Dual function of thalamic low-vigilance state oscillations: rhythm-regulation and plasticity.

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Title: Dual function of thalamic low-vigilance state oscillations: rhythm-regulation and plasticity.
Authors: Crunelli, Vincenzo, Lőrincz, Magor L., Connelly, William M., David, François, Hughes, Stuart W., Lambert, Régis C., Leresche, Nathalie, Errington, Adam C., Lőrincz, Magor L (AUTHOR), David, François (AUTHOR), Lambert, Régis C (AUTHOR)
Source: Nature Reviews Neuroscience. Feb2018, Vol. 19 Issue 2, p107-118. 12p. 6 Diagrams, 1 Graph.
Abstract: During inattentive wakefulness and non-rapid eye movement (NREM) sleep, the neocortex and thalamus cooperatively engage in rhythmic activities that are exquisitely reflected in the electroencephalogram as distinctive rhythms spanning a range of frequencies from <1 Hz slow waves to 13 Hz alpha waves. In the thalamus, these diverse activities emerge through the interaction of cell-intrinsic mechanisms and local and long-range synaptic inputs. One crucial feature, however, unifies thalamic oscillations of different frequencies: repetitive burst firing driven by voltage-dependent Ca2+ spikes. Recent evidence reveals that thalamic Ca2+ spikes are inextricably linked to global somatodendritic Ca2+ transients and are essential for several forms of thalamic plasticity. Thus, we propose herein that alongside their rhythm-regulation function, thalamic oscillations of low-vigilance states have a plasticity function that, through modifications of synaptic strength and cellular excitability in local neuronal assemblies, can shape ongoing oscillations during inattention and NREM sleep and may potentially reconfigure thalamic networks for faithful information processing during attentive wakefulness. [ABSTRACT FROM AUTHOR]
Copyright of Nature Reviews Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Nature+Reviews+Neuroscience%22&quot;&gt;Nature Reviews Neuroscience&lt;/searchLink&gt;. Feb2018, Vol. 19 Issue 2, p107-118. 12p. 6 Diagrams, 1 Graph.
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  Data: During inattentive wakefulness and non-rapid eye movement (NREM) sleep, the neocortex and thalamus cooperatively engage in rhythmic activities that are exquisitely reflected in the electroencephalogram as distinctive rhythms spanning a range of frequencies from &lt;1 Hz slow waves to 13 Hz alpha waves. In the thalamus, these diverse activities emerge through the interaction of cell-intrinsic mechanisms and local and long-range synaptic inputs. One crucial feature, however, unifies thalamic oscillations of different frequencies: repetitive burst firing driven by voltage-dependent Ca2+ spikes. Recent evidence reveals that thalamic Ca2+ spikes are inextricably linked to global somatodendritic Ca2+ transients and are essential for several forms of thalamic plasticity. Thus, we propose herein that alongside their rhythm-regulation function, thalamic oscillations of low-vigilance states have a plasticity function that, through modifications of synaptic strength and cellular excitability in local neuronal assemblies, can shape ongoing oscillations during inattention and NREM sleep and may potentially reconfigure thalamic networks for faithful information processing during attentive wakefulness. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Nature Reviews Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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