Thalamo-Cortical White Matter Underlies Motor Memory Consolidation via Modulation of Sleep Spindles in Young and Older Adults

Vien, Catherine; Boré, Arnaud; Boutin, Arnaud; Pinsard, Basile; Carrier, Julie; Doyon, Julien; Fogel, Stuart

doi:10.1016/j.neuroscience.2018.12.049

Cited by 25 publications

(19 citation statements)

References 81 publications

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“…For instance, motor learning-related development of dendritic spines was observed during subsequent NREM sleep [47], and replay of task-related ensembles was linked to the coincidence of slow-wave events and bursts of spindle activity [94]. In the context of the focus of this review on experience-dependent structural modifications, it is noticeable that robust relationships have been evidenced between features of sleep oscillations reflecting brain plasticity processes (e.g., sleep spindles [95][96][97], slow-wave activity [98] or the slope of slow oscillations [99] during NREM sleep), and brain structural measures such as inter-individual differences in GM volume [95,96,98,100], GM cortical thickness [101] or WM diffusion [96,98]. These results indicate that besides reflecting the dynamics of neuronal networks, sleep oscillations may to some extent reflect, and be constrained by, the microstructural properties of their underlying localized brain sources.…”

Section: Sleep and Memory Consolidation: Structural Changesmentioning

confidence: 98%

“…Indeed, specific white matter tracts located in the frontal temporal and subcortical regions exhibited higher axial diffusivity in individuals with a steeper rising slope of slow wave oscillations or increased sleep spindle power [95]. Additionally, data linking sleep spindles with learning-related projections and offline memory gains suggest that the way microstructural white matter fascicles characteristics influence memory consolidation is mediated through sleep spindles density [97]. Lastly, hippocampal GMV was found correlated with differential spindle expression; whereas hypothalamic and medial prefrontal cortical GMV were associated with slow wave oscillations [100].…”

Section: Sleep and Memory Consolidation: Structural Changesmentioning

confidence: 99%

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Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Stee

Peigneux

2021

Biochemical Pharmacology

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Neuroplasticity refers to the fact that our brain can partially modify both structure and function to adequately respond to novel environmental stimulations. Neuroplasticity mechanisms are not only operating during the acquisition of novel information (i.e., online) but also during the offline periods that take place after the end of the actual learning episode. Structural brain changes as a consequence of learning have been consistently demonstrated on the long term using non-invasive neuroimaging methods, but short-term changes remained more elusive. Fortunately, the swift development of advanced MR methods over the last decade now allows tracking fine-grained cerebral changes on short timescales beyond gross volumetric modifications stretching over several days or weeks. Besides a mere effect of time, post-learning sleep mechanisms have been shown to play an important role in memory consolidation and promote long-lasting changes in neural networks. Sleep was shown to contribute to structural modifications over weeks of prolonged training, but studies evidencing more rapid post-training sleep structural effects linked to memory consolidation are still scarce in human. On the other hand, animal studies convincingly show how sleep might modulate synaptic microstructure. We aim here at reviewing the literature establishing a link between different types of training/learning and the resulting structural changes, with an emphasis on the role of post-training sleep and time in tuning these modifications. Open questions are raised such as the role of post-learning sleep in macrostructural changes, the links between different MR structural measurement-related modifications and the underlying microstructural brain processes, and bidirectional influences between structural and functional brain changes.

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Section: Sleep and Memory Consolidation: Structural Changesmentioning

confidence: 98%

Section: Sleep and Memory Consolidation: Structural Changesmentioning

confidence: 99%

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Stee

Peigneux

2021

Biochemical Pharmacology

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“…All participants then underwent a full night of polysomnography, in which we measured spindle density, amplitude, duration and oscillation frequency, as well as sigma-band power. Considering previous findings in healthy populations where the integrity of thalamo-cortical tracts was associated with spindle density and amplitude ( Piantoni et al , 2013 ; Mander et al , 2017 ; Gaudreault et al , 2018 ; Vien et al , 2019 ), we hypothesized that more white matter damage, globally and in the thalamo-cortical tracts, would affect spindles, resulting in lower density, lower sigma-band power and spindles of lower amplitude. Due to the effect of white matter damage on axonal conduction speed ( Waxman, 1977 ; Hartline and Colman, 2007 ; Marion et al , 2018 ), we also hypothesized that white matter deterioration would result in slower spindle oscillation frequency, which represents the speed at which the impulses complete the loop between the thalamus to the cortex.…”

Section: Introductionmentioning

confidence: 97%

“…A first study found that higher axial diffusivity in the corpus callosum, temporal fascicles and tracts surrounding the thalamus, interpreted in this case as a marker of better white matter integrity, was associated with higher spindle density and sigma-band power in young healthy adults ( Piantoni et al , 2013 ). Two other studies investigated how white matter moderates the relationship between spindles and motor memory consolidation, and found that its integrity strengthens this association ( Mander et al , 2017 ; Vien et al , 2019 ). Finally, one recent study found that markers of better thalamo-frontal white matter integrity predict higher spindle amplitude and sigma-band power in young individuals only, and not in older adults ( Gaudreault et al , 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Sleep spindles are resilient to extensive white matter deterioration

Sanchez

Arbour

El-Khatib

et al. 2020

Brain Communications

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Sleep spindles are an essential part of non-rapid eye movement sleep, notably involved in sleep consolidation, cognition, learning, and memory. These oscillatory waves depend on an interaction loop between the thalamus and the cortex, which relies on a structural backbone of thalamo-cortical white matter tracts. It is still largely unknown if the brain can properly produce sleep spindles when it underwent extensive white matter deterioration in these tracts, and we hypothesized that it would affects sleep spindle generation and morphology. We tested this hypothesis with chronic moderate to severe traumatic brain injury (n = 23; 30.5 ± 11.1 years old; 17m/6f), a unique human model of extensive white matter deterioration, and a healthy control group (n = 27; 30.3 ± 13.4 years old; 21m/6f). Sleep spindles were analyzed on a full-night of polysomnography over the frontal, central, and parietal brain regions, and we measured their density, morphology, and sigma-band power. White matter deterioration was quantified using diffusion-weighted MRI, with which we performed both whole-brain voxel-wise analysis (Tract-Based Spatial Statistics) and probabilistic tractography (with High Angular Resolution Diffusion Imaging) to target the thalamocortical tracts. Group differences were assessed for all variables and correlations were performed separately in each group, corrected for age and multiple comparisons. Surprisingly, although extensive white matter damage across the brain including all thalamo-cortical tracts was evident in the brain-injured group, sleep spindles remained completely undisrupted when compared to a healthy control group. In addition, almost all sleep spindle characteristics were not associated with the degree of white matter deterioration in the brain-injured group, except that more white matter deterioration correlated with lower spindle frequency over the frontal regions. This study highlights the resilience of sleep spindles to the deterioration of all white matter tracts critical to their existence, as they conserve normal density during non-rapid eye movement sleep with mostly unaltered morphology. We show that even with such a severe traumatic event, the brain has the ability to adapt or to withstand alterations in order to conserve normal sleep spindles.

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“…Visual perceptual learning (VPL), which is defined as long-term enhanced performance on a visual task (Lu et al, 2011;Sagi, 2011;Sasaki et al, 2010;Shibata et al, 2011;Watanabe et al, 2001), is one type of learning that shows higher performance after sleep than before sleep. Such improvement over sleep in skill learning (Fischer et al, 2002;Karni et al, 1994) is called offline performance gain (Albouy et al, 2013;Korman et al, 2007;Lugassy et al, 2018;Tamaki et al, 2020b;Vien et al, 2019). However, the underlying mechanism of how sleep results in offline performance gain in learning has been controversial.…”

Section: Introductionmentioning

confidence: 99%

Sleep-dependent offline performance gain in visual perceptual learning is consistent with a learning-dependent model

Tamaki

Sasaki

2020

Preprint

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Are the sleep-dependent offline performance gains of visual perceptual learning (VPL) consistent with a use-dependent or learning-dependent model? Here, we found that a use-dependent model is inconsistent with the offline performance gains in VPL. In two training conditions with matched visual usages, one generated VPL (learning condition), while the other did not (interference condition). The use-dependent model predicts that slow-wave activity (SWA) during posttraining NREM sleep in the trained region increases in both conditions, in correlation with offline performance gains. However, compared with those in the interference condition, sigma activity, not SWA, during NREM sleep and theta activity during REM sleep, source-localized to the trained early visual areas, increased in the learning condition. Sigma activity correlated with offline performance gain. These significant differences in spontaneous activity between the conditions suggest that there is a learning-dependent process during posttraining sleep for the offline performance gains in VPL.

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Thalamo-Cortical White Matter Underlies Motor Memory Consolidation via Modulation of Sleep Spindles in Young and Older Adults

Cited by 25 publications

References 81 publications

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Sleep spindles are resilient to extensive white matter deterioration

Sleep-dependent offline performance gain in visual perceptual learning is consistent with a learning-dependent model

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