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      Cortical dendritic activity correlates with spindle-rich oscillations during sleep in rodents

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          Abstract

          How sleep influences brain plasticity is not known. In particular, why certain electroencephalographic (EEG) rhythms are linked to memory consolidation is poorly understood. Calcium activity in dendrites is known to be necessary for structural plasticity changes, but this has never been carefully examined during sleep. Here, we report that calcium activity in populations of neocortical dendrites is increased and synchronised during oscillations in the spindle range in naturally sleeping rodents. Remarkably, the same relationship is not found in cell bodies of the same neurons and throughout the cortical column. Spindles during sleep have been suggested to be important for brain development and plasticity. Our results provide evidence for a physiological link of spindles in the cortex specific to dendrites, the main site of synaptic plasticity.

          Abstract

          Different stages of sleep, marked by particular electroencephalographic (EEG) signatures, have been linked to memory consolidation, but underlying mechanisms are poorly understood. Here, the authors show that dendritic calcium synchronisation correlates with spindle-rich sleep phases.

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          Most cited references39

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          Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration.

          Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the offline, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This Perspective considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity. Copyright © 2014 Elsevier Inc. All rights reserved.
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            Causal evidence for the role of REM sleep theta rhythm in contextual memory consolidation.

            Rapid eye movement sleep (REMS) has been linked with spatial and emotional memory consolidation. However, establishing direct causality between neural activity during REMS and memory consolidation has proven difficult because of the transient nature of REMS and significant caveats associated with REMS deprivation techniques. In mice, we optogenetically silenced medial septum γ-aminobutyric acid-releasing (MS(GABA)) neurons, allowing for temporally precise attenuation of the memory-associated theta rhythm during REMS without disturbing sleeping behavior. REMS-specific optogenetic silencing of MS(GABA) neurons selectively during a REMS critical window after learning erased subsequent novel object place recognition and impaired fear-conditioned contextual memory. Silencing MS(GABA) neurons for similar durations outside REMS episodes had no effect on memory. These results demonstrate that MS(GABA) neuronal activity specifically during REMS is required for normal memory consolidation.
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              Nonlinear dendritic integration of sensory and motor input during an active sensing task.

              Active dendrites provide neurons with powerful processing capabilities. However, little is known about the role of neuronal dendrites in behaviourally related circuit computations. Here we report that a novel global dendritic nonlinearity is involved in the integration of sensory and motor information within layer 5 pyramidal neurons during an active sensing behaviour. Layer 5 pyramidal neurons possess elaborate dendritic arborizations that receive functionally distinct inputs, each targeted to spatially separate regions. At the cellular level, coincident input from these segregated pathways initiates regenerative dendritic electrical events that produce bursts of action potential output and circuits featuring this powerful dendritic nonlinearity can implement computations based on input correlation. To examine this in vivo we recorded dendritic activity in layer 5 pyramidal neurons in the barrel cortex using two-photon calcium imaging in mice performing an object-localization task. Large-amplitude, global calcium signals were observed throughout the apical tuft dendrites when active touch occurred at particular object locations or whisker angles. Such global calcium signals are produced by dendritic plateau potentials that require both vibrissal sensory input and primary motor cortex activity. These data provide direct evidence of nonlinear dendritic processing of correlated sensory and motor information in the mammalian neocortex during active sensation.
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                Author and article information

                Contributors
                j.seibt@surrey.ac.uk
                Matthew.larkum@gmail.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                25 September 2017
                25 September 2017
                2017
                : 8
                : 684
                Affiliations
                [1 ]ISNI 0000 0001 2218 4662, GRID grid.6363.0, NeuroCure Cluster of Excellence, , Charité-Universitätsmedizin, ; D-10117 Berlin, Germany
                [2 ]ISNI 0000 0004 0407 4824, GRID grid.5475.3, Surrey Sleep Research Centre, , University of Surrey, ; GU2 7XP Guildford, UK
                [3 ]ISNI 0000 0001 2248 7639, GRID grid.7468.d, Bernstein Center for Computational Neuroscience Berlin, , Humboldt-Universitätzu Berlin, ; D-10115 Berlin, Germany
                [4 ]ISNI 0000 0001 2248 7639, GRID grid.7468.d, Institute for Biology, , Humboldt-Universität zu Berlin, ; D-10117 Berlin, Germany
                [5 ]ISNI 0000 0001 0726 5157, GRID grid.5734.5, Department of Physiology, , Universität Bern, ; 3012 Bern, Switzerland
                Author information
                http://orcid.org/0000-0001-9799-2656
                Article
                735
                10.1038/s41467-017-00735-w
                5612962
                28947770
                a2fed7ad-7e00-49b5-ac98-ed5339a18270
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 February 2017
                : 21 July 2017
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