scholarly journals Coupling between motor cortex and striatum increases during sleep over long-term skill learning

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Stefan M Lemke ◽  
Dhakshin S Ramanathan ◽  
David Darevksy ◽  
Daniel Egert ◽  
Joshua D Berke ◽  
...  
Keyword(s):  
Nrem Sleep ◽  
Skill Learning ◽  
Neural Dynamics ◽  
Sleep Spindles ◽  
Behavioral Variability ◽  
Slow Oscillations ◽  
Corticostriatal Plasticity ◽  
Repeated Training ◽  
Time Away

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or 'offline' during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-REM (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

scholarly journals Shining a Light on the Mechanisms of Sleep for Memory Consolidation

2021 ◽  
Author(s):  
Michelle A. Frazer ◽  
Yesenia Cabrera ◽  
Rockelle S. Guthrie ◽  
Gina R. Poe
Keyword(s):  
Rem Sleep ◽  
Neural Activity ◽  
Memory Consolidation ◽  
Strong Support ◽  
Nrem Sleep ◽  
Future Research ◽  
Sleep Spindles ◽  
Slow Oscillations ◽  
Theta Waves ◽  
Learning Tasks

Abstract Purpose of review This paper reviews all optogenetic studies that directly test various sleep states, traits, and circuit-level activity profiles for the consolidation of different learning tasks. Recent findings Inhibiting or exciting neurons involved either in the production of sleep states or in the encoding and consolidation of memories reveals sleep states and traits that are essential for memory. REM sleep, NREM sleep, and the N2 transition to REM (characterized by sleep spindles) are integral to memory consolidation. Neural activity during sharp-wave ripples, slow oscillations, theta waves, and spindles are the mediators of this process. Summary These studies lend strong support to the hypothesis that sleep is essential to the consolidation of memories from the hippocampus and the consolidation of motor learning which does not necessarily involve the hippocampus. Future research can further probe the types of memory dependent on sleep-related traits and on the neurotransmitters and neuromodulators required.

scholarly journals Nonrapid eye movement sleep electroencephalographic oscillations in idiopathic rapid eye movement sleep behavior disorder: a study of sleep spindles and slow oscillations

SLEEP ◽  
2020 ◽  
Author(s):  
Jun-Sang Sunwoo ◽  
Kwang Su Cha ◽  
Jung-Ick Byun ◽  
Jin-Sun Jun ◽  
Tae-Joon Kim ◽  
...  
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Rem Sleep Behavior Disorder ◽  
Behavior Disorder ◽  
Nrem Sleep ◽  
Sleep Spindles ◽  
Rapid Eye Movement ◽  
Sleep Behavior ◽  
Slow Oscillations ◽  
Lower Amplitude

Abstract Study Objectives We investigated electroencephalographic (EEG) slow oscillations (SOs), sleep spindles (SSs), and their temporal coordination during nonrapid eye movement (NREM) sleep in patients with idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD). Methods We analyzed 16 patients with video-polysomnography-confirmed iRBD (age, 65.4 ± 6.6 years; male, 87.5%) and 10 controls (age, 62.3 ± 7.5 years; male, 70%). SSs and SOs were automatically detected during stage N2 and N3. We analyzed their characteristics, including density, frequency, duration, and amplitude. We additionally identified SO-locked spindles and examined their phase distribution and phase locking with the corresponding SO. For inter-group comparisons, we used the independent samples t-test or Wilcoxon rank-sum test, as appropriate. Results The SOs of iRBD patients had significantly lower amplitude, longer duration (p = 0.005 for both), and shallower slope (p < 0.001) than those of controls. The SS power of iRBD patients was significantly lower than that of controls (p = 0.002), although spindle density did not differ significantly. Furthermore, SO-locked spindles of iRBD patients prematurely occurred during the down-to-up-state transition of SOs, whereas those of controls occurred at the up-state peak of SOs (p = 0.009). The phase of SO-locked spindles showed a positive correlation with delayed recall subscores (p = 0.005) but not with tonic or phasic electromyography activity during REM sleep. Conclusions In this study, we found abnormal EEG oscillations during NREM sleep in patients with iRBD. The impaired temporal coupling between SOs and SSs may reflect early neurodegenerative changes in iRBD.

Sleep spindles coordinate corticostriatal reactivations during the emergence of automaticity

2020 ◽  
Author(s):  
S. M. Lemke ◽  
D. S. Ramanathan ◽  
D. Darevsky ◽  
D. Egert ◽  
J. D. Berke ◽  
...  
Keyword(s):  
Primary Motor Cortex ◽  
Activity Patterns ◽  
Behavioral Flexibility ◽  
Sleep Spindles ◽  
Behavioral Consistency ◽  
Natural Activity ◽  
Trigger Activity ◽  
Corticostriatal Plasticity ◽  
Repeated Training ◽  
Activity Dependent

Plasticity within the corticostriatal network is known to regulate the balance between behavioral flexibility and automaticity. Repeated training of an action has been shown to bias behavior towards automaticity, suggesting that training may trigger activity-dependent corticostriatal plasticity. However, surprisingly little is known about the natural activity patterns that may drive plasticity or when they occur during long-term training. Here we chronically monitored neural activity from primary motor cortex (M1) and the dorsolateral striatum (DLS) during both training and offline periods, i.e., time away from training including sleep, throughout the development of an automatic reaching action. We first show that blocking striatal NMDA receptors during offline periods prevents the emergence of behavioral consistency, a hallmark of automaticity. We then show that, throughout the development of an automatic reaching action, corticostriatal functional connectivity increases during offline periods. Such increases track the emergence of consistent behavior and predictable cross-area neural dynamics. We then identify sleep spindles during non-REM sleep (NREM) as uniquely poised to mediate corticostriatal plasticity during offline periods. We show that sleep spindles are periods of maximal corticostriatal transmission within offline periods, that sleep spindles in post-training NREM reactivate neurons across areas, and that sleep-spindle modulation in post-training NREM is linked to observable changes in spiking relationships between individual pairs of M1 and DLS neurons. Our results indicate that offline periods, in general, and sleep spindles, specifically, play an important role in regulating behavioral flexibility through corticostriatal network plasticity.

scholarly journals Corticostriatal dynamics encode the refinement of specific behavioral variability during skill learning

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Fernando J Santos ◽  
Rodrigo F Oliveira ◽  
Xin Jin ◽  
Rui M Costa
Keyword(s):  
Motor Task ◽  
Skill Learning ◽  
Projection Neurons ◽  
Behavioral Variability ◽  
Task Constraints ◽  
Striatal Projection Neurons ◽  
Behavioral Features ◽  
Complex Motor ◽  
Feature Sequence ◽  
Corticostriatal Plasticity

Learning to perform a complex motor task requires the optimization of specific behavioral features to cope with task constraints. We show that when mice learn a novel motor paradigm they differentially refine specific behavioral features. Animals trained to perform progressively faster sequences of lever presses to obtain reinforcement reduced variability in sequence frequency, but increased variability in an orthogonal feature (sequence duration). Trial-to-trial variability of the activity of motor cortex and striatal projection neurons was higher early in training and subsequently decreased with learning, without changes in average firing rate. As training progressed, variability in corticostriatal activity became progressively more correlated with behavioral variability, but specifically with variability in frequency. Corticostriatal plasticity was required for the reduction in frequency variability, but not for variability in sequence duration. These data suggest that during motor learning corticostriatal dynamics encode the refinement of specific behavioral features that change the probability of obtaining outcomes.

scholarly journals Local coupling between sleep spindles and slow oscillations supports the consolidation of motor memories

2020 ◽  
Author(s):  
Agustín Solano ◽  
Luis A. Riquelme ◽  
Daniel Perez-Chada ◽  
Valeria Della-Maggiore
Keyword(s):  
Motor Learning ◽  
Memory Consolidation ◽  
Nrem Sleep ◽  
Motor Memory ◽  
Common Mechanism ◽  
Long Term Memory ◽  
Memory Retention ◽  
Term Memory ◽  
Slow Oscillations

AbstractThe precise coupling between slow oscillations (SO) and spindles is critical for sleep-dependent consolidation of declarative memories. Here, we examined whether this mechanism also operates in the stabilization of human motor memories during NREM sleep. We hypothesized that if the coupling of these oscillations is instrumental to motor memory consolidation then only SO-coupled spindles would predict long-term memory. We found that sleep enhanced long-term memory retention by 34%. Motor learning increased the density of spindles but not their frequency, duration or amplitude during NREM sleep. This modulation was manifested locally over the hemisphere contralateral to the trained hand. Although motor learning did not affect the density of SOs, it substantially modulated the spindle-SO coupling in an inter-hemispheric manner, suggesting it may rather increase the ability of slow oscillations to promote thalamic spindles. The fact that only coupled spindles predicted long-term memory points to the association of these oscillations as a fundamental signature of motor memory consolidation. Our work provides evidence in favor of a common mechanism at the basis of the stabilization of declarative and non-declarative memories.

scholarly journals Interrelations between delta waves, spindles and slow oscillations in human NREM sleep and their functional role in memory

2021 ◽  
Author(s):  
Julia Ladenbauer ◽  
Larissa Wuest ◽  
Daria Antonenko ◽  
Robert Malinowski ◽  
Liliia Shevchuk ◽  
...  
Keyword(s):  
Functional Role ◽  
Critical Role ◽  
Nrem Sleep ◽  
Human Memory ◽  
Memory Formation ◽  
Sleep Spindles ◽  
Slow Oscillations ◽  
Delta Waves ◽  
Sleep Physiology ◽  
Temporal Coupling

Certain neurophysiological characteristics of sleep, in particular slow oscillations (SO), sleep spindles, and their temporal coupling, have been well characterized and associated with human memory formation. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SO, have only recently been found to play a critical role in memory processing of rodents, through a competitive interplay between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta waves, their interactions with spindles and SOs as well as their functional role for memory are still lacking. Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories. Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found that increased delta activity was accompanied by stronger SO-spindle coupling. Moreover, we identified the ratio between SO- and delta-nested spindles as the sleep parameter that predicted ability to form novel memories best. Our study suggests that SOs, delta waves and sleep spindles should be jointly considered when aiming to link sleep physiology and memory formation in aging.

Effect of interictal epileptic spikes on sleep spindles in medial temporal regions during NREM sleep: are there consequences on memory long-term consolidation? A SEEG study

2017 ◽  
Vol 40 ◽  
pp. e177
Author(s):  
I. Lambert ◽  
E. Tramoni-Negre ◽  
N. Roehri ◽  
B. Giusiano ◽  
C. Benar ◽  
...  
Keyword(s):  
Nrem Sleep ◽  
Sleep Spindles ◽  
Epileptic Spikes

Long-term monitoring provides insight into estuarine top predator (Carcharhinus leucas) resilience following an extreme weather event

2020 ◽  
Vol 639 ◽  
pp. 169-183
Author(s):  
P Matich ◽  
BA Strickland ◽  
MR Heithaus
Keyword(s):  
Habitat Use ◽  
Acoustic Telemetry ◽  
South Florida ◽  
Behavioral Variability ◽  
Catch Per Unit Effort ◽  
Ontogenetic Shifts ◽  
Carcharhinus Leucas ◽  
Acute Disturbance ◽  
Cold Snap

Chronic environmental change threatens biodiversity, but acute disturbance events present more rapid and immediate threats. In 2010, a cold snap across south Florida had wide-ranging impacts, including negative effects on recreational fisheries, agriculture, and ecological communities. Here, we use acoustic telemetry and historical longline monitoring to assess the long-term implications of this event on juvenile bull sharks Carcharhinus leucas in the Florida Everglades. Despite the loss of virtually all individuals (ca. 90%) within the Shark River Estuary during the cold snap, the catch per unit effort (CPUE) of age 0 sharks on longlines recovered through recruitment within 6-8 mo of the event. Acoustic telemetry revealed that habitat use patterns of age 0-2 sharks reached an equilibrium in 4-6 yr. In contrast, the CPUE and habitat use of age 3 sharks required 5-7 yr to resemble pre-cold snap patterns. Environmental conditions and predation risk returned to previous levels within 1 yr of the cold snap, but abundances of some prey species remained depressed for several years. Reduced prey availability may have altered the profitability of some microhabitats after the cold snap, leading to more rapid ontogenetic shifts to marine waters among sharks for several years. Accelerated ontogenetic shifts coupled with inter-individual behavioral variability of bull sharks likely led to a slower recovery rate than predicted based on overall shark CPUE. While intrinsic variation driven by stochasticity in dynamic ecosystems may increase the resistance of species to chronic and acute disturbance, it may also increase recovery time in filling the diversity of niches occupied prior to disturbance if resistive capacity is exceeded.

Distinguishable Brain Activation Networks for Short- and Long-Term Motor Skill Learning

2005 ◽  
Vol 94 (1) ◽  
pp. 512-518 ◽  
Author(s):  
A. Floyer-Lea ◽  
P. M. Matthews
Keyword(s):  
Motor Skill ◽  
Isometric Force ◽  
Brain Activation ◽  
Skill Learning ◽  
Anterior Cingulate ◽  
Motor Skill Learning ◽  
Short Term ◽  
Learning Stage ◽  
The Right

The acquisition of a new motor skill is characterized first by a short-term, fast learning stage in which performance improves rapidly, and subsequently by a long-term, slower learning stage in which additional performance gains are incremental. Previous functional imaging studies have suggested that distinct brain networks mediate these two stages of learning, but direct comparisons using the same task have not been performed. Here we used a task in which subjects learn to track a continuous 8-s sequence demanding variable isometric force development between the fingers and thumb of the dominant, right hand. Learning-associated changes in brain activation were characterized using functional MRI (fMRI) during short-term learning of a novel sequence, during short-term learning after prior, brief exposure to the sequence, and over long-term (3 wk) training in the task. Short-term learning was associated with decreases in activity in the dorsolateral prefrontal, anterior cingulate, posterior parietal, primary motor, and cerebellar cortex, and with increased activation in the right cerebellar dentate nucleus, the left putamen, and left thalamus. Prefrontal, parietal, and cerebellar cortical changes were not apparent with short-term learning after prior exposure to the sequence. With long-term learning, increases in activity were found in the left primary somatosensory and motor cortex and in the right putamen. Our observations extend previous work suggesting that distinguishable networks are recruited during the different phases of motor learning. While short-term motor skill learning seems associated primarily with activation in a cortical network specific for the learned movements, long-term learning involves increased activation of a bihemispheric cortical-subcortical network in a pattern suggesting “plastic” development of new representations for both motor output and somatosensory afferent information.

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