can faithfully recapitulate many known attributes of these networks.

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Section: Methodsmentioning

confidence: 99%

Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states

Nair

Klaassen

Poirot

et al. 2016

Journal of Physiology-Paris

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“…Interestingly, when a memory is being encoded indicating its importance for future use in a test appears to increase the likelihood of that memory being consolidated in sleep (Wilhelm et al 2011). Our understanding of specific memory functions and neurobiological processes in sleep is increasing, yet there remain many issues requiring further research (Chauvette, Seigneur, and Timofeev 2012;Grosmark et al 2012). …”

Section: Other Educational Considerationsmentioning

confidence: 99%

Synchronizing education to adolescent biology: ‘let teens sleep, start school later’

Kelley

Lockley

Foster

et al. 2014

Learning, Media and Technology

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Arne Duncan, US Secretary of State for Education, tweeted in 2013: 'let teens sleep, start school later'. This paper examines early starts and their negative consequences in the light of key research in the last 30 years in sleep medicine and circadian neuroscience. An overview of the circadian timing system in adolescence leading to changes in sleep patterns is given and underpins the conclusion that altering education times can both improve learning and reduce health risks. Further research is considered from education, sleep medicine and neuroscience studies illustrating these improvements. The implementation of later starts is briefly considered in light of other education interventions to improve learning. Finally, the impact of introducing research-based later starts synchronized to adolescent biology is considered in practical and policy terms.Keywords: education; adolescence; school start times; circadian; sleep deprivation; learning; health Introduction Time is a fundamental variable in human biology and in education, yet currently the two disciplines measure time in different ways. For the educator, student development is defined by age and the daily timetable by social conventions that vary between countries, regions and even individual schools. In contrast, biological time is measured in developmental changes in the body, and over the day by our internal biological clock. It is no surprise given the relative novelty of mechanical clocks in evolutionary timescales that our ability to function optimally, including in learning, varies with biological time rather than conventional social times.

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“…Vyazovskiy et al [37] also found that periods of neural silence are long and frequent during early non-REM sleep after prolonged wakefulness. On the other hand, Grosmark et al have also recently found that the alternating REM and non-REM episodes during sleep are characterized by different hippocampal excitability [38], implying a possible neuromodulation of firing in the sleep states. These observations are consistent with a scenario in which the homeostatic equilibrium of neurotransmitters is different between sleep states and the awaken state and could be mimicked by adjusting the values of these probabilities.…”

Section: A Cellular Automata Network Model Of the Brainmentioning

confidence: 99%

Firing patterns in a random network cellular automata model of the brain

Acedo¹,

Lamprianidou²,

Moraño³

et al. 2015

Physica A: Statistical Mechanics and its Applications

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One of the main challenges in the simulation of even reduced areas of the brain is the presence of a large number of neurons and a large number of connections among them. Even from a theoretical point of view, the behaviour of dynamical models of complex networks with high connectivity is unknown, precisely because the cost of computation is still unaffordable and it will likely be in the near future. In this paper we discuss the simulation of a cellular automata network model of the brain including up to one million sites with a maximum average of three hundred connections per neuron. This level of connectivity was achieved thanks to a distributed computing environment based on the BOINC (Berkeley Open Infrastructure for Network Computing) platform. Moreover, in this work we consider the interplay among excitatory neurons (which induce the excitation of their neighbours) and inhibitory neurons (which prevent resting neurons from firing and induce firing neurons to pass to the refractory state). Our objective is to classify the normal (noisy but asymptotically constant patterns) and the abnormal (high oscillations with spindle-like behaviour) patterns of activity in the model brain and their stability and parameter * e-mail: luiacrod@imm.upv.es 1 ranges in order to determine the role of excitatory and inhibitory compensatory effects in healthy and diseased individuals.

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REM Sleep Reorganizes Hippocampal Excitability

Cited by 295 publications

References 43 publications

Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states

Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states

Synchronizing education to adolescent biology: ‘let teens sleep, start school later’

Firing patterns in a random network cellular automata model of the brain

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